Introduction: The COVID-19 pandemic is a global crisis, the number of cases and deaths are on a steep incline. This article reviews the possible immunological mechanisms which underlie the disease pathogenesis by looking at the behaviour of previous coronaviruses not only in humans but also other mammals which possibly act as reservoir hosts. Observations: A key aspect of this coronavirus as well as the previous SARS CoV seems to be the importance of host immune response in the pathology and clinical severity of illness caused by them. A hyperactive innate immune state in combination with an exhausted adaptive immune response are possible determinants of severe illness. Conclusion: There is a possibility that the current SARS CoV 2 has immune evasive tactics similar to SARS CoV in its repertoire, since they share a 76% homology. These might have been learnt behaviour from long periods of persistence in their reservoir hosts and they may be the reason behind the dysregulated immune response evoked in humans. That in turn is highly likely to be one of the factors which govern disease severity. With this in mind we want to bring the medical community’s attention to a ‘hit early, hit hard’ intervention as a possible strategy to modify the course of the disease and bring down the numbers of severe sufferers.

Histone deacetylases inhibitors (HDACi) have shown promising therapeutic outcomes in haematological malignancies such as leu-kaemia, multiple myeloma and lymphoma, with dis-appointing results in solid tumours when used as monotherapy. As a result, combination therapies either with radiation or other deoxyribonucleic acid (DNA) damaging agents have been suggested as ideal strategy to improve their efficacy in solid tumours. Numerous in vitro and in vivo studies have demonstrated that HDACi can sensitise malignant cells to both electromagnetic and particle types of radiation by inhibiting DNA damage repair. Although the radiosensitising ability of HDACi has been reported as early as 1990s, the mechanisms of radiosensitisation are yet to be fully understood. This review brings forth the various protocols used to sequence the administration of radiation and HDACi treatments in the different studies. The possible contribution of these various protocols on the ambiguity that surrounds the mechanisms of radiosensitisation is also highlighted.

Based on the land use data of Qingmei Harbor Mangrove Nature Reserve in Sanya, China, in 2009, 2015 and 2022, this paper utilizes the PLUS model to predict the land use changes in the region in 2035 under three development scenarios, namely natural development, urban construction and ecological protection. The results of the study show that the area of building land in this region increased rapidly from 2009-2015, and the corresponding cropland, parkland and arbor forest land as a whole showed a different degree of decline, while the expansion of the area of manmade land, such as building land, basically came to a standstill after 2015. However, the mangrove area in this region has maintained a stable growth trend from 2009-2022. The results of multi-scenario modeling of land in this region showed that the area of building land, unutilized land, and artificial land such as parkland and grassland increased the most under the urban development scenario. In the ecological protection scenario, the area of ecological land, such as arbor forest land and river and lagoon, increases significantly. However, there is no significant increase in the area of mangrove forests under any of the three development scenarios. At present, the task of “returning ponds to wetlands” has been basically completed in this area, and the space for large-scale expansion of mangrove forests in Qingmei Harbor is limited in the future, and the focus of subsequent work should be shifted to the enhancement of the quality and function of mangrove ecosystems.

Growth environment greatly alters many facets of pathogen physiology, including pathogenesis and antimicrobial tolerance. The importance of host-mimicking environments for attaining an accurate picture of pathogen behaviour is widely recognised. Whilst this recognition has translated into the extensive development of artificial cystic fibrosis (CF) sputum medium, attempts to mimic the growth environment in other respiratory disease states have been completely neglected. The composition of the airway surface liquid (ASL) in different pulmonary diseases is far less well characterised than CF sputum, making it very difficult for researchers to model these infection environments. In this review we discuss the components of human ASL, how different lung pathologies affect ASL composition, and how different pathogens interact with these components. This will provide researchers interested in mimicking different respiratory environments with the information necessary to design a host-mimicking medium, allowing for better understanding of how to treat pathogens causing infection in these environments.

How complex morphological patterns form is an intriguing question in developmental biology. However, the mechanisms that generate complex patterns remain largely unknown. Here we sought to identify the genetic mechanisms that regulate the tan (t) gene in a multi-spotted pigmentation pattern on the abdomen and wings of Drosophila guttifera. Previously, we showed that yellow (y) gene expression completely prefigures the abdominal [1] and wing [2] pigment patterns of this species. In the current study, we demonstrate that the t gene is co-expressed with the y gene in nearly identical patterns, both transcripts foreshadowing the adult abdominal and wing melanin spot patterns. We identified cis-regulatory modules (CRMs) of t, one of which drives reporter expression in six longitudinal rows of spots on the developing pupal abdomen, while the second CRM activates the reporter gene in a spotted wing pattern. Comparing the abdominal spot CRMs of y and t, we found a similar composition of putative transcription factor binding sites that are thought to regulate the complex expression patterns of both terminal pigmentation genes y and t. In contrast, the y and t wing spots appear to be regulated by distinct upstream factors. Our results suggest that the D. guttifera abdominal and wing melanin spot patterns have been established through the co-regulation of y and t, shedding light on how complex morphological traits may be regulated through the parallel coordination of downstream target genes.

This paper present a platform for airborne sensor applications using low-cost, open-source components carried by an easy-to-fly unmanned aircraft vehicle (UAV). The system, available in open-source [1], is designed for researchers, students and makers for a broad range of their exploration and data-collection needs. The main contribution is the extensible architecture for modularized airborne sensor deployment and real-time data visualisation. Our open-source Android application provides data collection, flight path definition and map tools. Total cost of the system is below 800 dollars. The flexibility of the system are illustrated by mapping the location of Bluetooth beacons (iBeacons) on a ground field and by measuring water temperatures in a lake.

Antarctica has attracted increasing interest in understanding its microbial communities, metabolic potential, and as a source of microbial hydrolytic enzymes with industrial applications, for which advances in next-generation sequencing technologies have greatly facilitated the study of unculturable microorganisms. In this work, soils from seven sub-Antarctic islands and Union Glacier were studied using a whole-genome shotgun metagenomic approach. The main findings were that the microbial community at all sites was predominantly composed of the bacterial phyla Actinobacteria and Cyanobacteria, and the families Streptomycetaceae and Pseudonocardiaceae. Regarding the xenobiotic biodegradation and metabolism pathway, genes associated with benzoate, chloroalkane, chloroalkene, and styrene degradation were predominant. In addition, putative genes encoding industrial enzymes with predicted structural properties associated with improved activity at low temperatures were found, with catalases and malto-oligosyltrehalose trehalohydrolase being the most abundant. Overall, our results show similarities between soils from different Antarctic sites with respect to more abundant bacteria and metabolic pathways, especially at higher classification levels, regardless of their geographic location. Furthermore, our results strengthen the potential of Antarctic soils as a source of industrially relevant enzymes.

Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions becomes a challenge due to the stringent requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts where an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live-video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal has been implemented and assessed in a laboratory context, analyzing the model performance and QoS metrics. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% of accuracy. Also, obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.

Historical maps possess significant theoretical and practical value in fields such as historical geography and urban planning, making them essential tools for studying urban spatial structure. This study explores the evolution of Xi'an's urban spatial structure from the Five Dynasties (909 CE) to the late PRC period (1949 CE), using historical maps and Historical GIS (HGIS) methodologies. By integrating Space Syntax and Kernel Density Estimation (KDE) with data from The Historical Atlas of Xi'an, this research identifies key trends in the city's spatial transformation. Two distinct phases of development were observed: the simpler, centralized structure during the Five Dynasties, Northern Song, and Yuan periods, and a more complex, decentralized structure during the Ming, Qing, and PRC periods. These changes were influenced by a dynamic interplay of political, economic, cultural, and environmental factors, as well as the city's need to adapt to external military threats and internal socio-economic shifts. The study emphasizes the value of HGIS in analyzing urban historical geography and the potential it offers for both understanding past urban dynamics and informing contemporary urban planning and cultural heritage preservation efforts. The findings demonstrate how Xi'an's spatial evolution reflects broader trends in Chinese history and provides insights for future sustainable development.

The increasing demand for energy, driven by technological advances, population growth, and economic expansion, has intensified the focus on efficient energy management. Tri-generation systems, such as Combined Cooling, Heating, and Power (CCHP) systems, are of particular interest due to their efficiency and sustainability. Integrating renewable energy sources like solar power with traditional fossil fuels further optimizes CCHP systems. This study presents a novel method for enhancing CCHP system efficiency by identifying optimal design parameters and assisting decision-makers in selecting the best geometric configurations. A mathematical programming model using the Harris Hawks optimizer was developed to maximize net power and exergy efficiency while minimizing CO2 emissions in a solar-assisted CCHP system. The optimization resulted in 100 Pareto optimal solutions, offering various choices for performance improvement. This method achieved higher net power output, satisfactory exergy efficiency, and lower CO2 emissions compared to similar studies. The study shows that maximum net power and exergy efficiency, with reduced CO2 emissions, can be achieved with a system having a low compression ratio and low combustion chamber inlet temperature. The proposed approach surpassed the response surface method, achieving at least a 4.2% reduction in CO2 emissions and improved exergy values.

Cancer is one of the most dreaded illnesses of the 20th century, cancer is continuing to spread and is becoming more common in the 21 st century.As of right now, breast cancer seems to be the most common cancer worldwide and the leading cause of cancer-related fatalities.In present study we used different network pharmacology tools for identification of target that involved in breast cancer that network pharmacology tool used target identification and validation process in drug discovery.In present study we used UniprotKB as text mining tool for identification of breast cancer gene in that we got the 2,658 gene in that we take the 165 in study the we done the GO and KEGG enrichment analysis in that we take pathways related to the breast cancer further we used STRING for determination protein-protein interaction in that we got the interaction between NDUFA1 with NDUFA3 and EREG,MYO1B with ACTN4 and XRCC3 with XRCC2.The interaction network was drawn and the network was analyzed by Cytoscape.

The dynamic evolution and variation of electrical loads is now a priority for optimum management and, above all, forecasting. Indeed, these dynamic load variations require computer tools able to implement optimal load forecasting models. Scientific research into automated models for forecasting electrical loads therefore represents a challenge for scientific researchers. Several research studies have therefore been carried out. These include machine learning approaches such as: LSTM (Long Short-Term Memory), Support Vector Machine (SVM) and others. This article proposes a comparison study between a hybrid model based on the wavelet transform coupled with the adaboost method, and LSTM, for forecasting electricity consumption loads. Python 3.10 was used for the studies. The first results obtained consisted in the study of electricity load forecasts over four (04) data sets of the year (January, April, August and December). These results are very satisfactory, showing a good correlation between the real results of the electrical load consumption data, and the results of the implemented model. The electrical load consumption data are collected from a renewable energy production source: photovoltaic solar energy. The model test results (R2) obtained range from 0.919 to 0.958. These results are representative of real data and reflect the model's performance. The second set of results concerns a comparative study between the methods used by Y. Xie et al (CNN, MLP, LSTM-AM and LSTM-AM-MLP), and our approach. The prediction results obtained between the approaches show a prediction gap ranging from 0.15 to 0.78 for RMSE and 0.83 for MAPE. These results show significant differences between the methods. The minimization of errors by our model, therefore, reflects the model's performance in terms of accuracy, which is necessary for the optimal management of consumer electricity load forecasts in order to ensure balance between supply and demand.

High-precision dynamic positioning of highway vehicles is the foundation and prerequisite for achieving intelligent connected transportation. For the shortcomings of GNSS/INS combination and GNSS/INS/OD combination in tunnel vehicle positioning, this paper proposes a tunnel vehi-cle positioning method of GNSS/INS/OD combination based on lateral distance measurement and lane constraint. Firstly, lateral distance measurement of vehicles inside the tunnel is conducted based on laser radar point cloud data. Secondly, map matching positioning is performed based on lateral distance measurement, odometer, and lane markings. Experimental results demonstrate that for a 4.6 km tunnel, the average absolute error of lateral positioning is 0.294 meters, and the longitudinal positioning error is no more than 0.6 meters, which can effectively meet practical operational requirements.

The antimicrobial quantitative structure–activity relationship of plant flavonoids against Gram-positive bacteria was established in our previous works, and the cell membrane was confirmed as a major site of action. To investigate whether plant flavonoids have similar antibacterial effects and mechanisms against both Gram-negative and Gram-positive bacteria, here, the minimum inhibitory concentrations (MICs) of 37 plant flavonoids against Escherichia coli were determined using the microdilution broth method, and then the correlation between their lipophilic parameter ACD/LogP or LogD_7.40 value and their MIC was analyzed. Simultaneously, the correlation between the ACD/LogP or LogD_7.40 value and the MIC of 46 plant flavonoids reported in literature against E. coli was also analyzed. Both sets of results showed that there is a significant correlation between the LogP value and the MIC of plant flavonoids against Gram-negative bacteria. However, it is difficult to effectively predict the MIC of plant flavonoids against Gram-negative bacteria from their lipophilic parameters. By comparing two regression curves derived from plant flavonoids against Gram-negative and Gram-positive bacteria, it was further discovered that the antibacterial activities of most plant flavonoids against Gram-negative bacteria are stronger than those against Gram-positive bacteria when their LogP values are less than about 3.0, but the opposite is true when their LogP values are more than about 3.6. Moreover, this comparison also suggests that unlike mainly acting on the cell membrane of Gram-positive bacteria, plant flavonoids have multiple mechanisms against Gram-negative species, while the cell membrane is also an important action site among them. Combined with the correlation analyses between the enzyme inhibitory activity and the LogP value of the reported flavonoids, it was further suggested that DNA gyrase is another important target of plant flavonoids against Gram-negative bacteria.

In this research, a screw-barrel system was designed and implemented, coupled with material extrusion, to print high-melt-temperature thermoplastic materials. The aim was to integrate two methods: the direct extrusion of thermoplastic polymer pellets with material extrusion,utilize various polymers in the form of pellets, especially high melt temperature ones, instead of traditional filaments. This addresses one of the significant challenges in filament preparation for various materials that are not readily available in the market or nearly impossible to fabricate (such as highly filled plastics). First, the screw-barrel assembly performance and factors influencing feed rate were evaluated. Subsequently, specimens were printed with polyether ether ketone (PEEK), an advanced plastic material known for its outstanding mechanical properties, high-temperature tolerance, and broad applications in various sectors, such as medical. Additionally, the material was reinforced with 2.5% continuous glass fibers while printing, which presented a novel product. Upon comparing theoretical values with experimental data from the tensile testing, a notable observation emerged: the inclusion of 2.5% glass fibers led to an approximate 43% increase in the tensile strength of the material. Furthermore, SEM images provided visual evidence of satisfactory adhesion between layers and fibers.

This study aimed to use spatiotemporal tensor data to measure the level of employment quality in China's provinces and analyzed the magnitude and direction of its influencing factors in the spatiotemporal dimension. Taked 30 provinces, autonomous regions and municipalities directly under the central government in China from 2011 to 2020 as the research object, the employment quality evaluation system was constructed from six dimensions of employment environment, employment status, employability, labor remuneration, social security, and labor relations. The employment quality index data was expressed as a three-order high-dimensional tensor spatio-temporal data form, and the employment quality of China's provinces was measured from the spatio-temporal perspective by using principal tensor analysis, and the visual analysis of the development and change process of employment quality was carried out. The spatial autocorrelation analysis of employment quality was carried out, and the time-space dual fixed effect model of the spatial Dubin model was selected to analyze the direction and magnitude of the influence factors of employment quality on itself and its neighboring provinces. The research showed that: (1) The overall level of employment quality in China was not high and the employment quality varies greatly among provinces, and the employment quality development gap among provinces showed a trend of widening. (2) The development of employment quality in western China was relatively fast, while the development of employment quality in central China showed insufficient stamina. (3) Sichuan Province had a strong radiation effect on the development of employment quality in neighboring provinces, and Beijing and Tianjin had a strong siphon effect on the development of employment quality in neighboring provinces. (4) The level of industrialization and informatization promoted the development of employment quality in China's provinces, while the industrial structure had a significant negative effect on the development of employment quality.

In modern automobiles, Infotainment High-Performance Computing (HPC) systems play a vital role in enhancing the capabilities of drivers and passengers by providing advanced features consisting of music, navigation, communication, entertainment, etc. However, as the use of information technology in vehicles increases, it results in cybersecurity threats such as data breaches and the loss of sensitive information. To improve the security of the infotainment system in automotive vehicles, the research conducted threat modeling at the component level using Microsoft’s STRIDE tool and performed risk assessment by using SAHARA (Safety-Aware Hazard Analysis and Risk Assessment) and DREAD methodologies to evaluate associated risks. It provides a systematic representation of threats, associated risks, and generic mitigation strategies to counter cybersecurity attacks. Through the threat modeling process, 34 potential security threats were identified. The study also provided a comparative analysis to calculate the risk values of the threats to prioritize for treatment. These identified threats and associated risks need to be considered to avoid potential cyberattacks, before deploying the infotainment HPC system in real-world automotive vehicles.

The purpose of this study is to analyze the self-regulated learning and the ability to write scientific papers of students after learning with the Project-Based Digital Science Module (DSM). This research is a mixed methods by analyzing quantitatively and qualitatively. The research instrument used to obtain data is using a product assessment sheet and a self-regulated learning questionnaire. Data analysis uses N-Gain to determine the increase in self-regulated learning scores and student scientific writing skills scores, and uses linear regression analysis to determine the effect of self-regulated learning on student scientific writing skills. The results obtained showed N-Gain score of learning independent is 0,65 and scientific writing ability is 0,94, then significant’s score from linear regression by using SPSS is 0,22 < 0,05. This result showed an increase in self-regulated learning and the ability to write scientific papers of students on each indicator after learning using the Project-Based Digital Science Module (DSM). In addition, based on the results of data analysis, it can be seen that there is an influence of self-regulated learning on the ability to write scientific papers of students after learning using the Project-Based Digital Science Module.

This study aims to develop a novel retention method combining the retrievability of the screw retention method with the ideal occlusal table and the aesthetics capability of cement retention. Coping was developed to have lateral screw access allowing the screw to lock coping using lateral forces from screw tightening and friction between the tip of the screw and the sandblasted surface of an abutment. Sandblasting parameters varied based on particle size. Results show a positive correlation to surface roughness and indicate a positive correlation to retention force. The highest surface roughness and retention force result was shown by groups that were sandblasted using 686 μm of aluminum oxide. Experiment on the tightening strength of 48 subjects measured in simulated conditions similar to assembly conditions of lateral screw retention implant resulted in a mean of 69.75 Nmm with the highest and lowest values of 120.67 Nmm and 34.67 Nmm. This result became the basis of tightening torque variation. Each group's retention capability is measured and compared to cement-retained dental implants. Results show that tightening torque correlates positively with retention force, with the highest average retention score showed by lateral screw retained under tightening torque of 200 Nmm with 317.87 N higher than cement-retained.

The Dst index is the geomagnetic storm index used to measure the energy level of geomagnetic storms, and the prediction of this index is of great significance for the geomagnetic storm study and the solar activity. In contrast to traditional numerical modelling techniques, machine learning, which has emerged in decades ago based on rapidly developing computer hardware and software and artificial intelligence methods, has been unprecedentedly developed in geophysics, especially solar-terrestrial space physics. This study chooses two machine learning models, the LSTM (Long-Short Time Memory, LSTM) and EMD-LSTM model (Empirical Mode Decomposition, EMD), to model and predict the Dst index. By building the Dst index data series from 2018-2023, two models were built to fit and predict the data. Firstly, we evaluated the influences of the learning rate and the amount of training data on the prediction accuracy of the LSTM model, and finally, 10-3 was thought as the optimal learning rate; secondly, the two models were used to predict the Dst index in the solar active and quiet periods, respectively, and the RMSE (Root Mean Square Error) of the LSTM model in the active period is 7.34 nT, the CC (correlation coefficient) is 0.96, those of the quiet period are 2.64nT and 0.97; the RMSE and r of EMD-LSTM model are 8.87nT and 0.93 in active time and 3.29nT and 0.95 in the quiet time. Finally, the prediction accuracy of the LSTM model in short time period is slightly better than the EMD-LSTM model. However, there will be a problem of prediction lag, which the EMD-LSTM model can then solve, and can better predict the geomagnetic storm.

This paper presents the concept of a novel adaptable sensing solution currently being developed under the EU Commission founded PHOTONGATE project. This concept will allow to quantify multiple analytes of the same or different nature (chemicals, metals, bacteria, etc.) in a single test with levels of sensitivity and selectivity at/or over those offered by current solutions. PHOTONGATE relies on two core technologies: a bio-chemical technology (molecular gates) which will confer the specificity and, therefore, the capability to be adaptable to the analyte of interest, and which combined with porous substrates will increase the sensitivity, and a photonic technology based on Local Surface Plasmonic Resonance (LSPR) structures serves as transducer for light interaction. Both technologies are in the micron range, facilitating the integration of multiple sensors within a small area (mm²). The concept will be developed for its application in health diagnosis and food safety sectors. It is thought as an easy-to-use modular concept, which will consist of the sensing module, mainly of a microfluidics cartridge that will house the photonic sensor, and a platform for fluidic handling, optical interrogation, and signal processing. The platform will include a new optical concept, fully Europe Union Made, avoiding optical fibers and expensive optical components.

Intramuscular fat content (IFC) and meat color are vital indicators affecting pork quality. A significant positive correlation between IFC and redness meat color (a* value) indicates that these two traits are likely to be regulated by shared molecular pathways. To identify candidate genes, hub genes, and signaling pathways that regulate these two traits, we measured the IFC and a* value in 147 hybrid pigs and selected individuls with extreme phenotypes for transcriptome analysis. The results revealed 485 and 394 overlapping differentially expressed genes (DEGs) using DESeq2, limma, and edgeR packages affecting IFC and a* value, respectively. Weighted gene co-expression network analysis (WGCNA) identified four modules significantly correlated with IFC and a* value. Moreover, we integrated functional enrichment analysis results based on DEGs, GSEA, and WGCNA conditions to identify candidate genes, and identified 47 and 53 candidate genes affecting IFC and a* value, respectively. The protein-protein interaction (PPI) network analysis of candidate genes showed that 6 and 14 hub genes affecting IFC and a* value, respectively. These genes mainly participated in various pathways related to lipid metabolism and redox reactions. Notably, four crucial hub genes (MYC, SOX9, CEBPB, and PPAGRC1A) were shared for these two traits. After functional annotation of these four hub genes, we hypothesized that the SOX9/CEBPB/PPARGC1A axis could co-regulate lipid metabolism and myoglobin redox response. Further research on these hub genes, especially the SOX9/CEBPB/PPARGC1A axis, will help to understand the molecular mechanism of the co-regulation of IFC and a* value, which will provide the theoretical basis for improving pork quality.

The concept of collecting data of people using a domestic space is not novel. However, the methods and processes used to decipher this raw data and transform it into useful and appropriate information (i.e., sequence, duration, and timing derived from domestic activities) have been challenging and the focus of many research groups. But how are the results of the decoded transposition received, interpreted and used by the various professionals (e.g., occupational therapists and architects) who consume the information? This paper describes the inclusive evaluation process undertaken, which involved architects, engineers and end-users (not the occupant, but the care team managing the occupant). Finally, our study evidence the importance of making accessible to a multidisciplinary audience spatial, temporal and sequential aspects derived from people's domestic routines. Shedding light on how a systematic approach to collecting, processing and mapping low-level sensor data into higher forms and representations can be a valuable source of knowledge for improving the domestic living experience.

RF photonic transversal signal processors, which combine reconfigurable electrical digital signal processing and high-bandwidth photonic processing, provide a powerful solution for achieving adaptive high-speed information processing. Recent progress in optical microcomb technology provides compelling multi-wavelength sources with compact footprint, yielding a variety of microcomb-based RF photonic transversal signal processors implemented by either discrete or integrated components. Although operating based on the same principle, processors in these two forms exhibit distinct performance. This letter presents a comparative investigation into their performance. First, we compare the performance of state-of-the-art processors, focusing on the processing accuracy. Next, we analyze various factors that contribute to the performance differences, including tap number and imperfect response of experimental components. Finally, we discuss the potential for future improvement. These results provide a comprehensive comparison of microcomb-based RF photonic transversal signal processors implemented using discrete and integrated components and provide insights for their future development.

Climate change is expected to result in rising temperatures, leading to increased occurrences of extreme weather events like heat waves and cold spells. Urban planning responses are crucial for improving the adaptive capacity of cities and communities in dealing with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, the study identifies built-environment factors that contribute to moderate seasonal land surface temperatures (LST). The research focuses on Seoul, South Korea as a case study and calculates seasonal LST values at both the grid level (100m×100m) and street-block level, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for natural reserves. The quadrant analysis reveals spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. The spatial regression analysis demonstrates that higher vegetation density and proximity to water bodies play key roles in moderating LST, leading to cooler summers and warmer winters. Building characteristics have an invariant impact on LST across all seasons, where horizontal expansion contributes to higher LST, while vertical expansion reduces LST. These findings are consistent for both grid- and block-level analyses. The study emphasizes the flexible role of the natural environment in moderating temperatures.

To digital grade the color fastness of fabrics after rubbing, an automatic grading method based on spectral reconstruction technology and BP neural network was proposed. Firstly, the modeling samples are prepared by rubbing the fabrics according to the ISO standard of 105-X12. Then, to comply with visual rating standards for color fastness, the modeling samples are professionally graded to obtain the visual rating result. After that, a digital camera is used to capture digital images of the modeling samples inside a closed and uniform lighting box, and the color data values of the modeling samples are obtained through spectral reconstruction technology. Finally, the color fastness prediction model for rubbing was constructed using the modeling samples data and BP neural network. The color fastness level of the testing samples was predicted using the prediction model, and the prediction results were compared with the existing color difference conversion method and curve fitting method. Experimental show that the prediction model of fabric color fastness can be better constructed using the BP neural network, where the root-mean-square error of the prediction for the training sample is 0.30, and the root-mean-square error of the prediction for the test sample is 0.25. The overall performance of the method is slightly better than the color difference conversion method, and it is significantly outperforming the curve fitting method. It can be seen that the digital rating method of fabric color fastness to rubbing based on spectral reconstruction and BP neural network has a high consistency with the visual evaluation, which will help for the automatic color fastness grading.

Polymethyl methacrylate (PMMA) polymer is widely used in various fields today. In order to thoroughly reveal the structural impact performance of PMMA materials, this paper is based on the comprehensive Johnson-Cook constitutive model and damage failure model, and accurately confirm the J-C constitutive and damage failure model parameters of PMMA through material test data, The dynamic process of steel bullet impacting PMMA plate structure is analyzed by finite element software ABAQUS. The calculation results show that the numerical simulation results in this paper are in good agreement with the experimental test data. Therefore, the feasibility and accuracy of the impact analysis of PMMA structures based on J-C constitutive and damage failure models in this paper are studied. Finally, based on the J-C constitutive model and damage failure model, the variation of the residual velocity of the bullet with the PMMA plate thickness is analyzed in depth, that is, the results show that the residual velocity of the bullet has a certain linear relationship with the plate thickness.

The synthesis of the presented benzo[d]thiazol-2-amine derivatives was performed by condensing-(4-chlorobenzylidene) benzo[d]thiazol-2-amine with a number of substituted phenols in the presence of potassium iodide and anhydrous potassium carbonate in dry acetone. IR spectroscopy, 1HNMRspectroscopy and spectroscopy methods were used to characterize the structural properties of newly synthesized derivatives. In order to observe the attributes of drug-like candidates of these derivatives, the number of their molecular properties was estimated. Benzo[d]thiazol-2-amine derivatives were molecularly docked with selective enzymes COX-1 and COX-2. Findings suggested that Compounds G3, G4, G6, G8 and G11 possess higher binding affinity than diclofenac sodium, when docking was performed with enzyme COX-1. Compounds G1, G3, G6, G8and G10 showed lower binding affinity than Indomethacin when docking performed with enzyme COX-2.In vitro evaluation of the COX-1 and COX-2 enzyme inhibitory activities were performed for synthesized compounds. Compounds 10 and 11 exhibited significant COX-1 and COX- enzyme inhibitory action with IC50 values of 5.0 and 10 µM, respectively. Using the hot plate method and the carrageenan-induced rat paw edema model, the synthesized compounds were screened for their biological activities, including analgesic and anti-inflammatory activities. The highest analgesic action was exhibited by derivative G11and the compound G10 showed the highest anti-inflammatory response.

Drafting formations have been long recognized as highly effective for reducing drag and enhancing athletic performance, particularly in race walking events. The precise spacing and positioning of the race walkers are critical to optimizing the effectiveness of drafting. In this study, the drag reduction of 15 drafting formations is investigated using wind-tunnel experiments and CFD numerical simulations. The results show excellent consistency in drag reduction rate between the two methods, with differences being within 10%. This can be attributed to spacing replacing body shape differences as the primary factor influencing drag reduction. Optimal double, triple, and quadruple drafting formations produce the same results in both wind-tunnel experiments and CFD simulation, resulting in drag reductions of 67%, 66%, and 81% (wind-tunnel) and 65%, 72%, and 85% (CFD). The sources of drag differences in the two methods are discussed from various aspects. The flow field obtained through CFD analysis is used to examine the mechanism of drag reduction, revealing that drafting formations have a significant shielding effect on incoming air, which reduces the number and speed of airflow impacting the core race walker. This shielding effect is identified as the primary cause of drag reduction. Using an empirical model for mechanical power output, optimal double, triple, and quadruple drafting formations enhance sport economy (4.4-5.7%), speed (3.61-4.67%), and performance (173.8-223.3s) compared to race walking alone. The findings can serve as a reference for race walkers' positioning strategy and provide insights for considering drafting formations in various running events.

This study, based on the AISAS model, explores the impact of the interaction effect between visual and auditory signals on consumer purchase behavior. Using experimental methods, 120 participants were randomly assigned to four different visual and auditory signal combinations, and their purchase intentions and actual purchase behavior were measured. The results show that the interaction effect between visual and auditory signals has a significant impact on both purchase intentions and actual purchase behavior, and there is a significant positive relationship. Specifically, when visual and auditory signals are mutually consistent, consumers have the highest purchase intentions and actual purchase behavior; when both visual and auditory signals are absent, consumers have the lowest purchase intentions and actual purchase behavior; when either the visual or auditory signal is missing, consumers' purchase intentions and actual purchase behavior are in between the two extremes. This study provides a new perspective for understanding consumers' decision-making processes in multi-sensory environments and offers valuable insights for the development of marketing strategies.

The problem of health status prediction of insulated-gate bipolar transistors (IGBTs) gains a lot of attention in the field of health management of power electronic equipment. The performance degradation of IGBT gate oxide layer is one of the important failure modes. In view of failure mechanism analysis and easy implementation of monitoring circuit, this paper selects the gate leakage current of IGBT as the precursor parameter of gate oxide degradation, and uses time domain characteristic analysis, gray correlation degree, Mahalanobis distance, Kalman filter and other methods to carry out feature selection and fusion, and finally obtains a health indicator characterizing the degradation of IGBT gate oxide. Based on the Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) network, this paper constructs an IGBT gate oxide degradation prediction model, and performs experimental analysis on the dataset released by NASA-Ames Laboratory, and the average absolute error of performance degradation prediction is as low as 0.0216. Compared with Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Support Vector Regression (SVR) and CNN-LSTM models, CNN-LSTM network has the highest prediction accuracy. These results show the feasibility of gate leakage current as a precursor parameter of IGBT gate oxide layer failure, as well as the accuracy and reliability of the CNN-LSTM prediction model.

Background: Visceral leishmaniasis (VL) is s critical public health problem in over ninety countries. The control measures adopted in Brazil have been insufficient when it comes to preventing the spread of this neglected disease. In this context, a precise diagnosis of VL in dogs and humans could help to reduce the number of cases of this disease. Distinct studies for the diagnosis of VL have used single recombinant proteins in serological assays; however, results have been variable, mainly in the sensitivity of the antigens. The development of multiepitope-based proteins could be relevant in solving such a problem. Methods: A chimeric protein (rMELEISH) was constructed based on amino acid sequences from kinesin 39 (k39), alpha-tubulin, and heat shock proteins HSP70 and HSP 83.1, and tested in ELISA for the detection of L. infantum infection in humans and dogs. Results: rMELEISH was able to discriminate between VL cases and cross-reactive diseases and healthy samples, with sensitivity and specificity values of 100% as compared to the use of a soluble Leishmania antigenic extract (SLA). Conclusions: Preliminary data suggest that the rMELEISH protein presents a potential to be tested in future studies against a larger serological panel for the diagnosis of canine and human VL.

: In this article, the authors propose an algorithmic approach to building a model of the dynamics of economic and, in particular, innovation processes. The approach under consideration is based on a complex algorithm that includes (1) decomposition of the time series into components using singular spectrum analysis; (2) recognition of the optimal component model based on fuzzy rules, and (3) creation of statistical models of individual components with their combination. It is shown that this approach corresponds to the high uncertainty characteristic of the tasks of the dynamics of innovation processes. The proposed algorithm makes it possible to create effective models that can be used both for analysis and for predicting the future states of the processes under study. The advantage of this algorithm is the possibility to expand the base of rules and components used for modeling. This is an important condition for improving the algorithm and its applicability for solving a wide range of problems.

(1) Background: In order to study the effects of different electric cookers on the nutritional components of millet porridge, five different electric cookers were selected to cook millet porridge, and sensory and nutritional components in millet porridge, millet soup, and millet grains were analyzed. (2) Methods: Using principal component and cluster analysis, a variety of nutritional components were comprehensively compared. (3) Results: The results showed that among the different cooked samples, the content of amylose and reducing sugar was the highest in the samples cooked by electric cooker no. 3. The electric cooker no. 4 samples had the highest sensory evaluation score, crude fat, and protein content. The contents of ash, fatty acids, bound amino acids, and minerals were the highest in the electric cooker no. 5 samples. The sensory evaluation score and content of crude fat, ash, reducing sugar, direct starch, and Cu were higher in millet grains than in millet soup or porridge. The content of fatty acid, protein, amino acid, Zn, Fe, Mg, Mn, and Ca was highest in millet soup. Different electric cookers produced millet porridge with varying nutritional levels. (4) Conclusions: This study provides a reference for the further development of new electric cookers.

Specific emissivity features of swamps and wetlands of Western Siberia were studied for changing seasonal conditions with the use of daily data of satellite microwave sounding. The research technique involved the analysis of brightness temperatures of the underlying surface at the test sites. Variations in seasonal dynamics of brightness temperatures were mainly caused by different rates of seasonal freezing of the upper waterlogged layer of the underlying surface and dielectric characteristics of water containing natural media (water body, soil, vegetation). We analyzed long-term trends in seasonal and annual dynamics of brightness temperatures of the underlying surface and estimated hydrological changes in the Arctic and Subarctic. The findings open up new possibilities for using satellite data in the microwave range for studying natural seasonal dynamic processes and predicting hazardous hydrological phenomena.

The aim of this study was to determine gender differences in the level of motor skills and effects of a multi-year exercise program on the level of motor skills in 161 preschool children (5-6 yo). Patricipants were deployed into one control and three experimental groups. Motor skills were assessed with the Bruininks-Oseretsky Test of Motor Proficiency (BOT-2). To determine difference in scores for each BOT-2 tests between control and experimental groups, one-way ANOVA was used for girls and boys separately while two-way ANOVA was employed to determine difference between the gender in the overall BOT-2 score. The results indicates that one-year multilateral exercise program has a positive effect on the level of motor skills in preschool children. Interestingly, additional years of participation in exercise program yielded in maintenance of acquired motor skills level. Also, exercise program affected more girls than preschool boys considering both individual and composite BOT-2 scores. According to the findings of this study, presented exercise program could have potential benefits on multilateral development of the motor skills in preschool children which could facilitate balance of locomotor and manipulative skills. Therefore, integration of multilateral program intended for preschool children could be considered for implementation within the kindergarten curriculum.

Here, we designed the composition of the coating of the paper sheets composed of chitosan, bacterial cellulose (nanofibres), and ZnO with boosted antibacterial and mechanical activity. We investigated the compositions with ZnO exhibiting two different sizes/shapes: (1) rods and (2) irregular sphere-like particles. The proposed processing of bacterial cellulose resulted in the formation of nanofibers. Antimicrobial behavior was tested using E. coli ATCC® 25922™ following ASTM E2149-13a standard. Mechanical properties of the paper sheets were measured by comparison of tearing resistance, tensile strength, and bursting strength according to ISO 5270 standard. The increased antibacterial response is assigned to the combination of chitosan and ZnO (independently of its shape and size), while the boosted mechanical behavior is due to bacterial cellulose nanofibers. Therefore, the proposed composition is an interesting multifunctional mixture for coatings in food packaging applications.

Inorganic polymeric materials react slowly at room temperature and as a result usually require high-temperature curing. This study used the Arrhenius equation to analyze the correlation between curing temperature and curing duration during high-temperature curing. The test results show that optimal values exist for each alkali equivalent of the activator (weight ratio of Na2O/glass powder), curing temperature, and curing duration. Extending the curing duration and increasing the curing temperature have positive effects when the alkali equivalent is lower than the optimal value. However, over-curing results in invisible cracking in the specimens. Furthermore, despite exhibiting high strength initially, the strength of specimens gradually diminishes after standing in air. To ensure the durability of glass-based geopolymer, the curing temperature should not exceed 70℃, and the curing duration should be less than one day.

Abstract: The Tropical Rainfall Measuring Mission (TRMM) and then Global Precipitation Mission (GPM) are the most important and widely used data sources in the forecasting of drought, flood, and water resources management. However, since this sensor’s data is primarily used for tropical regions, it is necessary to evaluate the accuracy for optimal use of the data across varying climatic and physiographic conditions. In this study, the accuracy of the satellite data for a span of 17 years (2000-2017) for three climatic zones has been explored using synoptic ground station data. The climates include a) arid and low rainfall, b) semi-arid and low rainfall, and c) humid and high rainfall. We evaluated satellite data accuracy in drought and wet conditions based on the Standard Precipitation Index (S.P.I.) and different seasons. For available ground control stations, 13 stations were used in the humid, seven stations in a semi-arid climate, and 12 stations in the dry climate. The results show that the monthly precipitation product of GPM (IMERG product) and TRMM (TMPA/3B43 product) overestimate the rainfall. In the arid climate, the precipitation is estimated 43%, in the semi-arid environment 50%, and in the humid weather 11% more than the ground-based data on average. Therefore, to use satellite data in different climates, it is necessary to make corrections to obtain precise results. Based on 32 ground stations, the correction coefficient has a positive relationship with average precipitation and altitude and an inverse relationship with the latitude. Further in-depth investigations showed that the accuracy of satellite data in wet conditions is higher than the accuracy of normal circumstances, and the accuracy of normal conditions is more accurate than drought conditions. Besides, the accuracy of satellite data in wet or dry conditions increases with increasing time scales. The highest accuracy was obtained for a 12-month time scale and the lowest accuracy for the 3-month time scale of drought conditions in the arid climate.

Taking a typical forest underlying surface as the research area, this study employed the unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including tree height and canopy radius, which were used to improve the Noah-MP land surface model conducted in Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of CN-Din forest followed a Weibull distribution. The replacement of the parameters by these observed UAV would result in the Noah-MP model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux which could decrease up to -11% in the midday while increase up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately deliver the heterogeneity for the underlying surface.

This paper develops the mathematical modeling and deflection control of a textile-reinforced composite integrated with shape memory actuators. The model of the system is derived using identification method and unstructured uncertainty approach. Based on this model and robust stability analysis a robust proportional-integral controller is designed for controlling the deflection of the composite. The performance of the proposed controller is compared with a classical one through experimental analysis.

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

Laboratory experiments were performed to measure the supercritical CO2 (scCO2) storage ratio (%) of the conglomerate and sandstone in Janggi Basin, which are classified as rock in Korea available for CO2 storage. The scCO2 storage capacity was evaluated by direct measurement of the scCO2 amount replacing pore water in a reservoir rock core. The scCO2 sealing capacity of the cap rock (i.e., tuff and mudstone), was also compared by measuring the initial scCO2 seepage pressure (Δp) into the rock core. The measured average scCO2 storage ratio of the conglomerate and the sandstone in Janggi Basin was 30.7 % and 13.1 %, respectively, suggesting that the scCO2 storage capacity is greater than 360,000 metric tons in the Janggi Basin. The initial scCO2 seepage pressure of the tuff in the Janggi Basin was 15 bar and continuous scCO2 injection into the tuff core occurred at Δp higher than 20 bar. For the mudstone, the initial scCO2 seepage pressure was higher than 150 bar (10 times higher than that of the tuff), demonstrating that the mudstone is more suitable than the tuff to shield scCO2 leakage from the reservoir rock in the Janggi Basin.

The aim of this article was to assess how the professional competence of PETs (Physical Education Teachers) can predict student satisfaction in high school and student satisfaction with life itself. In line with these aims, this study was completed as a cross-sectional study, which was carried out in a total 890 Physical Education (PE) students. Of the research group, 50.3% were female and 49.7% were male. Age average was 15.49 years old for females (SD 1.79) and 15.00 years old for males (SD 2.00). The data collection instrument was the Intrinsic Satisfaction Classroom Scale and Satisfaction with Life Scale. The results are presented as descriptive statistics, correlations and structural equation modelling analysis, and they show that the competences of the PE teacher determine in great measure student’s satisfaction with school and with their own personal lives.

This paper deals with the design, simulation and implementation of shunt hybrid compensator to maintain the power quality in 3-phase distribution networks feeding different types balanced and unbalanced nonlinear loads. The configuration of the compensator consists of a selective harmonic elimination passive filter, a series connected conventional 6-pulse IGBT inverter, acting as the active filter terminated with a dc link capacitor. The theory and modelling of the compensator based on current harmonic components at the load end and their decomposition in d-q axis frame of reference are utilized in the reference current generation algorithm. Accordingly, the source current waveform is made to follow the reference current waveform using a high frequency carrier based controller. Further, this inner current control loop is supported by a slower outer voltage control loop for sustaining desirable dc link voltage. Performance of the compensator is evaluated through MATLAB simulation covering different types of loads and reduction of harmonic currents and THD at the supply side along with excellent regulation of dc link voltage are confirmed. The performance of a hybrid compensator designed and fabricated using the above principles is evaluated and corroborated with the simulation results.

This paper deals with the techno-economic study of the hybrid renewable energy system based on energy storage aspect under the form of hydrogen and methane. Indeed, with the intermittency of the renewable energy sources such as photovoltaic and wind energy, several problems of produced energy injection to the power system network can be encountered due to the shortage or the excess of these sources. This situation appeals the use of systems that ensure the stability of network based on the storage of energy surplus into gas using electrolyzer systems, which will be used afterward to cover the eventual shortage. In the present paper, the study of performance of each pathway of methane and hydrogen storage has been performed by the treatment of multiple scenarios via different architecture case studies in an Algerian location. Whereas, the energy produced by the photovoltaic system, the wind energy and the gas micro turbine sources are considered similar in each case. The modeling and simulation of the studied system operation under optimization criteria has been performed in this work, where the main aim is to define the appropriate configuration taking into account the different with low costs of investment, maintenance operation and immediate reactivity with a big storage capacity.

This paper reports on the production and mechanical properties of Ti6Al4V micro-lattice structures, with strut thickness nearing the single-track width of the laser-based powder bed fusion (LPBF) system used. Besides providing new information on the mechanical properties and manufacturability of such thin-strut lattices, this paper also reports on the in-situ deformation imaging of micro-lattice structures with 6 unit cells in every direction. LPBF lattices are of interest for medical implants, due to the possibility of creating structures with an elastic modulus close to that of the bones and small pore sizes which allow effective osseointegration. In this work four different cubes were produced by laser powder bed fusion and subsequently analyzed using microCT, compression testing and one selected lattice was subjected to in-situ microCT imaging during compression. The in-situ imaging was performed at 4 steps during yielding. The results indicate that mechanical performance (elastic modulus and strength) correlate well with actual density and that this performance is remarkably good, despite the high roughness and irregularity of the struts at this scale. In-situ yielding is visually illustrated.

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

Data dealing with the assessment of heavy metal pollution in road dusts in Jeddah, Saudi Arabia and its implication to human health risk of human exposure to heavy metals, are scarce. Road dusts were collected from five different functional areas (traffic areas TA, parking areas PA, residential areas RA, mixed residential commercial areas MCRA and suburban areas SA) in Jeddah and one in rural area (RUA) in Hada Al Sham. We aimed to measure the pollution levels of heavy metals and estimate their health risk of human exposure applying risk assessment models described by USEPA. Using geo-accumulation index (I_geo), the pollution level of heavy metals in urban road dusts was in the following order Cd > As > Pb > Zn > Cu > Ni > Cr > V > Mn > Co > Fe. Urban road dust was found to be moderately to heavily contaminated with As, Pb and Zn, and heavily to extremely contaminated with Cd. Calculation of enrichment factor (EF) revealed that heavy metals in TA had the highest values compared to that of the other functional areas. Cd, As, Pb, Zn and Cu were severely enriched, while Mn, V, Co, Ni and Cr were moderately enriched. Fe was consider as a natural element and consequently excluded. The concentrations of heavy metals in road dusts of functional areas were in the following order: TA > PA > MCRA > SA > RA > RUA. The study revealed that both children and adults in all studied areas having health quotient (HQ) < 1 are at negligible non-carcinogenic risk. The only exception was for children exposed to As in TA. They had an ingestion health quotient (HQ_ing) 1.18 and a health index (HI) 1.19. The most prominent exposure route was ingestion. The cancer risk for children and adults from exposure to Pb, Cd, Co, Ni, and Cr was found to be negligible (< 1 x 10^-6).

Antimicrobial resistance (AMR) represents a growing crisis in both human and veterinary medicine. We evaluated the use of two categories of antibiotic alternatives – heavy metals and essential oils – in beef cattle, and their effects on gram-negative and gram-positive bacteria. In this randomized controlled field trial, we measured the impact of supplemental zinc and menthol on antimicrobial resistance among commensal enteric bacteria of feeder cattle. Fecal suspensions were plated onto plain- and antibiotic-supplemented MacConkey and m-Enterococcus agar for quantification of total and antimicrobial-resistant Escherichia coli and Enterococcus spp., respectively. Temporal effects on overall E. coli growth were significant (P&lt; 0.05); however, there were no significant effects on antibiotic-supplemented agar. Zinc was associated with significant increases in growth on erythromycin-supplemented m-Enterococcus agar. Cattle fed zinc exhibited significantly higher macrolide resistance among fecal enterococci isolates.

Microalgae cultivation for biotechnological purposes is an expanding field. Their cultivation is usually performed on a liquid culture medium and require the presence of an energy source. Culture media are water-salt solutions containing nitrogen, sulfur, phosphate sources, with trace of transition metals. Light source supplies energy through photosynthesis process, resulting in metabolic reactions and cell growth. Thanks to the huge number of existing species and their diversity, it is possible to exploit alternative water sources with chemical and physical properties far from the commonly used freshwater media. Among these, oilfield or formation waters (AFW) are saline wastewater produced during oil drilling. They represent over 95 % of the total fluids collected from gas and oil wells during fuel extraction. This study exploits the adaptation capability of a Galdieria sulphuraria strain in different salinity conditions to build up a more feasible microalgae-based platform. Batch cultivation of G. sulphuraria was evaluated in a range from 0 to 20 g/L NaCl in terms of growth rate, metabolite content, photophysiology, and intracellular redox state. Moreover, the same strain has been tested for artificial formation water growth in semicontinuous cultivation mode. In these condition, NaCl preadaptation effect has been assessed too. Results clearly demonstrate that biomass composition is influenced from medium salinity. Strains preadapted in 0 to 20 g/L range of NaCl salinity show almost same cell growth profile and a slightly different ratio between lipids, carbohydrates, and proteins. Pigments content and photophysiology point out that variations of osmotic pressure and ionic strength in medium affect Photosystem II (PSII). Regulation of light harvesting is necessary to trigger metabolism shift toward synthesis of metabolites required in the adaptation process.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive sense single stranded RNA genome containing virus which has infected millions of people all over the world particularly China. The virus has been mutating rapidly enough resulting in the emergence of new variants and sub-variants which have reportedly been spread from Wuhan city of China, the epicenter of the virus, to the rest of China and all over the world. The occurrence of mutations in the viral genome especially in the viral spike protein region has resulted in the evolution of multiple variants and sub-variants which gives the virus benefit of host immune evasion and render the modern-day vaccines and therapeutics ineffective. Therefore, there is a continuous need to study the genetic characteristics and evolutionary dynamics of the SARS-CoV-2 variants. Hence, in this study, a total of 833 complete genomes of SARS-CoV-2 variants (including the wild-type or reference sequence) from Taiyuan and Wuhan cities of China were genetically characterized and studies their phylogenetic and evolutionary dynamics using phylogenetics, genetic similarity, and phylogenetic network analysis. Our results show a lot of useful information regarding the evolutionary dynamics of the viral variants, their genetic similarities/dissimilarities, and their phylogenetic relationships. It has been reported in this study that the SARS-CoV-2 variants have nine recombinant events which suggest very important information regarding the viral evolution. In addition, the phylogenetic network analysis shows the number of mutations resulting in emergence and clustering of the viral variants of both cities which reveal significant information regarding the phylodynamics of the virus. This study, to the best of our knowledge, is the first ever genetic comparative study of Taiyuan and Wuhan cities. This study will help better understand the virus, cope with the emergence, and spread of new variants at local level as well as at international level and inform the public health authorities to make better informed decisions in designing new viral vaccines and therapeutics.

Taxonomic studies of dreams that continue to influence the dreamer’s thoughts and feelings after awakening have distinguished three types of impactful dreams: nightmares, existential dreams, and transcendent dreams. Of these, existential dreams and transcendent dreams are characterized by recurrent metacognitive appraisal of the epistemic tension between complementary (a) metaphoric (A “is” B) assertions and (b) literal (A “is not” B) assertions. Metacognitive appraisal of such complementary metaphoric and literal assertions is detectible as the felt sense of inexpressible realizations. The poesy of such inexpressible realizations depends upon the juxtaposition of a metaphoric topic and vehicle that are both “semantically dense” but at an abstract level “distant” from each other. The result is the “emergence” of attributes of the metaphoric vehicle that are sufficiently abstract to be attributes also of the metaphoric topic. The cumulative effect of successive metaphoric/literal categorical transformations produces a higher-level form of metacognition that is consistent with a neo-Kantian account of sublime feeling. Sublime feeling occurs as either sublime disquietude (existential dreams) or as sublime enthrallment (transcendent dreams). The aftereffects of these two dream types are thematically iterative “living metaphors” that have existential (but not totalizing) abstract ontological import.

Introduction: The care of dependent people is eminently family-oriented, and often, there is a high level of dedication to this family care. Constant and continuous care leads to a series of negative psychological consequences. Social support has been related to improved mental health in family caregivers. We found heterogeneous results regarding the relationship between the types of social support received and the perceived level of support. In addition, to our knowledge, no reviews analyze this relationship among family caregivers. Therefore, we aimed to systematically syn-thesize the relationships between perceived and received social support in informal caregivers. Methodology: We have carried out a quantitative systematic review with meta-analysis, regis-tered in PROSPERO (id: CRD42023470047); the systematic search was carried out in the following databases: PubMed, CINAHL, PsycINFO, and Scopus, until November 2023. After the selection and review of the results, 12 studies were obtained, two of which were eliminated due to a high risk of classification bias. Regarding the results, a medium size positive statistical association was found (r = 0.43). The results were consistent, accurate, and robust. The Trim and Fill test showed a vari-ation of 7%. Subgroup analysis indicated no differences in the age group of the people cared for (adults or children), selection bias, and confounding bias. In conclusion, perceived social support is related to more social support received by family caregivers.

Floods in various regions cause irreparable damage to infrastructure, agricultural lands, and industrial centers. In recent years, due to the effects of climate change and, in particular, the increased activity of the monsoon system in the Balochistan region located in southern Sistan and Baluchestan province, local rivers have overflowed, causing widespread flooding and significant damage. Accurate flood routing not only provides decision-makers with precise information about flood volume and flow behavior but also facilitates planning for effective preventive measures. In this study, the Muskingum-Cunge model was used to simulate floods in eight major rivers of Balochistan, including Kajou, Sarbaz, Nik Shahr, Kehir, Bahu, Sia Jangal, Rapch, and Kamb. The model parameters (K and X) were optimized using two machine learning algorithms: Particle Swarm Optimization (PSO) and Harmony Search (HS). The results showed that in most stations, the PSO algorithm outperformed HS. The algorithms were evaluated using the coefficient of residual mass (CRM), normalized root mean square error (NRMSE), efficiency (EF), and agreement index (d). For instance, at the Kajou station, PSO improved CRM by 0.017, Ef by 0.921, d by 0.982, and NRMSE by 0.099 compared to HS. At the Kamb station, both algorithms yielded comparable results. Considering the overall better performance of the PSO algorithm in most evaluation indices, it can be concluded that this algorithm is a more suitable option for optimizing the parameters of the Muskingum-Cunge model and simulating flood hydrographs with higher accuracy at most of the studied stations.

The Colorado and Mississippi River Basins are crucial for water supply, agriculture, and ecological stability in the U.S., yet climate change, water management practices, and energy sector demands pose significant challenges to their sustainability. This paper highlights the potential of leveraging the Voluntary Carbon Market (VCM) to address these challenges by creating new revenue streams and incentivizing sustainable water management practices. The paper provides high-level estimates by extrapolating from existing literature. The results suggests that water projects in these basins could generate over 45 million carbon credits annually, potentially attracting around $4.5 billion in investments over the next decade. However, challenges such as high costs, complex regulations, and stakeholder coordination must be addressed. The paper also identifies opportunities for advancing water resiliency projects, including increasing public awareness, engaging corporations, and utilizing innovative financing mechanisms. Recommendations include promoting the VCM-water relationship, encouraging methodology innovation, developing pilot programs, investing in digital monitoring technologies, and conducting localized analysis to optimize carbon credit potential in water management. By integrating carbon markets with water management strategies, the paper suggests significant contributions to global climate goals and enhanced water resilience in these critical regions.

Background: Diets based on meat products are not recommended in the case of ulcerative colitis (UC). However, some foods, as those containing high oleic acid and a low omega-6/omega-3 ratio show anti-inflammatory properties. The objective here is to test if some traditional cured meat products, as acorn-fed ham (high levels of oleic acid), may be useful for controlling inflammatory diseases as UC in animal models. Methods: 3 rat cohorts have been used: vegetable rat feed, control ham and acorn-fed ham (a traditional ham where high oleic acid concentration from acorns is storage in the muscle fat). UC was induced with DSS in drinking water ad libitum for one week. Short-chain fatty acids (SCFAs) and 16S rRNA from bacterial populations were analyzed in cecum samples. Colon samples were analyzed for histological parameters (inflammatory cell density, mucosa damages, myeloperoxidase). Results: In the acorn-fed ham cohort, a protective effect was observed with respect to UC disease activity index, inflammatory cells density, colon mucosa alterations, myeloperoxidase levels, blood total antioxidant capacity and lower levels of pro-inflammatory cytokines, in comparison with feed cohort. Both ham diets caused a reduction in Firmicutes and an increase in Actinobacteria, Bacteroidetes and Proteobacteria in comparison with rat feed diet. Also, acorn-fed ham diet induced changes in gut microbiota composition, with pronounced enrichments in anti-inflammatory bacterial genera such as Alistipes, Bacteroides, Blautia, Butyricimonas and Parabacteroides. Conclusions: In the acorn-fed ham cohort, as a result of the dietary intake of oleic acid and low intake of omega-6 fatty acids, a strong preventive effect against UC symptoms was observed, indicating a valuable effect of this traditional Mediterranean cured meat product.

Taking four of the United Nations Development Goals as reference, this overview describes the need to see from a systemic perspective, the food certifications programs along the food chain in Mexico as today food certifications are voluntary. Using secondary data, the main objectives were: a) there is a fall short in food safety policies and those federal agencies responsible for food safety, to guarantee safe food along the whole domestic food chain, especially in that for low income players; b) the amount of the Mexican Federal Budget Expenses devoted to safety food issues is really low, considering the health, well- being, and food security consequences; and c) due the structural heterogeneity of the Mexican food market, there is a lack of coordination in food regulations along all agents of the food supply chain, bringing to alternate informal markets that put at risk peoples´ health, increasing poverty and inequalities. According to this exercise, only 0.7- 8.7% of producers, 12.5% of supermarkets as well as 42.8% of restaurants would have some type of certifications. Public policies must attend this issue in order to improve food safety and security for the whole population, reducing inequalities, poverty and ensuring them a healthy live.

In this paper we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near-real time (3h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (<3 mm hr⁻¹).

Background: The aim of this study was to design and analyze the content validity of an instrument to assess the risk of behaviors associated with the Chemsex phenomenon since there is currently no instrument with this objective. Method: Firstly, a bank of items identified from the literature was elaborated. Secondly, 50 experts with knowledge of the Chemsex phenomenon at the national level were contacted. A Delphi group was formed with them to carry out two rounds of item evaluation (comprehension and appropriateness) using a Likert scale of 1 to 5. To assess linguistic validity, the mean score of the item comprehension scores was used. The content validity index (CVI) and Aiken's V (VdA) were calculated for each item. A minimum value of CVI and VdA of 0.6 was established to include the items in the questionnaire. Results: In the first round of evaluation, 36 experts evaluated 114 items, of which 61 were selected. In a second round, 30 experts evaluated the 61 items selected, leaving the scale finally made up of 52 items. Conclusion: A questionnaire has been designed to assess the risk of behaviors associated with the Chemsex phenomenon. The items that make up the questionnaire have shown adequate content and linguistic validity, so this instrument can be considered valid. The Delphi method proved to be a useful technique for the proposed objective.

Tuberculosis (TB) associated with diabetes (DM) is a growing problem, particularly in low and medium-resource countries. We conducted an open-label, parallel-group, randomized, and controlled trial in a tertiary care center in Mexico City to assess TB preventive treatment with isoniazid (INH) or rifampicin (RIF) in people with DM. Participants were assigned six months of INH 300mg/day plus pyridoxine 75mg or three months of RIF 600mg/day. The primary outcomes were adverse events resulting in permanent treatment cessation and considered possibly or probably related to study drugs. We included 130 subjects, 68 randomized to INH and 62 to RIF. We prematurely halted the study based on recommendations of the Adverse Event Safety Panel. There was no difference between arms in the overall frequency of adverse events. However, the INH group had significantly more permanent treatment interruptions due to grade 2 recurrent or grade 3 or 4 hepatoxicity. In comparison, the RIF arm had more treatment interruptions due to grade 3 or 4 gastrointestinal intolerance. TB preventive treatment is not safe enough to be considered a universal indication to patients with DM and LTBI. These results underline the need to search for alternative TB prevention in DM patients with better safety profiles.

Pigeon Newcastle disease, caused by pigeon paramyxovirus type 1 (PPMV-1), is a significant infectious disease in pigeons that can result in substantial mortality and poses a severe threat to the pigeon industry. Rapid and accurate onsite diagnosis of pigeon disease is crucial for timely diagnosis and the implementation of effective prevention and control measures. In this study, we established a rapid detection method for PPMV-1 based on recombinase-aided amplification (RAA) and CRISPR/Cas12a. The RAA primers target the conserved regions of the L gene for preamplification in clinical nucleic acid samples, followed by CRISPR/Cas12a detection of the target gene. Visualization could be achieved by combination with a lateral flow dipstick (LFD). This method demonstrated high specificity, showing no cross-reactivity with non-PPMV-1 samples. The sensitivity of the method assessed by fluorescence analysis reached 100 copy/µL, and when it was combined with an LFD, the sensitivity was 103 copies/µL. The constructed RAA-CRISPR/Cas12a-LFD visual detection method was applied to clinical sample testing and was found to enable rapid and accurate detection of swab samples and tissue specimens. Its sensitivity was consistent with the current gold standard, quantitative real-time PCR results. The RAA-CRISPR/Cas12a-LFD detection method we developed provides a novel approach for the rapid, simple, precise, and specific onsite diagnosis of pigeon Newcastle disease.

The presented work is aimed at studying the gas transport characteristics of polymeric hollow-fibre gas separation membranes. Such materials as: polysulfone (PSF), polyphenylene oxide (PFO), polyetherimide (PEI), polyetherimide with polyimide (PEI+PI) were studied on the example of air mixture separation. The values of the permeances of pure gases O2 and N2 and the mixed permeances of oxygen and nitrogen during air separation were obtained. Mathematical models of the gas separation process built on the basis of these values show significant discrepancies. To obtain a gas mixture with 95 mol.% nitrogen from air, taking into account the mixture permeance, 15.8% more PSF membrane area is required than taking into account the permeance of pure gases. For a PPO membrane this value is 13.9%, for PEI 19.8% less area is required, and for PEI+PI 15.9% less. In the design of industrial or semi-industrial membrane installations, such discrepancies can lead to significant errors, including technical and economic ones.

The movement toward prevention trials in people at-risk for Parkinson’s is rapidly becoming a reality. The authors of this article include a genetically at-risk advocate with the LRRK2 G2019S variant and two patients with rapid eye movement sleep behavior disorder (RBD), one of whom has now been diagnosed with Parkinson’s disease (PD). These authors participated as speakers, panelists, and moderators in the “Planning for Prevention of Parkinson’s: A Trial Design Forum” hosted by Massachusetts General Hospital in 2021 and 2022. Other authors include a young onset person with Parkinson’s (PwP) and retired family physician, an expert in patient engagement in Parkinson’s, and early career and veteran movement disorders clinician researchers. Several themes emerged from the at-risk participant voice concerning the importance of early intervention, the legitimacy of their input in decision-making, and the desire for transparent communication and feedback throughout the entire research study process. Challenges and opportunities in the current environment include lack of awareness among primary care physicians and general neurologists about PD risk, legal and psychological implications of risk disclosure, limited return of individual research study results, and undefined engagement and integration of individuals at-risk into the broader Parkinson’s community. Incorporating the perspectives of individuals at-risk as well as those living with PD at this early stage of prevention trial development is crucial to success.

A fundamentally new synthetic approach to the synthesis of 2-aminopurine has been developed. It consists in the combination of creation of condensed polyazotic heterocyclic tetrazolopyrimidine structure, it’s transformation into triaminopyrimidine and subsequent cyclization into 2-aminopurine. The structure of the obtained compounds was established based on spectral characteristics and intermediate 5 directly by X-ray diffraction analysis.

Tyrosyl-DNA phosphodiesterase 1 (TDP1) is a human DNA repair protein. It is a member of the phospholipase D family based on the structure similarity. TDP1 is a key enzyme involved in repairing stalled topoisomerase 1 (TOP1)-DNA complexes. Previously we obtained with the CRISPR/Cas9 method HEK293A cells with the homozygous knockout of the Tdp1 gene and used knockout cells as a cellular model for studying the mechanisms of anticancer therapy. In this work we studied for the first time by transcriptomic analysis the effect of Tdp1 gene knockout on genes expression changes in human HEK293A cell line. We received original data that may indicate a role of TDP1 in other process besides repair of DNA-TOP1 complex. The differentially expressed genes (DEGs) analysis revealed that TDP1 could be involved in different processes such as cell adhesion and communication, spermatogenesis, mitochondrial function, neurodegeneration, cytokine response, and MAPK pathway signaling.

Salinity is the most significant abiotic stress affecting crop yield worldwide, breeders are Salinity is the most important abiotic stress limiting crop production throughout the world, and breeders are encouraged to test novel genotypes for their resistance to this selection agent. However, getting a sufficient number of plants for the evaluation can be a lengthy and time-consuming procedure that might be shortened by applying in vitro techniques. An experiment was conducted under controlled saline circumstances using a tissue culture technique to investigate the influence of salt on several physic-biochemical parameters. Micro-shoots of Volkamariana lemon, sour orange, trifoliate orange, and Cleopatra mandarin rootstocks were re-cultured on MS media supplemented with NaCl from 25, up to 150 mM. Following the experiments, all of the tested rootstocks' morphological and biochemical characteristics, stomata behavior, and element accumulation were measured. As a result, adding NaCl from 25 to 150 mM to MS media caused a reduction in all morphogenetic parameters such as shoot number, shoot length, leaves number, and survival percentage was measured compared with control. Photosynthesis pigment, RWC, K, and Ca ions were decreased by increasing NaCl from 100 to 150 mM. On the contrary, proline, Cl, and Na were increased. Cleopatra mandarin and Trifoliate orange are more tolerant to salt stress than Volkamariana lemon and sour orange citrus.

The tobacco cembranoid (1S,2E,4R,6R,7E,11E)-2,7,11-cembratriene-4,6-diol (4R) is known to induce neuroprotection against brain ischemia, systemic inflammation, Parkinson's disease, and organophosphate toxicity in rodents. Studies examining the compound's safety in male and female Sprague Dawley rats demonstrated no significant side effects after a single injection of 4R at various concentrations (6, 24, or 98 mg/kg). To evaluate the neurotherapeutic feasibility of 4R for clinical trials, we have assessed the safety of this compound in nonhuman primates. We investigated whether 4R induces toxicity in male Macaca mulatta when administered for 11 consecutive days via intravenous injection at a dose of 1.4 mg/kg. Electroencephalogram, somatosensory evoked potential, and transcranial motor evoked potentials were measured at days 0, 4, 8, and 12 and remained unaffected during the experimental study. Spontaneous behavior was not affected between the groups. Small histopathological changes in the organs were observed in some animals, both treated and non-treated; thus, these changes cannot be attributed to 4R. Minor hematological and blood composition variations with no clinical significance were detected in the experimental animals. In conclusion, our data support previous findings that 4R is a non-toxic compound that proved safe in nonhuman primates during the given period and dose.

Environmental physical and chemical factors controlling the abundance and biodiversity of zooplankton in permafrost-affected lakes are poorly known yet they determine the response of the ecosystems to on-going climate change and water warming. Here we assessed the current status of zooplankton communities of lake ecosystems in the North-West of the Bolshezemelskaya tundra (Nenets Autonomous district), and provide new information about the composition and structure of zooplankton. Results demonstrate that the structure of zooplankton communities is influenced by morphometric features of lakes and the degree of their overgrowth by macrophytes. According to the level of zooplankton development, most tundra lakes were of the oligotrophic type with an average biomass of up to 1 g/m3. The largest number of species was observed in zooplankton communities of small lakes with an area of up to 0.02 km2 and overgrown with macrophytes. The analysis of factors that influence the formation of the lakes zoocenosis demonstrated that the species composition and quantitative characteristics of zooplankton are chiefly controlled by pH and water mineralization. A comparison of the results obtained with the literature data on the lakes of this region collected 60 years ago confirms that the ecosystems of the studied lakes are in a stable state. Overall, these new insights will improve our knowledge of factors controlling the zooplankton spatial dynamics in unique but quite abundant thermokarst lakes of NE European Tundra, subjected to on-going climate warming.

Hadhramout Initiative Against Corona (HIAC ) formed a working group of clinicians relevant to the management of COVID-19 to formulate clinical practice guidelines (CPG) for clinicians caring for the patients infected with COVID-19 in Yemen. The regional guidelines on the management of COVID-19 were thoroughly reviewed and its applicability was assessed for Yemen. HIAC’s recommendations covered (2) sections: the first one is the diagnosis, including case definition, risk stratification of the affected cases, investigations (prioritization of reverse transcription-polymerase chain reaction (RT-PCR) testing, D-dimer, chest x-ray, and chest computed tomography, while the second part covers the treatments (mainly Favipiravir, Remdesivir, Hydroxychloroquine, and Glucocorticoid, Anticoagulants, and Supportive measures). In conclusion, the adoption of cost-effective and evidence-based guidelines in Yemen will standardize the management of the patients infected with COVID-19 and protect both the patients and the health care workers from malpractice.

This study tested the association between FecXG point mutation located in exon 2 of BMP15 gene and the prolificacy of Dubasi, Shugor and Watish sheep ecotypes, under dryland farming, Sudan. Blood samples were randomly collected from unrelated 100 ewes (Dubasi; n= 30, Shugor: n= 30, and Watish: n= 40). Bone Morphogenetic protein (BMP15) gene was amplified using PCR-RFLP. Two genotypes were found in all studied breeds (heterozygous and wild type). The calculated total genotype frequencies of BB, Bb and bb genotypes were 0.31, 0.69 and 0.00, respectively, while allele frequencies were 0.66 for B and 0.34 for b. Litter size was influenced by the genotypes of BMP15 gene, parities and subtypes (p<0.05), highest for Watish and 4th parity. Alignment of BMP15 samples along with database reference sequence revealed that most sequence regions were identical except for one variable nucleotide at position 111 bp where a guanine (G) was replaced by adenine (A) in Watish and Shugor samples. All amino acids were the same at residue 275. Watish and Shugor breeds are more related. The study concluded that the presence of one copy of FecXG point mutation of BMP15 gene increased the litter size by 0.17 lambs in the studied ecotypes.

The vegan diet excludes animal-derived products consumption. The objective of the present study is to analyze dietary lipid intake, nine plasmatic fatty acids concentrations (from C14:0 [lauric acid] to C20:4 [arachidonic acid]), and conventional clinical lipid profile among vegan individuals with omnivore controls. A case-control and cross-sectional study was performed between 2016 and 2017. Vegans were paired in a 1:1 ratio with omnivores from Merida, Mexico. A 150-item Semi-Quantitative Food Frequency Questionnaire was conducted to evaluate eating patterns. Serum fatty acids were determined from total blood with a gas chromatography assay. Lower cholesterol, stearic, arachidonic and trans fatty acids intake, but higher consumption of lauric acid were observed in the vegan group (p= <0.001, 0.014, <0.001, 0.005, respectively). Decreased plasma concentrations of stearic, arachidonic and linoleic acids were found (p= 0.017, <0.001 and 0.026, respectively). Following a vegan diet for more than three years generate modifications in serum concentrations of saturated and polyunsaturated ω-6 fatty acids, which could lower inflammatory markers’ biosynthesis. Potential benefits regarding cardiovascular risk may be assumed in favor of vegan individuals.

Cardiac β₂-adrenergic receptors (ARs) are known to inhibit collagen production and fibrosis in cardiac fibroblasts and myocytes. The β₂AR is a Gs protein-coupled receptor (GPCR) and, upon its activation, stimulates generation of cyclic 3', 5'-adenosine monophosphate (cAMP). cAMP has two effectors: protein kinase A (PKA) and the exchange protein directly activated by cAMP (Epac). Epac1 has been shown to inhibit cardiac fibroblast activation and fibrosis. Osteopontin (OPN) is a ubiquitous pro-inflammatory cytokine, mediating also fibrosis in several tissues, including the heart. OPN underlies several cardiovascular pathologies, including atherosclerosis and cardiac adverse remodeling. We have found that the cardiotoxic hormone aldosterone transcriptionally upregulates OPN in H9c2 rat cardiac myoblasts, an effect prevented by endogenous β₂AR activation. Additionally, CRISPR-mediated OPN deletion enhances cAMP generation in response to both b₁AR and β₂AR activation in H9c2 cardiomyocytes, leading to upregulation of Epac1 protein levels. These effects render β₂AR stimulation capable of completely abrogating transforming growth factor (TGF)-β-dependent fibrosis in OPN-lacking H9c2 cardiomyocytes. Finally, OPN interacts constitutively with G_as subunits in H9c2 cardiac cells. Thus, we have uncovered a direct inhibitory role of OPN in cardiac β₂AR anti-fibrotic signaling via cAMP/Epac1. OPN blockade could be of value in the treatment and/or prevention of cardiac fibrosis.

In this study, we propose a scalable deep learning approach to automated phenotyping using UAV multispectral imagery, exemplified by yellow rust detection in winter wheat. We adopt a high granularity scoring method (1 to 9 scale) to align with international standards and plant breeders’ needs. Using a lower spatial resolution (60m flight height at 2.5cm GSD), we reduce the data volume by a factor of 3.4, making large-scale phenotyping faster and more cost-effective while obtaining results comparable to those of the state-of-the-art. Our model incorporates explainability components to optimise spectral bands and flight schedules, achieving top-3 accuracies of 0.87 for validation and 0.67 and 0.70 on two separate test sets. We demonstrate that a minimal set of bands (EVI, Red, and GNDVI) can achieve results comparable to more complex setups, highlighting the potential for cost-effective solutions. Additionally, we show that high performance can be maintained with fewer time steps, reducing operational complexity. Our interpretable model components improve performance through regularisation and provide actionable insights for agronomists and plant breeders. This scalable and explainable approach offers an efficient solution for yellow rust phenotyping and can be adapted for other phenotypes and species, with future work focusing on optimising the balance between spatial, spectral, and temporal resolutions.

The use of sustainable energy sources is a feasible alternative for fossil fuel products, which can represent a positive factor to alleviate many current environmental issues. In that sense, not only the sustainable industrial development is important, but also sustainable practices at local level, including households. Specifically, heating and cooking are one of the most important activities that require energy in households, where the role of biomass could be interesting, as it can provide an energy source with lower environmental impact. However, there is room for improvement in biomass stoves, whose adaptability to specific wastes, as well as their improvement in efficiency, should be accomplished. The aim of this work was to assess the improvement of combustion performance of a domestic stove by the implementation of a programmable logic converter for a better adaptation to different biomass samples (holm oak, pear tree, poplar and sugarcane bagasse pellets). Thus, the working regime of the stove was controlled, especially concerning the screw conveyor (to regulate pellet feeding) and flue gas fan (to change oxygen supply). As a result, better combustion performances were obtained, heat capacities from 5.66 to 8.67 kW for the selected samples. On the other hand, different improvements of the combustion stove to avoid blockages, for instance, are proposed as further steps.

(1) Background: Since microplastics in the aquatic environment are difficult to prevent and can cause adverse physiological and biochemical reactions to various organisms, we aimed to analyze the effectiveness of an eco-friendly removal method using aquatic plants with high ornamental value and excellent water purification ability. (2) Methods: Iris pseudacorus and Lythrum anceps were planted in tap water contaminated with microplastics to analyze the removal rate and root adsorption of microplastics. (3) Results: The amount of microplastics in the planting boxes of Iris pseudacorus and Lythrum anceps was significantly reduced, and the adsorption of microplastics on the roots was confirmed. (4) Conclusions: It was found that the removal of microplastics in water by aquatic plants is effective and that microplastic pollution does not significantly affect plant growth. However, the removal of microplastics by adsorption on plant roots may be affected by various environmental factors, so it is necessary to consider various limitations.

Based on the traditional Chinese cultural belief of "male breadwinner, female homemaker," as well as the systemic and interactive characteristics of families, this study aims to explore the influence of maternal gatekeeping behavior on the quality and quantity of paternal parenting, as well as adolescent aggressive behavior. A total of 483 seventh-grade students completed questionnaires on maternal gatekeeping behavior, paternal involvement, parenting styles and aggressive behavior. Latent profile analysis identified four parenting combinations: positive, negative, mixed, and neglectful. Adolescents under negative parenting exhibited the highest aggression, while those under positive and neglectful parenting showed the least aggression. Maternal gatekeeping behavior correlated with paternal negative parenting and adolescent aggression. Paternal negative parenting mediated the relationship between maternal gatekeeping and aggression, while paternal involvement moderated this relationship. These findings highlight the role of parental interaction in adolescent behavior and support family-based interventions.

Background: The study aimed to explore the association between the prognostic nutrition index (PNI) and in-hospital complication and mortality in patients with spontaneous intracerebral hemorrhage (ICH). Methods: We conducted a retrospective analysis using data from the Changhua Christian Hospital Clinical Research Database (CCHRD) between January 2015 and December 2022. 2402 patients were included, with the median PNI value set at 42.77. The restricted cubic spline model, Kaplan-Meier and ROC analysis for overall survival were used to evaluate the association of PNI with medical complications and mortality. Propensity score matching (PSM) analysis was performed to balance these clinical variables between groups, which could reduce potential bias to some extent. Results: PNI was significantly associated with in-hospital complications and 28-day and 90-day mortality in multivariate analysis. The main finding of our study is that a low PNI score at admission was independently associated with a poor ICH outcome. The Kaplan-Meier curves revealed higher survival rates in the high PNI group. PNI demonstrated sensitivity to predict medical complications and mortality based on ROC analysis. Conclusions Our study suggests that PNI could serve as a valuable marker for predicting medical complications and mortality in patients with spontaneous ICH.

The rapid expansion of flexible and wearable electronics has necessitated a focus on ensuring their safety and operational reliability. Gel Polymer Electrolytes (GPEs) have become preferred alternatives to traditional liquid electrolytes, offering enhanced safety features and adaptability to the design requirements of flexible lithium-ion batteries. This review provides a comprehensive and critical overview of recent advancements in GPEs technology, highlighting significant improvements in their physicochemical properties, which contribute to superior long-term cycling stability and high-rate capacity compared to traditional organic liquid electrolytes. Special attention is given to the development of smart GPEs endowed with advanced functionalities such as self-protection, thermotolerance, and self-healing properties, which further enhance battery safety and reliability. The review also critically examines the application of GPEs in high-energy cathode materials, including Lithium Nickel Cobalt Manganese (NCM), Lithium Nickel Cobalt Aluminum (NCA), and thermally stable Lithium Iron Phosphate (LiFePO4). Despite the advancements, several challenges in GPE development remain unresolved, such as improving ionic conductivity at low temperatures and ensuring mechanical integrity and interfacial compatibility. The review concludes by outlining future research directions and the remaining technical hurdles, providing valuable insights to guide ongoing and future efforts in the field of GPEs for lithium-ion batteries, with a particular emphasis on applications in high-energy and thermally stable cathodes.

Lean practice is recognised for having a great potential in promoting safety risk management in offsite construction (OSC). This paper presents results of a study conducted to assess the impact of lean practice in safety risk management in OSC in a developing country. A quantitative approach using survey-based questionnaire was adopted. Lean management practices (LMPs) identified from literature review were empirically tested using a sample survey of 103 OSC contractors. The survey responses were subjected to descriptive and inferential statistics. The top ranked LMPs for safety risk management in OSC included two mistake proofing practices, i.e., use of personal protective equipment (PPE) and use of hazard warning equipment; two last planner system (LPS) practices, i.e., involvement of workers in safety planning and providing necessary working equipment and one first run studies (FRS) practice, i.e., critical analysis of work methods. These LMPs are useful in controlling high consequence safety risks in OSC. Based on evidence found in this study, the paper argues that lean practice can bring great value in the safety risk management in OSC in countries where OSC is transitioning.

Correct diagnosis and early treatment of respiratory diseases can significantly improve the health status of patients, reduce healthcare expences, and enhance quality of life. Therefore, there has been extensive interest in developing automatic respiratory disease detection systems. Most of these methods have recently been using machine and deep learning algorithms. The success of machine learning methods depends heavily on the selection of proper features to be used in the classifier. Although metaheuristic-based feature selection methods have been successful in addressing difficulties presented by high-dimensional medical data in various biomedical classification tasks, there is not much research on the utilization of metaheuristic methods in respiratory disease classification. This paper aims to conduct a detailed and comparative analysis of six widely used metaheuristic optimization methods using eight different transfer functions in respiratory disease classification. For this purpose, two different classification cases were examined: binary and multi-class. The findings demonstrate that metaheuristic algorithms using correct transfer functions could effectively reduce data dimensionality while enhancing classification accuracy.

Although metastasis-associated protein 1 (MTA1) is known to play a role in cancer invasion and metastasis of various cancers, the clinical significance of its expression in canine urothelial carcinoma (UC) has not been explored. We sought to evaluate the expression of MTA1, cyclooxygenase 2 (COX2) and E-cadherin (E-cad) in association with clinicopathological parameters in clinical samples of canine UC. Here, we show that MTA1 and COX2 are overexpressed in canine UC samples compared to normal canine bladder samples, whereas E-cad levels are higher in normal bladder. The results demonstrated that MTA1 expression correlated with aggressive clinicopathological features such as high tumor-grade, muscular/vascular invasion, and metastasis. The expression of MTA1 differed in tumors depending on their localization, with the highest being in the urethra adjoining the prostate. Unexpectedly, higher E-cad levels were detected in metastatic tumor cells compared to primary tumor cells. Overall, these findings suggest that MTA1 may represent a key upstream effector tightly associated with COX2 and E-cad-mediated events in canine UC. Accordingly, MTA1 may be considered a feasible interceptive and therapeutic target for canine UC treatment.

The popularity of handheld devices for point-of-care ultrasound (POCUS) has increased in recent years due to their portability and cost-effectiveness. However, POCUS has the drawback of lower imaging quality compared to conventional ultrasound, because of hardware limitations. Improving the quality of POCUS through post-image processing would therefore be beneficial, with deep learning approaches showing promise in this regard. This review investigates the state-of-the-art progress of image enhancement using deep learning suitable for POCUS applications. A systematic search was conducted from January 2024 to February 2024 on PubMed and Scopus. From the 457 articles that were found, the full text was retrieved for 69 articles. From this selection, 15 articles were identified addressing multiple quality enhancement aspects. A disparity in the baseline performance of the low-quality input images was seen across these studies, ranging between 8.65–29.24 dB for the Peak Signal-to-Noise Ratio (PSNR) and 0.03-0.71 for the Structural Similarity Index Measure (SSIM). In six studies, where both PSNR and the SSIM metrics were reported for the baseline and the generated images a mean difference of 6.60 (SD ± 2.99) and 0.28 (SD ± 0.15) was observed for the PSNR and SSIM, respectively. The reported performances demonstrate the potential of deep-learning-based image enhancement for POCUS. However, variability in the extent of performance gain across datasets and articles was notable, and the heterogeneity across articles makes quantifying the exact improvements challenging.

Ondol, a heating system unique to Korean homes, raises indoor temperatures by supplying hot water through pipes embedded in the floor slab. Known for its comfort and sustained heat advantages, Ondol has garnered international interest in countries requiring efficient heating solutions. Given the inherent challenges during installation and operation, timely inspection is crucial due to difficulties in detecting and pinpointing defects in the buried concrete pipes, often leading to costly rework and removal. Yet, specialized inspection systems tailored for Ondol pipes remain underexplored. Therefore, this study proposes a robotic inspection system capable of assessing the condition of Ondol pipelines. We analyzed the characteristics of Ondol piping to establish the system requirements and developed a prototype of a compact capsule-shaped inspection robot tailored for Ondol pipe inspection. Subsequent laboratory testing validated its performance and usability, confirming its capability for field application through tests on curvature maneuverability and image reception quality. This research aims to motivate advancements in Ondol-specific system implementation and performance validation, potentially contributing to the smartification of Ondol maintenance practices.

Urbanization-led economic growth has created cities to drive infrastructure investments and population accumulation and exploit natural resources at an extreme phase. While coastal cities become vulnerable to climate change-induced extreme weather events and human-made disasters in recent history, effective measures to improve the resilience of cities are pivotal to developing sustainable living environments. This study proposes a framework to assess urban resilience to natural disasters (floods) using bottom-up spatial interactions among natural, physical, and social systems within cities and regions. It is noted that studies focus on either the vulnerability or coping capacity of urban communities to assess resilience, where effective strategies to manage disaster risk demand adaptation and mitigation measures at a spatial scale. Quantified resilience at small spatial units assists urban planning and disaster management agencies in the timely allocation of resources to optimize the recovery process. Moreover, spatial planning agencies can adopt resilience mapping to identify the potential growth zones while minimizing the natural disaster risks in urban growth management. Urban resilience can be embodied in spatial strategies with the operational framework proposed here, and future urban growth scenarios can be tested in multiple disaster conditions.

In the realm of agribusiness, transformative shifts are underway, propelled by the growing demands and expanding scales of grain production. This evolution calls for a critical reevaluation of the existing paradigms in coffee production and marketing paradigms, with a specific focus on integrating Artificial Intelligence (AI). This work aims to review, synthesize, and summarize the available data regarding how Machine Learning (ML) has been used to detect and classify characteristics in coffee beans and leaves. For this purpose, a comprehensive literature review of the most significant research contributions describing the application of AI for advanced classification techniques in coffee agriculture has been carried out. Our analysis suggests that implementing AI technologies allows the classification of coffee, encompassing various attributes such as maturity, roast intensity, disease identification, flavor profiles, and overall quality. More largely, this technological advancement holds the potential to revolutionize coffee farming by providing producers and agricultural specialists with sophisticated tools to enhance production efficiency, minimize costs, and improve the accuracy and confidence of their decision-making processes.

The aim of the study was to develop casein-fucoidan composite nanostructures through the method of polyelectrolyte complexation and subsequent spray drying. To determine the optimal parameters for the preparation of the composite structures and to investigate the influence of the production and technological parameters on the main structural and morphological characteristics of the obtained structures, 3(k-p) fractional factorial design was applied. The independent variables (casein to fucoidan ration, glutaraldehyde concentration and spray intensity) were varied at three levels (low, medium, and high) and their effect on the yield, the average particle size and the zeta potential were evaluated statistically. Based on the obtained results, models C1F1G1Sp.30, C1F1G2Sp.40, and C1F1G3Sp.50, which have an average particle size ranging from (265 ± 32) nm to (357 ± 25) nm, production yield in the range (48.9 ± 2.9) % to (66.4 ± 2.2) % and zeta potential varying from ( −20.12 ± 0.9) mV to (−25.71 ± 1.0) mV were selected as optimal for further use as drug delivery systems.

Federated learning (FL) has emerged as a crucial technology in today’s data-centric technological environment, enabling decentralized machine learning and safeguarding user privacy. This study introduces “Federated Operations (FedOps) Mobile,” a novel FL framework optimized for the dynamic and heterogeneous ecosystem of mobile devices. FedOps Mobile enhances traditional FL approaches for mobile devices by integrating real-time operational control and advanced on-device training capabilities using TensorFlow Lite and CoreML, addressing critical challenges in scalability, efficiency, and system heterogeneity. Our approach utilizes a wide range of devices, facilitated by intelligent client-selection mechanisms. This mechanism evaluates the capabilities and readiness of multiple devices per client to ensure fair and efficient network participation. The framework also utilizes remote device control for seamless task management and sustained engagement, enabling continuous learning without compromising the user experience. We conducted extensive experiments to validate the framework’s performance, focusing on three core aspects: operational efficiency, model personalization, and resource optimization in multi-device environments. The results demonstrate that the proposed method is effective for efficient client selection, energy consumption, and model optimization.

Boost-derived converters are most popular in Power Factor Correction AC-DC conversion applications and alternative energy generation systems. The proper operation of such converters relies on housekeeping power supplies providing auxiliary power for their control circuitry. The purpose of this study is to present a design-oriented analysis of a simple, passive, isolated, self-bias circuit that can provide a stabilized voltage for the control circuits of boost-derived converters. The circuit’s output voltage inherently follows the main regulated output and therefore, does not require an additional active control. The paper presents a detailed analysis of the circuit and offers design guidelines. Following the presentation of the basic idea several variations of the circuit, that can be used in special applications, are presented. The feasibility of the proposed bias circuits was verified by simulation and experiment on a laboratory prototype.

This work is aimed at investigating the capabilities and limits of the mid-fidelity numerical solver DUST for the evaluation of wind turbines aerodynamic performance. In particular, this study was conducted by analysing the benchmarks NREL- 5MW and Phase VI wind turbines, widely investigated in literature by from experimental and numerical activities. The work started by simulating simpler configuration of the NREL- 5MW turbine to progressively integrate complexities such as shaft tilt, cone effects and yawed inflow conditions, offering a detailed portrayal of their collective impact on turbine performance. A particular focus was then given to the evaluation of aerodynamic responses from the tower and nacelle, as well as aerodynamic behavior in yawed inflow condition, crucial for optimizing farm layouts. In the second phase, the work was focused on NREL Phase VI turbine due to the availability of experimental data on this benchmark case. Comparison of DUST simulations results with both experimental data and high-fidelity CFD tools shows the robustness and adaptability of this mid-fidelity solver for this applications, thus opening a new scenario for the use of such mid-fidelity tools for the preliminary design of novel wind turbines configurations or complex environments as wind farms, characterised by robust interactional aerodynamics.

In recent times, there has been significant enthusiasm for the development of all solid state batteries. This interest stems from a dual focus on safety—addressing concerns related to toxic and flammable organic liquid electrolytes—and the pursuit of high energy density. \cite{SCHNELL2018160,Zheng2018}. While liquid electrolyte batteries constitute for now the vast majority of commercial cells, solid electrolyte batteries show great promise. In parallel with experimental research, computational models \cite{GrazioliEtAlCM2016} clarify the several fundamental physics \cite{LiMonroeARCBM2020} that take place throughout battery operations. We review some classical models, emphasizing the conceptual advancements documented in the most recent works.

The two-parameter distribution introduced by Kumaraswamy (1980) is a very flexible alternative to the Beta distribution with the same (0,1) support. Originally proposed in the field of hydrology, it has subsequently received a good deal of positive attention in both the theoretical and applied statistics literatures. Interestingly, the problem of testing formally for the appropriateness of the Kumaraswamy distribution appears to have received little or no attention to date. To fill this gap, in this paper we apply the “biased transformation” methodology proposed by Raschke (2009) to several standard goodness-of-fit tests based on the empirical distribution function. A simulation study reveals that these (modified) tests perform well in the context of the Kumaraswamy distribution, in terms of both low size distortion, and respectable power. In particular, the “biased transformation” Anderson-Darling test dominates the other tests that are considered.

In this paper, we introduce a compressible formulation for dealing with 2D/3D compressible interfacial flows. The formulation is combined with an original monolithic solver, according to which a strong velocity-pressure coupling is achieved. The results show that the scheme can ensure accuracy and stability for various fluid flow scenarios: from the standard incompressible conditions to compressible flows, spanning both single-phase and two-phase flows.

Unmanned agricultural tractor (UAT) represents the advanced stage of autonomous navigation and serves as a core technology in agricultural production. It reduces the operator’s workload, and improves operational accuracy and efficiency. This article reviews three aspects of key autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages, and shortages of these key technologies on UATs are clarified by analyzing technical principles and the current research status. We conducted summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of key autonomous navigation technologies on UATs, it can be seen that fruitful research progresses have been achieved. The review also summarizes the common problems in current technologies. The application research on sharing and integrating multi-source data for autonomous navigation are relatively weak. There is an urgent need of high-precision, and high-stability sensing equipment. The universality of path planning methods, and the efficiency and precision of path tracking need to be improved. It is necessary to develop high reliability electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in seafood was performed, with the objective of appraising the effectiveness of the control strategies placed along the food chain. Whereas all the 13 QRA models retrieved were of short scope, covering at most from end of processing to consumption; the majority (85%) focused on smoked or gravad fish. Since the modelled pathways commenced with the packaged product, none of the QRA models addressed cross-contamination events. Many models agreed on the fact that keeping the product’s temperature at 4.0-4.5 ºC leads to greater reductions in the final risk of listeriosis than reducing the shelf life by one week; and that the effectiveness of both measures can be surpassed by reducing the initial occurrence of L. monocytogenes in the product (at the end of processing). It is therefore necessary that future QRA models for RTE seafood contains a processing module that can provide insight into intervention strategies that can retard L. monocytogenes growth, such as the use of bacteriocins, ad-hoc starter cultures and/or organic acids, and other strategies seeking to reduce cross-contamination at the facilities, such as stringent controls for sanitation procedures. Since risk estimates were shown to be moderately driven by growth kinetic parameters, namely, the exponential growth rate, the minimum temperature for growth, and the maximum population density, further work is needed to reduce uncertainties about them.

In this review paper, we discuss the use of BERT, one of the most well-liked deep learning-based language models. The model's operation mechanism, key areas of applicability to text analytics tasks, comparisons with related models for each activity, and a description of certain proprietary models are all covered in this work. The data from several dozen original scientific studies that have been published in the last few years and have garnered the greatest interest from the scientific community were systematized in order to prepare this review. All researchers and students who wish to learn about the most recent developments in the field of natural language text analysis may find this survey helpful. Bidirectional Encoder Representations from Transformers, or BERT for short, is the subject of a thorough investigation that we present. The area of natural language processing holds significant importance in the creation of intelligent systems. To do a variety of activities, one must comprehend the sentence's correct meaning in order to produce the desired result. Computers have a hard time understanding languages because of how context constantly changes. The main challenge in natural language processing tasks is getting computers to understand text context, and BERT is seen as a revolution in this regard. It picks up the language and its meaning in a manner that is quite similar to how the human brain processes meaning from sentences. Its capacity to identify a word from both the left and right contexts of a sentence makes it special. A new era in the perception and comprehension of natural languages has been ushered in with the development of BERT, which could help computers understand natural languages more fully. This study aims to provide readers with a deeper knowledge of the BERT language model and how it is applied to different NLP tasks.

The COVID-19 pandemic has led to a substantial revolution in the incorporation of digital solutions in healthcare. This systematic review investigates the enduring physical and psychological consequences individuals experience up to two years post-recovery. Additionally, it focuses on examining the influence of mHealth interventions on these effects. Significantly, 41.7% of survivors experience lingering symptoms that have not been addressed, while 14.1% encounter difficulties in returning to work. The presence of anxiety, compromised respiratory functioning, and persistent symptoms highlight the immediate requirement for specific therapies. Telehealth, particularly telerehabilitation, presents itself as a possible way to address these difficulties. The study thoroughly examines 10 studies encompassing 749 COVID-19 patients, investigating the efficacy of telerehabilitation therapies in addressing various health markers. Telerehabilitation-based breathing exercises yield substantial enhancements in functional performance, dyspnea, and overall well-being. The results emphasize the potential of telerehabilitation to have a favorable effect on patient outcomes, however more research is needed to strengthen the existing evidence basis as one of the most important limitation is the limited number of trials and the evaluation of varied therapies. The analysis highlights the significance of digital solutions in post-COVID care and calls for ongoing research to improve comprehension and implementation of telehealth interventions in a swiftly changing healthcare environment.

Prospecting for a future breeding site is an essential component of informed dispersal. It allows individuals to reduce the uncertainty of their environment by gathering personal and social information about the local quality of alternative breeding areas, and to make informed emigration and settlement decisions. Although this process has been studied in territorial and social animal species for decades, it is still not well-understood and spatial patterns of prospecting movements are hard to generalize over taxa or even species due to substantial intra and inter-specific variability. Using 124 empirical studies which have explicitly described prospecting in a context of breeding habitat selection in birds, mammals, fish and invertebrates, I review why, how, when and which individuals prospect depending on their life history traits and sociality. From this synthesis, I identify persisting knowledge gaps which explain why prospecting is still understudied and sometimes overlooked. I finally propose key objectives and research directions, to shed light on prospecting movements and their consequences on informed dispersal strategies, individual fitness and population dynamics, both empirically and theoretically. A better understanding of the mechanisms underlying prospecting, their causes and their consequences will fully reveal how prospecting could constitute a powerful adaptive response to environmental changes for many social and territorial species which will help them persist on the long-term. It will also significantly enhance our ability to predict species responses to environmental changes and thus, inform more effective management plans for threatened species

The paper describes and analyzes the performance of a new thermoelectric generation system based on the use of Peltier cells inserted in the ducts of the air conditioning equipment. The hot and cold air streams that flow in the two separated sections of an air conditioning system are used to create a thermal gradient between the two faces of the Peltier cells. Hot and cold air flow inside the A/C unit are driven to a built in thermal chamber where the Peltier cells are placed. Peltier cells are incrusted into an insulation wall that separates the two sections of the chamber through which hot and cold air streams are flowing. The so designed configuration allows the Peltier cells to generate electric current. The study has been run for constant cold air temperature and variable hot air temperature, resulting in a variable performance of the thermoelectric generator. Theoretical study has been completed with experimental tests to determine real performance of the thermoelectric unit. Efficiency of the thermoelectric generator has been found to be linearly dependent on the temperature difference between hot and cold air subsections of the chamber. Maximum efficiency, however, is limited by the hot air stream temperature, since in real conditions ambient temperature cannot overpasses a specific value. For standard operational conditions, 5º C and 45º C for the cold and hot air streams, the thermoelectric generator operates at 44% of the maximum efficiency attainable.

The silane (3-Aminopropyl)triethoxysilane (APTES), possesses one terminal amine group and three ethoxy groups extending from each silicon atom, serving as a crucial interface adherent between organic and inorganic materials. In corrosion prevention, APTES is frequently employed as a primer, with subsequent topcoat as an extra protective layer. This topcoat is particularly useful in covering sites where APTES may exhibit poor bonding, such as those involving Cu or Cu-rich alloying elements. In our study, we applied a thin layer of APTES to cleaned AA2024-T3 samples using concentrated vapor deposition, followed by spin-coating with a diluted PS/acetone solution. Through combinatorial experimentation, we investigated the impact of APTES on the corrosion resistance of the coating system on AA2024-T3. Our findings indicate that a higher surface energy of the APTES primer contributes to better corrosion resistance in the overall coating system. This improvement can be attributed to enhanced wettability achieved by the PS/acetone solution on the cured APTES primer, leading to a more uniform coverage of the dried PS topcoat. Additionally, our research revealed that, in the early stages of exposure to the corrosion solution, a thinner APTES primer enhances protection against corrosion. This effect is attributed to hydrolytic stability mechanisms, and the interactions between hydrolyzation/condensation in soaked APTES and the dissolution of naturally formed aluminum oxide pre-existing in the bare samples. Finally, we observed that an APTES primer subjected to additional heat treatment before topcoating exhibits superior performance in corrosion resistance.