Appropriate animal models of human diseases are a cornerstone in the advancement of science and medicine. To create animal models of neuropsychiatric and neurobehavioral diseases such as ASD necessitates the development of sufficient neurobehavioral measuring tools to translate human behavior to expected measurable behavioral features in animals. Indeed, at least in rodents, adequate neurobehavioral and neurological tests have been developed. Since ASD is characterized by a number of specific behavioral trends with significant severity, animal models of autistic-like behavior have to demonstrate the specific characteristic features, namely impaired social interactions, and communication, restricted, repetitive behavioral patterns with association to several additional impairments such as somatosensory, motor and memory impairments. Thus, an appropriate model must show behavioral impairment of a minimal number of neurobehavioral characteristics using an adequate number of behavioral tests. The proper animal models enable the study of ASD like-behavior from the etiologic, pathogenetic and therapeutic aspects. From the etiologic aspects, models have been developed by the use of immunogenic substances like polyinosinic-polycytidylic acid (PolyIC), Lipopolysaccharide (LPS) and propionic acid or other well-documented immunogens or pathogens, like mycobacterium tuberculosis. Another approach is the use of chemicals like valproic acid, Polychlorinated biphenyls (PCBs), organophosphate pesticides - chlorpyrifos (CPF) and others. These substances were administered either prenatally, generally after the period of major organogenesis, or, especially in rodents, during the early postnatal life. In addition, using modern genetic manipulation methods, genetic models have been created of almost all human genetic diseases that are manifested by autistic like behavior (i.e. fragile X, Rett syndrome, SHANK gene mutation Neuroligin genes and others). Ideally, we should not only evaluate the different behavioral modes affected by the ASD-like behavior but also assess the severity of the behavioral deviations by an appropriate scoring system, as applied to humans.

Semi-Interlocking Masonry (SIM) represents an innovative building system developed at the Centre for Infrastructure Performance and Reliability at The University of Newcastle, Australia. This system employs a unique approach to interlocking mortar-less engineered masonry panels constructed from SIM units. These units are designed to offer substantial energy dissipation capacity, primarily attributed to the friction occurring on the sliding bed joints between the units within the panel during seismic events. The primary aim of this study is to evaluate the viability of incorporating semi-interlocking masonry as infill panels in the construction of multi-storey buildings across diverse geographical locations with varying seismic conditions in Australia. To assess the feasibility of SIM panels in different conditions (according to Australian Standard AS1170) in Australia, a comprehensive analysis using Strand7 is conducted on a three-storey structure incorporating traditional masonry infill panels and SIM panels. The comparison of displacement and base shear capacities is carried out in response to seismic events across various scenarios in different locations within Australia. The insights gained from this comparative analysis contribute valuable information regarding the viability of implementing SIM as a contemporary construction material.

Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

Quaking aspen (Populus tremuloides Michx.) landscapes are valued for their biodiversity, water retention, fire mitigation, aesthetics, and recreation opportunities. Across North America, some aspen populations are experiencing population declines as they face uninhibited ungulate browsing, drought, fire suppression, insects, disease, and inappropriate management. Increased human development and recreational use within aspen landscapes can serve as additive stressors, though there is a dearth of literature examining these elements. At a popular recreational area in Utah, USA, identifying the cause of apparent decline within a larger aspen community is complicated by development upstream and recreation-related activities. We sought to: 1) assess the overall condition of the aspen at the site, 2) understand key variables that influence aspen conditions, and 3) elucidate how aspen fitness varies across the site. We collected data from forty-five plots using established aspen sampling methods, including ungulate presence, tree characteristics, soil chemistry, and environmental descriptors. Results suggest that a combination of higher levels of browsing and elevated soil sodium may be causing premature mortality and limiting aspen recruitment in a portion of the study area. These findings will inform future management at this site, as well as similar recreational forest settings experiencing compound stressors.

The observation that certain therapeutic strategies for targeting inflammation benefit patients with distinct immune-mediated inflammatory diseases (IMIDs) is exemplified by the success of TNF blockade in conditions including rheumatoid arthritis, ulcerative colitis and skin psoriasis, albeit only for subsets of individuals with each condition. This suggests intersecting "nodes" in inflammatory networks at a molecular and cellular level may drive and/or maintain IMIDs, being “shared” between traditionally distinct diagnoses without mapping neatly to a single clinical phenotype. In line with this proposition, integrative tumour tissue analyses in oncology have highlighted novel cell states acting across diverse cancers, with important implications for precision medicine. Drawing upon advances in the oncology field, this narrative review will first summarise learnings from the Human Cell Atlas in health as a platform for interrogating IMID tissues. It will then review cross-disease studies to date that inform this endeavour, before considering future directions in the field.

CO2 emission activity of xylotrophic fungi response to an increase in temperature in the range of 10-30 °C on the example of pure dikaryotic cultures of Fomes fomentarius s. str., F. inzengae, Fomitopsis betulina, F. pinicola, Phellinus igniarius was analyzed. Emission activity was assessed by the difference in CO2 concentration in 0.5-liter exposure chambers with Petri dishes with mycelium growing on agar at the beginning of exposure and an hour later using a Gasmet DX-4030 FTIR spectrometer (Gasmet Technologies Oy, Finland), error measurements ±50 ppm. Specific (μg CO2/cm2/h) and total (μg CO2/h) emission activity and its relationship with temperature and size (area) of the mycelium were assessed. It has been shown that in the range of 10-30 °C, the specific and total CO2 emission activity of the mycelium is closely and positively related to temperature. Specific emission, which is an indicator of the respiratory activity of the mycelium, does not depend on its size; its only driver is temperature, the relationship with which is linear: an increase in temperature by 10 °C causes an increase in the specific emission activity of the mycelium by 1.7 times. The total CO2 emission activity, which is an indicator of the total amount of CO2 emitted, is directly proportional to the specific emission activity and the size of the mycelium. In the range of 10-30 °C, an increase in temperature causes an almost equal increase in both the specific emission activity of the mycelium (Q10 1.7) and its growth (Q10 1.5) and causes an exponential increase in the total emission of CO2. This must be taken into account when predicting CO2 emissions from woody debris under climate change, as it could potentially contribute to accelerating climate change.

As technology advances, the field of electrical and computer engineering continuously demands the introduction of innovative new tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. This research addresses an identified gap in technology-augmented education capabilities and researches the integration of Virtual Reality (VR) technology with real-time electronic circuit simulation to enable and enhance the visualization of non-observable concepts such as voltage distribution and current flow within these circuits. In this paper, we describe the development of our immersive educational platform, which makes understanding these abstract concepts intuitive and engaging. This research also involved the design and development of a VR-based circuit simulation environment. By leveraging VR’s immersive capabilities, our system enables users to physically interact with electronic components, observe the flow of electrical signals, and manipulate circuit parameters in real-time. Through this immersive experience, learners can gain a deeper understanding of fundamental electronic principles, transcending the limitations of traditional two-dimensional diagrams and equations. Furthermore, this research focuses on the implementation of advanced and novel visualization techniques within the VR environment for non-observable electrical and electromagnetic properties, providing users with a clearer and more intuitive understanding of electrical circuit concepts. Examples include color-coded pathways for current flow and dynamic voltage gradient visualization. Additionally, real-time data representation and graphical overlays are researched and integrated to offer users insights into the dynamic behavior of circuits, allowing for better analysis and troubleshooting.

Greek roots: "phos" (φῶς) - means "light" and "dynamis" (δύναμις) - means "force" or "power". Photodynamic therapy (PDT) is an innovative treatment method based on the ability of photosensitizers to produce reactive oxygen species after exposure to light of a specific wavelength range, either in the visible or near infrared range. This process results in damage to pathological cells, such as cancer cells, while minimizing the impact on healthy tissues. PDT is a promising direction in the treatment of many diseases, with particular emphasis on the fight against cancer and other diseases asso-ciated with excessive cell growth. The power of light contributed to the creation of phototherapy, whose history dates back to ancient times. It was then noticed that some substances exposed to the sun have a negative effect on the body, while others have a therapeutic effect. This work provides a detailed review of photodynamic therapy, from its origins to the present day. It is surprising how a seemingly simple beam of light can have such a powerful healing effect, which is used not only in dermatology, but also in oncology, surgery, microbiology, virology, and even dentistry. However, despite promising re-sults, photodynamic therapy still faces many challenges. The availability of this thera-py is limited due to the small number of centers offering this type of treatment and the high costs, which may be unaffordable for many patients. Moreover, photodynamic therapy requires further research and improvement.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

In the ground-based infrared optical remote sensing system, the target signal is very weak due to the dynamic strong light background and the movement of small and small targets. In order to improve the limit detection capability, the background suppression and target enhancement methods are required to be more suitable for this scene. To solve this problem, we first analyze the image features in the current scene, and propose a more perfect point target and noise model. Then, we propose a new WY distribution function based on the Fermi Dirac distribution function, and propose an anisotropic filtering method based on this function, and further suppress the back-ground through the difference results of two steps. Then, based on the distribution function, we further designed an energy concentration accumulation strategy in 9 scale directions, through which the SNR of the target is effectively improved and the suppression ability of the background is enhanced. Through quantitative and qualitative experimental analysis, compared with the same type of algorithms, the proposed method has better robustness against extremely weak targets and dynamic backgrounds.

Over the last decade, a lot of research has been conducted on memristors. Most of this research focusses on using memristors for Artificial Intelligence (AI) applications and to fabricate non-volatile memory, but also the security aspects of memristors have been examined. The current study summarises and compares five reviews on the security aspects of memristors. These reviews cover two different perspectives: (1) security applications of memristors such as Physical Unclonable Functions (PUFs) or True Random Number Generators (TRNGs), and (2) potential threats when using memristors to train and store neural networks. The comparison of the reviews reveals that different sets of studies are included in the reviews and different characterisations of the studies are provided. This shows that different perspectives are necessary to get a comprehensive overview of the security aspects of memristors. By synthesising the perspectives of different reviews, this study helps to get such an overview.

To address the problems of insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model called BERT_hybrid based on BERT and hybrid attention mechanism. In this model, BERT is utilized to separately map the text and questions into the feature space. Through the integration of Bi-LSTM, attention mechanism, and self-attention mechanism, the proposed model achieves comprehensive semantic fusion between text and questions. The probabilities distribution of answers is computed using Softmax. Experimental results on the public dataset DuReader demonstrate that the proposed model achieves improvements in BLEU-4 and ROUGE-L scores compared to existing models. Furthermore, to validate the effectiveness of the proposed model design, we analyze the factors influencing the model’s performance.

In this paper, the feasibility and potential assessment (PA) of wind power in six different areas MehalMeda, Eneware, DebreBerhan, AlemKetema, GundoMekel, and Majet are investigated. The data is collected from the National Metrological Agency (NMA) in Addis Ababa and from the districts of the case study areas and analyzed using MATLAB and HOMER software. Using the data collected at 10 meter height, wind direction using a wind rose, the wind frequency distribution, and wind turbine characteristics have been analyzed. Moreover, to obtain a more realistic wind potential study, the wind speed at a 10 meter height is extrapolated to a height of 50 meter in order to determine wind speed, wind power density, and wind energy density. The average wind speed of the zone at 10m and 50m heights are 1.58 m/s and 1.99 m/s, 3.06 m/s and 3.85 m/s, 4.75 m/s and 5.98 m/s, 2.29 m/s and 2.88 m/s, 1.01 m/s and 1.27 m/s and 4.07 and 5.12m/s at Alemketema, Debreberhan, Eneware, Gundemeskel, Majete and Mehalmeda respectively. The extrapolated result shows that the maximum wind speed and power densities at a height of 50 meter for Eneware, MehalMeda and Debre Berhan are 10.4 m/s, 689 W/m2, 8.9m/s, 429 W/m2 and 6.3m/s, 152.2 W/m2 respectively. The energy densities at a height of 50 meter for AlemKetema, DebreBerhan, Eneware, GundoMekel, Majete, and MehalMeda are 181.06 kWh/m2*yr , 1332.83 kWh/ m2*yr, 6078.91 kWh/ m2*yr, 857.76 kWh/ m2*yr, 58.78 kWh/ m2*yr, and 3939.42 kWh/ m2*yr respectively. As per the international standard for wind power and wind speed classification, considering the extrapolated height, Eneware, MehalMeda, and DebreBerhan have feasible wind potential for both small-scale and large-scale wind farm implementation, whereas Majete, AlemKetema, and GundoMeskel of the North Shewa Zone in the Amhara region have poor wind potential.

The fatty acid composition, biophenol, tocopherol, sterol and triterpenic dialcohol content and composition of the autochthonous Slovenian olive varieties 'Buga', 'Črnica' and 'Drobnica' were studied during a three-year period with the aim to valorise the characteristics of the three olive varieties. Standardized and accredited analytical methods were applied. The results of the investigation showed that the highest average amount of oleic acid (75.75%) was determined in oils of the variety 'Črnica', followed by 'Drobnica' (72.06%) and 'Buga' (68.73%). All the three varieties are a good source of total biophenols ('Buga' 616 mg/kg, 'Drobnica' 569 mg/kg and 'Črnica' 427 mg/kg) and α-tocopherol ('Buga' 378 mg/kg, 'Drobnica' 279 mg/kg and 'Črnica' 243 mg/kg). 'Buga' and 'Drobnica' are characterised by high amounts of total sterols, 2468 mg/kg and 2391 mg/kg, respectively, 'Črnica' oils, in comparison, showed a lower average value of total sterols (1351 mg/kg). The acquired data of the autochthonous Slovenian olive varieties 'Buga', 'Črnica' and 'Drobnica' are very important to valorise the characteristics of the produced oils. The studied varieties showed a great potential for further cultivation and valorisation of the traditional olive oil production of the region and are important for preserving the biodiversity and tradition of the territory.

In Mexico there is a deficit in the production of pine resin, because it depends on natural forests. Therefore, it is necessary to select provenances and phenotypes of potential species such as P. oocarpa. The objective was to determine the difference between provenances and the variation of resin components and quality, as well as the effect of geographic and climatic factors. Resin from five provenances was collected from southern Mexico. The percentage of rosin, turpentine and water was obtained, as well as the acidity and saponification index. P. oocarpa resin had 80.94 % rosin, 7.7 % turpentine and 11.49 % water. The saponification and acidity index was 125.47 and 117.49 mg KOH.g_1, respectively. All variables showed differences (p≤ 0.0001) between provenances. The provenance contributed between 6.44 and 11.71 % to the total variance, the error contributed between 88.29 and 93.56 %. Geographic and climatic variables only had an effect on the percentage of turpentine; the correlation was negative with altitude and longitude, but positive with temperature and precipitation. The results allow defining seed collection sites for resin plantations and orienting the selection for a P. oocarpa improvement program.

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020-2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment's effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.

Graph visualization has evolved significantly over time, offering various methods to effectively represent complex data structures. This study introduces a novel force-directed algorithm for 3D data visualization, specifically tailored for commonly used datasets in linked data visualization. Leveraging the power of graph theory and methods, the algorithm aims to address the challenge of creating visually appealing and easily interpretable visualizations, which often necessitate advanced user interaction. By utilizing 3D space and the Unity Engine, the research successfully visualizes data and develops interactive visualizations, overcoming limitations of basic force-directed implementations. The main contribution of presented research is in the force-directed algorithm with springs and controlled placement as a visualization technique that combines the use of springs and attractive forces to stabilize a graph in a 3D environment. The combination of these two techniques also helps prevent the formation of a single large cluster within the graph, enhancing the overall visualization quality.

The mechanisms underlying the establishment of asymmetric structures during development remain elusive. The wing of Drosophila is asymmetric along the Anterior-Posterior (AP) axis, despite that its growth signals that drive its growth are presumably symmetric. Here, we investigated the contribution of cell recruitment, a process that drives wing fate differentiation in Drosophila, to the asymmetric shape and pattern of the adult wing. Genetic impairment of cell recruitment results in a significant reduction in adult wing asymmetry, primarily affecting the region between longitudinal vein 5 and the wing margin (L5-M). Morphometric analysis reveals that the lack of cell recruitment results in a more symmetric wing with respect to the AP, suggesting a contribution of cell recruitment to the establishment of asymmetry in the adult wing. A close examination of the expression of the wing selector gene vestigial (vg) in wing disc does not support this hypothesis. However, the circularity of the Vg pattern significantly increase in recruitment-impaired wing disc, suggesting that while the decrease of the L5-M region in the adult wing may not be attributed to cell recruitment, it could contribute to the overall asymmetry of the adult wing. We conclude that cell recruitment, a widespread mechanism that participates in growth and patterning of several developing systems, could drive, at least partially, the asymmetric shape of the Drosophila wing.

The analysis and simulation of water quality in distribution networks is a complex issue of great concern today. The analysis of the evolution of water age, as a simple indicator of water quality in the network, is of great interest in both design and operation phases. Understanding the factors that have the strongest influence on water quality is key to developing adequate strategies aimed at preserving it. This paper firstly analyses the factors with biggest influence in the tanks water age, to support the selection of the most appropriate configuration from the point of view of water quality during design phases. Then, the main considerations when modelling tanks following the different mixing models considered in Epanet have been presented. Also, a real tank behaviour has been characterised through field measurements and Epanet simulations in order to determine the best fitted mixing model.

Reasonable allocation of production plans and saving the overall electricity cost are crucial for large manufacturing conglomerates, which is an effective way for conglomerates to realize open-source and cost-saving. This paper develops an optimization model of off-site industrial production scheduling for enterprises in response to the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's electric power and the difficulty of promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and different electricity prices in different places to optimize the scheduling of industrial production in different places. The model is embedded with two sub-models of the electricity price prediction model and distributed photovoltaic kWh cost model to complete the model parameters, in which the electricity price prediction model utilizes the LSTM neural network. The integrated model is then solved by the particle swarm algorithm. To verify the effectiveness of the model in solving the problem of off-site production scheduling on the demand side of electricity, the research team researched two off-site pharmaceutical factories belonging to the same large pharmaceutical company. Finally, the research data were substituted into the model for solving, and it was concluded that the optimization model could significantly reduce the cost of electricity consumption of the enterprise by about 7.9 %.

Globalization, knowledge economy, information technology advancements, and the rise of learning societies contribute to the concept of a learning city. The study examines the economic indicators of Yazd city, Iran, in the context of learning city development. A descriptive-analytical approach with a survey method and cluster sampling was employed. Data analysis involved Kolmogorov-Smirnov normality test, single-sample T-test, simple linear regression, and Kendall's W test. The normality test confirmed data normality. The T-test indicated that experts perceived the current state of most variables in Yazd as undesirable. Regression analysis revealed a significant positive association between the economic index and independent variables. Kendall's W test prioritized areas based on economic indicators, with the top 7 and bottom 5 areas identified for focused interventions. The study emphasizes the need to prioritize areas within Yazd based on their economic indicators. This prioritization informs strategies for enhancing social and legal aspects of Yazd's transformation into a learning city. Further research should explore effective methods to cultivate a full-fledged learning environment in the city.

Tuberculosis (TB) remains a global health threat, necessitating innovative strategies for control and prevention. This comprehensive review explores the Mycobacterium tuberculosis Lysine Exporter (LysE) gene, unveiling its multifaceted roles and potential uses in controlling and preventing tuberculosis (TB). As a pivotal player in eliminating excess L-lysine and L-arginine, LysE contributes to the survival and virulence of M. tuberculosis. This review synthesizes findings from different electronic databases and includes 13 studies focused on the LysE of M. tuberculosis. The research unveils that LysE can be a potential drug target, a diagnostic marker for TB, and a promising candidate for vaccine development. The absence of LysE in the widely used BCG vaccine underscores its uniqueness and positions it as a novel area for TB prevention. In conclusion, this review underscores the significance of LysE in TB pathogenesis and its potential as a drug target, diagnostic marker, and vaccine candidate. The multifaceted nature of LysE positions it at the forefront of innovative approaches to combat TB, calling for sustained research efforts to harness its full potential in the global fight against this infectious disease.

Hepatitis C virus (HCV) is a major public health threat associated with serious clinical consequences worldwide. The WHO reports an estimated 58 million people globally living with chronic hepatitis C virus (HCV) infection, with 1.5 million new cases and over 350,000 deaths annually due to HCV-related diseases. Despite the existence of multiple diagnostic methods, the accessibility of diagnosis and treatment is often hindered across the continent by limited resources, insufficient healthcare infrastructure, and low public awareness of Hepatitis C virus Hepatitis C virus infection is a major public health concern in African countries, which have the highest prevalence rates of HCV in the world (1–26%). Egypt, African country which had the highest prevalence of Hepatitis C virus infection in the world. Its national hepatitis C elimination initiative emerges as an exemplary case of success an having screened over 60 million individuals, and treated more than 4 million, thereby markedly diminishing both the prevalence and incidence of the disease. The strategies employed by Egypt offer critical insights and adaptable frameworks for other African Countries facing analogous challenges. The Aim of this Review is to highlight the triumphs and hurdles of Egypt's approach, while also providing strategic guidance for African Countries to accelerate the journey towards the eradication of hepatitis C.

This study aimed to review the dietary risk factors for root caries prevalence in older adults, from socially active people to frail patients. A comprehensive search strategy was used to select studies from PubMed and Scopus databases. Two evalua-tors performed data extraction, screening, and quality assessment independently. Only studies written in English were included. Caries is very common in the elderly, as there are several aggravating factors such as the decrease of the ability to self-care and, by extension, insufficient oral hygiene, a carious diet, limited exposure to fluoride, xero-stomia, gingival recession, limited access to dental care. Root caries is prevalent in the elderly due to gingival recession and root exposure to the oral environment. Dietary risk factors significantly affect root caries prevalence in older adults, including high intake of sugars and an alteration of their composition preference in this age group. Caries risk appears more significant in frail, standardized patients who feed with even softer food or supplements.

The increasing availability of longitudinal data (repeated numerical observations of same units at different times) requires the development of flexible techniques to automatically detect common errors in such data. Besides obvious and easily identifiable cases, such as missing or out-of-range data, large longitudinal dataset often present problems not easily traceable by the techniques used for generic datasets. In particular, elusive and baffling problems are i) inversion of one or more values from one unit to another; ii) anomalous jumps in the series of values, iii) errors in the timing of the values due to a recalculation operated by the data providers to compensate previous errors. This work proposes a statistical-mathematical approach based on a system of indicators that is able to capture the complexity of the described problems by working at the formal level, regardless of the specific meaning of the data. The proposed approach identifies suspect erroneous data and is applicable in a variety of contexts. We implement this approach in a relevant database of European Higher Education institutions (ETER) by analyzing Total academic staff, that is one of the most important variables, used in empirical analysis as proxy of size and also considered by policy makers at European level.

In the dynamic landscape of modern education, characterized by an increasingly active involvement of IT technologies in learning, the imperative to transfer to students the skills necessary to integrate Artificial Intelligence (AI) into the process represents an important goal. This paper presents a novel framework for knowledge transfer, diverging from traditional programming language-centric approaches by integrating PSoC 6 microcontroller technology. This framework establishes a cyclical learning cycle encompassing theoretical fundamentals and practical experimentation, fostering AI literacy at the edge. Through a structured combination of theoretical instruction and hands-on experimentation, students develop proficiency in understanding and harnessing AI capabilities. Emphasizing critical thinking, problem-solving, and creativity, this approach equips students with the tools to navigate the complexities of real-world AI applications effectively. By leveraging PSoC 6 as an educational tool, a new generation of individuals is efficiently cultivated with essential AI skills. These individuals are adept at leveraging AI technologies to address societal challenges and drive innovation, thereby contributing to long-term sustainability initiatives. Specific strategies for experiential learning, curriculum recommendations, and results of knowledge application are presented, aimed at preparing students to excel in a future where AI will be omnipresent and indispensable.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Floods are among the most serious natural disasters worldwide; they cause enormous crop losses every year and threaten world food security. There are many studies focused on flood impact assessments for administrative districts but fewer on postdisaster impact assessments for specific crops. Therefore, this study used remote sensing data, including the normalized difference vegetation index (NDVI), elevation data, slope data, and rainfall data, combined with crop growing season data to construct a crop flood damage assessment index (CFAI). First, an analytic hierarchy process (AHP) was used to assign weights to the impact factors; then, the weighted composite score method was used to calculate the CFAI; and finally, the impact was classified as slight, moderate, or severe based on the magnitude of the CFAI . This method was used for the Missouri River floods of 2019 in the U.S. Due to the lack of measured data, the disaster vegetation damage index (DVDI) was used to validate the results. The combined approach achieved a high degree of consistency in spatial distribution. The CFAI can respond well to the degree of crop impact after flooding, providing new ideas and reference standards for agriculture-related departments.

Giant unilamellar vesicles (GUVs) are membrane model used to study membrane properties. Electroformation is one of the methods used to produce GUVs. During electroformation protocol dry lipid film is formed. Drying of the lipid film induce Cholesterol (Chol) demixing artifact, in which Chol forms anhydrous crystals, where these crystals does not participate in formation of vesicles. This leads to a lower Chol concentration in the vesicle bilayers compared to the Chol concentration in the initial lipid solution. To address this problem, we propose novel electroformation protocol that includes rapid solvent exchange, plasma cleaning and spin-coating methods to produce GUVs. We tested the protocol focusing on vesicles with high Chol content using different spin-coating durations and vesicle types deposition. Additionally, we compared the novel protocol using completely dry lipid film. The optimal spin-coating duration for vesicles made out of phosphatidylcholine/Chol mixture was 30 s. Mulitlamellar vesicles (MLVs), large unilamellar vesicles (LUVs) obtained by extrusion of MLVs through 100 nm membrane pores and LUVs obtained by extrusion of previously obtained LUVs through 50 nm membrane pores were deposited on electrode for 1.5/1 Chol/phosphatidylcholine lipid mixture and the results were compared. Electroformation using all three deposited vesicle types gave a high GUVs yield, but deposition of LUVs obtained by extrusion of MLVs through 100 nm membrane pores gave the most reproducible results. Using deposition of these LUVs, we produced GUVs with high yield for 6 different Chol concentrations (from 0 % to 71.4%). Using protocol that includes dry lipid film GUVs yield was lower and Chol demixing artifact was induced, proving that the lipid film should never undergo drying when Chol content is high.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

Nanocrystalline silicon oxide (nc-SiOx:H) is a multipurpose material with its varied application in solar cells as a transparent front contact, intermediate reflector, back reflector layer and even tunnel layer for passivating contacts, owing to easy tailoring of its optical properties. In this work, we systematically investigate the influence of gas mixture (SiH4, CO2, PH3 and H2), RF power and process pressure on the optical, structural and passivation properties of thin n-type nc-SiOx:H films prepared in an industrial, high throughput, plasma-enhanced chemical vapor deposition (PECVD) reactor. We provide a detailed description of the n-type nc-SiOx:H material develop-ment using various characterization techniques (SEM, EDX, Raman spectroscopy, and spectro-scopic ellipsometry) with a focus on the relationship between the material properties and the pas-sivation they provide to n-type c-Si wafers characterized by their effective carrier lifetime (τeff). Further, we also outline the parameters to be kept in mind while developing different n-type nc-SiOx:H layers for different solar cell applications. We report a tunable optical gap (1.8 – 2.3 eV) for our n-type nc-SiOx:H films as well as excellent passivation properties with τeff up to 3.5 ms (iVoc ~ 715 mV) before annealing. Oxygen content plays an important role in determining the crystallinity and hence passivation quality of the deposited nanocrystalline silicon oxide films.

China's cotton production has shown a concentration to the advantageous regions in recent years. Based on the relevant data of cotton production in China, the study measures the cotton production agglomeration levels of 16 major cotton-producing provinces from 1978 to 2020, summarizes the spatiotemporal evolution characteristics of cotton production agglomeration, and analyzes the factors influencing cotton production agglomeration using spatial econometric models. The results indicate that: Firstly, since the opening-up and reform, China's cotton production agglomeration levels have shown an overall upward trend, exhibiting periodic dynamic changes over time, and the spatial pattern reveals a dynamic regional gradient. Secondly, there is spatial correlation among the production scales of cotton in different provinces, with a trend resembling a "U" shape, and the agglomeration form shows a low-level convergence. Thirdly, technological level, policies, substitute industrial products and foreign trade are identified as important factors. The cotton production in each province is spatially correlated through these factors, and there is also a presence of spillover effects. In conclusion, the government should prioritize considerations of various influencing factors to formulate tailored support policies, promote large-scale production to enhance technological levels, and focus on policies aimed at improving the quality of cotton.

Global warming may increase the potential evapotranspiration (Etp), thereby affecting the amount of clean water resources available in a region. In this study, the systematic biases in temperature outputs of 24 global climate models (GCMs) under 3 emission scenarios are corrected by using 8 bias correction methods. The trend of Etp in Yangzi River Delta in the 21st century is projected by using 4 Etp calculation formulas. The uncertainty of the projections is estimated and decomposed by using multi-way analysis of variance. The influence of uncertainty on the projected change signal is quantified by using the signal-to-noise ratio. The results show that, relative to the reference period (1971~2000), the annual mean daily Etp in Yangzi River Delta will increase by 0.14~0.17mm/d during the period 2021~2050 and by 0.21~0.41mm/d during the period 2061~2090, respectively. During 2021~2050, the uncertainty of Etp increase projections is dominantly contributed by the main effects of GCM (63%) and Etp calculation formula (24%). During 2061~2090, it is mainly contributed by the main effect of GCM (36%), followed by the main effects of emission scenario (34%) and Etp calculation formula (18%). The increase projections of Etp are generally reliable and robust during the two projection periods.

In this study, the olive pomace was considered because of its importance in the environment. So, this study carried out to estimate the total nitrogen content and the fatty acids profile of olive pomace. The olive pomace samples were collected from Irbid, Jarash, Ajloun and Mafraq during the harvesting season 2014 to study the biochemical characteristics of fatty acid composition and the total nitrogen (TN) content. The total nitrogen content was determined by standard Kjeldahl method and the fatty acid profile was detected by gas chromatography (GC). The results show that the total nitrogen content ranged from (0.39 ± 0.0) to (0.62 ± 0.02) with statistically significant difference suggesting that the composition of matrices and their percentage may be responsible for composition of amendments. The calculated total protein percentage ranged between (2.43 ± 0.00) to (3.87 ± 0.17). Also, 13 different fatty acids were quantitatively profiled and quantitated. Oleic acid (C 18:1) was found to be the highest percentage of all other fatty acids and ranged between (59.03%) and (63.81%), moreover the C 18:1/C 18:2 (oil quality) was calculated and C.V% showed variation meaning that nutritional implication could affect the oxidative stability of oils. In conclusion, OP by-product could give a sustainable and alternative-cheap source for fertilizers, pharmaceutical industries, cosmetics and other industries.

A typhoon-induced storm surge is considered one of the most severe coastal disasters in Taiwan. However, the combination of the storm surge and the astronomical tide called the storm tide can actually cause extreme flooding in coastal areas. This study implemented a two-dimensional hydrodynamic model to account for the interaction between tides and storm surges on the coast of Taiwan. The model was validated with observed water levels at Sauo Fish Port, Hualien Port, and Chenggong Fish Port under different historical typhoon events. The model results are in reasonable agreement with the measured data. The validated model was then used to evaluate the effects of the typhoon's intensity, bathymetric change, and the combination of the typhoon’s intensity and bathymetric change on the maximum storm tide and its distribution along the east coast of Taiwan. The results indicated that the maximum storm tide rises to 1.92 m under a typhoon with an intensity of a 100-year return period. The maximum storm tide increased from a baseline of 1.26 m to 2.63 m for a 90% bathymetric rise at Sauo Fish Port under the conditions of Typhoon Jangmi (2008). The combination of the intensity of a typhoon with a 100-year return period and a 90% bathymetric rise will result in a maximum storm tide exceeding 4 m, 2 m, and 3 m at Sauo Fish Port, Hualien Port, and Chenggong Fish Port, respectively. We also found that the distribution of the maximum storm tide on the east coast of Taiwan can expand significantly subject to the bathymetric rise.

As with many of the non-deterministic search algorithms, particularly those are analogous to complex biological systems, there are a number of inherent difficulties, and the Bees Algorithm (BA) is no exception. Basic versions and variations of the BA have their own drawbacks. Some of these drawbacks are a large number of parameters to be set, lack of methodology for parameter setting and computational complexity. This paper describes a Grouped version of the Bees Algorithm (GBA) addressing these issues. Unlike its conventional version, in this algorithm bees are grouped to search different sites with different neighbourhood sizes rather than just discovering two types of sites, namely elite and selected. Following a description of the GBA, the results gained for 12 benchmark functions are presented and compared with those of the basic BA, enhanced BA, standard BA and modified BA to demonstrate the efficacy of the proposed algorithm. Compared to the conventional implementations of the BA, the proposed version requires setting of fewer parameters, while producing the optimum solutions much faster.

Mass hauling operations play central roles in construction projects. They typically use many haulers that consume large amounts of energy and emit significant quantities of CO₂. However, practical methods for estimating the energy consumption and CO₂ emissions of such operations during project planning are lacking. This paper presents a detailed model for estimating the energy consumption and CO₂ emissions of mass haulers that integrates the mass hauling plan with a set of predictive equations. The mass hauling plan is generated using a planning program such as DynaRoad in conjunction with data on the productivity of selected haulers and the amount of material to be hauled during cutting, filling, borrowing, and disposal operations. This plan is then used as input for estimating the energy consumption and CO₂ emissions of the selected hauling fleet. The proposed model will help planners to assess the energy and environmental performance of mass hauling plans, and to select hauler and fleet configurations that will minimize these quantities. The model was applied in a case study, demonstrating that it can reliably predict energy consumption, CO₂ emissions, and hauler productivity as functions of the hauling distance for individual haulers and entire hauling fleets.

Wildfires have always been a part of the history of Mediterranean forests. However, forest regeneration after a wildfire is not certain. It depends on many factors, some of which may be influenced by land management activities. Failure of regeneration will cause a regime shift in the ecosystem, reducing the provision of ecosystem services and ultimately leading to desertification. How can we increase Mediterranean forests’ resilience to fire? To answer this question, we did a literature review, investigating chains of processes that allow forests to regenerate (which we label “regeneration mechanisms”), and assessed the impact of selected management practices documented in the WOCAT database on the regeneration mechanisms. We identified three distinct regeneration mechanisms that enable Mediterranean forests to recover, as well as the time frame before and after a fire in which they are at work, and factors that can hinder or support resilience. The three regeneration mechanisms enabling a forest to regenerate after a fire consist of regeneration (1) from a seed bank; (2) from resprouting individuals; and (3) from unburned plants that escaped the fire. Management practices were grouped into four categories: (1) fuel breaks, (2) fuel management, (3) afforestation, and (4) mulching. We assessed how and under what conditions land management modifies the ecosystem’s resilience. The results show that land management influences resilience by interacting with resilience mechanisms before and after the fire, and not just by modifying the fire regime. Our analysis demonstrates a need for adaptive – i.e. context- and time-specific – management strategies.

Urbanization is considered as a main indicator of regional economic development due to its positive effect on promoting industrial development; however, many regions, especially developing countries, are troubled by its negative effect — the aggravating environmental pollution. Many researchers have indicated that rapid urbanization stimulated the expansion of industrial production scale and increased industrial pollutant emissions. However, this judgement contains a grave deficiency in that urbanization not only expands industrial production scales but can also increase industrial labour productivity and change the industrial structure. To modify this deficiency, we first decompose the influence which urbanization impacts on industrial pollutant emissions into the scale effect, the intensive effect and the structure effect by using the Kaya Identity and the LMDI Method; second, we perform an empirical study of the three effects’ impacts by applying the spatial panel model with data from 282 Chinese cities between 2003 and 2013. Our results indicate that (1) there are significant reverse U-shapes between Chinese urbanization rate and its industrial pollutant emissions; (2) the scale effect and the structure effect have aggravated Chinese industrial waste water discharge, sulphur dioxide emissions and soot (dust) emissions, while the intensive effect has generated a decreasing and ameliorative impact on that aggravated trend. The definite relationship between urbanization and industrial pollutant emissions depends on the combined influence of the scale effect, the intensive effect and the structure effect; (3) there are significant spatial autocorrelations of industrial pollutant emissions between Chinese cities, but the spatial spillover effect from other cities does not aggravate local urban industrial pollutant emissions, we offer an explanation to this contradiction that the vast rural areas surrounding Chinese cities have served as sponge belts and have absorbed the spatial spillover of cities’ industrial pollutant emissions. According to the results, we argue that this type of decomposition of the influence into three effects is necessary and meaningful, it establishes a solid foundation for understanding the relationship between urbanization and industrial pollutant emissions, and effectively helps to meet relative policy making.

Abstract Introduction: Despite the determination to succeed in eliminating neglected tropical diseases, these have been increasing within certain endemicities, particularly in depriving region. Objective: This study aimed to assess the relative burden of neglected tropical diseases in rural and urban slum settings in Eastern Ethiopia. Methods: A comparative cross-sectional study was conducted from February 25 to April 30, 2024 with a multistage random sampling technique used. A survey tool with the integration of the spectrum was employed. Data were entered using Epi-Data version 3.1 and analyzed using STATA 16. Descriptive statistics and multivariable logistic regression analysis was used to identify the risk factors and the level for statistical significance was declared at p-value < 0.05 with 95 % CI. Result: The response rate was 93 % and the mean age of house heads was 31.6 (Range; 18. 63) with 5.7 average family size. The overall prevalence of NTDs among study participants was 22.6 % (95% CI; 20.2, 25.2); urban slum it was 15 % (95% CI; 12.2, 18.4) while it was 29.8 % (95% CI; 26, 33.9) in rural. Though there is no statistically significant difference, the relative prevalence of NTDs in rural to urban was two. The multivariable analysis provided that the risk factors associated with NTDs were government employment (AOR: 12.5 (1.17, 132.4)), good income (AOR: 0.13 (.03, 0.57)), Child playing with soil (AOR: 5.8 (1.52, 22.0)); child hand washing at critical times ( AOR: 11.2 (1.7, 74.9)), presence of flies in the child faces (AOR: 20.3 (4.7, 88.6)) and type of drinking water sources (AOR: 0.11 (0.02, 0.73)). Conclusion: the burden of NTDs was moderate in the study area dominated by STH, Trachoma, and scabies. Socio economic and WASH factors were found to be associated with NTDs. Collaborated efforts among stakeholders are crucial to prevent and control NTDs.

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater Based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time and resource-efficient manner, as wastewater samples are representative of all cases within the catchment area, whether they are clinically reported or not. However, analysis and interpretation of WBS datasets for decision-making during public health emergencies, such as the COVID-19 pandemic, remains an area of opportunity. In this article, a database obtained from wastewater sampling at wastewater treatment plants (WWTPs) and university campuses in Monterrey and Mexico City between 2021 and 2022 was used to train simple clustering and regression-based risk assessment models to allow for informed prevention and control measures in high-affluence facilities, even if working with low-dimensionality datasets and a limited number of observations. When dividing weekly data points based on whether the seven-day average daily new COVID-19 cases were above a certain threshold, the resulting clustering model could differentiate between weeks with surges in clinical reports and periods between them with an 83.3% accuracy rate. Moreover, the clustering model provided satisfactory forecasts one week (79.2% accuracy) and two weeks (72.9%) into the future. However, the prediction of the weekly average of new daily cases was limited (R2 = 0.452, MAPE = 180.2%), likely because of insufficient dimensionality in the database. Overall, while simple, WBS-supported models can provide relevant insights for decision-makers during epidemiological outbreaks, regression algorithms for prediction using low-dimensionality datasets can still be improved.

It is expected that two-dimensional (2D) metal nitrides (MNs), consisting of the elements of the 13th group of the periodic table and nitrogen, namely aluminium nitride (AlN), gallium nitride (GaN), indium nitride (InN) and thallium nitride (TlN) have enhanced physical and mechanical properties, due to a honeycomb graphene-like atomic arrangement, characteristic to these compounds. The basis for the correct design and improved performance of nanodevices and complex structures based on 2D MNs of the 13th group is the understanding of the mechanical response of their components. In this context, a comparative study to determine the elastic properties of metal nitride nanosheets was carried out making use of the nanoscale continuum modelling (or molecular structural mechanics) method. The differences in the elastic properties (surface Young´s and shear moduli, and Poisson´s ratio) found for 2D 13th group MNs are attributed to the bond length of the respective diatomic hexagonal lattice. The results obtained contribute to a benchmark in the evaluation of mechanical properties of AlN, GaN, InN and TlN monolayers by analytical and numerical approaches.

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of skin cancer, with an increasing global incidence. While most cases are successfully treated with surgical excision, a subset can metastasize, leading to significant morbidity and mortality. Current staging systems based on clinical and histopathological features have shown limitations in accurately predicting metastatic risk. This review examines the role of gene expression profiling (GEP), particularly the 40-gene expression profile (40-GEP) test, in improving risk stratification and management of cSCC. We assess the prognostic value of the 40-GEP test, its integration with current staging systems, and its impact on clinical decision-making. Recent studies suggest that incorporating GEP results with traditional staging methods can enhance the identification of high-risk patients, potentially leading to more personalized treatment strategies. The review also explores the challenges of implementing GEP in routine clinical practice, including cost-effectiveness considerations and the need for standardization. Finally, we discuss the implications for future cSCC management and highlight areas for further research. As molecular profiling techniques continue to evolve, GEP represents a promising approach to optimizing care for cSCC patients, aligning with the growing emphasis on personalized medicine in oncology.

Species of the genus Kalanchoe have a long history of therapeutic use in ethnomedicine linked to their remarkable medical properties. One of them is Kalanchoe blossfeldiana succulents occurring in tropical regions. Despite the great interest in this plant, there are no reports about its therapeutic effects on the skin. In this study, the antioxidant properties and skin permeation of a topical hydrogel containing K. blossfeldiana ethanol extract was assessed. Additionally, the content of active compounds in the K. blossfeldiana extract was evaluated by UHPLC-MS and HPLC-UV. The extract was analysed with three antioxidant assays: ABTS, DPPH and FRAP. Furthermore, antielastase and antihialuronidase properties of the tested extract were assessed. The ex vivo penetration studies were performed using the Franz diffusion cells. The obtained results show that antioxidant properties of K. blossfeldiana extract were similar to ascorbic acid, while antielastase and antihialuronidase tests indicated strong antiaging and anti-inflammatory activity (IC50 was 26.8 ± 0.13 and 77.31 ± 2.44 µg/mL, respectively). Moreover, active ingredients contained in K. blossfeldiana extract penetrated through human skin and accumulate in it. In conclusion, the hydrogel containing K. blossfeldiana extract can be considered as an interesting and new alternative to dermatologic and cosmetic preparations.

Background/Objectives: Pityriasis rosea (PR) is a self-limiting exanthematous disease associated with the endogenous reactivation of human herpesvirus (HHV)-6 and HHV-7. Classically, the lesions gradually resolve leaving no sequelae. Therefore, the best treatment is reassuring the patient and suggesting a resting period. However, atypical PR cases characterized by extensive, persistent lesions and systemic symptoms may impact the patient’s quality of life, and, therefore, a treatment can be prescribed. There is limited evidence on the comparative effectiveness of pharmacological treatments for PR, therefore we performed a network meta-analysis to compare these interventions. Methods: Overall, 12 randomized control trials (RCTs) were identified. The outcomes were itch resolution and rash improvement. Results were expressed as risk ratio (RR) and 95% confidence interval (CI). We also calculated the relative ranking of the interventions for achieving the aforementioned outcomes as their surface under the cumulative ranking (SUCRA). Results: On network meta-analysis, only oral steroids and the combination of oral steroids+antihistamine resulted significantly superior to the placebo in terms of itch resolution (RR 0.44, CI 0.27-0.72 and RR 0.47, CI 0.22-0.99). Oral steroids resulted as the best treatment (SUCRA 0.90) for itch resolution. In terms of rash improvement, only acyclovir and erythromycin resulted significantly superior to placebo (RR 2.55, CI 1.81-3.58 and RR 1.69, CI 1.23-2.33), and acyclovir outperformed all the other tested interventions. Consequently, acyclovir ranked as the best intervention (SUCRA score 0.92). Conclusions: Acyclovir represents the best option in PR patients with extensive, persistent lesions or systemic symptoms. Steroids and antihistamines seemed the best treatment for itch resolution.

This study provides a detailed numerical assessment of the productivity of single-slope solar stills across key cities in the Caspian region, including Aktau, Atyrau, Astrakhan, Makhachkala, Baku, Tehran, and Turkmenbashi. Employing a mathematical model based on heat balance equations and the 4th-order Runge-Kutta method, we simulated the distillation process under various climatic conditions. The results reveal that productivity is significantly influenced by geographic location and local meteorological conditions. Tehran demonstrated the highest productivity across all seasons, with values of 1.75 × 10³ kg/(m²·year) and an efficiency of 0.53, due to its optimal solar irradiation and ambient temperature. In contrast, Atyrau and Makhachkala exhibited lower productivity, particularly in colder months, highlighting the effect of ambient temperature on solar still efficiency. The analysis identified optimal water depth at 2 cm and insulation thickness between 4 and 9 cm for enhancing productivity in continental climates like Aktau. Additionally, the lowest cost of distilled water was $0.024 per kilogram in Baku. These findings align with existing literature, validating the numerical model's accuracy. Future research will explore integrating solar stills with other renewable and fossil fuel-based technologies.

Energy generation now heavily relies on the field of photocatalysis. Many conventional research topics have been superseded by the conversion of solar energy into chemical or thermal energy for a variety of energy-related applications. The urgent necessity of moving away from non-renewable energy sources is a result of the problem of global warming. In an effort to create the best photocatalysts for effective solar conversion, scientists are investigating a variety of material systems and material combinations. By examining the influence of morphology changes on the photoelectrochemical activity of zinc oxide nanostructures, here electrodeposition was used to create the nanostructures. By using the proper capping agents, it is possible to control the growth rates of different ZnO facets and get well-defined nanostructures and orientation. In order to generate distinct ZnO morphologies, we report here the electrodeposition of ZnO nanostructured thin films in the presence of different capping agents. A zinc nitrate (Zn (NO₃)₂) bath was used to electrodeposit ZnO nanostructures on indium tin oxide glass (ITO) substrate at 70 °C with an applied potential of -1.0 V. Capping agents such as ethylenediamine (EDA) or ammonium fluoride (NH₄F) were added to this zinc nitrate bath. The photoelectrochemical capabilities of the morphology-controlled zinc oxide nanostructures were extensively evaluated and characterised. Thus various ZnO morphologies had an impact on the PEC properties.

Crops obtained by genome editing (GE) technologies represent a notable and disruptive shift from genetically modified or transgenic plants, outpacing public perception and regulatory frame-works. Multiple aspects of GE are contributing to the advancement of modern agriculture, in-fluencing the market structure by introducing specific changes within the existing genetic blue-print of an organism. Generally, the GE toolbox includes distinct technologies able to incorporate site-specific and pre-determined genomic modifications, exploiting well-established genetic modification strategies. For these reasons, GE-derived approaches are considered new plant breeding methods, known as new breeding techniques (NBTs). Particularly, CRISPR/Cas-based technologies represent a considerable improvement over prior techniques, being more precise, accurate and straightforward for targeted gene editing, in a reliable and reproducible way, with numerous applications. CRISPR/Cas system exploitation for non-editing purposes has also been widely documented, ranging from cell imaging to expression regulation and DNA assembly. Recently, CRISPR/Cas systems have been employed for target detection and could be used to ef-ficiently identify multiple organic chemicals. High-sensitivity and high-specificity detection are two main points of the CRISPR/Cas technology, without needing complex expertise or technical pipelines. This manuscript aims to provide an overview of the main advances of CRISPR/Cas-based systems into new frontiers of non-editing. The associated implications (e.g., molecular traceability) and their relative impacts are also presented and discussed.

Background: Despite the tremendous effort in hamstring injury prevention, injury rates in soccer remain elevated. Hypothesis: Hamstring and hip/pelvic isometric strength imbalances may increase the likelihood of hamstring strain injury (HSI) occurrence amongst soccer players.Study design: Case-control study.Methods: In 120 male soccer players (mean age: 20.0 +/- 6.96 years) pre-season maximum isometric strength of the hip adductors, abductors, flexors, and knee flexors were measured, and strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus. A multivariate and Machine learning-based Logistic Regression model was employed to estimate the likelihood of players sustaining a hamstring injury.Results: 21 players sustained 32 hamstring injuries. Players with higher abduction strength in the dominant leg had an 18.5% lower risk of sustaining a hamstring injury (OR = 0.818, CI 95% = [(0.695-0.964]). No other significant contributor variables were found to be significant predictors of hamstring injury in the player group (p> 0.05).Conclusion: Isometric strength of the abductor muscles in the dominant limb had a significant association with hamstring injury.Clinical relevance: Our findings indicate the utilization of hip strength measurements as an integral component of the pre-season screening assessment, thereby affirming prior research on the correlation between lumbo-pelvic stability and incidence of hamstring injuries. Consequently, clinicians should contemplate incorporating hip strengthening exercises into regular training sessions, rehabilitation programs, and injury prevention protocols especially indicated when lower hip strength levels are observed.

BReast CAncer gene 1 (BRCA1) and BReast CAncer gene 2 (BRCA2) encode for tumor suppressor proteins which are critical regulators of the homologous recombination (HR) pathway, the most precise and important DNA damage response mechanism. Dysfunctional HR proteins cannot repair double-stranded DNA breaks in mammalian cells, a situation called HR deficiency. Since their identification, pathogenic variants and other alterations of BRCA1 and BRCA2 genes have been associated with an increased risk of developing mainly breast and ovarian cancer. Interestingly, HR deficiency is also detected in tumors not carrying BRCA1/2 mutations, a condition termed “BRCAness”. One of the main mechanisms causing the BRCAness phenotype is the methylation of the BRCA1/2 promoters and this epigenetic modification is associated with carcinogenesis and poor prognosis mainly among patients with breast and ovarian cancer. BRCA1 promoter methylation has been suggested as an emerging biomarker of great predictive significance, especially concerning Poly (ADP-ribose) Polymerase inhibitors (PARP inhibitor-PARPi) responsiveness, along with or beyond BRCA1/2 mutations. However, as its clinical exploitation is still insufficient, the impact of BRCA1/2 promoter methylation status needs to be further evaluated. The current review aims to gather the latest findings about the mechanisms that underline BRCA1/2 function as well as the molecular characteristics of tumors associated with BRCA1/2 defects, by focusing on DNA methylation. Furthermore, we critically analyze their translational meaning and the validity of BRCA methylation biomarkers in predicting treatment response and we suggest a diagnostic pipeline that could be implemented in liquid biopsy to aid precision pharmacotherapy in BRCA-associated tumors.

Plant activators have emerged as promising alternatives to conventional pesticides for crop disease manage-ment due to their unique mode of action. By priming the plant's innate immune system, these compounds can induce systemic acquired resistance against a broad spectrum of pathogens without directly inhibiting their proliferation. Key advantages of plant activators include prolonged defense activity, lower effective dosages, and negligible risk of developing pathogen resistance. Among the various defensive pathways tar-geted, the salicylic acid (SA) signaling cascade has been extensively explored, leading to the successful devel-opment of commercial activators like benzothiadiazole for widespread application in crop protection. While the action sites of many SA-targeting activators have been preliminarily mapped to different steps along the pathway, a comprehensive understanding of their precise mechanisms remains elusive. This review provides a historical perspective on plant activator development and outlines diverse screening strategies employed across multiple levels, from whole-plant bioassays to molecular and transgenic approaches. We expound on the intricate components, biological relevance, and regulatory circuits governing the SA pathway, while criti-cally examining the structural features, bioactivities, and proposed modes of action of classical activators such as benzothiadiazole derivatives, salicylic acid analogs, and other small molecules. Insights from field trials as-sessing their practical applicability are also discussed. Furthermore, we highlight the current status, challenges, and future prospects in the realm of SA-targeting activator development globally, with a focus on recent en-deavors in China. Collectively, this comprehensive review aims to synthesize existing knowledge and provide a roadmap for future research toward developing more potent and mechanistically understood plant activa-tors that fortify crop immunity against disease.

Serum biochemical indicators serve as vital proxies that reflect the physiological state and functions of different organs. The genetic parameters and molecular mechanisms underlying serum biochemical indicators of sheep (Ovis aries) have not been well understood. Therefore, the aim of the present study was to identify genetic architecture and genomic loci underlying ten serum biochemical indicators in sheep, including alanine transaminase, aspartate transferase, lactate dehydrogenase, cholesterol, glucose, phosphorus, calcium, creatinine, urea concentrations and total protein levels. We implemented genetic parameter estimations and GWAS for each trait in 422 Akkaraman lambs. Overall, low to moderate heritability estimates were found, in the range 0.14–0.55. Additionally, low to high genetic correlations were observed among traits. In total, 23 SNP loci were associated with serum biochemical indicators leading to 19 genes . These are SPTA1, MGST2, CACUL1, IGFBP7, PARD3, PHB1, SLC15A5, TRIM35, RGS6, NUP93, CNTNAP2, SLC7A11, B3GALT5, DPP10, HST2ST1, NRP1, LRP1B, MAP3K9, ENSOARG00020040484.1 as well as LOC101103187, LOC101117162, LOC105611309 and LOC101118029. To our knowledge, these data provide the first association between SPTA1 and serum cholesterol and between ENSOARG00020040484.1 and serum glucose. The current findings provide a comprehensive inventory of the relationships between serum biochemical parameters, genetic variants, and disease-relevant characteristics. This information may facilitate the identification of therapeutic targets and fluid biomarkers and establish a strong framework for comprehending the pathobiology of complex diseases as well as providing targets for sheep genetic improvement programmes.

In the context of rapid urbanization, the spatiotemporal patterns of socio-economic exposed to high seismic hazard in large cities lacks quantitative assessment, thus, it is difficult to understand the evolution of earthquake catastrophe risk there. In this paper, exposure change rate, and absolute and relatively exposure indices were proposed to quantitatively study the changes of spatiotemporal exposure to high seismic hazard in urban areas of large cities (i.e., permanent residents in urban areas more than 1 million) in Chinese mainland, using a set of multi-temporal population, GDP, and built-up datasets and a seismic hazard zoning map. The results show that, 64 out of 78 large cities are entirely or partially located in high seismically hazardous zones. Although the urban areas of large cities in high seismically hazardous zones (HSHUAs) cover only 1.73% (167177 km²) of mainland China, their share of population, GDP, and built-up land amounted to 18.14%, 30.24% and 24.55%, respectively, in 2015. Unprecedented urbanization has led to a dramatic exposure growth in HSHUAs between 1990 and 2015. The population, GDP, and built-up land in HSHUAs increased by 110 million people (with an average annual growth rate of 2.37%), 273.71 trillion USD(average annual growth rate of 11.15%), and 10593 km2 (average annual growth rate of 2.02%), respectively. HSHUAs experienced much faster population and GDP growth than the whole country, while relatively slower growth in built-up land. Exposure growth in HSHUAs also was varied for different types of large cities. Megacities had a higher proportion of increased GDP and population in HSHUAs, induced by industry and population agglomeration. Whereas, Type II large cities had a higher proportion of increased built-up land in HSHUAs, driven mainly by urban sprawl. Our analysis indicates that, for large cities under rapid urbanization, it is an urgent need to strengthen resilient urban planning, renewal and construction.

Broad bean paste (BBP) is a traditional fermented soy food, and its high salt content not only prolongs the fermentation time but also threatens human health. In this study, three BBP-meju with different salt concentrations were prepared, and the effects of varying salinity on the fermentation process were comprehensively compared. The results showed that salt-reduced fermentation contributed to the accumulation of amino acid nitrogen, reducing sugars, free amino acids, and organic acids. Alcohols, esters, aldehydes, and acids were the main volatile flavor compounds in BBP-meju, and the highest total volatile flavor compounds were found in medium-salt meju. Bacillus, Staphylococcus, Aspergillus, and Mortierella were the dominant microbial communities during fermentation, and there were also three opportunistic pathogens, Enterobacter, Pantoea, and Brevundimonas, respectively. According to Spearman correlation analysis, Wickerhamomyces, Bacillus, Staphylococcus, and Mortierella all showed highly significant positive correlations with ≥3 key flavor compounds, which may be the core functional flora. Furthermore, the dominant microbial genera worked synergistically to promote the formation of high-quality flavor compounds and inhibit the production of off-flavors during salt-reduced fermentation. This study provides a theoretical reference for the quality and safety control of low-salt fermented soy foods.

The aim of this study is to investigate and determine the key factors guiding customer attitudes towards social media influencers, and on that base to explore their effects on purchase intentions towards advertised products or services. A total of 376 fulfilled questionnaires from an online survey were analysed. The main characteristics of digital influencers’ behaviour, affecting consumer perceptions have been systematized and categorized through a combination of both traditional and advanced data analysis methods. Structural Equation Modelling (SEM), machine learning and multi-criteria decision-making (MCDM) methods were selected to uncover the hidden dependencies between variables from the perspective of social media users. The developed models elucidate the underlying relationships that shape the acceptance mechanism of influencers’ messages. The results obtained provide specific recommendations for stakeholders across the social media marketing value chain. Marketers can make informed decisions and optimize influencer marketing strategies to enhance user experience and increase conversion rates. Working collaboratively, marketers and influencers can create impactful and successful marketing campaigns that resonate with the target audience and drive meaningful results. Customers benefit from more tailored and engaging influencer content that aligns with their interests and preferences, fostering a stronger connection with brands and potentially affecting their purchase decisions. As the perception of customer satisfaction is individual and evolving process, stakeholders should organize regular evaluations of influencer marketing data and explore the possibilities to ensure continuous improvement of this e-marketing channel.

In response to the issues of sensor noise and accumulated motion errors that lead to low positioning accuracy and insufficient robustness during large maneuvers or continuous flight of small unmanned aerial vehicles (UAVs) in complex environments, this paper proposes a multi-source and multimodal data fusion method. Initially, it employs a multimodal data fusion of various sensors including GPS (Global Positioning System), IMU (Inertial Measurement Unit), and visual sensors to complement the strengths and weaknesses of each hardware component, thereby eliminating motion errors to enhance accuracy. To mitigate the impact of sudden changes in sensor data, the method introduces a digital twin UAV data source. By utilizing the Extended Kalman Filter algorithm, it fuses data from both the real UAV and its digital twin, and the filtered positional information is fed back into the control system of the real UAV. This enables real-time correction of UAV positional deviations caused by sensor noise and environmental disturbances. The multi-source multimodal fusion Kalman filter method proposed in this paper significantly improves the positioning accuracy of UAVs in complex scenarios and the overall stability of the system. This method holds significant value in maintaining high-precision positioning in variable environments and has important practical implications for enhancing UAV navigation and application efficiency.

Background: Permanent tracheostomy because of total laryngectomy surgery entails great conse-quences for the patient regarding respiratory physiopathology such as the filtering, humidifying, and heating function of the air by the nose is lost. The use of special stomal filters can determine adequate protection of the trachea-broncho-pulmonary system with a reduction in respiratory pathologies. In fact, in most cases laryngectomee patients are first cigarette smokers who for this reason already have also respiratory diseases such as chronic obstructive pulmonary disease (COPD). Despite the availability of tracheal filters, multiple times, as reported in the literature, the patient tends to limit their use due to reported breathing difficulties, especially in conditions of intense breathing. Methods: The objective of this clinical study was to evaluate the most suitable stomal filter for the laryngectomee patient during physical activity. The filters studied were an INHEALTH device (Blom-Singer SpeakFree HME); two ATOS devices (Provox® Life™ Energy HME and Provox® Life™ Home HME); and an FAHL device (Laryvox HME Sport). Results: For this purpose, the performances of 31 laryngectomee patients, subjected to medi-um-high physical effort, were analyzed through a standardized pneumological test, the Six Minute Walking Test (6MWT) which involves a sustained walk lasting six minutes, with evaluation , every 60 seconds, heart rate, oxygen saturation and meters travelled; furthermore, it examines two sub-jective indices, namely, the basal and final dyspnea index and the initial and final muscular fatigue index.

The photosystem I (PSI) of the green alga Chlamydomonas reinhardtii associates with 10 light-harvesting proteins (LHCI) to form the PSI-LHCI complex. Binding of LHCII to PSI may also occur and is controlled by a process called state transitions. Hereby, two LHCII trimers bind to the PSAL, PSAH and PSAO side of PSI to produce the PSI-LHCI-LHCII complex. In this work, we took advantage of chemical crosslinking of proteins in conjunction with mass spectrometry to identify protein-protein interactions between the light-harvesting proteins of PSI and PSII. We detected binding of LHCBM proteins to the LHCA1-PSAG side of PSI and identified protein-protein interactions of LHCSR3 with LHCA5 and LHCA3. Our data indicate that the binding of LHCII to PSI is more versatile as anticipated and reveal that LHCSR3 likely regulates excitation energy transfer to the PSI core via LHCA5/LHCA3.

The Vu Gia - Thu Bon River Basin (VG-TB) is confronting numerous challenges related to water security (WS), particularly in the face of the impacts of climate change. These challenges manifest in salinity intrusion, altered rainfall patterns, and reduced water supply in downstream areas. To assess the current state of water security in the basin, the study employed statistical analysis methods, Process Analysis Method (PAM), SMART, and Analytic Hierarchy Process (AHP) to develop a comprehensive Assessment Framework for Water Security (AFWS) in the VG-TB. The AFWS encompasses five key dimensions, 17 indicators, and 28 variables, aligning with the UN-Water definition of water security and addressing the Sustainable Development Goal 6 (SDG6) criteria for global water sustainability. It also adheres to the Asian Development Bank's (ADB) approach to water security assessment as outlined in the Asian Water Development Outlook (AWDO) reports. This allows for the computation of a comprehensive Water Security Index (WSI) for specific regions, serving as a foundation for decision-making and policy formulation aimed at enhancing water security in the context of climate change and facilitating sustainable basin development in the future.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

The ceramic sherds from approximately 20 samples of lead-glazed tableware, recovered from diverse archaeological sites, including three repurposed storage pits transformed into dumpsters within the medieval city of Santarém (13th-14th century), underwent a meticulous examination. This investigation utilized techniques such as micro-Raman, ground state diffuse reflectance absorption, and X-ray fluorescence spectroscopies, in addition to X-ray diffraction and stereomicroscopy. A parallel study was conducted on contemporaneous European ceramics (glazed sherds) sourced from archaeological sites dating back to the 13th-15th centuries in Saintonge (France), Ardenne, Zomergem, and Bruges (Belgium), as well as Surrey-Hampshire, Kingston, and Cheam (England). The colour of the ceramic bodies is predominantly white or whitish, with a few exhibiting a vivid red hue. Ceramic sherds with a light paste composition were likely crafted using kaolin clays as raw materials. Analyses of fabric, mineralogical, and elemental composition of the sherds suggest that the majority of Santarém's glazed ceramics were locally or regionally produced, potentially derived from a Pliocene kaolin-rich sand formation. However, this conclusion is not supported by the absence of discovered lead glaze kilns or workshops in Santarém for the late Middle Ages. A distinctive feature from the European workshop ceramics lies in the quartz temper content and fabric.

The traditional practice of harvesting and processing raw date palm sap is not only culturally significant but also an essential nutritional source in South Asia. Yet, the potential for bacterial or viral contamination from animals and environmental sources during its collection remains a real and insufficiently studied risk. Implementing improved food safety measures and collection techniques could mitigate the risk of these infections. Additionally, the adoption of advanced food analytical methods has the potential to identify pathogens and uncover the natural bacterial diversity of these products. The advancement of NGS technologies, particularly nanopore sequencing, offers rapid and highly mobile capabilities. In this study, we employed nanopore sequencing for bacterial metabarcoding of a set of raw date palm sap samples collected without protective coverage against animals in Bangladesh in 2021. We identified several bacterial species with importance in the natural fermentation of the product and demonstrated the feasibility of this NGS method in the surveillance of raw palm sap products. We revealed two fermentation directions dominated by either Leuconostoc species or Lactococcus species in these products at the first 6 hours from harvest along with opportunistic human pathogens in the background, represented with low abundance. Plant pathogens, bacteria with the potential for opportunistic human infections and the sequences of the Exiguobacterium genus were also described and their potential role is discussed.

The state detection of power cable is very important to ensure the reliability of power supply. Traditional sensors are mostly based on electric field detection, the operation is complex, and its efficiency needs to be improved. This paper optimizes the design and development of the magnetic field detection sensor for AC power cables. Firstly, through the establishment of the magnetic field sensor model, it is determined that permalloy is the material of the magnetic core, the optimal aspect ratio of the magnetic core is 20, and the ratio of coil length to core length is 0.3. Secondly, the coil simulation model is established, and it is determined that the optimal number of turns of the coil is 11000 turns, the diameter of the enamelled copper wire is 0.08mm, and the equivalent magnetic field noise of the sensor is 0.06pT. Finally, the amplifying circuit based on negative magnetic flux feedback is designed and the sensor is assembled, and the experimental circuit is built for sensitivity test. the results show that the sensitivity of the magnetic field sensor is 327.6mV/μT. The sensor designed in this paper has the advantages of small size, high sensitivity, easy to carry and high reliability.

There is a need to find methods to intensify the anaerobic digestion process. One possibility is the use of pre-treatment techniques. Many laboratory tests confirm their effectiveness, but in most cases, there is no verification work carried out on industrial plants. The aim of the research carried out under laboratory conditions and on a large scale was to determine the technological and energy efficiency of the use of hydrodynamic cavitation in the pre-treatment of a waste mixture from dairy farms. It has been shown that hydrodynamic cavitation significantly increases the concentration of organic compounds in the dissolved phase. In the most effective variants, the increase in the content of these indicators was over 90% for both COD and TOC. The degree of solubilisation achieved was 49±2.6% for COD and almost 52±4.4% for TOC. Under laboratory conditions, the highest effects of anaerobic digestion were achieved after 10 minutes of pre-treatment. The amount of biogas was on average 367±18 mL/gCOD and the amount of methane 233±13 mL/gCOD. Further large-scale optimisation trials showed that after 8 minutes of hydrodynamic cavitation, the biogas yield was 327±8 L/kgCOD with a CH4 content of 62.9±1.9%. With this variant, the net energy yield was 66.4±2.6 kWh/day, a value that was 13.9% higher than the original variant with 10 minutes of disintegration and 3.1% higher than the variant without pre-treatment.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

Neuronal cells are believed to rely on autophagy to maintain cellular homeostasis. Nevertheless, autophagy may be a therapeutic target for neurodegenerative diseases because of the role it plays in neuronal cell death. Despite Beclin 1 association with autophagy and apoptosis, the molecular mechanisms that underlie Tau-induced vesicular pathology and Tau protein aggregates in humans remain poorly understood. Here, we set out to examine the role of three genes-ATG14L, Beclin 1 and VPS34- in autophagy nucleation failure-associated Tau disorders in fruit fly models. We found that either reduced ATG14L levels improve neuronal outcomes, or transgenic expression of ATG6/Beclin 1 greatly reduced age-dependent neurodegeneration and Tau pathology; whereas, the loss of Beclin 1 exacerbated these effects. Prior to p-Tau accumulation, the neuronal Beclin 1 network is critical for reducing p-Tau accumulation, indicating that the loss of Beclin 1 causes Tau pathology and neurodegeneration. As neurodegeneration progressed, glial cells showed an upregulation of vesicular Beclin 1 immunoreactivities. The reduced VPS34 also resulted in p-Tau accumulation, suggesting that neurons require both Beclin 1 and VPS34 to reduce p-Tau accumulation. Our results provide mechanistic insight into the molecular pathways that cause age-dependent Tau pathology and neurodegeneration due to an excess of autophagy nucleation processes and autophagy activity, and we derive novel inferences on the therapeutic possibilities of rebalanced Beclin 1 network by reducing autophagic specific nucleation component of ATG14L.

Background and Objectives: The aim of this study was to determine the job-related and individual features that influence BS and depression levels among dentists working in faculties, oral and dental health centres (ODHC) and private clinics. Materials and Methods: This prospective, cross sectional study was carried out on dentists working in different regions of Turkey. Data were collected using an on-line questionnaire created using Google Forms. The questionnaire consisted of demographic data, Maslach BS Inventory (MBI) and Beck Depression Inventory (BDI) sections. Demographics were age, height, weight, marital status, blood type, gender, monthly income, income satisfaction and having enough free time. The dentists were divided into 3 groups as faculty, private clinic and ODHC according to the institutions in which they worked. Results: Of the total 290 dentists enrolled in the study, there were 172 males and 118 females with a mean age of 36.98±5.6 years. 128 of the dentists worked in faculties, 72 in private clinics and 90 in ODHCs. It was observed that women's EE scores were higher than men's (P&lt;0.05). No statistically significant difference was found between the groups when comparing BS and depression scores according to marital status and blood group (P&gt;0.05). There was no significant relationship between emotional exhaustion (EE), depersonalisation (DP), personal accomplishment (PA) and depression scores according to age, BMI and work experience, age, work experience and BMI (P&lt;0.05). It was found that the EE scores of the dentists working in the faculty and private clinic were lower than those of the dentists working in the ODHC (P&lt;0.05). Monthly income was associated with depression (r = -0.35). Conclusions: This study showed that dentists working in ODHCs had more EE. These findings suggest that there is a need for improvement in the working conditions of dentists, particularly in ODHCs.

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

In a recent paper, we calculate spectral energy distributions (SEDs) for 1425 Fermi blazars, classifications of low synchrotron peak sources (LSPs) if log $\nu_{\rm p} (\rm Hz) \leq $ 14.0, intermediate synchrotron peak sources (ISPs) if $14.0 < \,\log\, \nu_{\rm p} (\rm Hz) \leq 15.3 $, and high synchrotron peak sources (HSPs) if $ \log\, \nu_{\rm p} (\rm Hz) > 15.3$ are made based on 999 logarithms of synchrotron peak frequencies with known redshift, and we obtain an empirical relation to estimate the synchrotron peak frequency, $\nu_{\rm p}^{\rm Eq.}$ from effective spectral indexes $\alpha_{ox}\, {\rm and}\, \alpha_{ro}$ as $\log \nu_{\rm p}^{\rm Eq.} = 16+4.238X $ if $X < 0$, and $\log \nu_{\rm p}^{\rm Eq.} = 16+4.005Y $ if $X > 0$, where $X = 1.0 - 1.262 \alpha_{ro} - 0.623 \alpha_{ox}$, and $Y = 1.0 + 0.034 \alpha_{ro} - 0.978 \alpha_{ox}$ \cite{Fan16}. In the present work, we investigate the correlation between the peak frequency and the radio to X-ray spectral index, that between peak luminosity (integrated luminosity) and $\gamma$-ray/optical luminosity, and that between peak luminosity and integrated luminosity. Some discussions are presented.

Biological nanoparticles (NPs), such as extracellular vesicles (EVs), exosome-mimetic nanovesicles (EMNVs) and nanoghosts (NGs), are perspective non-viral delivery vehicles for all types of therapeutic cargo. Biological NPs are renowned for their exceptional biocompatibility and safety, alongside their ease of functionalization, but a significant challenge arises when attempting to load therapeutic payloads, such as nucleic acids (NAs). One effective strategy involves fusing biological NPs with liposomes loaded with NAs, resulting in hybrid carriers that offer the benefits of both biological NPs and the capacity for high cargo loads. Despite their unique parameters, one of the major issues of virtually any nanoformulation is the ability to escape degradation in the compartment of endosomes and lysosomes which determines the overall efficiency of nanotherapeutics. In this study, we fabricated all major types of biological and hybrid NPs and studied their response to acidic environment observed in endolysosomal compartment. In this study, we show that EMNVs display increased protonation and swelling relative to EVs and NGs in an acidic environment. Furthermore, the hybrid NPs exhibit an even greater response compared to EMNVs. Short-term incubation of EMNVs in acidic pH corresponding to late endosomes and lysosomes again induces protonation and swelling, whereas hybrid NPs are ruptured, resulting in the decline of their quantities. Our findings demonstrate that in an acidic environment, there is enhanced rupture and release of vesicular cargo observed in hybrid EMNVs that are fused with liposomes compared to EMNVs alone. This was confirmed through PAGE electrophoresis analysis of mCherry protein loaded into nanoparticles. In vitro analysis of NPs colocalization with lysosomes in HepG2 cells demonstrated that EMNVs mostly avoid endolysosomal compartment whereas hybrid NPs escape it over time. To conclude, (1) hybrid biological NPs fused with liposomes appear more efficient in the endolysosomal escape via the mechanism of proton sponge associated with scavenging of protons by NPs, influx of counterions and water, and rupture of endo/lysosomes, but (2) EMNVs are much more efficient than hybrid NPs in actually avoiding endolysosomal compartment in human cells. These results reveal biochemical differences across four major types of biological and hybrid NPs, and indicate that EMNVs are more efficient in escaping or avoiding endolysosomal compartment.

In patients with primary central nervous system lymphoma (PCNSL), the choice of surgical strategy for histopathologic assessment is still controversial, particularly in terms of preoperative corticosteroid (CS) therapy. To provide further evidence for clinical decision-making, we retrospectively analyzed data from 148 consecutive patients who underwent surgery at our institution. Although patients treated with corticosteroids preoperatively were significantly more likely to require a second or third biopsy (p=0.049), it was only necessary in less than 10% of the cases with preoperative corticosteroid treatment. The choice of surgical procedure did not affect diagnostic accuracy (p&gt;0.05). Preoperative CSF sampling did not provide additional information but was associated with delayed surgery (p=0.02). Surprisingly, diagnostic accuracy was significantly lower when patients were treated with anticoagulation or dual antiplatelet therapy (p=0.015). In conclusion, preoperative CS therapy can challenge the histological diagnosis of PCNSL. At the same time, our data suggest that preoperative CS treatment only presents a relative contraindication for an early surgical intervention. The standard surgical approach is stereotactic biopsy, but other approaches can be individually considered. If a definitive diagnosis cannot be made after the first surgical intervention, the timing of a repeat biopsy after discontinuation of CS remains a case-by-case decision.

This study introduces a novel and sustainable method of producing graphene from coconut shells and investigates its application in Graphene, Ni/Graphene, and Zn/Graphene electrodes for advanced energy storage devices. The graphene was synthesized scalably using a pyrolysis and impregnation technique, with its successful synthesis verified by X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), and electrical conductivity measurements characterizations. The study highlights the enhanced performance of Zn/Graphene electrodes, which outperform both pure graphene and Ni/Graphene variants. This superior performance is attributed to the smaller particle size of Zn (mean = 2.356 µm) compared to Ni (mean = 3.09 µm), and Zn’s more favorable electron configuration for electron transfer. These findings demonstrate the potential of bio-derived graphene composites as efficient, high-performance electrodes, paving the way for more sustainable and cost-effective energy storage solutions.

The production of recombinant enzymes, mainly used for obtaining pure and functional target molecules, holds significant importance in modern biotechnology. This study aimed to produce recombinant α-amylases (Amy3500 and Amy1974), derived from B. amyloliquefaciens MDC1974 and B. subtilis MDC3500 respectively, using the pBE-S shuttle vector, and to characterize them. Both α-amylase genes were molecularly cloned into the E. coli/B. subtilis pBE-S shuttle vector, both with (Amy1974sig and Amy3500sig) and without their own signal peptides (Amy1974 and Amy3500), along with a signal peptide originating from the plasmid, and tested in flask fermentations. For recombinant Amy3500, the amylase variants resulted in similar levels of volumetric activity (700-750 U/mL). In contrast, the expression of Amy1974 nearly doubled compared to Amy1974sig with double signal peptides, reaching 2000 U/mL. The SDS-PAGE estimated the molecular weight of Amy1974 α-amylase to be 54.6 kDa, which was in accordance with the theoretical molecular mass calculations. However, the estimated molecular weight of Amy3500 amylase was significantly reduced when exiting the producer cells. Ca2+ had no significant activating effect on the activities of Amy1974 amylase and Amy3500 amylase, likely due to its tight binding to the protein scaffold. Both enzymes exhibited broad activity peaks between 45-70°C, with a maximum at 65°C. The Amy1974 and Amy3500 α-amylases demonstrated broad pH optima and pH-dependent thermostability, with optimum pH values at 6.5 and 5.8, and thermal stability peaks at pH 7.6 and 5.9, respectively. Both α-amylases displayed high relative activity against various starches, including corn amylopectin and potato amylose, while showing comparatively lower activity towards cyclodextrins. The Amy1974 amylase converts starch to dextrins of varying lengths, whereas Amy3500 almost entirely converts starch into glucose.

Background: Colorectal cancer (CRC) patients experienced multiple chemotoxicity affecting treatment compliance, survival, and quality of life (QOL). Prior research shows clinician-reported chemotoxicity (i.e., grading scales or diagnostic codes) predicts rehospitalization and cancer survival. However, a comprehensive synthesis of clinician-reported chemotoxicity is still lacking. Objectives: We conducted a systematic review and meta-analysis to determine the chemotoxicity's prevalence and risk factors in CRC. Methods: A systematic search from 2009 to 2024 yielded 30 studies for review, with 25 included in the meta-analysis. Results: Pooled prevalences of overall, non-hematological, and hematological moderate-to-severe toxicities were 45.7%, 39.2%, and 25.3%, respectively. The most common clinician-reported chemotoxicities were gastrointestinal (GI) toxicity (22.9%) and neuropathy or neutropenia (17.9%). Significant risk factors at baseline were malnutritional status, frailty, impaired immune or hepato-renal functions, short telomere lengths, low gut lactobacillus levels, age, female sex, aggressive chemotherapy, and low QOL. Age was associated with neutropenia (β: -1.44) and GI toxicity (β:1.85) (Ps 65 y.o.) had higher prevalences of overall (OR: 1.14) and GI (OR: 1.65) toxicities, but a lower prevalence of neutropenia (OR: 0.65) than younger adults (Ps

CoCrFeNiMn high-entropy alloy coatings were prepared on compacted graphite iron（CGI） through plasma cladding to strength the CGI substrate. The effects of heat treatment temperatures and times on the microstructure and mechanical properties of the CoCrFeNiMn coatings were investigated. After heat treatment, a single FCC phase was remained in the coating as compared to the deposited one, with smaller dendrites, larger dendritic spacing and more Cr-rich compounds precipitated between dendrites. The coatings’ microhardness was increased after heat treatment. After heat treated at 660°C for 90 minutes, the coating had the highest microhardness of 563±6.9 HV0.2, the lowest frictional coefficient of 0.71 and the smallest wear mass loss of 1.12 mg, and it had the best wear resistance.

The CH2Cl2-MeOH extract of the Mediterranean sponge Crambe crambe was investigated via UHPLC-HRMS/MS employing manual dereplication and in silico mass spectrometry tools. A deconvolution approach was implemented toward the extensive metabolic characterization of the sample, resulting in the annotation of 53 compounds. The analysis of data-dependent HRMS/MS scans was conducted to establish fragmentation patterns characteristic of each crambescin A, B and C sub-families. Among the 39 compounds identified from these groups, 22 analogues were reported for the first time including 4 new homologous series that differed by the ratio of methylene units in the upper (n+2) and lower (m+2) alkyl side chains. More specifically, crambesins presenting m= 5 or 6 and n=5 (compounds 7, 11, 22 and 24) as well as m=5 or 6 and n=4 (compounds 5, 6, 8, 9, 12 and 14) were characterized. Additionally, 4 new crambescidin analogues (compounds 13, 15, 35 and 39) were also reported. The identity of the dereplicated features was further validated by studying crambescins spectral similarities through feature-based molecular networking approach. Overall, this study suggests UHPLC-HRMS/MS—through integration of manual and computational dereplication approaches—as a valuable tool for the investigation and high-throughput characterization of C. crambe metabolome.

The goal of the study presented in this work is to evaluate the performance of a proposed adaptive beamforming approach when combined with non-orthogonal multiple access (NOMA) in cell-free massive multiple input multiple output (CF m-MIMO) orientations. In this context, cooperative beamforming is employed taking into consideration the geographically adjacent access points (APs) of a virtual cell, aiming to minimize co-channel interference (CCI) among mobile stations (MSs) participating in NOMA transmission. Performance is evaluated statistically via extensive Monte Carlo (MC) simulations in a two-tier wireless orientation. As results indicate, for high data rate services various key performance indicators (KPIs) can be improved compared to orthogonal multiple access, such as the minimum number of users in the topology as well as the available PRBs for downlink transmission. Although in NOMA transmission more directional beamforming configurations are required to compensate for the increased CCI levels, the increase in the number of hardware elements is reduced compared to the corresponding gain in the considered KPIs.

Water stable proteins may offer a new field of applications in smart materials for buildings and infrastructures where hydraulic reactions are involved. In this study, cement mortars modified through water-soluble silk fibroin (SF) are proposed. Water-soluble SF obtained by redissolving SF films in phosphate buffer solution (PBS) showed the formation of a gel with β-sheet features of silk II. Electrical measurements on SF indicate that calcium ions are primarily involved in the conductivity mechanism. By exploiting the water solubility properties of silk II and Ca2+ ion transport phenomena and its trapping effect over water molecules, SF provides piezoresistive and piezocapacitive properties to cement mortars, thus enabling self-sensing of mechanical strain which is quite attractive in structural health monitoring applications. SF/cement-based composite introduces the capacitive gauge factor that surpasses the traditional resistive gauge factor reported in the literature by threefold. Cyclic voltammetry measurements demonstrated SF cement mortars possess memcapacitive behavior for positive potentials around +5 V, attributed to an interfacial charge build-up modulated by the SF concentration and the working electrode. Electrical square-biphasic excitation combined with cyclic compressive loads revealed memristive behavior during the unloading stages. These findings along with the availability and the sustainability of SF pave the way for the design of novel multifunctional materials, particularly for applications in masonry and concrete structures.

In typical whiskey, the content of higher alcohols is about 1500-2000 mg/L, lead to high intoxicating degree (ID). To produce the low-ID whiskey, the Saccharomyces cerevisiae XF0-h, XF0-H and XF0-LH were successfully constructed by CRISPR-Cas9 gene editing technology to knock out HOM2 (encoding aspartate β-semialdehyde dehydrogenase) in the original strain XF0 and the LEU1 knockout strain XF0-L. The content of higher alcohols in whiskey fermented by the XF0-h, XF0-H, and XF0-LH were 704±8 mg/L, 685±6 mg/L, and 685±19 mg/L, respectively, showing reductions of 23.93%, 25.98%, and 15.81% compared to the XF0, XF0, and XF0-L. The fermentation conditions of the XF0-LH were optimized through single-factor experiments and Box-Behnken design. The optimal conditions were the wort concentration of 9.8 °P, the hydrolyzed broken rice syrup addition of 78 g/L, and the inoculum size of 2.7 × 106 cells/mL. The low-ID whiskey was brewed with higher alcohols content at 556 mg/L by 50L fermenter at the optimal conditions.

Gold nanoparticles (NPs) are among the most commonly employed metal NPs in biological applications, with their distinctive physicochemical features. Their extraordinary optical properties, stemming from the strong localized surface plasmon resonance (LSPR), contribute to the devel-opment of novel approaches in the areas of bioimaging, biosensing, and cancer research, especially for photothermal and photodynamic therapy. The ease of functionalization with various lig-ands provides a novel approach to the precise delivery of these molecules to targeted areas. Gold NPs ability to transfer heat and electricity positions them as valuable materials for advancing thermal management and electronic systems. Moreover, their inherent characteristics, such as in-ertness, give rise to the synthesis of novel antibacterial and antioxidant agents as they provide a biocompatible and low-toxic approach. Chemical and physical synthesis methods are utilized to produce gold NPs. The pursuit of more ecologically sustainable and economically viable large-scale technologies, such as environmentally benign biological processes referred to as green/biological synthesis, has garnered increasing interest among global researchers. Green synthesis methods are favorable among other synthesis techniques as they minimize the necessity for hazardous chemicals in the reduction process due to their simplicity, cost-effectiveness, energy efficiency, and biocompatibility. This article discusses the importance of gold NPs, their optical and conductivity properties, antibacterial, antioxidant, and anticancer properties, synthesis methods, contemporary uses, and biosafety, emphasizing the need to understand toxicology principles and green commercialization strategies.

The role of onion as a second most consumed and cultivated vegetable around the world and its renown qualities that made it to be called as “queen of the kitchen” have positioned it to be very vital to the nutritional and economical contributions around the world. Polyploidy serves the purpose of groundbreaking innovation towards plant breeding by improving plants’ yield and vigor. This study was conducted to determine the effect of different concentrations of colchicine on the seedlings of onion on the morphology, antioxidant activity and dissolved sugars. Three concentrations of colchicine were used; including 0.05, 0.1 and 0.2% (w/v) which were applied to the seeds of Allium cepa for the exposure period of 24 hours. Chromosomal analysis confirmed the induction of polyploidy which led to the successful duplication of the chromosomes number from diploid (2n = 16) to tetraploid (4n = 32). Successful induction of polyploidy was achieved by the application of 0.05% (w/v) concentration of colchicine as it yielded the formation of seedlings which were morphologically and biochemically superior over the remaining concentrations and control at p ≤ 0.05 probability. The 0.05% (w/v) concentration showed the highest survival rate between the treatments by recording 83.33% compared to 33.33% and 0.00% of 0.1 and 0.2% (w/v) concentrations respectively, but topped by the control which recorded 91.57% survival rate. Furthermore, the 0.05% concentration of colchicine showed significant difference in the morphology as it recorded the biggest size of seedlings by height reaching up to 73.6cm tall with the diameter of the bulbs reaching 5.64 cm after 14 weeks. It also showed significant difference in the antioxidant activity by recording the highest DPPH scavenging percentage of up to 72.58%, followed by 0.1% and control. The tetraploids also showed significant difference in the dissolved sugars as they recorded the highest refractive index between the treatments and control. The application of 0.05% (w/v) concentration of colchicine resulted in the formation of the seedlings that have superiority in the morphology, antioxidant activity and amount of dissolved sugars compared to other treatments and control.

Quenchbody (Q-body), a new type of fluorescent immunosensor, is an antibody fragment labeled with a fluorescent dye. When Q-body binds to its antigen, the fluorescence intensity increases. Highly sensitive detection of antigens by changes in fluorescence intensity is performed in a single step by mixing sample and reagent. In this study, to reveal the structural basis for Q-body, we solved the crystal structures of antigen-binding fragment (Fab) of an anti-osteocalcin antibody KTM219, which is applicable to Q-body, and its complex with the antigen osteocalcin C-terminal peptide (BGP-C7). Also, we solved the structure of a KTM219 Fab crystal grown in the presence of a fluorescent dye 5(6)-carboxytetramethylrhodamine (TAMRA), however, a tightly bound TAMRA was not found in the electron density map. We predicted the binding site of TAMRA by docking simulations. These results support the structural basis for the Q-body mechanism as follows. In the absence of the antigen, the fluorophore located near tryptophan residues is quenched in the hydrophobic pocket of the antigen binding site between VH and VL. In association with the competitive binding of the antigen, the fluorophore is released from the antigen binding pocket and emits fluorescence. The crystal structures of KTM219 Fab and the structural basis of Q-body would be useful for further development and improvement of Q-body fluorescent immunosensors.

In a V2V communication environment, the control of electric vehicle platoons faces issues such as random communication delays, packet loss, and external disturbances, which affect sustainable transportation systems. In order to solve these problems and promote the development of sustainable transportation, a longitudinal control algorithm for the platoon based on robust Unscented Kalman Filter (UKF) and Model Predictive Control (MPC) is designed. First, a longitudinal kinematic model of the vehicle platoon is constructed, and discrete state-space equations are established. The robust UKF algorithm is derived by enhancing the UKF algorithm with Huber-M estimation. This enhanced algorithm is then used to estimate the state information of the leading vehicle. Based on the vehicle state information obtained from the robust UKF estimation, feedback correction and compensation are added to the MPC algorithm to design the robust UKF-MPC longitudinal controller. Finally, the effectiveness of the proposed controller is verified through CarSim/Simulink joint simulation. The simulation results show that in the presence of communication delay and data loss, the robust UKF-MPC controller outperforms the MPC and UKF-MPC controllers in terms of MSE and IAE metrics for vehicle spacing error and acceleration tracking error, and exhibits stronger robustness and stability.

Familial Mediterranean fever (FMF) is a genetically determined autoinflammatory disease transmitted by an autosomal recessive mechanism. The cause of the nosology is point mutations of the MEFV (Mediterranean FeVer) gene coding for pyrin protein. Inflammasomes are molecular platforms altered in autoinflammatory diseases. The aim of this study was to evaluate the expression of inflammasome genes (p65, Casp-1, MEFV-d2, MEFV-I, NLRP3) in patients with FMF compared to controls to understand the changes that may play a key role in disease development. We found altered expression levels of the full-length MEFV isoform as well as Casp1 and p65 in FMF patients versus controls. This, once again highlighted the significance of inflammasome genes in terms of FMF.

Background/Objectives: Pulmonary diseases are common in patients with thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA). Although high prevalences of chronic obstructive pulmonary disease and lung cancer (LC) are known, the prevalence of these and other pulmonary diseases regarding their relation to outcome of TAA and/or AAA are not determined. Methods: Pulmonary diseases present at aortic aneurysm (AA) diagnosis and follow-up periods and cause of death of 952 patients with TAA, AAA, or TAA+AAA (including thoracoabdominal AA) treated at our institution in Japan, were retrospectively analyzed. Cox regression analysis was used to investigate potential risk factors of mortality. Results: Mean patient age was 72.4 years, and median follow-up was 4.92 years. At diagnosis, 528 (55.5%) patients had pulmonary diseases, including emphysema without interstitial lung disease (ILD) or LC, LC, idiopathic pulmonary fibrosis (IPF) without LC, non-IPF ILD without LC, and interstitial lung abnormalities (ILAs) without LC in 250, 85, 65, 15, and 58 patients, respectively. During follow-up, LC and acute exacerbation (AE) of IPF developed in 50 and 12 patients, respectively. In 213 patients who died, there were 45 (21.1%) aortic disease-related deaths. Other causes of death included LC (27.7%), cardiovascular event (9.4%), pneumonia (5.6%), and interstitial lung disease (4.7%). In a multivariate Cox regression hazard model, age, larger maximum aneurysm diameter, and coexisting LC, IPF, or concomitant cancer were associated with poor prognosis. Conclusions: In patients with AA, not only age and aneurysm diameter but also coexisting LC and IPF were prognostic factors for mortality.

Diabetes mellitus is a prevalent disease with a rapidly increasing incidence projected worldwide, affecting both industrialized and developing regions. Effective diabetes management requires precise therapeutic strategies, primarily through self-monitoring of blood glucose levels to achieve tight glycemic control, thereby mitigating the risk of severe complications. In recent years, there have been significant advancements in non-invasive techniques for measuring blood glucose using photoacoustic spectroscopy (PAS) as it shows great promise for the detection of glucose using the Infrared region (e.g. MIR & NIR) of light. A critical aspect of this method is the detection of the photoacoustic signal generated from blood glucose, which needs to be amplified through a photoacoustic resonator (PAR). In this work, an overview of various types of PARs used for noninvasive glucose sensing is reviewed, highlighting their operating principle, design requirements, limitations, and potential improvements needed to enhance the analysis of photoacoustic signals. This analysis will be helpful for the basic understanding and achieving the highly sensitive PAR required for noninvasive glucose monitoring.

The aim of this work is to propose an angular positioning solution for the round cutting insert of an indexable insert torus milling cutter, dedicated to the multi-axis milling process under HSM conditions. The solution was based on the development of a wear model using a nonlinear estimation method with an eigenfunction, the development of a tool life model taking into account parameter of the cutter blade working angle and the method of reference marking and insert mounting, as well as the measurement methodology. The own function adopted to approximate the wear of the tool over its useful life is adequate and provides a prediction accuracy of 90%. The developed procedure for angular positioning and measurement enables the entire cutting edge of the cutting blade to be fully used, so that the total lifespan of the tool as an indexable insert tool is significantly extended. In addition, the measured largest defect values between the worn cutting edge and the nominal outline of the insert indicate the location of “notching” type wear.

Cervical mesonephric ductal adenocarcinoma (MA) is a HPV-independent adenocarcinoma that originates from remnants of the wolffian duct in the male reproductive system during fetal development and occurs in middle-aged women. MA is a rare disease that accounts for less than 1% of all cervical adenocarcinomas. We report a case of MA in which abdominal radical hysterectomy(ARH) was performed after neoadjuvant chemotherapy (NAC). The patient was a 66-year-old woman with abnormal genital bleeding. A colposcopy examination revealed macroscopic invasive cancer. A pelvic MRI scan revealed a 53 × 26 mm tumor in the cervix, and the histological diagnosis of the cervix was endometrioid carcinoma, with the diagnosis being cervical adenocarcinoma cT1b3N0M0. One course of NAC with paclitaxel-carboplatin (PC) was administered to shrink the tumor and stop the bleeding, and ARH was performed. Postoperative histopathological diagnosis was MA. The surgical margins of the resected specimen were negative, and NAC had been effective, so the patient underwent five courses of PC therapy after surgery. There has been no recurrence 12 months after surgery. There is no established standard treatment, but there are reports that PC therapy is effective. It is necessary to search for effective treatments by following up and accumulating further cases.

This paper explores various aspects of microbiology and immunology, focusing on the epidemiology and molecular characterisation of infectious diseases in the Caribbean and South America. Key areas of investigation include tuberculosis (TB), nosocomial infections, Salmonella infections, and bloodborne pathogens. A retrospective study in Jamaica underscores the high mortality rates in HIV-positive TB patients and the need for early HIV diagnosis and integrated care. Research in Trinidad and Tobago reveals the genetic diversity of Mycobacterium tuberculosis strains, highlighting high HIV-TB co-infection rates. The paper also examines the challenges posed by nosocomial infections, particularly those caused by antibiotic-resistant Gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA), and emphasises the importance of infection control. In addition, the study investigates Salmonella prevalence in poultry in Jamaica and the risks associated with foodborne infections. The paper further explores transfusion-transmitted infections and the development of IgM antibodies in egg whites for bacterial antigen detection. Lastly, it addresses immune responses in patients with immunodeficiency disorders, such as severe combined immunodeficiency (SCID) and chronic granulomatous disease (CGD), highlighting their susceptibility to a wide range of infections.

The past few decades have brought tremendous insight into the molecular and pathophysiological mechanisms responsible for thrombus generation. For the clinician it is usually sufficient to explain the incident deep vein thrombosis (DVT) with provoking factors such as trauma with vascular injury, immobilization, hormonal factors, or inherited or acquired coagulation defects. About half of the DVTs are, however, lacking such triggers and are called unprovoked. Venous stasis and hypoxia at the valve sinus level may start a chain of reactions. In order to better understand the mechanisms behind DVT and reach beyond the above-mentioned simplifications animal models and clinical epidemiological studies have informed of the complex interplay between leukocytes, platelets, endothelium, cytokines, complements and coagulation factors and inhibitors. These pathways and the interplay will be reviewed here.

The architecture, Engineering, and Construction (AEC) industry is dealing with serious challenges on a global scale, i.e., project delays, budget overruns, and insufficient stakeholder collaboration. In this context, Value Engineering (VE) and Building Information Modeling (BIM) have been used recently to address these challenges and cope with large-scale and complex construction projects. An extensive body of literature highlights significant advantages of integrated VE within BIM technology. Despite this, it is full practical potential has not yet been realized. For this reason, this paper aims to investigate the integration of Value Engineering (VE) and Building Information Modeling (BIM) within a Common Data Environment (CDE) for the Architecture, Engineering, and Construction (AEC) industry. In doing this research, a comprehensive framework was developed and systematically implemented into practice through the use of four interconnected modules: (M. 1); Creating CDE, (M. 2); Design BIM Model Development, (M. 3); Value Analysis / Engineering Model, and (M. 4); Value Engineering Study. Introducing a new term the ""VEIDEA"" databank based on the OmniClass classification system provides a structured database utilized to store, manage, and accumulate VE ideas. Moreover, the study incorporates the Analytical Hierarchy Process (AHP) to automate the evaluation phase. Such a framework seeks to assist designers and VE team members make informed decisions when choosing appropriate design alternatives. Lastly, a case study method was adopted to examine the proposed framework for an office building. Quantitative data showed a significant link between cost savings and VR integration with BIM technology. For instance, cost of the RC slabs dropped by 20%, while flooring materials cost dropped by a 39%. Empirically, evidence from the case study supports literature regarding t the potential for significant enhancements in both cost-effectiveness and overall project performance through this innovative integration. In the context of knowledge contribution, this study provides an innovative way to assist designers and VE team members in making well-informed decisions when choosing appropriate design alternatives.

The elasticity of red blood cells (RBCs) is crucial for their ability to fulfill their role in the blood. Decreased RBC deformability is associated with various pathological conditions. This study explores the application of machine learning to predict the elasticity of RBCs using both image data and detailed physical measurements derived from simulations. We simulated RBC behavior in a microfluidic channel. The simulation results provided the basis for generating data on which we applied machine learning techniques. We analyzed the surface-area-to-volume ratio of RBCs as an indicator of elasticity, employing statistical methods to differentiate between healthy and diseased RBCs. The Kolmogorov–Smirnov test confirmed significant differences between healthy and diseased RBCs, though distinctions among different types of diseased RBCs were less clear. We used decision tree models, including random forests and gradient boosting, to classify RBC elasticity based on predictors derived from simulation data. The comparison of the results with our previous work on deep neural networks shows improved classification accuracy in some scenarios. The study highlights the potential of machine learning to automate and enhance the analysis of RBC elasticity, with implications for clinical diagnostics.

7046 aluminum alloy has good fatigue property, corrosion resistance and weld property, but the moderate strength and plasticity limit its wider application and development. In the present study, severe plastic deformation (SPD) was applied prior to T6 treatment to significantly strengthen and toughen the 7046 aluminum alloy. Results indicate that the alloy processed by 4 passes of equal channel angular pressing (ECAP) at 300 ℃ prior to T6 treatment exhibits an excellent mechanical performance, with ultimate tensile strength (UTS) and elongation (EL) of 485 MPa and 19%, exhibiting an improvement of 18.6% and 375% compared to that of the T6 alloy, respectively. The mechanical properties of the alloy are further improved by the additional room temperature (RT) rolling process, with UTS of 508 MPa and EL of 23.4%. There are more precipitates of η' and Al6Mn phases in the 300℃4P-R80%-T6 and 300°C4P-T6 alloys, which contribute to the strengthening and toughening enhancement by SPD processed T6 alloy. The results of this work may shed some light on enhancing 7046 aluminum alloy.

Due to its intriguing applications across a wide range of industries, nanotechnology is generating a lot of interest globally. Titanium dioxide (TiO2) nanoparticles are one type of nanoparticle (NP) that is commonly utilised in everyday use and can be produced using a variety of physical, chemical, and environmentally friendly techniques. Green synthesis is an economical, environmentally benign, and non-toxic method of synthesising NPs. Under normal circumstances, the application of TiO2 greatly enhanced the plants' shoot length, leaf area, and root dry weight. These growth-promoting factors coincided with elevated proline, soluble sugar, and chlorophyll B levels as well as improved antioxidant enzyme activity. Thus, higher levels of proline and other metabolites played a role in osmo-protection, while increased antioxidant enzyme activities helped to explain the observed decrease in hydrogen peroxide and malondialdehyde contents. Taken together, these factors significantly improved plant growth under salinity. TiO2 nanoparticles have demonstrated efficacy in treating contaminated water and have been shown to positively impact plant physiology, particularly in response to abiotic stresses. However, the reaction to these nanoparticles varies depending on characteristics such as metal species, type, size, shape, dose, duration of exposure, and other variables. One of the most popular nanomaterials in customer goods, agricultural, and energy industries is TiO2 NPs. Therefore, harm to ecosystems and living things will unavoidably result from high demand and widespread usage. Gaining more knowledge about the toxicity of TiO2 NP to living things could help with risk assessments and safe handling procedures for these nanoparticles. The synthesis of titanium oxide, its many uses, the toxicity of titanium dioxide nanoparticles, and their mode of toxicity are all summarised in this paper.

In the last decade, the application of non-Saccharomyces yeasts in oenology as a natural tool to obtain wine diversification and higher quality has aroused great interest. In this work, three M. pulcherrima strains, isolated from vineyard, were characterized through the evaluation of their main technological properties, antimicrobial activity and specific enzymatic activities (β-glucosidase, β-lyase, polygalacturonase and protease). The M. pulcherrima strains did not produce any inhibition against S. cerevisiae, while they were able to exert an antimicrobial action against some unwanted bacteria and yeasts frequently present in grape must and potentially causing alteration of wines. After this preliminary screening, M. pulcherrima AS3C1 has been selected to be used in the winemaking of red grape Vitis vinifera cv. Aglianico on a pilot scale. The effect of sequential inoculation of M. pulcherrima AS3C1 with a commercial strain of Saccharomyces cerevisiae was verified using for comparison a single inoculum with S. cerevisiae and a spontaneous fermentation. Our results showed a higher concentration of anthocyanins and catechins in wines obtained by sequential inoculation of M. pulcherrima AS3C1 and S. cerevisiae. On the basis of the data obtained, M. pulcherrima AS3C1 possesses an enzymatic profile and some oenological properties that could contribute positively to the definition of the chemical composition of wines, suggesting its possible use for red winemaking processes.

This study simulated the effects of direct predatory pressure, indirect predatory pressure, and conspecific injury signals on the sea cucumber (Apostichopus japonicus) to determine changes in the activity of immune defense enzymes (lysozyme, acid phosphatase, alkaline phosphatase) and antioxidant stress enzymes (catalase, superoxide dismutase, malondialdehyde). Samples of sea cucumber juveniles were collected at 3 hours, 12 hours, 72 hours, and 96 hours post-predatory stress, and six enzymes related to immune defense and antioxidant stress were selected for activity assays, namely lysozyme (LZM), acid phosphatase (ACP), alkaline phosphatase (AKP), superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA). The results indicated that under direct predatory pressure, the activity of catalase in sea cucumbers was significantly higher than that of the control group at 3 hours (P < 0.05), while the activities of acid phosphatase, alkaline phosphatase, and catalase were significantly lower at 72 hours (P < 0.05). Under indirect predatory pressure, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), the activity of alkaline phosphatase was significantly higher at 72 and 96 hours (P < 0.05), catalase was significantly lower at 72 hours, and the activity of superoxide dismutase was significantly higher at 72 hours (P < 0.05). Under the influence of conspecific injury signals, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), and the activity of superoxide dismutase was significantly higher at 96 hours (P < 0.05). The sea cucumber enhanced its antioxidant capacity 3 hours after facing the predator, while its immune defense mechanism was suppressed at 72 hours. When facing indirect predatory pressure, the sea cucumber may have made immune and antioxidant preparations for the arrival of unknown risks. The experimental results show that predatory pressure has a significant impact on the immune and antioxidant functions of sea cucumbers, which may be related to the physiological state and environmental adaptability of the sea cucumber. This study provides a new perspective for understanding how sea cucumbers cope with predatory pressure in the natural environment and offers theoretical support for the cultivation management of sea cucumbers.

This study aims to evaluate the effectiveness of inactivating Salmonella enteritidis in fresh chicken breast by irradiation using a combination of short-wave UV (0, 3, 6, 9, 12 and 15 J / cm2) and a natural antimicrobial such as caffeine (0, 5, 10, 15 and 20 nM/g) as alternative proposals to conventional techniques to reduce pathogens in food. The temperatures used were from 2 to 22°C. The most suitable models were double Weibull in 60% of cases with an adjustment of R2 0.9903-0.9553 and Weibull + cola, in 46.67%, with an adjustment of R2 of 0.9998-0.9981. Noting that the most effective combination in the reduction of Salmonella was 12 J/cm2 of UV light and 15 nM/g of caffeine, with a reduction of 6 CFU/g and an inactivation rate of 0.72. The synergistic effect was observed by increasing caffeine and UV light. Furthermore, the physic-chemical characteristics of the food matrix were not affected by the combination of both technologies. Therefore, these results suggest that this combination can be used in the food industry to effectively inactivate Salmonella enteritidis, without deteriorating product quality.

Refractory materials are used worldwide in process equipment. However, gaseous and liquid process products penetrate the surface layer, and deep into the volume of refractories destructing rather expensive constructions complicated to repair. To address this challenge, there is a need to develop protective coatings for refractory that can limit the penetration of working media and extend their operational lifespan. In this work, the application of gas-dynamic cold spraying (CGDS) to produce a coating on the refractory using fine titanium dioxide (TiO2) particles is explored. These particles are accelerated within a nitrogen flow, passing through a Laval nozzle, and then sprayed onto a fireclay surface. The mechanisms of particle deposition and layer formation on porous surfaces through experiments and numerical simulations were investigated. The geometry of a typical refractory pore was determined, which was then incorporated into Computational Fluid Dynamics (CFD) simulations to model the cold spraying process of porous substrates. As a result, the influence of the particle size on its velocity and angle of penetration into pores was established. Experimental findings demonstrate the effective closure of pores and the formation of a particle layer on the refractory surface. Furthermore, the nanoindentation tests for the refractory samples showcase capabilities for checking coating thickness for porous materials.

The purpose of this study was to establish the association between total and segmental body composition (BC) variables and anaerobic performance and to create optimal models that best predict such performance in CrossFit® (CF) athletes. Fifty athletes, 25 males and 25 females (age: 33.26 ± 6.81 years; body mass: 72.57 ± 12.17 kg; height: 169.55 ± 8.71 cm; BMI: 25.06 ± 2.31 kg·m−2) were recruited to participate and underwent BC analysis using dual-energy X-ray absorptiometry (DXA) and an all-out laboratory test on a cycle ergometer (Wingate) to determine their anaerobic performance. The results show a significant correlation between BC values and performance, ranging from moderate (r = -0.34, p = 0.015) to near-perfect (r = 0.96, p &lt; 0.01). Furthermore, the created performance prediction models exhibited predictive capacities ranging from 19% (p = 0.017) to 93% (p &lt; 0.001). All prediction models were created using total or segmental lean mass variables, excluding others. BC and performance variables found significant differences between males and females. The findings demonstrate that BC variables are crucial indicators of anaerobic performance in CF athletes. Professionals responsible for athlete performance should use this information to monitor athletes and design training programs.

The AUC-ROC is a widespread measure to assess the performance of a binary classification model across various discrimination thresholds. Yet, it is not apt for unbalanced class problems and is misleading for early retrieval. For instance, link prediction in complex networks is an unbalanced early retrieval problem, whose goal is to offer a ranking of the nonobserved network links, prioritizing a small cohort of positive links (for which we are sure the labels are reliable) on top of a list largely populated by unlabeled links (for which the labels are uncertain). Differently from binary classification, here the evaluation focuses on how the predictor prioritizes the positive class, because the negative class does not exist and is replaced by an unlabeled class. For decades, scholars have been investigating the necessity to correct and to generalize the AUC-ROC to work for both unbalanced classification and early retrieval evaluation, this is requested in many applied domains of computational science. Here we propose the area under the magnified ROC (AUC-mROC), a new measure that adjusts the standard AUC-ROC to work for unbalanced early retrieval problems such as link prediction. Finally, we introduce the area under the generalized ROC (AUC-gROC), which unifies both AUC-mROC and AUC-ROC to provide a universal and reliable evaluation measure that can work for both classification and early retrieval problems, regardless of class proportion.This discovery represents a critical achievement, culminating in success after decades of contentious research. Its solution promises to significantly impact various domains within applied computational science.