The primary objective of this study was to demonstrate the potential of digital image analysis as a tool to identify microplastic (MP) particles in surface waters and to facilitate their characterisation in terms of 2D and 3D morphology. Digital image analysis preceded by microscopic analysis was used for an exhaustive quantitative and qualitative evaluation of MPs isolated from the Vistula river. Using image processing procedures, 2D and 3D shape descriptors were determined. The Principal Components Analysis (PCA) was used to interpret the relationships between the parameters studied, characterising MP particle geometry, type and colour. This multivariate analysis of the data allowed 3 or 4 main factors to be extracted, explaining approximately 90% of the variation in the data characterising MP morphology. It was found that the first principal component for granules, flakes and films was largely represented by strongly correlated with 2D shape descriptors (area, perimeter, equivalent area diameter) and 3D shape descriptors (CSF, Compactness, Dimensionality). Considering the scraps, PC1 was represented by only five of the above descriptors, and the Compactness variable had the largest contribution to PC2. In addition, for granules, flakes and films, a relationship between 2D shape and the colour of their particles could be observed. For the most numerous MP group identified of multicoloured scraps, no such association was found. The results of our study can be used for further multivariate analysis regarding the presence of microplastic floating on the river surface, with a particular focus on particles of secondary origin. This is of key importance for optimising future efforts in conducting small-scale and multidimensional monitoring of and reducing plastics in the aquatic environment.

Addressing real-time aircraft target detection in microsatellite-based visible light remote sensing video imaging requires considering the limitations of imaging payload resolution, complex ground backgrounds, and the relative positional changes between the platform and aircraft. These factors lead to multi-scale variations in aircraft targets, making high-precision real-time detection of small targets in complex backgrounds a significant challenge for the detection algorithms. Hence, this paper introduces a real-time aircraft target detection algorithm for remote sensing imaging using an improved lightweight attention mechanism that relies on the YOLOv7 framework (SE-CBAM-YOLOv7). The proposed algorithm replaces the standard convolution (Conv) with a lightweight convolutional SEConv to reduce the computational parameters and accelerate the detection process of small aircraft targets, thus enhancing real-time onboard processing capabilities. Besides, the SEConv-based SPPCSPC (Spatial Pyramid Pooling and Connected Spatial Pyramid Convolution) module extracts image features. It improves detection accuracy while the feature fusion section integrates the CBAM hybrid attention network, forming the CBAMCAT module. Furthermore, it optimizes small aircraft target features in channel and spatial dimensions, improving the model's feature fusion capabilities. Experiments on public remote sensing datasets reveal the proposed SE-CBAM-YOLOv7 improves detection accuracy by 3% and mAP value by 4.2% compared to YOLOv7, significantly enhancing the detection capability for small-sized aircraft targets in satellite remote sensing imaging.

Since December 2019, the COVID-19 virus has rapidly spread worldwide, prompting the World Health Organization (WHO) to declare it a pandemic and advocate for the widespread use of face masks to mitigate transmission. In this review, we delve into the potential impact of prolonged face mask use on temporomandibular joint (TMJ) health, an area that has garnered limited attention amidst COVID-19 research. Research has revealed that improper mask fit, and constant readjustment can lead to TMJ abnormalities. Similarly, there is a demonstrated correlation between continuous mask usage and increased incidence of headaches, temporomandibular pain, and diminished quality of life. Many studies have highlighted discomfort in the preauricular area, headaches, TMJ noises, headache, jaw pain, and muscle fatigue, as well as dermatological disorders that have been attributed to prolonged mask wear and its impact on TMJ. Our study catalyzes future research endeavors, urging a deeper exploration of the implications of long-term mask wear, not only in the context of the COVID-19 pandemic but also among occupational groups regularly exposed to extended mask use. By unraveling the complexities of TMJ health in the face of evolving preventive measures, we aim to enhance our understanding and safeguard the well-being of mask-wearers worldwide.

The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. Based on the core essentials of economic toughness, this paper constructs the tourism economic toughness evaluation index system, uses the entropy weight TOPSIS method to measure the tourism economic toughness of 10 counties and cities in the Yili River Valley in 2010-2019, analyzes its spatio-temporal evolution characteristics through the standard deviation ellipse, the traditional Markov chain, and the spatial Markov chain, and uses the grey correlation analysis method to analyze the driving factors of the tourism economic toughness. The results show that: (1) the economic resilience of tourism in the Yili River Valley shows a "W"-shaped time-series dynamic development trend with an average index of 0.28394, in which it experienced a decline from 0.28 to 0.27 during 2012-2013 and 2015-2016; (2) Spatial Pattern: The Yili River Valley tourism economic resilience is characterized by a clear uneven spatial distribution. The city of Yining, representing the northwestern region, exhibits a high level of resilience, while the southwestern region, endowed with rich tourism resources, demonstrates a medium level of resilience. Conversely, the central to southeastern counties and cities, such as ChabuchaerXibo Autonomous County and other counties and cities, are characterized by a lack of developed tourism facilities, which has resulted in a lower level of resilience and a weak development situation; (3) In terms of spatial and temporal evolution, the standard deviation ellipse is stabilized year by year pointing to "northwest-southeast", the clustering tendency is gradually enhanced, and five tourism economic resilience convergence clubs are identified, whose internal transition probability is significantly affected by spatial location, and which show obvious stability and neighborhood effects; (4) Regarding the driving factors, the impact of each driving factor on the resilience of the tourism economy reaches the statistical significance threshold of 0.77 or above. Among them, the number of employees in the tertiary industry, especially the input of high-quality talents in the tourism industry, plays a key role in improving the quality of tourism services and strengthening the industry's ability to withstand risks and development potential.

Quite a number of cottonseed varieties are existed. The seeds of each variety produce a different amount of gossypol as a natural toxic compound. The increased interest in this natural product and its toxic effects were enhanced the demand for establishing simple silica-gel-based methods for its isolation, purification, and characterization. Historically, silica gel plays a significant role in isolation and purification of many different natural products. Silica gel is variants and can intro-duce a lab, simple tool for tracking a compound in certain plants during its purification process. In this study, gossypol was isolated and purified in the form of yellow crystals as gossypol acetic ac-id. Several methods and tools were used for its characterization including TLC, preparative TLC, silica gel column, UV/IR spectrophotometer and HPLC (Robust spherical silica gel). A compara-tive study between its amounts in both Egyptian and Chinese varieties were performed. Under the experimental condition, the Egyptian cottonseeds contain 8.705 gm/kg, while the Chinese contains 5.395 gm/kg. Thin Layer Chromatography (TLC) had been flourished the science of the phytochemistry and still popular till nowadays and is recommended for fast, accurate, and inex-pensive evaluation and quantification of gossypol. It is recommended to isolate and purify gossy-pol as gossypol acetic acid using optimized combined methods used in this study. Using Silica gel different protocols will assist and facilitate the parallel comparison and save the compact column from any unexpected contaminants during the purification steps. During each step the silica gel itself could be simply removed by paper filtration.

In this study, nanostructured cerium-doped TiO2 (Ce-TiO2) films with the addition of different amounts of cerium (0.00, 0.08, 0.40, 0.80, 2.40, and 4.10 wt. %) were deposited on a borosilicate glass substrate, by flow coating sol-gel process. After flow coating, deposited films were dried at the temperature of 100 °C for 1 h, followed by calcination at the temperature of 450 °C for 2 h. For the characterization of sol-gel TiO2 films, the following analytic techniques were used: X-ray diffraction (XRD), thermal gravimetry (TG), differential thermal analysis (DTA), and differential scanning calorimetry (DSC). Sol-gel derived Ce-TiO2 films were used for photocatalytic degrada-tion of the ciprofloxacin (CIP). The influence of the amount of Ce in TiO2 films, the duration of the photocatalytic decomposition, and the irradiation type (UV-A and simulated solar light) on the CIP degradation were monitored. Kinetics parameters (reaction kinetics constants and the half-life) of the CIP degradation, as well as photocatalytic degradation efficiency, were determined. The best photocatalytic activity was achieved by the TiO2 film doped with 0.08 wt.% Ce, under both UV-A, and solar irradiation.

Background: Ultraviolet (UV) radiation from the sunlight can harm skin cells, causing short-term effects, such as sunburns and long-term effects, such as pigmentation changes, changes in the skin's immune responses, and increased risk of skin cancer. These conditions can be largely prevented with proper sun protection measures and behavioural changes. This study aims to assess the knowledge on sun protection behaviour and baseline knowledge of medical students from the “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania. Methods: Data in this cross-sectional study were collected through a Google Forms questionnaire, which was distributed from November 2023 to December 2023 via digital communication channels to students across all academic years. STROBE guidelines were consulted for data synthesis; Results: A total of 668 stu-dents responded. The student cohort demonstrated a commendable level of awareness of the risks associated with sun exposure and the advantages of employing sun protection factor (SPF); how-ever, the incidence of sunburns remained notably elevated (72.3%). Further analysis revealed cor-relations among gender, academic year, presence of photosensitizing conditions, and adherence to SPF application. Additionally, there is a need to improve understanding of the appropriate appli-cation techniques for SPF, as only 11.5% of the students exhibited proficiency in this regard; Con-clusions: As future healthcare providers, medical students hold significance in promoting healthy behaviours in the broader community. This study indicates that while their knowledge about sun protection is satisfactory, there is scope for enhancement.

The high dependence on light crude oil as the main source of energy in automobiles., industrial processes, source of raw material for various industrial synthesis have made the heavy crude more available in the world and open for research work on its potentials as a source of energy for the increasing population of the world in areas like energy source for powering big marine engines, energy source in heavy industrial machines e.t.c. Though the relatively unfavourable characteristics of heavy fuel oil such as; high viscosity, high probability of precipitating is a reasonable challenge to the possible utilization of heavy fuel as a source of energy in the areas highlighted above. These issues of heavy fuel oil are largely due to the presence of Asphaltene in it which is a large complex hydrocarbon in heavy fuel oil. Understanding the combustion potential of asphaltene is therefore an interesting and challenging problem that has attracted increasing attention from both academia and industry. This research work is aimed at carrying combustion studies on the Forcados (Ni-geria) heavy fuel fraction asphaltene HFFA extracted from Forcados crude Oil and examining its combustion characteristics with the view to examine it for future sweet heavy fuel generation for it source got low sulphur content, to ascertain the volatile composition, moisture and ash content. The HFFA extracted to determine physical characteristics of the HFFA extracted for fuel properties potentialities and this study was carried out to evaluate the chemical constituents of forcadous asphaltene lead-ing to the generaration of HFFA using GCMS. The Forcados asphaltene showed some good fuel properties when subjected to ce-tane number, API gravity, flash point and cloud point parameter test. Probing further with AAS for trace metal presence showed some high concentration on Chromium (Cr), Nickel (Ni), Iron (Fe), Lead (Pb), Cadmium (Cd), Copper (Cu), Manganese (Mn) and Zinc (Zn) indicating the potential for residual and soot formation after combus-tion. But still being a sweet asphaltene from Nigerian sweet crude source will be de-void of corrosive effect on machineries and heavy fuel engine if used to power it as in the case of high sulphur content in Venezuelan crude oil and some other world. The GCMS showed the decomposition of heavy crude asphaltene peaks and sig-naling the presence of heavy fuel fraction in the composition of the asphaltene while the FTIR and the UV-VIS identified the various functional groups in the compounds and the identification of signals that cannot be seen in the normal spectrum respec-tively.

Understanding and controlling reproductive cycles and gonadal maturation in cultivated species are crucial in aquaculture. The sea urchin Paracentrotus lividus, known for its edible gonads, requires careful maturation control for both reproduction and commercialization. This study explores the impact of temperature, photoperiod, and diet on gonadal development to enhance year-round aquaculture practices. Using two independent cultivation systems, we manipulated environmental conditions to mimic different seasons. Sea urchins were exposed to natural or manipulated temperature and photoperiod conditions and fed either natural (Ulva spp.) or formulated diets. The gonadosomatic index (GI) and histological analysis assessed gonadal development. Results revealed a clear correlation between environmental conditions, diet, and gonadal maturation. Manipulated conditions accelerated maturation, with sea urchins showing advanced stages compared to natural conditions. Furthermore, sea urchins fed formulated diets exhibited higher GI values, indicating enhanced maturation. Histological analysis confirmed accelerated maturation, particularly in females. The study underscores the feasibility of controlling gonadal maturation through environmental manipulation and diet, enabling year-round marketable gonad production. Providing formulated diets rich in polyunsaturated fatty acids, notably docosahexaenoic acid (DHA), enhances commercial value. These findings optimize aquaculture practices for P. lividus, highlighting its adaptability to yield-maximizing production strategies. Understanding and controlling reproductive cycles and gonadal maturation in cultivated species are crucial in aquaculture. The sea urchin Paracentrotus lividus, known for its edible gonads, requires careful maturation control for both reproduction and commercialization. This study explores the impact of temperature, photoperiod, and diet on gonadal development to enhance year-round aquaculture practices. Using two independent cultivation systems, we manipulated environmental conditions to mimic different seasons. Sea urchins were exposed to natural or manipulated temperature and photoperiod conditions and fed either natural (Ulva spp.) or formulated diets. The gonadosomatic index (GI) and histological analysis assessed gonadal development. Results revealed a clear correlation between environmental conditions, diet, and gonadal maturation. Manipulated conditions accelerated maturation, with sea urchins showing advanced stages compared to natural conditions. Furthermore, sea urchins fed formulated diets exhibited higher GI values, indicating enhanced maturation. Histological analysis confirmed accelerated maturation, particularly in females. The study underscores the feasibility of controlling gonadal maturation through environmental manipulation and diet, enabling year-round marketable gonad production. Providing formulated diets rich in polyunsaturated fatty acids, notably docosahexaenoic acid (DHA), enhances commercial value. These findings optimize aquaculture practices for P. lividus, highlighting its adaptability to yield-maximizing production strategies.

Reducing CO2 emissions is urgently needed to slow down the impacts of climate change. CO2 capture using an amine solution has been developed and implemented on pilot and commercial scales. However, amine scrubbing, in particular, produces a lot of degraded solvent as waste and is energy intensive. Solid sorbents have been called to overcome those drawbacks. In this work, waste biomass-derived carbon materials were developed and tested for CO2 capture and conversion. Advanced thermal chemical processes i.e. hydrothermal and pyrolysis were applied to produce materials from agri-food waste such as soybean and okara. It was found that the number of functional groups (-C=O and -OH) in activated carbon appears in the synthesized materials, implying the generation of surface oxygenated groups. Preliminary results showed that the synthesized activated carbons are obtained with good yields, and a relatively high surface area, which may be applied as CO2 adsorption materials to solve the CO2 emission problems.

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics, and thermodynamic parameters of peanut shell using TGA under atmospheric air. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1. Pre-exponential factors using FWO range from 2.19×106 to 8.06×107 s–1, and for KAS range from9.72×105 to 2.25×107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤ ±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

The collaboration of multimodal transport documents is the foundation for conducting multimodal transport operations. Blockchain technology can effectively address trust issues and information sharing difficulties in current multimodal transport document collaboration. However, in current blockchain-based electronic document research, the bottleneck problem lies in the collaboration of multiparty in multimodal transport under the "one-bill coverage system". We design a blockchain platform architecture for multimodal transport, reshaping collaboration processes for different modes of transport based on the blockchain platform. It proposes a collaboration model for multimodal transport under the "one-bill coverage system" and performs model solving and case analysis. The obtained collaboration strategies are embedded into the platform's application layer. Finally, using Solidity language, it writes smart contracts related to multimodal transport under the "one-bill coverage system " and deploys and executes them on the Remix platform.

The collapsible loess will rapidly soften and lose its bearing capacity when soaked in water. Under a mild condition (20°C), the biomimetic inorganic agent, Diammonium phosphate (DAP), reacts with calcite in the collapsible loess, producing a stronger bonding material, hydroxyapatite (HAP), to modify and stabilize the soil. Uniaxial compression, permeability tests and morphological analysis using XRD and SEM/EDX microscopy were carried out to assess the effectiveness of DAP stabilization on the collapsible loess. The results indicated that HAP improved the inter-particle bonding within loess, filled the pores within particles, reduced the permeability, and consequently mitigated collapsibility of loess. The compressive strength of DAP-treated loess increased as DAP concentration increased. Following 28-days curing, the compressive strength of the loess treated with a 3.0 mol/L DAP solution was six times greater than that of the untreated group. DAP's reinforcement effect on loess was superior to that of cement. The compressive strength of DAP-treated loess was about double that of cement-treated loess and the permeability coefficient was reduced by more than 50% at equivalent solid content. Furthermore, DAP generated 68% fewer carbon emissions compared to Portland cement. Considering eco-friendly and sustainable development, DAP offers a more competitive alternative for modification and stabilization of loess.

Cholangiocellular carcinoma (CCA) is the second most common primary liver cancer, with increasing incidence worldwide and inadequate therapeutic options. Intra- and extrahepatic bile ducts have distinctly different embryonic origins and developmental behavior, and accordingly intra- and extrahepatic CCAs (ICC vs. ECC) are molecularly different. A promising strategy in oncotherapy is targeted therapy, targeting proteins that regulate cell survival and proliferation; such as the MAPK/ERK and PI3K/AKT/mTOR signaling pathways. Inhibitors of these pathways have been tested previously in CCA cell lines. However, these cell lines could not be clearly assigned to ICC or ECC, and results indicated apoptosis induction by targeted therapeutics. We tested targeted therapeutics (selumetinib, MK2206) in three defined ICC cell lines (HuH28, RBE, SSP25). We observed cooperative effects of dual inhibition of the two pathways, in accordance with inhibition of phospho-AKT and phospho-ERK1/2 expression. Proliferation was blocked more effectively with dual inhibition than with each single inhibition, but cell numbers did not drop below baseline. Accordingly, we observed G1-phase arrest, but not apoptosis (cleaved caspase-3, AIFM1 regulation, subG1-phase) or necroptosis (phospho-MLKL). We conclude that dual inhibition of MAPK/ERK and PI3K/AKT/mTOR pathways is highly effective to block proliferation of ICC cell lines, but therapy must certainly be supplemented with standard therapies.

Meat serves as a vital component of the human diet, offering a rich source of protein and essential trace elements. China stands as both a significant producer and consumer of meat on a global scale, leading the world in terms of total meat production and consumption. As the standard of living within the country continues to rise, there is a growing emphasis on the nutritional value and safety of meat consumption. The tenderness of meat is a critical factor influencing its overall quality. Traditionally, tenderness has been assessed through shear force testing, a method that is inherently destructive, inefficient, and results in considerable sample wastage. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into the application of five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations aimed at guiding the future direction of non-destructive, AI-enhanced meat tenderness detection, thereby contributing to the ongoing improvement of the meat industry in China and beyond.

The study delves into the multifaceted landscape of human-macaque conflict within temple ecosystems, with a specific focus on Bonnet Macaques. In the context of intertwined religious, cultural, and social values, understanding public attitudes towards these commensal species becomes pivotal. The research aims to decipher the socio-economic factors that shape perceptions of human-monkey conflict within temples and to explore public attitudes within sacred groves. To achieve these objectives, a comprehensive questionnaire was administered through household interviews to 100 residents living within both a 1 sq. km and a 2 sq. km radius of the study area, ensuring direct participant interaction. The survey, taking approximately 40 minutes per participant, examined six variables, including occupation, religion, and annual income. The data collected was analysed using SPSS ver. 24 software, employing the chi-square test of independence to explore associations between categorical variables. The findings revealed that occupation and religion emerged as influential factors in shaping perceptions of Bonnet Macaques as problematic. While annual income hinted at significance, age, education, and knowledge of Kysannur Forest Disease (KFD) did not significantly impact Bonnet Macaque perception. Interestingly, age emerged as a significant factor influencing the perception of the monkeys' religious significance, whereas only education and religious affiliation impacted feeding practices towards the monkeys. Surprisingly, other demographic variables such as age, gender, occupation, and income showed no significant influence on monkey feeding practices. These results underscore the intricate interplay of socioeconomic, cultural, and religious factors in shaping public attitudes and behaviours towards Bonnet Macaques. The study further sheds light on the impact of education and religious affiliation on feeding practices, emphasizing the need for nuanced conservation strategies. Recognizing these complexities is crucial for developing culturally sensitive conservation efforts. By acknowledging the influential factors identified in this research, conservation strategies can be tailored to specific communities, fostering harmonious coexistence between humans and Bonnet Macaques in temple ecosystems. This nuanced approach ensures that conservation efforts are not only effective but also respectful of the diverse socio-cultural contexts within which they are implemented.

Arboviruses are infections caused by arboviruses that may be either symptomatic or asymptomatic, according to individuals' resistance and immune response, which dietary patterns can influence. Thus, this study aimed to investigate the possible association between the occurrence of clinical manifestations of arboviruses and the dietary pattern of the population studied. The study was conducted in a rural population in the metropolitan area of Belém, Pará State, Brazil. The sampling consisted of 95 individuals during a febrile outbreak. Two investigations were conducted: clinical-epidemiological-dietary and laboratory investigation based on blood samples taken for arbovirus analysis. Out of the 95 individuals studied, more than half (57.89%) showed clinical manifestations. Following the laboratory serology (HI and IgM ELISA) analyses, viral isolation in C6/36 cells, and viral genome detection (RT-qPCR), the final diagnosis of the cases was 47.37% Oropouche Fever, 2.11% Oropouche Fever and Chikungunya Fever, and 1.05% Mayaro Fever. Regarding dietary pattern, as for the comparison analyses, statistical significance was observed between dietary pattern and classification regarding the presence of symptoms (p<0.05); after the correspondence analysis, symptomatic cases were more associated with a bad dietary pattern, while asymptomatic cases were more associated with a good dietary pattern.

This study aimed at testing the effectiveness of novel combinations of chemical and physical methods to control Prosopis juliflora, an invasive weed in the Moshi and Simanjiro districts of Nothern Tan-zania. Six different treatments including manual uprooting, glyphosate, bark chop with chemical application, two separate chemical mixtures and control were tested in a total of 32 plots, which represented two land use types (grazing land and farmland) found in the two districts. Each plot covered 20m×30m plot area. Two response variables (stem count and tree volume) were recorded to compare weed population density before and after treatment six months later. An analysis of the untreated control plots, showed that the inherent growth potential of P. juliflora was higher in Moshi than in Simanjiro district. The number of stems increased during the experiment for all six treatments showing that the P. juliflora population had not yet reached the local carrying capacity. For the manual control treatment, the increase was reduced compared to the untreated control. For all other treatments, the increase in stem count was on par with that in the untreated control or even higher. Thus, we conclude that only manual uprooting had a controlling effect but not to the extent that it eradicated P. juliflora. Thus, it is for P. juliflora as for weed control in general: weed control must be an ongoing effort.

Carbon dioxide (CO2)miscible fracturing huff and puff technology plays a pivotal role in enhancing the recovery rate of crude oil, particularly in reservoirs with challenging physical properties, strong water sensitivity, high injection pressure, and complex water injection dynamics. In this study, the oil-increasing mechanism and huff and puff effect of CO2 miscible fracturing fluid are investigated through a comprehensive experimental approach. Specifically, experiments on PVT gas injection expansion, minimum miscible pressure, and CO2 miscible fracturing huff and puff are conducted on the G fault block reservoir in J Oilfield. The findings demonstrate that injecting CO2 into reservoirs leads to oil volume expansion, viscosity reduction, and saturation pressure increase. Additionally, the inclusion of solubilizers and viscosity reducers further enhances the efficiency of crude oil extraction. Solubilizers not only improve oil recovery but also reduce the minimum miscible pressure required for effective CO2 dispersion. Furthermore, the shut-in time, permeability, and huff and puff method all have considerable impacts on huff and puff recovery rate. This study offers valuable technical insights, supporting the application of CO2 miscible fracturing huff and puff technology to enhance oil recovery in low-permeability reservoirs.

In this follow-up study, we aimed to assess the effectiveness of the “I do not smoke, I exercise”, anti-smoking preventive health education program. The program was based on the Theory of Planned Behavior supplemented with life-skills teaching and targeted at high school students. The intervention comprised ten one-hour online sessions, administered by physical education instructors. The study cohort comprised 222 students (109 boys, 113 girls) from 11 secondary schools, with an average age of 16.42 ± 1.36 years. Data collection involved pre- and post-intervention self-assessment questionnaires. The examined variables included attitudes towards smoking, intention to smoke, subjective norm, perceived behavioral control (PBC), knowledge about smoking, smoking behavior, exercise behavior, attitudes toward the program's implementation, and satisfaction with the program. Separate paired samples t-test revealed a significant improvement in students' knowledge about smoking, perceived behavioral control, and overall program satisfaction following the intervention. However, no significant changes were observed in the remaining variables. These findings suggest that the health education smoking prevention intervention incorporates techniques and strategies that influence the Perceived Behavioral Control variable, emphasizing students' strong interest in educationally theorized programs integrating technology into their design. Future studies should consider further examination of tobacco control strategies within the high school context.

Despite saltmarshes being considered as nature-based solutions (NbS) towards climate change mitigation, India’s saltmarsh ecosystems are least studied. This study quantifies the seasonal variation in carbon stocks mono-specific saltmarsh species (Porteresia coarctata) and its potential to play an important role in India’s climate change mitigation plans. Seasonal (pre-and post-monsoon) sampling of P. coarctata surface water, biomass and 30 cm sediment core was collected across four locations on the east coast of India to quantify sediment dry bulk density (DBD), organic matter (OM%), organic carbon (Corg%), Corg stocks of sediment and biomass, total carbon (C%) and nitrogen (N%) and stable isotopes of δ13C and δ15N. In general, the sediment DBD, OM and Corg of P. coarctata meadows was higher in post-monsoon and was influenced by salinity and pH changes. Isotope (δ¹³C) modelling of various sediment C sources suggested, particulate organic matter (POM) contribution was highest (0.04-0.79%) followed by P. coarctata (0.01–052%) and other macrophytes across our study locations. The seasonal variation of δ¹³C showed increased contribution of marine derived particulate and dissolved organic matter into P. coarctata meadows in post-monsoon season. Heavier δ¹⁵N values were observed in post-monsoon season suggesting anthropogenic input, that was utilized by P. coarctata to increase its above and below-ground biomass and shoot density. The combined ecosystem (30 cm sediment + biomass) Corg stocks of P. coarctata was 1.7-fold higher in post-monsoon (4021.20± 917 Mg C) compared to pre-monsoon (2297.36 ±647 Mg C) season among the four locations with a sediment Corg contribution >70%. Based on the International Panel for Climate Change Tier II assessment the P. coarctata meadows (443 ha) can help in avoiding the pre and post-monsoon emissions of 8431.34 and 14757.84 Mg CO₂ respectively. The combined price of the total CO₂ equivalent stored in P. coarctata meadows in pre- and post-monsoon is US$ 14.50 and US$ 25.38 million respectively. Further studies quantifying the NbS potential of P. coarctata mono-specific and mixed meadows of India’s coast is needed along with integration of saltmarsh ecosystems into India’s National Action Plan on Climate Change.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

Background: Gender stereotypes and biases can influence perceptions of competence and suitability for certain medical specialties. Empathy is an important component of an optimal doctor-patient relationship. The scope of our study is to verify the correlation between “empathetic" behavioral style with attention and sensibility to the gender differences of patients of the medical students. Methods: An online survey was conducted using the Jefferson Scale for Empathy (JSE), to measure empathy in the context of health professions education and patient care; and the Nijmegen Gender Awareness in Medicine Scale (N-GAMS), which measures attitudes and assumptions about gender. A total of 234 students (52.1% M; mean age: 22.68±2.48) from Medicine and Surgery at the University of Salerno (Italy) participated, of whom n° 175 were third-year students and n° 59 were fifth-year students. Results: The JSE score shows that male students have higher scores (77.29±12.38) than females (75.91±10.39). Conversely, female students have higher perspective-taking (JSE Factor 1: Male= 51.26±11.84; Female= 52.72±11.88). In addition, third-year students are much more empathetic than their fifth-year colleagues (JSE Score: 3°ys= 77.35±11.46; 5°ys= 74.49±11.33). With reference to the GS, we found that male students have greater sensitivity than their female colleagues (GS: Male= 2.67±0.68; Female= 2.37±0.48); conversely, they have higher scores of gender stereotype towards patients (GRIP: Male= 2±0.88; Female= 1.59±0.61) and doctors (GRID: Male= 1.88±0.89; Female= 1.64±0.63). Also, the third-year students compared to their fifth-year colleagues are characterized by greater gender sensitivity (GS: 3°ys= 2.57±0.62; 5°ys= 2.42±0.57), less bias with respect to patients (GRIP: 3°ys= 1.77±0.79; 5°ys= 1.90±0.78) but, on the other hand, show more stereotypes and prejudices towards doctors (GRID: 3°ys= 1.77±0.81; 5°ys= 1.75±0.74). Conclusions: Humanistic attitudes, including empathy, should be instilled, and evaluated among trainees as an essential part of their postgraduate medical education.

Good governance in natural resource management (NRM) is one of the most challenging issues in developing countries that often inappropriately embedded in national policies and political agendas. It is, in fact, even more important for countries like Bangladesh with exceptionally high pressure and dependence on its natural resources for sustaining rural livelihoods. Globally, nowadays, good governance is considered as one of the key factor for achieving the goal of sustainable development and biodiversity conservation. Bangladesh, of late has responded to that global zeal by involving local communities in the management of country’s declining forest and other natural resources. The colonial legacy of the forestry sector of Bangladesh was planned and, managed as interim projects through donors’ prescriptions. Thus, institutions, management processes and conservation outcomes were problematic. The conventional approach adopted by colonial and post-colonial regimes for forest management also proved to be inefficient due to its top-down management system. The absolute dependency on donor support, and their prescription sometimes worsened the situation both ecologically and socially. Global, regional and local trends supported the need for a different dimension in the governance paradigms. The introduction of a pluralistic approach, known as co-management in protected areas (PAs) is an example of an attempt whereby shared governance mechanism are implemented to attain the desired goals of conservation that will also address the livelihoods and aspirations of communities living in and around PAs of the country. However, in designing future forest and PA regimes the concern of the external aid support and attached conditions remain a reality that needs to be addressed. Adequate attention should be given to our vanishing biodiversity, culture and community livelihoods through devising an appropriate governance mechanism recognizing and supporting local rights, access and participation in the environmental management. It is now time to mainstream the adhoc nature of governance according to our national conservation strategy and policy frameworks in order to achieve the goals and objectives of the Bangladesh NRM sector addressing the human and community right of people in the specific context of forest protected areas management.

"Public legal information from all countries and international institutions is part of the common heritage of humanity. Maximizing access to this information promotes justice and the rule of law". In accordance with the aforementioned declaration on Free Access to Law by Legal information institutes of the world, a plethora of legal information is available through the Internet, while the provision of legal information has never before been easier. Given that law is accessed by a much wider group of people, the majority of whom are not legally trained or qualified, diversification techniques, should be employed in the context of legal information retrieval, as to increase user satisfaction. We address diversification of results in legal search by adopting several state of the art methods from the web search, network analysis and text summarization domains. We provide an exhaustive evaluation of the methods, using a standard data set from the Common Law domain that we subjectively annotated with relevance judgments for this purpose. Our results i) reveal that users receive broader insights across the results they get from a legal information retrieval system, ii) demonstrate that web search diversification techniques outperform other approaches (e.g., summarization-based, graph-based methods) in the context of legal diversification and iii) offer balance boundaries between reinforcing relevant documents or sampling the information space around the legal query.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

This article provides a comprehensive overview of lung cancer from a genetic perspective, emphasizing the molecular pathways involved in its pathogenesis. This review presents the genetic syndromes and key genomic variations, including alterations and instabilities, that contribute to tumor development and progression. Furthermore, advancements in genomic testing, such as liquid biopsy, are explored, highlighting their utility in early diagnosis, prognostic evaluation, and personalized treatment strategies. The role of biomarkers in informing therapeutic decisions and optimizing patient outcomes is also examined, offering insights into their potential to refine clinical interventions. This review aims to enrich the understanding of the genetic landscape of lung cancer, providing insights that may lead to improved diagnostic and therapeutic approaches.

The valorization of aquaculture/fisheries processing by-products, as well as unavoidable/unwanted catches and discards in Greece is currently an underutilized activity despite the fact that there are several best practices in Northern Europe and overseas. One of the main challenges is to determine whether the available quantities for processing are sufficient to warrant valorization of discards and fish side streams. This is the first attempt to systematically record and analyze the available quantities of fish by-products and discards in Greece in a spatial and temporal way in an effort to create a national exploitation Master Plan for the valorization of this unavoidable and unwanted biomass. A thorough survey conducted within the VIOAXIOPIO project unveiled a substantial biomass of around 19,000 tonnes annually that could be harnessed for valorization. Furthermore, the production of various High Added Value Biomolecules (HAVB) was investigated, and experimental trials were conducted to assess the potential yields and the collected data were used to formulate four valorization scenarios.

This study aimed to investigate the potential of Cord Blood Stem Cell-derived exosome vesicles (CBSC-EVs) in regulating cancer growth and preventing cellular damage. The study aimed to examine the effects of CBSC-EVs on CHL1 cancer cells and healthy fibroblasts. The study results reveal that CBSC-EVs have an anti-cancer/antioxidant effect on CHL1 cancer cells without inducing any toxic effects on healthy lymphocytes. Further analysis of CBSC-EVs revealed the presence of seven miRNAs (noncoding RNA molecules), including three from the Let 7 family, two from the Let 5 family, and two novel miRNAs. The function of the novel miRNAs was the main focus of the study. To assess the efficacy of CBSC-EVs, CHL1 cells (a type of malignant melanoma cell line) and human fibroblasts were grouped into different treatments. One group of those cell lines were treated with CBSC-EVs, and in the second group, the cells were transfected with either miRNA inhibitor Novel 1 (miRNA IN1) plus CBSC-EVs or miRNA inhibitor Novel 2 (miRNA IN2) and CBSC-EVs to knock down those novel miRNAs in the CBSC-EVs. Therefore, by comparing these groups, the function of novel miRNAs is more understandable. In this study, the Comet assay was employed to evaluate cancer cells' DNA damage and CCK8 to measure cell viability. The findings revealed that CBSC-EVs caused an increase in DNA damage in CHL1 cells compared to cells without treatment (p

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

In the era of mounting water scarcity, particularly in arid regions, the agricultural sector is striving to optimize the water resource management practices. Treated wastewater (TWW) has emerged as a viable alternative to freshwater for irrigation, offering a sustainable solution to water conservation. However, ensuring the safety and quality of TWW is paramount to safeguard for both crop health and environmental integrity. Electrical conductivity (EC), a critical factor in assessing TWW suitability for irrigation, can significantly impact crop yields and soil health since it is directly linked to the concentration of dissolved salts and ions. Therefore, this study delves into the development of advanced predictive models for EC assessment by employing supervised machine learning (ML) techniques like the Support Vector Regression (SVR), Adaptive Network-based Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR). The TWW samples collected from Al-Qatif area, Saudi Arabia were assessed in the lab through a sensor-based real-time monitoring system integrated with Internet of Things (IoT) network and a multiprobe device. The key water quality parameters assessed involved, temperature (T), pH, Oxidation Reduction Potential (ORP), Resistivity (RES), Total Dissolved Solids (TDS), Salinity and Turbidity which served as the foundation for these models, given their profound influence on and their anticipated impact on EC levels. Following feature selection, two distinct model combinations were identified for the SVR, ANFIS and MLR models. Furthermore, to evaluate prediction performance, four statistical criteria, including coefficient of determination (R²), correlation coefficient (R), mean square error (MSE), and root mean square error (RMSE), were employed. Overall, the comparative performance results proved that ANFIS-M2 indicated the strongest predictive capability with the R² value of 0.99572 and 0.75145 and the RMSE values of 0.00965 and 0.01134, respectively in both calibration and verification stages.

Background/Objectives: The global burden of colorectal cancer (CRC) is projected to increase by 2040, highlighting the need for prevention strategies, early detection and adequate follow. The aim of this study was to provide an overview of the progress in personalized medicine of CRC in Serbia, with results and insights from the Institute for Oncology and Radiology of Serbia (IORS), and to propose guidance for tackling observed challenges in the future. Methods: Epidemiological data was derived from official global and national cancer registries and IORS electronic medical records. Germline genetic testing for Lynch syndrome was performed by Next Generation Sequencing. RAS and BRAF mutation analyses were performed using qPCR diagnostic kits. Results: Epidemiology and risk factors, prevention and early detection programs, as well as treatment options and scientific advances have been described in detail. Out of 103 patients who underwent germline testing for Lynch syndrome, 19 (18.4%) had a pathogenic or likely pathogenic mutation in one of the MMR genes, and 8 (7.8%) in other CRC-associated genes (APC, CHEK2, MUTYH). Of 6369 tested patients, 50.43% had a mutation in KRAS or NRAS genes, while 9.54% had the V600 mutation in the BRAF gene. Conclusions: Although significant improvements in CRC management have occurred globally in recent years, the high incidence of young-onset CRC and the growing elderly population due to a rise in life expectancy require a strategic approach leading to population-based systemic solutions, especially important for countries with limited health care resources as Serbia.

Purpose: This study aimed to identify the risk factors for acute pancreatitis (AP) and its impact on outcomes in Polish children treated for ALL. Methods: The study group included 2303 children who received intensive chemotherapy for ALL. The group was subdivided into patients with at least one episode of AP and those who did not develop AP following treatment for ALL. Results: The cumulative incidence of AP in the study group was 4.08%. Older age was an independent risk factor for AP development (OR 1.05; 95%CI: 1.006 – 1.098; p=0.03). The overall mortality related to AP was 2.13%. The probabilities of disease-free survival (p-DFS) and event-free survival (p-EFS) were 0.84 vs. 0.86, log-rank: p=0.65 and 0.75 vs. 0.80, log-rank: p=0.12, respectively in both subgroups. A total of 22 out of 94 patients (23.4%) with AP were re-exposed to asparaginase (ASP) during the subsequent phases of the treatment. Only one re-exposed to ASP patient (4.5%) developed a second episode of AP. There were no significant differences in p-DFS and p-EFS between patients re-exposed and not re-exposed to asparaginase (0.78 vs. 0.86, log-rank p=0.27 and 0.63 vs. 0.79, log-rank p=0.09 respectively). Conclusions: The incidence of AP in children with ALL is low and related to the patient’s age. AP development doesn’t seem to impact p-DFS and p-EFS in children with ALL. The recurrence of AP following re-exposure to asparaginase in patients with ALL and a history of AP is low (4.5%). Re-exposure to asparaginase after the first episode of AP doesn’t improve either p-DFS or p-EFS in children with ALL.

One of the foundations of Smart Cities is mobility. To manage the efficiency of urban mobility, continuous recording of traffic flows is essential. The road traffic parameters in the cross section of the road network can be registered with the use of various measurement technologies. This is indirectly due to the complexity of the phenomenon of vehicle traffic and the disturbances in physical quantities generated as a result of it. Traffic data carries: sound waves, vibrations, optical waves and other media. The characteristics of these physical media, properly recorded and mathematically transformed, may constitute a superposition of the position of individual vehicles moving in the traffic flow. Moreover, these waves interfere with each other depending on the observed parameters of the movement of individual vehicles at different places of the network. In this context, information obtained from various media is the overall view of traffic. This article focuses on acquiring infrared traffic data. The movement of each vehicle, regardless of its type, is inextricably linked to infrared radiation, the distribution changing as a function of the road network. Each vehicle is a source of heat and therefore also emits infrared radiation (it heats up gradually while driving, with small temperature fluctuations). Therefore, the temperature of a moving vehicle is generally different from the background (road network) temperature. This article presents a successful attempt to analyze the infrared radiation accompanying road traffic in a selected cross section of the road. In order to register infrared radiation in the traffic stream, a prototype of a measuring system consisting of a pyrometer commonly used in thermometers (cost about 10 € and less) was used. Measurements of infrared radiation of the vehicle stream obtained in this way were compared with the measurement data of handheld traffic recorders, the so-called mechanical vehicle counters. The comparison of the results from both recording methods allows for the formulation of further research hypotheses towards extended research in the field of infrared radiation of the traffic stream. In this regard, it is important to research with various disturbances in the measurements that come from other heat sources located in the road network and its immediate vicinity. This study is important from the point of view of smart cities and C-ITS systems (mainly V2I communication). The registration of data describing the traffic flow with the use of a single pyrometer, instead of an expensive IR camera, is a cheap alternative in modern city information networks. This allows you to create intelligent sensor networks using connectivity based on, e.g., mesh networks. Such activities are possible with costs for one measuring point reduced by one or two orders of magnitude compared to the costs incurred with the use of IR cameras ( € 1000, € 10,000 and more). In the current situation of the energy crisis, the search for innovative solutions with lower energy demand is very important in the Smart City policy.

Introduction: Lumbar radiculopathy, frequently triggered by disc herniation, affects around one in 50 young adults (30-55 ages), leading to significant impacts on quality of life. When conservative treatments fail to alleviate symptoms, surgical intervention such as discectomy is often pursued. Technological advancements have led to various minimally invasive techniques, promising improved outcomes. Our aim was to compare clinical outcomes of different techniques. Methods: We conducted a systematic search in PubMed using "lumbar disc hernia" and the meta-analysis filter. Inclusion criteria comprised meta-analyses focusing on lumbar disc herniation treatments, published in English. A rigorous selection process adhering to PRISMA guidelines ensured high-quality evidence extraction. Results: From 28,171 initial records, 31 meta-analyses involving 87,852 patients were included. Heterogeneity across the literature presented challenges, notably in study populations, surgical techniques, and research designs. Among the techniques evaluated, full-endoscopic lumbar discectomy (FELD) emerged as superior in various perioperative parameters, including Visual Analog Scale (VAS) scores, Oswestry Disability Index (ODI), operation time, and complications. Conversely, automated percutaneous discectomy (AUTD) consistently exhibited poorer outcomes, suggesting limited effectiveness compared to other techniques. Conclusion: Despite advancements, the heterogeneity observed in the literature underscores the need for standardized approaches in minimally invasive spinal surgery research. FELD stands out as a preferred technique, offering favorable outcomes across multiple parameters. Conversely, techniques like AUTD raise concerns regarding efficacy. Future research should aim for uniformity in methodologies to facilitate accurate comparisons and guide clinical decision-making.

In the delicate context of climate change and global warming new technologies are being investigated in order to reduce pollution. The solid oxide fuel cell (SOFC) stands out as one of the most promising fuel cell technologies for directly converting chemical energy into electrical energy, with the added benefit of potential integration into co-generation systems due to its high-temperature waste heat. They also offer multi-fuel flexibility, being able to operate on hydrogen, carbon monoxide, methane, and more. Additionally, they could contribute to carbon sequestration efforts and, when paired with a gas turbine, achieve the highest efficiency in electricity generation for power plants. However, their development is still challenged by issues related to high-temperature materials, the design of cost-effective materials and manufacturing processes, and the optimization of efficient plant designs.To better understand SOFC operation, numerous mathematical models have been developed to solve transport equations coupled with electrochemical processes for three primary configurations: tubular, planar, and monolithic. These models capture reaction kinetics, including internal reforming chemistry. Recent advancements in modeling have significantly improved the design and performance of SOFCs, leading to a sharp rise in research contributions. This paper aims to provide a comprehensive review of the current state of SOFC modeling, highlighting key challenges that remain unresolved for further investigation by researchers.

Molecular inhibitors added to the corrosive medium attacking metallic materials are a well-established way of combating corrosion. The inhibitive action proceeds via adsorption of the inhibitor on the surface to be protected. Aromatic building blocks in the inhibitor play a major role in their protective action, further details like substituents, heteroatoms and molecular geometry contribute. An overview is provided focused on aromatic inhibitors aiming at the identification of particularly promising inhibitors and their mode of action. Directions of further research and development are pointed out in conclusion.

Cancer ranks second among the causes of mortality worldwide,following cardiovascular diseases.Brain cancer, in particular, has lowest survival rate of any kind of cancer. Brain tumours vary in their morphology, texture, and location, which determine their classification. Accurate diagnosis of the tumour category enables physicians to select optimal treatment strategies and potentially prolong patients’ lives. Researchers who also implemented deep learning models for diagnosing diseases in recent years largely focused on deep neural network optimization to enhance neural network performance. This implicates implementing models with the best performance and incorporating various network architectures by configuring their hyperparameters. This paper presents a novel hybrid approach method for improved brain tumour classification by combining CNN and EfficientNetV2B3 as feature extraction, followed by (KNN) for classification. To evaluate the recommended method’s efficacy, two widely known benchmark MRI datasets were utilized in the experiments. The initial dataset consisted of 3064 MRI images depicting meningiomas,pituitary,and gliomas tumours.Images from two classes of normal brain and brain tumour were included in the second dataset, which was obtained from Kaggle.In order to enhance performance even more, the study concatenates the CNN and EfficientNetV2B3 flattened outputs before feeding them into the KNN classifier. The proposed framework run on two different dataset and demonstrates outstanding performance with an accuracy of 99.51% and 99.8% on each dataset.

The experimental investigation of plant growth under space conditions is a necessary prerequisite of long-term space missions. Besides experiments in space, many studies are performed under simulated microgravity, using a clinostat. However, the Earth magnetic field is usually not taken into account in such investigations. Here, a self-designed and constructed system of coupled devices – a clinostat and a Helmholtz cage – is presented. The clinostat can, on the average, cancel the effective gravity field by using two independent rotations, enabling simulated zero-valued gravity experiments. Additionally, appropriately symmetrically mounted Helmholtz cage can be used to cancel the natural Earth magnetic field in the volume where the clinostat is located. The combination of these two devices offers the opportunity, e.g. for bio-inspired experiments in which plant cultivation can be carried out in conditions that imitate space environment. We provide information about the experimental setup and show first experimental results of growth tests.

Beliefs that maintain patriarchal principles may affect individuals’ willingness to avoid conflicts in their intimate partner relationships and eventually are likely to affect chances of intimate partner economic violence. Nonetheless, research has yet to fully explore these associations. This study used a sample of 321 adults in the ultra-Orthodox Jewish community—a patriarchal and traditional culture—to examine associations in beliefs supporting patriarchal principles at the micro (gendered domestic roles), meso, and macro ( institutional power of men and inherent inferiority of women) levels; conflict avoidance and economic violence; and sex differences in these factors. Descriptive statistics were used to explore gender differences in research variables, and path analysis examined the correlations between research variables for men and women. Beliefs in patriarchal ideologies were moderate at all levels, although slightly higher among men. Men tended to avoid conflict with their intimate partner significantly more than women did. Beliefs in support of patriarchal ideologies predicted conflict avoidance, especially among women. Finally, in opposition to prior research findings, this study revealed nonsignificant sex differences in the prevalence of economic violence victimization. These findings, however, do not suggest that economic violence victimization is not rooted in sex issues. We discuss the findings and the meanings assigned to conflict avoidance by men and women while considering gender disparities of power and control. We suggest that the contribution of men’s tendency to avoid conflict likely moderated their chances to perpetrate economic violence.

The article focusses on detecting the unbalance of a mechanical component in the electric drive system of a two-mass servomechanism with a PMSM motor, which is connected to the load via a long, flexible shaft. In the example analysed, the degree of unbalance was determined using the reference current signal from the speed controller of the FOC control system. The authors pre-sented a two-mass model with an unbalanced mechanical system. The STFT transform was used to analyse the symptoms of unbalance and an artificial neural network MLP was used for system state inference. The effectiveness of the presented analysis, based on the reference current signal from the sensor embedded in the control system, was experimentally confirmed.

This paper proposes a novel hybrid control strategy for quadrotor unmanned aerial vehicles (UAVs) based on bio-inspired neural dynamics. This strategy addresses the velocity jump issue prevalent in traditional backstepping control and the control signal chattering problem common in traditional sliding mode control. The control system comprises an outer-loop bio-inspired backstepping controller and an inner-loop bio-inspired sliding mode controller, ensuring smooth trajectory tracking even in the presence of external disturbances. The stability of the quadrotor UAV control system is rigorously analyzed using Lyapunov stability theory. Extensive comparative simulation experiments are conducted to assess the robustness and effectiveness of the control system. Results demonstrate superior trajectory tracking performance of the proposed control system compared to other control systems for quadrotor UAVs.

In this paper, we investigated the formation isolation regulation issue regarding multiple autonomous underwater vehicles (AUVs) characterized by a "leader-follower" framework. Considering the cooperative-competitive relationship among the follower AUVs and the impact of unknown external disturbances, an extended state observer was designed based on backstepping to mitigate these disturbances, and an event-triggered control scheme was designed to realize the two-part consensus control within the multi-AUV system. Through rigorous theoretical analysis, it is shown that the system achieves asymptotic steadiness and is free from zeno behavior under the proposed event-triggered control scheme. Finally, numerical simulations confirm the efficiency of the regulation strategy in achieving formation separation within the multi-AUV, where the trajectory tracking errors of individual AUVs gather in a compact vicinity close to the source and the structure converges was achieved, with the absence of zeno behavior also demonstrated.

Violence against healthcare workers (HCWs) is a widespread, underreported and inadequately prevented problem. Only a few companies have efficient systems for assessing the extent of the phenomenon. In 2005, the health surveillance service of a public health company introduced a system that monitored violence experienced by HCWs by means of three items from the Violent Incident Form (VIF), integrated with departmental in-depth analyses using the participatory ergonomics group technique. In 2005, the annual rate of physical assaults was 8.2%, that of threats 12.0%, while the harassment rate was 19.6%. Over the past twenty years of observation (2005-2024), the percentage of workers who reported experiencing a physical attack in the previous year at their periodic medical examination, has fluctuated between 5.8% and 11.1%, except for the years 2020 and 2021 when, during the COVID-19 pandemic, the rate was 3.9% and 3.2%, respectively. During the same pandemic period, the annual threat rate that ranged from 9.4% to 20.1%, dropped to 7.7%, while the prevalence of harassment, that was between 13.5 and 19.6, fell to 7.2%. HCWs believe that (i) limiting visitor access (ii) a better balance of the demand for services and (iii) a better attitude towards HCWs were the causes of the reduced rate of violence during the pandemic. Recording the violence experienced during health surveillance is an economical, reliable and sustainable risk assessment method.

The autonomous displacement and displacement measurement functions of the maglev ruler are performed by the mover core. The stability of the four magnetic field in air gaps and the levitation position of the maglev ruler is one of the key factors for the stability of the thrust force on the power core, and it is also one of the key factors for ensuring the precision of the maglev ruler. There is cross-coupling between the two ends of the mover core of the maglev ruler, resulting in a strongly coupled, nonlinear, multi-input and multi-output system for the levitating system of the maglev ruler. This paper establishes a mathematical model for the levitating system of the maglev ruler, and designs a levitating control system for the maglev ruler based on ADRC control algorithm to achieve decoupling and disturbance suppression. Through simulation analysis and experimental testing of the levitating system with starting and disturbance, it is proved that the levitating control system of the maglev ruler has good dynamic characteristics, static characteristics, and robustness.

Glaucoma, a global leading cause of blindness, necessitates accurate segmentation of the optic disc (OD) and optic cup (OC) for effective screening. However, existing segmentation methods based on convolutional neural networks (CNNs) suffer from high computational complexity and long inference times. In this paper, we propose an end-to-end segmentation method for the OD and OC using a lightweight MobileNetv3 as the feature extraction network. Our approach incorporates boundary branches and an adversarial learning network to achieve multi-label segmentation of the OD and OC. We evaluate the proposed method on three publicly available datasets: Drishti-GS, RIM-ONE-r3, and REFUGE. The experimental results demonstrate segmentation accuracies of 0.974/0.900, 0.966/0.875, and 0.962/0.880 for the OD and OC on the respective datasets, while significantly reducing inference time.

Geopolymers, made from aluminosilicate raw materials, offer significant environmental advantages over conventional concrete (CC) mixes. This study explores the compressive strength, setting time, and durability of geopolymer concrete (GPC) cylinders, some of which include an additional ordinary portland cement (OPC) mix. Consistent material composition and testing methods are emphasized to achieve reliable results. MATLAB was utilized to develop and assess a neural network model predicting the compressive strength of GPC based on key variables. The model was validated using 16 experimental samples and 1047 samples from various studies. The performance plot displayed the Mean Squared Error (MSE) over iterations, identifying the best training performance at epoch 658 with an MSE of 5.3408. The Error Histogram highlighted distribution errors between predicted and actual compressive strength values, with the highest range from -1.015 to 0.3587, meaning that the predicted values were mostly within a small margin of error from the actual values. This narrow error range indicates that the ANN model has high accuracy in its predictions, as most errors are small and clustered around zero, demonstrating reliable performance in estimating compressive strength. Regression analysis showed varying correlation coefficients (training set R=0.98373, test set R=0.88164, and whole set R=0.96982), indicating adequate predictive accuracy. The results demonstrate that properly trained neural networks can effectively predict the compressive strength of GPC, highlighting its potential as a sustainable construction material.

Background: In recent years, computational aesthetics and neuroaesthetics have provided novel insights into understanding beauty. Building upon the findings of traditional aesthetics, this study aims to combine these two research methods to explore an interdisciplinary approach to studying aesthetics; Method: Abstract artworks were used as experimental materials. Based on traditional aesthetics and in combination, features of composition, tone, and texture were selected. Computational aesthetic methods were then employed to correspond these features to physical quantities: blank space, gray histogram, GLCM, LBP, and Gabor filters. An EEG experiment was carried out, in which participants conducted aesthetic evaluations of the experimental materials in different contexts (genuine, fake), and their EEG data was recorded to analyze the impact of various feature classes in the aesthetic evaluation process. Finally, a SVM was utilized to model the feature data, EEG data, context data, and subjective aesthetic evaluation data; Result: Behavioral data revealed that higher aesthetic ratings in the genuine context. EEG data indicated that genuine contexts elicited more negative deflections in the prefrontal lobes between 200-1000ms. Class II compositions demonstrated more positive deflections in the parietal lobes at 50-120ms, while Class I tones evoked more positive amplitudes in the occipital lobes at 200-300ms. Gabor features showed significant variations in the parieto-occipital area at an early stage. Class II LBP elicited a prefrontal negative wave with a larger amplitude. The results of the SVM models indicated that the model incorporating aesthetic subject and context data (ACC=0.76866) outperforms the model using only parameters of the aesthetic object (ACC=0.68657); Conclusion: A positive context tends to provide participants with a more positive aesthetic experience, but abstract artworks may not respond to this positivity. During aesthetic evaluation, the ERP data activated by different features show a trend from global to local. The SVM model based on multimodal data fusion effectively predicts aesthetics, further demonstrating the feasibility of the combined research approach of computational aesthetics and neuroaesthetics.

Background: Symmetry is a special kind of balance. This study aims to systematically explore and apply the role of balanced composition in aesthetic judgments by focusing on balanced composition features and employing research methods from computational aesthetics and Neuroaesthetics. Methods: First, experimental materials were classified by quantifying balanced composition using several indices, including symmetry, center of gravity, and negative space. An EEG experiment was conducted with 18 participants, who were asked to respond dichotomously to the same stimuli under different judgment tasks (balance and aesthetics), with both behavioral and EEG data being recorded and analyzed. Subsequently, participants' data were combined with balanced composition indices to construct and analyze various SVM classification models. Results: Participants largely used balanced composition as a criterion for aesthetic evaluation. ERP data indicated that from 300-500ms post-stimulus, brain activation was more significant in the aesthetic task, with unbeautiful and imbalanced stimuli eliciting larger frontal negative waves and occipital positive waves. From 600-1000ms, beautiful stimuli caused smaller negative waves in the PZ channel. The results of the SVM models indicated that the model incorporating aesthetic subject data (ACC=0.9989) outperforms the model using only balanced composition parameters of the aesthetic object (ACC=0.7074). Conclusions: Balanced composition is a crucial indicator in aesthetics, with similar early processing stages in both balance and aesthetic judgments. Multimodal data models validated the advantage of including human factors in aesthetic evaluation systems. This interdisciplinary approach not only enhances our understanding of the cognitive and emotional processes involved in aesthetic judgments but also enables the construction of more reasonable machine learning models to simulate and predict human aesthetic preferences.

Cancer cells can release EGF-like peptides, acquiring the capacity of autocrine stimulation via EGFR-mediated signaling. One of these peptides (HBEGF) was found to be released from a membrane-bound precursor protein, and is critically implicated in the proliferative potential of cancer cells. We observed that the increased lactate levels characterizing neoplastic tissues can induce the release of uPA, a prote-ase promoting HBEGF shedding. This effect led to EGFR activation and increased ERK1/2 phosphoryla-tion. Since EGFR-mediated signaling potentiates glycolytic metabolism, this phenomenon can induce a self-sustaining deleterious loop, favoring tumor growth. A well characterized HBEGF inhibitor is CRM197, a single-site variant of diphtheria toxin. We observed that when administered individually, CRM197 did not trigger evident antineoplastic effects. However, its association with a uPA inhibitor caused dampening of EGFR-mediated signaling and apoptosis induction. Overall, our study highlights that the increased glycolytic metabolism and lactate production can foster the activated state of EGFR receptor, and suggests that the inhibition of EGFR-mediated signaling can be attempted by means of CRM197 administered with an appropriate protease inhibitor. This attempt could help in overcoming the problem of the acquired resistance to the conventionally used EGFR inhibitors.

In many European countries over the last decades, arable fields dominate agriculture landscapes, leading to a very intensive land-use practices. This reason seems to be the main cause of popula-tions declines for numerous farmland species, including the European hare (Lepus europaeus Pallas, 1778). The Research institute for Animal Production (National Agricultural and Food Centre, Luzianky, Slovakia) has been engaged in a long monitoring project (project currently run-ning), collecting certain indicators of hare population dynamics during hunting season since 1987 to 2023 in the Slovak Danubian Lowland. In the same macro-area (Čiližská Radvaň and Lehnice) a study was conducted on the influence of permanent semi-natural vegetation in relation to re-cruitment, population density and production. The whole monitored period was aggregated into 5-years intervals (for a total of 7 time-intervals), with the aim of analyzing the brown hare popu-lation dynamics. Spring hare density in the Danubian Lowland is currently 20.8 hares/km2, with harvests of 4.6 hares/km2. During all the monitoring period, bag’s animals have been examined following the regular hunting operations for the purpose of age determination (weight of eye lenses), sex ratio and productivity. The results of our analysis showed that the proportion of juve-nile in bag (PYB) among those shot varied from 37.0 % of the last 5-years interval (2018-2023), to a maximum of 51.0 % in interval of years 1998-2002. On total average there were 1.86 juveniles per adult female (r). The proportion of adult females in gamebag varied from 22.58 % (years in-terval 1992-1997) to 31.26 % (years interval 2018-2023). Sex-ratio (SI; males : females) among shot hares showed a value of 0.50, ranged from 0.48 in the period 2008-2012 to 0.52 in the first observed period (years 1987-1991) and in the last one (years 2018-2023). Average weight of shot hares was 4.04 kg (juveniles 3.83 kg, adults 4.27 kg, adult males 4.21 kg and females 4.32 kg). There was a large positive effect of set-aside with special mixtures, created for hares in large-scale farmed agrarian landscape, on hare density, bag and recruitment. In model hunting grounds with such set-asides increased the spring stock by 25 %, bag by 100 % and recruitment by 20 %. This study reveals that the management of European brown hare is not sustainable, and the population is decreasing. It is proved through the decline of harvest hares and by population dynamics parameters. Environmental improvements lead to the stabilization and increasing of requested parameters.

Knee osteoarthritis (KO) is an important health condition, affecting one third of the people aged 65 years or more. Pain is the main cause of disability. Pain management in KO includes pharmacological and non-pharmacological modalities. Patient education, lifestyle changes, physical exercise and physical agents are prescribed as a first approach for pain control. Laser therapy is part of many therapeutical protocols, with two forms, low-level laser therapy (LLLT) and high-intensity laser therapy (HILT). The paper aimed at stressing the advantages of HILT, based on a greater wavelength, higher energy delivery and deeper tissue penetration. Research on 23 published trials revealed that analgesic effect is rapid, cumulative and long lasting. Compared to sham, to LLLT or to other associations of therapeutical modalities, HILT provided significantly better results on pain reduction and functional improvement. Ultrasound examination showed reduction of intraarticular inflammation.

In the field of quality control, the critical challenge of analyzing microdefects in steel filament holds significant importance. This is particularly vital as steel filaments serve as reinforced fibers in the use and applications within various component manufacturing industries. This paper addresses the crucial requirement of identifying and investigating microdefects on steel filaments. Eddy current signals are used for the identification of microdefects, and an in-depth investigation is conducted. The core objective is to establish the relationship between the depth of defects and the signals detected through the eddy current sensing principle. The threshold of eddy current instrument was set at 10%, corresponding to a created depth of 20 µm, to identify defective specimens. A total of 30 defective samples were analyzed, and the phase angles between the experimental and theoretical results were compared. The depths of defects ranged from 20 to 60 µm, with one sample having a depth exceeding 75 µm. The calculated threshold of 10.18% closely aligns with the set threshold of 10%, with a difference of only 1.77%. The resulting root mean square error (RMSE) was found to be 10.53 degrees, equivalent to 3.49 µm for the difference in depth and phase between measured results and estimated results. This underscores the methodology's accuracy and its applicability across diverse manufacturing industries.

Driven by the growing interest of the scientific community and the proliferation of research in this field, cranial implants have seen significant advancements in recent years regarding design techniques, structural optimisation, appropriate material selection and fixation system method. Custom implants not only enhance aesthetics and functionality but are also crucial for achieving proper biological integration and optimal blood irrigation, critical aspects in bone regeneration and tissue health. This research aims to optimize the properties of implants designed from triply periodic minimal surface structures. The gyroid architecture is employed for its balance between mechanical and biological properties. Experimental samples were designed varying three parameters of the surface model: cell size, isovalue and shape factor. Computational simulation tools were used for determining the relationship between those parameters and the response variables: the surface area, permeability, porosity and Young modulus. These tools include computer aided design, finite element method and computational fluid dynamics. With the simulated values, the corresponding regression models were fitted. Using the NSGA-II, a multi-objective optimisation was carried out, finding the Pareto set which includes surface area and permeability as targets, and fulfil the constraints related with the porosity and Young modulus. From these non-dominated solutions, the most convenient for a given application was chosen, and an optimal implant was designed, from a patient computed tomography scan. An implant prototype was additively manufactured for validating the proposed approach.

With the increasing use of data-driven modeling methods new approaches to complex problems in the field of wind energy can be addressed. Topics reviewed through literature include wake modeling, performance monitoring and controls applications, condition monitoring and fault detection, and other data-driven research. Literature shows the advantages of data-driven methods reduce computational expense or complexity, particularly in the cases of wake modeling and controls, as well as various data-driven methodologies’ aptitude for predictive modeling and classification, as in the cases of fault detection and diagnosis. Significant work exists for fault detection while less work is found for controls applications. A methodology for creating data-driven wind turbine models for arbitrary performance parameters is proposed. Results are presented utilizing the methodology to create wind turbine models relating active adaptive twist to steady-state rotor thrust as a performance parameter of interest. Resulting models are evaluated by comparing root-mean-square-error (RMSE) on both the training and validation data sets, with Gaussian Process Regression (GPR), deemed an accurate model for this application. The resulting model undergoes particle swarm optimization to determine the optimal aerostructure twist shape at a given wind speed with respect to the modeled performance parameter, aerodynamic thrust load. The optimization process shows an improvement of 3.15% in thrust loading for the 10 MW reference turbine, and 2.66% for the 15 MW reference turbine.

Emerging data processing techniques brought back into attention the HF range communication as an interesting alternative to third-party solutions for IoT applications, such as data transmission in distributed energy production facilities. The physical size of HF antennas, often comparable to the surrounding objects, require in-situ radiation measurements. Drone-borne measuring systems are already known as a flexible solution, but mostly restricted to higher frequency ranges. In this work, we propose to use an electrically small, folded dipole as a probe for drone-borne measurements on HF antennas. We also propose a calibration approach for the effects related to the near-field zone, and to the drone body proximity. The impact of ground reflection is also investigated. We show that despite its low, realized gain figure such a probe can provide stable results for near-field measurements, even at low input power levels.

The challenging terrain and deep ravines characteristic of mountainous regions often result in slower path planning and suboptimal flight paths for Unmanned Aerial Vehicles (UAVs) when traditional meta-heuristic optimization algorithms are employed. This study investigates the application of an Improved Enhanced Snake Optimizer (IESO) for three-dimensional path planning in a simulated rugged mountainous terrain. The initialization process in the enhanced snake optimizer is refined by integrating the Chebyshev chaotic map. Additionally, a non-monotonic factor is introduced to modulate the "temperature," and a boundary condition is incorporated into the dynamic opposition learning mechanism. These modifications collectively reduce the likelihood of population convergence to local optima during optimization. The feasibility of IESO is validated through time complexity and global convergence analyses. Comparative simulation experiments benchmarked IESO against five state-of-the-art optimization algorithms across test functions and path-planning simulated scenarios. The experimental results indicate that the enhanced algorithm achieves superior optimization precision, faster convergence speeds, and improved quality in the planned trajectories by 30%.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

The number of physical devices connected to the Internet such as vehicles, household appliances and other "things" has been steadily increasing in recent years, thus forming the basis for the Internet of Things (IoT). IoT ecosystem extends beyond country borders and application domains, combining thousands of versatile devices that differ in terms of their structures, capabilities, and available resources. It is therefore not surprising that the landscape of wireless communication technologies and the degree of IoT devices available today is excessively broad and diverse. Interference between networks leads to frame collisions and consequent packet loss. Frame collisions occur when two or more packets overlap in time and frequency and use the same LoRa parameters, i.e. the same spreading factor (SF), bandwidth (BW) and carrier frequency (CF). When most devices use the same configuration, collision probability is higher. The probability of frame collisions is also affected by traffic characteristics, particularly the periodicity of the transmission and the payload size. Larger payload sizes and more frequent transmissions accumulate with higher time on air (ToA) and channel occupancy [1]. Transmission powers and the location of the gateways also influences this situation. The aim of this experimental work is to verify the effects of collisions and interference in LoRaWAN, regarding the periodicity of transmissions and the payload sizes. The hardware used is an Arduino board programmed in C/C++, a LoRa Bee module operating at a frequency of 868 MHz and a LoRaWAN LG02 gateway. Different scenarios were tested in an outdoor environment, with Line of Sight and Non-Line of Sight, and different variables such as: SFs equal to 7, 9 and 12; distances of 20, 40 and 60 meters and different data sizes of 14, 32 and 51 bytes, over the same channel. The packets with different SF’s and different data sizes were transmitted in a (pseudo) random way, one after the other, overlapping different SFs in the same channel and testing this way (theoretical) orthogonality among them. By fixing the bandwidth in 125 kHz, and testing different SFs we intend to increase the probability of cause packet loss by applying to our connection a combination of emitted power/short distance that leaves an interference power received, strong enough [2] for the effect. We validate our conclusions by analyzing ToA according with RSSI and different data sizes, the RSSI for different SFs and different data sizes and finally the packet loss through the PDR-Packet Delivery Ratio for a better understanding of the reliability of packet transmission in our link.

Starting from the model of a slow-rolling missile with six degrees of freedom (6 DOF) in the body frame, a 6 DOF model in the Resal frame is obtained, which is used to linearize the coupled commanded motion. Based on the linearized model, we obtain the structural scheme of the commanded object and define the quality parameters. The obtained parameters have a complex representation (with real and imaginary parts) due to the coupling between longitudinal channels. Then, the kinematic guidance equations, the seeker equations and the actuator specific to the slow-rolling single-channel missile are defined using a switching function. The guidance kinematic equations, the seeker equations and the actuator model are linearized in the Resal frame, and the structural diagram of the homing missile is constructed. Starting from this, the characteristic polynomial having complex coefficients is determined and then analyzed with the Frank-Wall stability criterion. Based on the analysis, a stability range is determined for the navigation constant and a minimum and possibly a maximum limit for the time to hit the target is obtained. The stability range defined for the navigation constant on the linear model is finally validated on the nonlinear model in the body frame.

Modern building automation systems implement plenty of advanced control and monitoring functions considering various parameters like users’ activity, lighting, temperature changes etc. Moreover, new solutions based on Internet of Things and cloud services are also being developed for smart buildings to ensure comfort of use, user safety, energy efficiency improvements and integration with smart grids and smart city platforms. Such a wide spectrum of technologies and functions requires a new approach in building automation systems design to provide effective way of their implementation and flexibility during operation. At the same time, in the building design and operation industries, tools based on building information modeling and digital twins are being developed. In this paper, the authors discuss development directions and application areas of these solutions, identifying new trends and possibilities of their use in smart homes and buildings. In particular, the focus is on procedures for selecting automation functions, effective integration, and interoperability of building management systems with Internet of Things considering organization of prediction mechanisms and dynamic functional changes in buildings and smart networks. Chosen solutions and functions should consider the requirements from EN ISO 52120 standard and the guidelines defined for the Smart Readiness Indicator.

Extruded polystyrene (XPS) is frequently used in the construction of many different structures. It is therefore necessary to appropriately characterize its mechanical properties to ensure the safety of said structures. Among the available characterization tests, static bending tests are simple and easy to perform; owing to these characteristics, they should be performed more frequently than other tests. However, in static bending tests on XPS, there are several challenges owing to the high flexibility of XPS, and the chosen testing method and sample configuration affect the accuracy of characterization. In this study, three bending properties (Young’s modulus, proportional limit stress, and bending strength) of samples cut from an XPS panel were determined using three-point bending (TPB), four-point bending (FPB), and compression bending (CB) tests with varying sample span/depth ratios, and statistical analyses were performed to determine the relevance of the tests. The experimental results suggest that the TPB and CB tests were more feasible than the FPB test when the span/depth ratio was appropriately determined. However, clear differences were observed in the sample bending properties determined in these tests. In light of these findings, further studies should be conducted to elucidate these differences.

The rapid development of the Industrial Internet of Things (IIoT) has brought enormous opportunities to the industrial environment but has also posed significant challenges to network security, especially the physical layer security challenges,which is crucial for the reliable transmission of messages interconnected devices and sensors. Focus on the enhancing the physical layer security in the IIoT communication, this paper proposed a mechanism of Spatial Secrecy Outage Probability (SSOP) to ensure the secure transmission of data. The SSOP algorithm assumes that the location of legitimate device is known, while eavesdropper on the random distribution of device locations, forming the SSOP model related to device locations from the perspective of insecure regions (ISR) and secure regions (SR), and deduce the closed-form expression for its upper bound. Subsequently under the constraint of SSOP conditions, establish an optimization model with the objective of system throughput maximization based on Spatial Secrecy Outage Probability(SRM-SSOP). By optimizing the transmission rate of legitimate channels or controlling the transmission power, the maximization of system throughput can be achieved, thus reducing the consumption of communication resources. Through sophisticated modeling and simulation in the MATLAB, we verified the accuracy of the definition and derived upper bound of SSOP. The experimental results also show that SSOP algorithm gradually converges to a specific value as the number of antenna elements increases. In addition, we observed that when the receiver device is aligned with the normal direction of the transmit antenna array, the SSOP reaches a minimum value. These performance are crucial for understanding and optimizing the security performance of IIoT communication systems.

Cities require flexible and participatory planning methodologies to address complex and evolving urban challenges. In Italy, the legislative framework is defined at the Regional level, according to the National laws and jurisprudence. The Lombardy region introduced the Planning Document (PD) in the Territorial Government Plan (PGT), as a strategic tool capable of adapting to changes. Based on a strategic vision, this document is useful to guide concrete actions for urban transformation, actively involving stakeholders, including citizens. The PD has the role to translate the political program into an urban planning design. So, the role it has is both technical and political. The political dimension is usually deepened in the strategic component of the document. Following the formation process of the whole city plan, the authors define the key strategies in the PD for a healthier urban future for the city of Voghera. It emerges as a balanced urban development that combines economic growth, environmental preservation, and community well-being. In the paper the authors synthesize the Voghera’s PD as an example of strategic planning that interacts with the practical planning actions and that guides both the public and the private decisions about the city development towards a healthier city.

Hydrodynamic modeling and hazard mapping are essential tools for urban flood mitigation and spatial planning. Leveraging software like HEC-RAS (Hydrologic Engineering Center - River Analysis System) and ArcGIS, this study aimed to map flood-prone areas along the Jijia River in the Ungheni administrative unit of Iasi County. Human-induced environmental changes and global climate shifts have heightened flood risks worldwide, particularly in urbanized areas. Hydrological and hydraulic modeling anticipate and assess flood events, while hydrodynamic modeling accurately simulates flow propagation, in-forming flood extent, timing, and volume. Flood hazard maps offer essential insights into flooded areas, water depths, and velocities, assisting in risk assessment and mitigation strategies. Through the use of different scenarios, river modeling aims to accurately replicate real-world conditions. This study focuses on Ungheni commune in Iasi County, Romania, situated along the Prut River's eastern bank. Utilizing a combination of fixed-grid and irregular mesh elements in modeling al-lows for fine-tuning of flow details and optimization of simulation times. Model accuracy, particularly regarding peak river levels, hinges on hydrograph duration. While a 30-minute error is typically accepted, greater tolerances may apply to river basins with longer response times. The extraction and processing of model results, including maximum water depths, flood extents, and velocity maps, are facilitated by ArcGIS, providing valuable data for effective flood management strategies.

Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). Current solutions for its management, such as oral rehydration salts (ORS), inhibitors of the gut motility, antibiotics, and living probiotics only partially counteract the mechanisms of the disease and do not provide a full coverage of the problem. Potential risks of the use of living probiotic strains, particularly in immunocompromised patients, can be eliminated with the use of tyndallized (heat-killed) postbiotic bacteria and yeast. ABB C22® is a postbiotic combination of three tyndallized yeasts, namely Saccharomyces boulardii, Saccharomyces cerevisiae, and Kluyveromyces marxianus. To assess the action of the postbiotic combination on diarrhoea, immune and gut epithelial cell signaling assays, gut barrier formation assay and rotavirus gene expression assay were performed. ABB C22® showed a strong anti-inflammatory effect, an induction of the build-up of the gut epithelium, and a degree of protection against rotavirus infection. These experimental studies support the use of the postbiotic ABB C22® as a solution for the management of diarrhoea and gastrointestinal conditions, alone or in combination with existing but incomplete treatments.

Productivity has been modest in construction due to many reasons, especially project-specific operations and fragmentation. The main aim of this research is to map the challenges towards industrialization in construction through a comparative study of the manufacturing industry. An inductive approach and a qualitative method are followed by applying semi-structured inter-views, and node-based thematic analysis. The key elements of industrialization in mature man-ufacturing companies are benchmarked. The findings indicate a specific order of steps for indus-trialization in construction. Data and information management with achieved systematization have been sources of productivity in manufacturing companies. However, the systematization starts from the offering, construction companies need to define their offering, that is the products, and define their respective data. Only accurate and good quality data on products enables the systematization of order delivery processes, which are the engine for a company’s success or failure. Continuous efficiency improvement is only possible with systematized processes and respective data related to the processes. The originality involves clarifying the industrialization of construction companies via products, respective data, and processes considering industrialized manufacturing companies.

Bladder cancer (BC) diagnosis is reliant on cystoscopy, an invasive procedure associated with urinary tract infections. This has sparked interest in identifying non-invasive biomarkers in body fluids such as blood and urine. A source of biomarkers in these biofluids are extracellular vesicles (EVs), nanosized vesicles that contain a wide array of molecular cargo, including small non-coding RNA such as microRNA and transfer RNA-derived fragments (tRF). Here we performed small-RNA next-generation sequencing for urine EVs, serum EVs and serum supernatant from 41 patients with non-muscle invasive BC (27 stage Ta, 14 stage T1) and 15 non-cancer patients (NCP) with benign cystoscopy findings. Serum and urine samples were collected before transurethral resection of bladder tumors (TUR-b) and at routine postsurgery check-ups. Expression levels of tRFs in presurgery samples were compared to those at postsurgery check-ups and to NCPs. To strengthen the reliability of our results, samples from 10 patients with stage T1 disease were resequenced. When comparing tRF expression in urine EVs between BC patients with stage T1 disease and NCPs, 14 differentially expressed tRFs (DEtRFs) were identified. In serum supernatant, six DEtRFs were identified among stage T1 patients when comparing presurgery to postsurgery samples, and four DEtRFs were found when comparing presurgery samples to NCPs. By performing a blast search, we found that sequences of DEtRFs aligned with genomic sequences pertaining to processes relevant to cancer development, such as enhancers, regulatory elements and CpG islands. Our findings display a number of tRFs that may hold potential as biomarkers for the diagnosis and recurrence-free survival of BC.

Insulated Gate Bipolar Transistor (IGBT) may convey high current and sustain high breakdown voltages; it may provide high power control. In a sense, how IGBT demonstrates the capability of power control was not specifically described, and the equivalent bipolar junction transistors (BJT) activated by an applied bias to the insulated gate is intriguing. As seen in Figure 1, IGBT shows an equivalent circuit structure containing two types of BJT, (NPN-type Bipolar transistor and PNP-type Bipolar transistor), which can be modeled as diode-associated transistor. Apparently, as a bias applies to the controlling gate, the channel beneath the gate oxide gets strongly inversed and turns out to be conductive just like what happens on metal-oxide-silicon field effect transistor (MOSFET), which provides necessary igniting currents to both BJTs and thus causes high current gain flowing through them-selves from the bottom. A proposed and renewed formula provides addressing the above scenario and successfully fitting the measured data that forms the characteristic curves. Some parameters in the proposed formula, which includes size and mobility associated constant, threshold voltage, and Early-Voltage-related lambda for MOSFET, explain and explore the underlying physics. IGBT thus enjoy high input impedance and high current gain due to MOSFET (Insulated Gate) and BJT, respectively. This formula combines both merits of MOSFET and BJT in order to fit the measured data. Indeed, the formula intimately fits IGBT electrical characteristic curves, and thus may be qualified and served as a model. The new model is then advisable for designing power integrated circuit to exactly achieve power saving, power control, and power efficiency.

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

Improper disposal of waste plastic has caused serious ecological and environmental pollution problems. Transforming plastics into high value-added chemicals can not only achieve efficient recycling of waste plastics, but also an effective way to control white pollution. The catalyst selectively breaks the C-C bond of polyolefin plastic under heat treatment and converts it into liquid fuel, thus realizing sustainable recycling of plastics and has a good development prospect. This review provides a detailed overview of the current development of catalytic pyrolysis, catalytic hydrolysis, solvent decomposition and supercritical hydrothermal liquefaction for cracking plastics to make fuel oil. The reaction mechanism, influencing factors and promoting effects of catalysts in various degradation technologies are analyzed and summarized and the latest proposed tandem reaction for degrading plastics is briefly introduced. Finally, some optimization paths of waste plastic pyrolysis to fuel oil technology are proposed: synergies between mixed raw materials, in-depth exploration of catalysts, design and manufacture of reactors that match the pyrolysis technology. All these are important research directions for promoting the industrialization of plastic pyrolysis to fuel oil.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

The Mara River basin (MRB) has a world-famous ecosystem, but the vegetation has been damaged due to economic development in recent years, and there is little known about the area that will experience severe vegetation damage in the future. Based on the vegetation vulnerability system, principal component analysis, and three CMIP6 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), vegetation vulnerability was calculated in the base period (2010-2019), near-term period (2020-2059) and long-term period (2060-2099) in the MRB. The spatial cluster of vegetation vulnerability was revealed by spatial correlation analysis, and the transition of vegetation vulnerability of different periods was analyzed by stochastic matrix. The results showed that in all periods, the vulnerability showed a high-high cluster in the east, and a low-low cluster midstream and downstream. From the stochastic matrix, the area of high vulnerability increased the least under the SSP1-2.6, while it increased the most under the SSP5-8.5. The vegetation vulnerability upstream increased the most from the base period to the near-term period and long-term period in the MRB. By comparing the vegetation vulnerability under different scenarios, and pointing out the areas with the highest vulnerability increase, this study can better provide comprehensive decision-making for vegetation protection in the MRB.

Chinese texts often feature a substantial volume of normative content, and their analysis has increasingly become a focal point in recent semantic analysis endeavors. Enhancing the effectiveness of text classification and clustering is pivotal in unveiling the intricate semantics within extensive textual data. Empirical research within the realm of computational social science has underscored the need for improved explanatory power when it comes to general text clustering methods applied to normative texts. This study introduces an innovative hierarchical clustering method that incorporates part-of-speech (POS) features and pioneers a novel semantic network model. It achieves this by amalgamating a POS-based feature weight calculation method with hierarchical clustering techniques. To assess its efficacy, the method is rigorously evaluated across three diverse text datasets, encompassing normative reports, news articles, and social media content. The experimental results unequivocally demonstrate the superior performance of the POS-HC method, surpassing the traditional TF and TF-IDF feature extraction methods in terms of clustering accuracy, and surpassing some existing clustering methods. Furthermore, its classification effectiveness exhibits notable advantages, particularly in the semantic classification of normative texts.

Dried blood spot (DBS) testing on confetti is one of the most common methods used to collect and extract DNA from field samples for molecular epidemiology of malaria studies. Here, we investigated whether ethanol or other solutions used to clean scissors are a source of sample contamination. DBS were prepared from 3 drops of blood from two Plasmodium falciparum cultures spotted on confetti, and 3 solutions (water, ethanol and DNase) were used to clean scissors between spots during DNA extraction. For each cleaning solution, two blank confetti were used as negative controls. Samples were analyzed by PCR-based genotyping of merozoite surface proteins 1 & 2 (msp-1 and msp-2), and P. falciparum chloroquine resistance transporter (Pfcrt). A total of 15 samples were analyzed. Based on msp-1 and msp-2 amplification, P. falciparum was detected on blank confetti when scissors were washed with ethanol. Based on Pfcrt amplification, DNA of P. falciparum was detected on blank confetti when scissors were cleaned with ethanol or water. No P. falciparum genes were detected on blank confetti when scissors were cleaned with DNase. Scissors cleaned with DNase prevented cross-contamination between samples during processing of dried blood spots, whereas ethanol (which is commonly used) fails to avert cross-contamination.

In pattern recognition domain, deep architectures are widely used nowadays and they have achieved fine grades. However, these deep architectures need special demands, especially big datasets and GPU. Aiming to gain better grades without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size, therefore it can gain more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features’ dimensions are reduced by Principal Component Analysis( PCA) and we apply softmax to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames to compare with their neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. This makes the salient areas found from different subjects have the same size. Besides, gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.

A portable laser photoacoustic sensor based on a Field-Programmable Gate Array (FPGA) is reported for methane detection. A tunable DFB diode laser in the 1654 nm wavelength range is used as an excitation source. The photoacoustic signal processing was implemented by a FPGA device. A small resonant photoacoustic cell is designed. The minimum detection limit (1σ) of 10 ppm for methane (CH₄) is demonstrated.

Quantifying the landscape pattern change can effectively demonstrate the ecological progresses and the consequences of urbanization. Based on remotely sensed land cover data in 1994, 2000, 2006 and a gradient analysis with landscape metrics at landscape- and class- level, we attempted to characterize the individual and entire landscape patterns of Shanghai metropolitan during the rapid urbanization. We highlighted that a roadscape transect approach that combined the buffer zone method and the transect-based approach was introduced to describe the urban-rural patterns of agricultural, residential, green, industrial, and public facilities land along the railway route. Our results of landscape metrics showed significant spatiotemporal patterns and gradient variations along the transect. The urban growth pattern in two time spans conform to the hypothesis for diffusion–coalescence processes, implying that the railway is adaptive as a gradient element to analyze the landscape patterns with urbanization. As the natural landscape was replaced by urban landscape gradually, the urban fringe expanded radically. The results also showed that the desakota region expanded its extent widely. Satellite towns witnessed the continual transformation from the predominantly rural landscape to peri-urban landscape. Furthermore, the gap between urban and rural areas remained large especially in public service. More reasonable urban plans and land use policies should push to make more of an effort to transition from the urban-rural separation to coordinated urban-rural development. This study is a meaningful trial in demonstrating a new form of urban–rural transects to study the landscape change of large cities from a strategic viewpoint. By combining gradient analysis with landscape metrics, we addressed the process of urbanization both spatially and temporally, and provided a more quantitative approach to urban studies.

(1) Background: Macrophages undergo polarization, resulting in distinct phenotypes. These transitions, including de-/repolarization, lead to hysteresis, where cells retain genetic and epigenetic signatures of previous states, influencing macrophage function. We previously identified a set of interferon-stimulated genes (ISGs) associated with high lipid levels in macrophages that exhibited hysteresis following M1 polarization, suggesting potential alterations in lipid metabolism; (2) Results: In this study, we applied Weighted Gene Co-expression Network Analysis (WGCNA) and conducted comparative analyses on 162 RNA-seq samples from de-/repolarized and lipid-loaded macrophages, followed by functional exploration; (3) Results: Our results show that in M1 hysteresis, the sustained high expression of Marco and suppression of Abca1/2 reduced lipid efflux, leading to elevated intracellular lipid levels. This accumulation may compensate for reduced cholesterol biosynthesis and provide energy for sustained inflammatory responses and interferon signaling; (4) Conclusions: Our findings elucidate the relationship between M1 hysteresis and lipid metabolism, contributing to understanding the underlying mechanisms of macrophage hysteresis.

Objective: To examine the dose-response relationship between average daily temperature and sunlight hours with daily steps across a 35-week period in school-aged children, and to evaluate whether there were differences by sex. Methods: We conducted a follow-up study involving 655 children (50.8% girls, mean age 10.45 ± 0.95) from six public primary schools in Cuenca, Spain. We measured daily steps using Xiaomi Mi Band 3 Smart Bracelets from October 2022 to June 2023 (over 35 weeks). We collected daily average temperature from the local weather station in Cuenca and sunlight hours during the same period. We used ANCOVA models and LOESS regression to examine the dose-response relationship between average daily temperature and daily hours of sunlight with daily steps. Additionally, we performed a multiple linear regression model. Results: Our findings revealed significant variations in daily steps across the 35 weeks. The relationship between environmental factors and daily steps was non-linear, in both girls and boys. The optimal values for higher activity levels were an average temperature of 14°C and 13 hours of sunlight. Furthermore, a 1 ºC increase in temperature was associated with an increase of 74 ± 130 steps/day, while an increase of one hour of sunlight was associated with an increase of 315 ± 237 steps/day. However, sunlight hours may act as a moderating factor. Conclusion: Our study showed a non-linear association between t average daily temperature and sunlight hours with daily steps over a 35-week period. Additional strategies may be necessary to encourage increased physical activity during periods of extreme temperatures or sunlight exposure.

Objectives: This study aimed to evaluate the risk of hepatitis B virus reactivation (HBVr) in COVID-19 patients receiving immunosuppressive treatment, which has been insufficiently studied to date. Secondarily, we aimed to evaluate the seroprevalence of HBV infection in COVID-19 patients. Methods: We performed an HBV screening in all Romanian adults hospitalized in 4 COVID-19 wards between October 2021 and September 2022. We enrolled patients with positive hepatitis B core antibody (anti-HBc) without protective hepatitis B surface antibody (anti-HBs), HBV treatment or immunosuppressive conditions, whom we followed virologically at 3 months. Results: We identified 333/835 (39.9%) anti-HBc-positive patients. Follow-up was performed in 13 patients with positive hepatitis B surface antigen (HbsAg) and 19 HBsAg-negative/anti-HBc-positive patients. Among those who received immunosuppressants, 4/23 (17.4%) patients experienced HBVr: 1 out of 8 (12.5%) HBsAg-positive patients (with 1.99 log increase in HBV DNA level) and 3 out of 15 (20%) HBsAg-negative/anti-HBc-positive patients (with de novo detectable HBV DNA level). Conclusions: Administration of COVID-19 immunosuppressants may result in a significant risk of HBVr in co-infected patients. We recommend performing an HBV triple screen panel (HBsAg, anti-HBs, anti-HBc) in all COVID-19 patients receiving immunosuppressive treatment. HBV prophylaxis may be indicated in certain patients. Larger studies are needed in order to establish an appropriate and cost-effective management in these patients.

Maintaining the optimal microclimate in broiler houses is crucial for bird productivity, yet enabling efficient temperature control remains a significant challenge. This study developed and validated a computational fluid dynamics (CFD) model to predict temporal changes in indoor air temperature in response to variable ventilation operations in a commercial broiler house. The model accurately simulated air velocity and airflow distribution for different numbers of tunnel fans in operation, with air-velocity errors ranging from -0.22 to 0.32 m s-1. The predicted airflow rates through inlets and cooling pads showed good agreement with measured values with an accuracy of up to 108.1%. Additionally, the CFD model effectively predicted temperature dynamics, accounting for chicken heat production and ventilation effect. The model successfully predicted the longitudinal temperature gradients and their variations during ventilation cycles, validating its reliability through comparison with experimental data. The study also explored different variable inlet configurations to mitigate the temperature gradient. The variable inlet adjustment showed the potential to relieve the high temperatures but may reduce overall ventilation efficiency or intensify temperature gradients, which confirms the importance of optimising ventilation strategies. This CFD model provides a valuable tool for evaluating and improving ventilation systems and contributes to enhanced indoor microclimates and productivity in poultry houses.

Background/Objectives: Habituation and sensitization are opposite phenomena that play a role in the pathophysiology of episodic migraine and its progression to chronic migraine (CM). There have been just a few studies that have investigated these phenomena in patients with medication overuse headache (MOH) in comparison to those with chronic migraine (CM) and healthy controls (HCs), and the findings have been inconsistent. Methods: We measured and examined visual evoked potentials (VEPs) in 81 patients with MOH and 24 patients with CM, as well as 24 HCs. The VEPs were used to assess sensitization by analyzing the amplitude of the first block (100 sweeps), and to evaluate habituation by measuring the amplitude response decrement after 6 blocks. We further examined patients diagnosed with MOH based on their acute medication type and after a 3-week acute medication withdrawal program. Results: There were no significant differences between groups in terms of the first N1-P1 VEP amplitude block and its habituation. It was found that patients with MOH had a greater drop in the amplitude of the VEP P1-N2 complex after repeated stimulation than patients with CM or HC. The VEPs parameters showed no significant differences based on the specific overused drug and after a 3-week acute medication off. Conclusions: We propose that the results obtained in patients with MOH indicate an abnormal activation of inhibitory circuits in the parieto-occipital region in response to repeated modulatory stimuli.

This study examines the relationship between Gross Domestic Product (GDP) and income inequality in Greece across three key periods: the pre-crisis period (2003-2008), the crisis and memoranda period (2009-2014), and the post-crisis period (2015-2020). Using data from the World Bank Open Data database, the study employs correlation analysis, and linear regression models to analyze how economic changes influence income distribution. The findings reveal that during the pre-crisis period, economic growth was moderately correlated with increasing inequality, although this relationship was not statistically significant, indicating uneven distribution of growth benefits. In the crisis period, a strong and statistically significant negative relationship between GDP and the Gini coefficient was identified, highlighting the sharp rise in inequality as the economy contracted due to austerity measures. In the post-crisis period, the relationship between GDP and inequality weakened, showing a statistically insignificant correlation, suggesting that economic recovery alone did not significantly reduce inequality. The study concludes that economic growth is insufficient to address income inequality without targeted policy interventions, particularly during periods of crisis. These findings underscore the importance of comprehensive social policies to mitigate inequality and suggest areas for future research on the impact of specific interventions on income distribution.

Soil contamination and the uptake of contaminants by food crops is a global problem that differs significantly from region to region, with the key factors affecting the contaminants present in local soils being the mineralogical composition of the underlying layers and local human activity. The area of ​​the Pannonian region is known for the fact that agriculture has, historically, played an important role since Roman times, which was particularly influenced by human activity. In this study we performed a preliminary study of the contamination of soil samples across the Pannonian region, to determine the potential presence of harmful contaminants. Both soil and crop samples were analysed for the potential presence of heavy metals, with additional focus placed on the potential presence of microplastics in the region`s soil.

Mosquitoes are responsible for the transmission of numerous pathogens, including Plasmodium parasites, arboviruses and filarial worms. They pose a significant risk to public health with over 200 million cases of malaria per annum and approximately four billion people at risk of arthropod-borne viruses (arboviruses). Mosquito populations are geographically expanding into temperate regions and their distribution is predicted to continue increasing. Mosquito symbionts, including fungi, bacteria and viruses, have desirable traits for mosquito disease control including spreading horizontally and vertically through mosquito populations and potentially colonising multiple important vector species. Paratransgenesis, genetic modification of mosquito symbionts with effectors to target the pathogen rather than the vector, is a promising strategy to prevent the spread of mosquito-borne diseases. A variety of effectors can be expressed but venom toxins are excellent effector candidates because they are target specific, potent, and, stable. However, the only toxins to be explored in mosquito paratransgenesis to date are Scorpine and mutated phospholipase A2. To enhance the scope, effectiveness, and durability of paratransgenesis, an expanded arsenal of effectors is required. This review discusses other potential toxins effectors for future paratransgenesis studies based on prior in vitro and in vivo antiparasitic and antiviral studies and highlights the need for further research and investment in this area. In terms of mosquito-borne diseases, paratransgenesis strategies have been developed to target Plasmodium. We postulate the potential to apply this principle to target arboviruses using antiviral toxin effectors.

Background/Objectives: Multisystem Inflammatory Syndrome in children (MIS-C) is a rare but severe post-infectious complication of COVID-19, that often requires admission to the Pediatric Intensive Care Unit (PICU). The present study aimed to compare the demographic, clinical and laboratory characteristics between children diagnosed with MIS-C who were admitted to the PICU or did not require PICU admission. Methods: Children diagnosed with MIS-C from September 2020 to April 2023 were included in this case-control study. Patient’s demographic, clinical and laboratory data, were collected from medical records. Results: Fifty children with MIS-C were included in the study [median (IQR) age: 7.5 (4.3, 11.4) years, 28/50 (56%) males]. Twenty-two (22/50, 44%) children required admission to the PICU. In the multivariate regression analysis, hepatic (OR:12.89, 95%CI: 1.35-123.41, p-value=0.03) and cardiological involvement (OR:34.55, 95%CI: 2.2-541.91, p-value=0.01) were significantly associated with hospitalization at the PICU. Regarding the laboratory and imaging parameters during the first 48 hours from admission, D-dimer levels higher than 4μg/mL and decreased Left Ventricular Ejection Fraction were associated with an increased risk of PICU admission (OR:7.95, 95%CI:1.48-42.78, p-value=0.02 and OR=1.28, 95%CI:1.07-1.53, p-value=0.01). Children who were admitted to the PICU were more likely to develop complications during their hospitalization (10/22, 45.5% vs. 3/28, 10.7%, p-value=0.005) and were hospitalized for more days, than children in the pediatric wards (median length of stay (IQR): 20 (15,28) days vs. 8.5 (6, 14) days, p-value&lt;0.001). Conclusions: In the present study, cardiovascular, hepatic involvement and increased D-dimer levels in children with MIS-C were associated with admission to the PICU.

The risk classification of barrier lake is the key to conducting emergency treatment in a scientific manner. Such difficulties are faced as short time for risk evaluation, complex evaluation indicators, difficulty in obtaining information quickly and quantifying index weights. Based on this, this paper constructs a quantitative risk classification model for barrier lakes based on D-AHP. On the basis of studies on nearly 100 cases of barrier lakes, an 8-factor evaluation index system and quantitative classification are proposed. The methods of rapid calculation of reservoir capacity curve of barrier lake and intelligent identification of particles on the surface of barrier body were developed, which realized the rapid acquisition of 8-factor evaluation index information in emergency environment. The D-AHP method dealt with inconsistent weight assignment to evaluation factors by experts, which helped achieve weight quantification of 8 factors. The risk assessment on15 barrier lakes such as Tangjiashan barrier lake show that the conclusion drawn with risk classification method proposed in this paper is basically consistent with that of the traditional table-lookup method. However, the table-lookup method ignores cumulative loss’s impacts on the risk level of barrier lakes, and considers the extremely severe loss of barrier lakes as a sufficient condition for the evaluation level to be grade I, and thus a deviation in the evaluation. The risk classification method proposed in this paper is more reasonable and reliable.

The color of carcass fat is an important factor in meat quality. To investigate the characteristics and changes in lipid metabolism of SAT in Mongolian cattle at 34 M of age compared with the control group, we evaluated the color, relative expression of genes associated with browning, and profiles of lipid metabolites by using qPCR and non-targeted lipidomics techniques. Overall, the yellowness value and relative expression of mitochondrial biogenesis–specific markers, thermogenic, UCP2, and beige adipocyte marker genes in the SAT of 34 M cattle were higher than those control (p &lt; 0.05). Using multivariate analysis, 172 significantly different lipids (SDLs) were identified. Triacylglycerols (TGs) and phosphatidylcholines (PCs) had high relative contents with abundant unsaturated fatty acids. The upregulation of TGs observed in the SAT of 34 M cattle mainly consisted of medium- and long-chain fatty acids. Pathway analysis demonstrated that 172 SDLs were primarily involved in glycerophospholipid, glycerolipid, ether lipid, and sphingolipid metabolism. In summary, yellow fat of naturally grazed cattle was impacted by many factors such as lipid metabolism, browning genes expression and age. These findings provide new insight into the characteristics and metabolic pathways of adipose tissue in natural grazing Mongolian cattle.

The role of astro- and microglial cells in the pathogenesis of epilepsy is currently under active in-vestigation. It is proposed that the activity of these cells may be regulated by agonists of peroxi-some proliferator-activated nuclear receptors (PPARs). The objective of this study was to investi-gate the effects of the PPAR β/δ agonist GW0742 (Fitorine) on the behavior and gene expression of astro- and microglial proteins involved in the regulation of epileptogenesis in rat brain in a lithi-um-pilocarpine model of temporal lobe epilepsy (TLE). A seven-day administration of GW0742 at a dose of 5 mg/kg/day has been shown to suppress TLE-related behavioral hyperactivity in the Open Field test and to attenuate the TLE-induced increase in gene expression and protein levels of astro- and microglial activation markers Gfap and Aif1 in the dorsal hippocampus and temporal cortex. Furthermore, GW0742 reversed the TLE-related increase in Lcn2 gene expression (a marker of the A1 phenotype of astrocytes) in the temporal cortex, the increase in the ratio of Nos2/Arg1 gene expression (markers of the M1/M2 phenotypes of microglia), and the decrease in Arg1 gene ex-pression in the dorsal hippocampus. The results suggest that GW0742 may mitigate behavioral and biochemical abnormalities in a lithium-pilocarpine model of TLE.

Tamil Nadu, a state in southern India, is bereft of any native milch or dual-purpose cattle breed and the state depends chiefly on crossbred cattle for milk production. As most (90 percent) of the milk production in the state was contributed by Jersey crossbred cattle, the genetic evaluation study was intended to assess the milk production traits viz., test-day milk yields (TDMYs), total milk yield (TMY) and 305-day milk yield (305MY) in these crossbred cattle reared under farmers’ rearing environment. Data on monthly TDMYs (TDMY1 to TDMY10) of Jersey crossbred cows (n=81,653) reared by the farmers over 24 years (1999-2022) were collected for evaluation. The influence of non-genetic factors viz., location (agroclimatic zones), period and season of calving, and parity on TDMYs, TMY, and 305MY were assessed, and the variance and covariance components for genetic parameters (heritability and genetic correlation) of the traits were estimated by the method of restricted maximum likelihood (REML) under multivariate animal model and by random regression model (RRM). The overall means of various TDMYs ranged from 4.98 (TDMY10) to 9.95 kg (TDMY2) and, for TMY and 305MY the means were 2480.33 and 2393.71 kg respectively. The heritabilities estimated by animal model for TDMYs were high and ranged from 0.39 ± 0.01 to 0.47 ± 0.01 and were fairly less variable throughout the lactation while the estimates obtained by RRM were medium to high and ranged between 0.28 ± 0.01 and 0.65 ± 0.02 for different days in milk (DIMs). The heritability estimated for TMY and 305MY were 0.48 ± 0.01 and 0.49 ± 0.01 respectively. The estimates of heritability in mid-lactation yields were comparatively little less than those at the beginning and the end of lactation. The high estimates of heritabilities for TDMYs, TMY, and 305MY obtained in the present study offered an ample scope for improving milk production through selective breeding. Genetic correlations between TDMYs estimated by animal model were positive and moderate to high, with a range between 0.47 ± 0.01 and 0.99 ± 0.00. Considerably higher estimates (0.97-0.99) were observed between adjacent TDMYs showing strong genetic associations. By RRM, genetic correlations estimated between DIMs were positive, except for a few estimates and the magnitude of genetic correlation decreased with an increase in the interval between the DIMs. The high genetic correlation observed between the TDMYs in early and mid stages of lactation with TMY and 305MY suggested that these test day yields could be used favorably for the early selection of cows for milk production which facilitates reduction in the generation interval and consequently increase the annual genetic gain for the milk production traits.

The COVID-19 pandemic profoundly impacted older people in residential aged care facilities (RACFs), especially those with dementia. This retrospective cohort study investigates the impact of the pandemic on agitation incidents within this population in 40 Australian RACFs. We compared pre-pandemic data (January-October 2019) with during-pandemic data (same months in 2020 and 2021) from electronic health records (EHRs) using Python to extract information from nursing notes. Various statistical analyses, including descriptive statistics to summarize the data, and a chi-square test to examine any significant association between the COVID-19 pandemic and the prevalence of dementia and agitation in dementia. Dementia prevalence dropped by 1.98% in 2021 compared to 2019, and by 4.09% compared to 2020 (p < 0.05). Overall agitation symptoms decreased by 20.1% from 2019 to 2021 (p < 0.05), but six specific symptoms increased: resisting (28.98%), wandering (11.78%), restlessness (3.19%), complaining (10.1%), arguing (2.36%), and outbursts (1.74%) (p < 0.05). Conversely, pacing decreased by 15.88% and speaking loudly de-creased by 10.9% (p < 0.05). Over half of the care recipients experienced agitation symptoms 2-5 times each year, increasing from 50.56% in 2019 to 58.28% in 2021 (p < 0.05). It is important to exercise caution regarding the accuracy of these findings due to the reduced opportunity for busy care staff to record behavioral changes caused by the isolation of individuals in their rooms during the pandemic.

The coexistence of SAH with T2DM is a common comorbidity. In this present study, we investigated the link between altered plasma antioxidant trace elements (ATE: Manganese, Selenium, Zinc and Copper) and fatty acids ratio (FAR: polyunsaturated/saturated) imbalance as transition biomarkers between vascular pathology (SAH) to metabolic pathology (T2DM). Our data revealed strong correlation between plasma ATE and FAR profile which is modified during SAH-T2DM association compared to healthy group. This relationship is mediated by lipotoxicity (simultaneously prominent visceral adipose tissue lipolysis, significant flow of non-esterified free fatty acids release, TG-Chol-dyslipidemia, high association of Total SFA, Palmitic acid, Arachidonic acid and PUFA 6/ PUFA 3; drop in tandem of PUFA / SFA and EPA+DHA); oxidative stress (lipid peroxidation confirmed by TAS depletion and MDA raise, concurrently drop of Zn/Cu-SOD, GPx, GSH, Se, Zn, Se/Mn, Zn/Cu; concomitantly enhance Cu, Mn and Fe); endothelial dysfunction (endotheline-1 increase); athero-thrombogenesis risk (concomitantly raise of ApoB100/ApoA1, Ox-LDL, tHcy and Lp(a)) and inflammation (higher of Hs-CRP, Fibrinogen and Ferritin). Our study open to new therapeutic targets and to better dietary management, such as to establish dietary ATE and PUFA 6 / PUFA 3 or PUFA / SFA reference values for atherosclerotic risk prevention in hypertensive-diabetics patients.

Delivering nucleic acid therapeutics across cell membranes is a significant challenge. Cell-penetrating peptides (CPPs) containing arginine (R), tryptophan (W), and histidine (H) show promise for siRNA delivery. To improve siRNA delivery and silencing a model STAT3 gene, we hypothesized that oleyl acylation to CPPs, specifically (WRH)n, would enhance STAT3 silencing efficiency in breast and ovarian cancer cells. Using Fmoc/tBu solid-phase peptide chemistry, we synthesized, purified, and characterized the oleyl-conjugated (WRH)n (n = 1-4) peptides. The peptide:siRNA complexes were non-cytotoxic at N/P 40 (~20 μM) against MDA-MB-231, MCF-7, SK-OV-3, and HEK-293 cells after 72 h incubation. All peptide:siRNA complexes showed serum stability at N/P ≥40. The synthesized conjugates, with a diameter of &lt;100 nm, formed nano complexes with siRNA and exhibited stable range of zeta potential values (13-18 mV at N/P 40). Confocal microscopy and flow cytometry analysis provided qualitative and quantitative evidence of successful cellular internalization of siRNA. Peptides oleyl-(WRH)3 and oleyl-(WRH)4 showed ~60% and ~75% cellular uptake of siRNA, respectively, in both MDA-MB-231 and SK-OV-3 cells. Western blot analysis of oleyl-(WRH)4 demonstrated effective silencing of the STAT-3 gene, with ~75% silencing in MDA-MB-231 cells and ~45% in SK-OV-3 cells.

This study investigated the development of novel probiotic formulations specifically designed for rainbow trout aquaculture. The project evaluated the effects of two formulations containing potential probiotic strains isolated from rainbow trout itself. These effects were assessed on various parameters including growth performance, immune response, liver enzyme activity, gene expression related to immunity, and the composition of the bacterial gut microbiota in rainbow trout (Oncorhynchus mykiss). In a completely randomized experimental design, a total of 450 rainbow trout were randomly divided into 70-liter fiberglass tank. The study included six treatments of three replicates (n=18 tanks). Six dietary treatments were included (A) and (B) containing three strains of Pediococcus sp P15, Lactococcus lactis ml3, Weissella cibaria ml6 at two dosages (300 and 500 mg/kg), treatments (C) and (D) containing five strains of P. sp P15, L. lactis ml3, W. cibaria ml6, Enterococcus faecium E10 and Lactobacillus curvatus 13A at two dosages (300 and 500 mg/kg), a commercial probiotic (E) at 300 mg/kg, and a control group (F) without probiotics. Treatments of (A), (B) and (E) resulted in the highest final weights in compared to control group. Fish fed treatments (A) and (B) had the lowest FCR than other groups. Treatments (A) and (D) showed a significant increase in immunoglobulin M (IgM) concentration compared to other groups. The expression of tumor necrosis factor (TNF) was significantly lower in group (A) than the control. In contrast, the expression of interleukin 6 (IL6) and immunoglobulin T (IgT) was increased 4.4-fold and 41-fold, respectively, in group (A) compared to control group. Among the probiotic fed treatments, group (A) showed a significant higher number of lactic acid bacteria compared to other groups during the experiment. This study highlights the significant role of treatment (A) containing three strains of P. sp P15, L. lactis ml3, and W. cibaria ml6 at a dosage of 300 mg/kg as a potential probiotic product for the rainbow trout industry.

Most of the mid-high permeability sandstone oilfields in China have entered the ultra-high water cut stage, accompanied with the highly-dispersed residual oil, and the control effect of mi-cro-heterogeneity on the residual oil is increasingly prominent. Understanding the microscopic characteristics of pore structural and its evolution during the long-term waterflooding is critical for enhancing the accuracy and efficiency of oil field exploitation. While the previous insights paid more attention to the geometrical and morphological features of pore structure and ignores the relation of pore structure with the fluid flow capacity. In this study, we propose a microscopic pore structure classification method considering pore size and local permeable capacity, which realizes the physical classification and quantitative evaluation of pore structure characteristics for different permeability rocks. The micro-pore structure is classified into 6 types based on the key evaluation parameters of pore diameter and flow flux area. By taking six mid-high permea-bility sandstone core samples from Daqing oilfield in China, a series of long-term waterflooding experiments are carried out and the interior pore structure was captured using high precision CT scanning technique. The results reveals that high-permeability reservoirs exhibit concentrated pores diameters and finer throats, whereas mid-permeability reservoirs exhibit smaller pores and throats in greater quantity. With the increase of water injection volumes, the permeable ca-pacity and connectivity of the high-connectivity pore space in ultra-high- and high-permeability reservoirs are enhanced, and in mid-permeability reservoirs, the micro-heterogeneity intensifies the increase in low-connectivity small pores. These findings provide new insights for the micro-scopic heterogeneity and a solid theoretical basis for investigating the occurrence of microscopic residual oil and optimising enhanced oil recovery strategies at the late stage of ultra-high water cut.

In this work, we introduce the first pipeline that combines a refraction-aware Structure-from-Motion (SfM) method with a deep learning model specifically designed for airborne bathymetry. We accurately estimate the 3D positions of the submerged points by integrating refraction geometry within the SfM optimization problem. This way, no refraction correction as post-processing is required. Experiments with simulated data that approach the real-world capturing conditions demonstrate that SfM with refraction correction is extremely accurate, with submillimeter errors. We integrate our refraction-aware SfM within a deep learning framework that also takes into account radiometrical information, developing a combined spectral and geometry-based approach, with further improvements on accuracy and robustness to different seafloor types, both textured and textureless. We conducted experiments with real-world data at 2 locations in the southern Mediterranean Sea, with varying seafloor types which demonstrate the benefits of refraction correction for the deep learning framework. We open-source our refraction-aware SfM, providing researchers in airborne bathymetry with a practical tool to apply SfM in shallow water areas.

This article presents the analysis of the allocation of important plant areas (IPA), which urgently identifies the most valuable sites for protecting plant objects. The study is based on a comprehensive inventory of the species composition of plants in the flora of the Western Karatau Ridge and the Mangyshlak Peninsula (arid regions)- key sites Akmysh, Samal, and Kogez, considered standard and the best preserved with natural vegetation cover. The flora of these critical sites was analysed using a combination of field surveys, herbarium studies, and a literature review. The results revealed a rich biodiversity, with 104 species from 82 genera and 33 families. Most species belong to 9 families, making up 60.6% of the total taxa. By the nature of life forms, perennial herbaceous plants dominate in all key sites (30 species, 50.0%). The eco-phylogenetic spectrum showed that a significant share of the flora of the studied IPAs is made up of xerophytes (21 species, 35%) and xeromesophytes (9 species, 15%); desert and mountain-steppe species prevail (53.0%). Rare, endangered and Red Book species account for 10-21.3% of those growing in the region. Regarding economic value, fodder, ornamental, honey, medicinal and food species dominate. The Shannon, Simpson, and Jaccard indices assessed alpha-beta and gamma diversity. The index showed that biodiversity in the Samal and Kogez sites is higher and more evenly distributed compared to the Akmysh site. The Whittaker, Harrison and Cody indices confirm significant differences in the species composition between the sites. In light of these compelling results, a clear and urgent call to action is proposed to allocate these areas to the IPA category, a crucial step towards ensuring the long-term existence of natural biocenoses.