Mental disorders impact a significant portion of the global population, presenting substantial challenges to healthcare systems due to high hospitalization costs and resource demands. This narrative review explores the economic implications of mental health disorders, focusing on hospitalization costs, the effectiveness of interventions, and the outcomes of recent research. Materials and Methods: A narrative review was conducted, sourcing articles from PubMed and Google Scholar published between 2014 and 2024. The search terms included combinations related to mental illness, costs, hospital care, and mental healthcare interventions. A total of 1,110 articles were initially identified, with 37 studies meeting the inclusion criteria after rigorous screening by two independent researchers. These studies included quantitative and qualitative data covering a range of outcomes such as hospital admission rates, consumer satisfaction, and quality of life. The findings of the present review reveal that mental disorders significantly increase hospitalization costs due to frequent admissions, extended stays, and the need for specialized treatments. Additionally, physical comorbidities in individuals with mental disorders lead to higher healthcare costs and resource use. Integrated care models, early intervention, and preventive strategies show promise in reducing these costs and improving patient outcomes. Conclusions: Our review emphasizes the critical need for integrated healthcare strategies that address both mental and physical health to reduce hospitalization costs and improve outcomes. Effective management of mental health disorders requires comprehensive approaches, including complex outpatient services and preventive care. Future research should focus on standardizing methodologies to provide clearer insights into the economic impact of mental health conditions and guide effective healthcare strategies.

In the context of evolving perceptions of sexuality, particularly within the realm of health and disability, this study investigates the impact of multiple sclerosis (MS) on female sexual function and quality of life. A quantitative study involving 130 female MS patients aged 35 to 50 was conducted, employing measures such as The Female Sexual Function Index (FSFI), The Multiple Sclerosis Intimacy and Sexuality Questionnaire-19 (MSISQ-19), and The Fatigue Severity Scale (FSS). Results indicate a significant association between greater sexual dysfunction and poorer quality of sex life, alongside the correlation of increased fatigue with diminished sexual satisfaction. Factors such as education level, time of diagnosis, and treatment regimen also influenced outcomes. Findings underscore the importance of supportive interventions, including counseling, to enhance the quality of sex life for women with disabilities, particularly those with MS.

We here report the purification of a novel member of the galectin family, the β-Galactoside-binding lectin hRTL, from the marine sponge Chondrilla australiensis. The hRTL lectin is a tetrameric proto-type galectin with a subunit molecular weight of 15.5 kDa, consisting of 141 amino acids and sharing 92% primary sequence identity with the galectin CCL from the congeneric species C. caribensis. Transcriptome analysis allowed the identification of additional sequences belonging to the same family, bringing the total number of hRTLs to six. Unlike most other galectins, hRTLs display a 23 amino acids long signal peptide that, according to Erdman degradation, is post-translationally cleaved, leaving a N-terminal end devoid of acetylated modifications, unlike most other galectins. Moreover, two hRTLs display an internal insertion, which determines the presence of an unusual loop region that may have important functional implications. The characterization of the glycan binding properties of hRTL revealed that it had high affinity to-wards TF-antigen, sialyl TF, and type-1 N-acetyl lactosamine with a Galβ1-3 structure. When administered to DLD-1 cells, a colorectal carcinoma cell line expressing mucin-associated TF-antigen, hRTL could induce glycan-dependent cell death by activating MAP kinases, thereby inhibiting cancer cell proliferation.

Introduction Meningioma is the second most common primary intracranial tumor of the central nervous system. in Sudan, meningioma is the most common primary brain tumor, among Sudanese patients, Surgical total excision of meningioma offers a better survival, however, Chemotherapy has largely been unsuccessful for meningioma treatment, and therefore, refractory and recurrence meningioma treated with palliative surgery and radiotherapy. Monosomy of chromosome 22 is the utmost common genetic alteration among meningioma and many genes were investigated and described in the development of this tumor of which , NF2 hSNF5/INI1gene, P53. In addition to this, Molecular signal pathways in meningioma, and that contribute to the survival, proliferation, self-renewal, and differentiation properties of normal stem cells which are abnormally activated and nominated as cancerous stem cell (CSCs). Objectives 1/ To identify the possible pathway of candidate genes in both setting and whole genes hypothesis free approach 2/ To assess the presence of mutations in candidate genes among histological subtypes of meningioma in Sudan. Material and methods This is a prospective cross-sectional study done at the National Center of Neurological Sciences (NCNS) Khartoum, from 2018 to 2021. The study included all cerebral tumors that were radio- logically diagnosed preoperatively as meningioma. Ethical approval was taken from Institute of Endemic disease, Khartoum University, and written consent was obtained Three DNA extracts were randomly selected from 20 meningioma tissue samples and processed for WES. All genes harboring exonic and splice site variations stratified into SNVs and INDELs sets were prepared. The 1000G online database was used to explore novel mutations per 3 samples. SIFT and PolyPhen-2 programs were used to predict possible impact of amino acids substitution. To address meticulous genes interaction and particular centrality, all shared genes within the class INDEL and SNVs were used as input on Network Analysis to predict protein- protein interaction and functional gene ontology. Finally, shared mutations within genes of centrality were detected via Sanger sequencing and mutations were correlated between histological sub-types and recurrenceThree non meningioma brain tumor used as control. Results WES analysis revealed high number for mutational signature within 2 classes (INDEL and SNVs) per 3 samples, the findings of 1000 genome online database showed number of novel mutations; 5618 in fibrous , 6032 in meningothelial while in recurrent fibrous sample 5930. Network analysis of shared genes per each class (INDEL, SNVs), showed UBC is the most protein of remarkable degree centrality over thousand of genes. Whereas, all shared genes per 3 samples within the 2 classes (INDEL and SNVs) revealed Akt1 with the highest degree of centrality and betweenness. Akt1 rs17846829was detected in 20% of the samples, while CD44 stemness gene revealed mutation A>G (rs9666607) in all meningioma samples (100%), this mutation was associated with 60% of the recurrence. Conclusions Nevertheless, the present study, highlight how such complex molecular processes might contribute to tumorogenesis, in attempt to shed light over thousands of genes and multifaceted network analysis rather than a solitary gene which is challenging question.

Background: Excessive sun exposure is a significant risk factor for various skin conditions, including sunburn, premature aging, and skin cancer. This study aims to assess the awareness, attitudes, and practices regarding sun exposure and sunscreen use among college students in Saudi Arabia. Methodology: A cross-sectional study was conducted with 388 college students from various disciplines. Data were collected using a structured questionnaire covering demographic information, knowledge, and practices related to sun exposure and sunscreen use. Descriptive statistics, chi-square tests, and multivariate logistic regression analysis were employed to analyze the data. Results: The study comprised 53.9% females, with the majority aged 18-23 years. Formal education on sun exposure dangers was lacking for 43.0% of participants. The most recognized consequences of excessive sun exposure were sunburn (80.6%) and skin cancer (74.4%). Intermediate knowledge of sun exposure effects was most common (40.7%). Sunscreen use was inconsistent, with 27.3% never using it during peak sunlight hours. Factors influencing sunscreen use included weather conditions and healthcare provider recommendations. Males were significantly less likely to use sunscreen. First-year students and participants without formal education on sun exposure were less likely to use sunscreen regularly. Conclusion: Despite awareness of the risks associated with excessive sun exposure, sunscreen use among college students in Saudi Arabia is inconsistent and influenced by various factors, including gender and education level. These findings highlight the need for enhanced educational initiatives to promote regular sunscreen use and other sun protection behaviors to mitigate the risk of skin conditions associated with sun exposure.

A temperature-modulated pyroelectricity measurement system for a small single crystal is developed and applied to standard sample measurements performed on a thin single crystal of lithium niobate. The modulation measurement is based on the AC technique, in which the temperature of the sample is periodically oscillated, and the synchronized pyroelectric signal is extracted using a lock-in amplifier. Temperature modulation is applied by irradiating periodic light on the sample placed in the heat exchange gas. To apply this technique to the transparent reference sample, a commercially available black resin is coated on the sample’s surface to absorb the light energy and transmits it to the specimen. The experimental results are analyzed using a two-layer heat transfer model to verify the effect of the light-absorbing layer as well as the non-contact temperature modulation system.

CO2 geological sequestration in coal seams can achieve the dual objectives of CO2 emission reduction and enhanced coalbed methane production, making it a highly promising carbon capture and storage technology. However, the injection of CO2 into coal reservoirs in the form of supercritical fluid (ScCO2) leads to complex physicochemical reactions with the coal seam, altering the properties of the coal reservoir and impacting the effectiveness of CO2 sequestration and methane production enhancement.In this paper, theoretical calculations based on ReaxFF-MD were conducted to study the interaction mechanism between ScCO2 and the macromolecular structure of both low-rank and high-rank coal, to address the limitations of experimental methods. The reaction of ScCO2 with low-rank coal and high-rank coal exhibits significant differences. At swelling stage, the low-rank coal experiences a decrease in aromatic structure and aliphatic structure, high-rank coal shows an increase in aromatic structure and a decrease in aliphatic structure, while swelling phenomenon is more pronounced in high-rank coal. At dissolution stage, low-rank coal is initially decomposed into two secondary molecular fragments, and then recombine to form new molecular structure, the aromatic structure increased and the aliphatic structure decreased. In contrast, high-rank coal occurs stretches-breakage-movement-reconnection, a reduction in aromatic structure and an increase in aliphatic structure.The primary reasons for these variations lie in distinct molecular structure compositions and the properties of ScCO2, leading to different reaction pathways of functional group and aromatic structure. The reaction pathways of functional groups and aromatic structures in coal can be summarized as follows: the breakage of the O-H bond in hydroxyl groups, the breakage of the C-OH bond in carboxyl groups, transformation of aliphatic structures into smaller hydrocarbon compounds or formation of long-chain alkenes, and various pathways involving broken, rearrangement, recombination of aromatic structures. In low-rank coal, there is a higher abundance of oxygen-containing functional groups and aliphatic structures. The breakage of O-H and C-OH chemical bonds results in the formation of free radical ions, while some aliphatic structures detach to produce hydrocarbons. Additionally, some of these aliphatic structures combine with carbonyl groups and free radical ions to generate new aromatic structures. Conversely, in high-rank coal, the lower content of oxygen-containing functional groups and aliphatic structures, along with stronger intramolecular forces, results in fewer chemical bond breakages and makes it less conducive to the formation of new aromatic structures.These results elucidate the specific deformations of different chemical groups, offering a molecular-level understanding of the interaction between CO2 and coal.

Keywords: AI Readiness Assessment; Business Processes; and Data Infrastructure.

Due to their independent structure, piping, and access, townhouses offer great flexibility in floor plan changes and high spatial autonomy, making them the mainstream housing type in Taiwan. This study focuses on row houses and examines 2022 completion cases in Kaohsiung City. It collects floor plans from 14 newly constructed buildings, totaling 227 units, and analyzes spatial dimensions including facade width, depth, habitable room, staircases, bathrooms, and total floor area for each case. The objective of this study is to examine the spatial layout of row houses in Kaohsiung City, with the aim of providing reference for future planning and design of such structures. The study resulted showed that 81.8% of the row houses analyzed have a total floor area per unit ranging from 136 to 192 m², a facade width between 4.1 and 6.38 meters, and a building depth from 7.67 to 12.68 meters. In addition, low negative correlation between facade width and total floor area, a high positive correlation between building depth and total floor area, and a moderate negative correlation between facade width and building depth. The spatial distribution within these houses includes 78% allocated to habitable room, 13.1% to staircases, and 8.7% to bathrooms. The total area of habitable room and bathrooms increases with the total floor area of the building. However, the total area of staircases remains almost constant as the area of habitable room increases. Furthermore, the most common location for staircase planning is the rear-right (RB) position, while the least common is the rear-left (LB) position. Among various staircase types, the C-shaped staircase has the largest average area per floor and the highest average proportion. Conversely, the I-shaped staircase has the smallest average area and the lowest average proportion. The U-shaped staircase is the most frequently planned, whereas the C-shaped staircase is the least frequently used.

Esophageal cancer (EC) is one of the most common malignant tumors worldwide, and its two major types, esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) present a severe global public health problem with an increasing incidence and mortality. Established risk factors include smoking, alcohol consumption, and dietary habits, but recent research highlights the substantial role of oral microbiota in EC pathogenesis. This review explores the intricate relationship between microbiome and esophageal carcinogenesis, focusing on eight significant mechanisms: chronic inflammation, microbial dysbiosis, production of carcinogenic metabolites, direct interaction with epithelial cells, epigenetic modifications, interaction with gastroesophageal reflux disease (GERD), metabolic changes, and angiogenesis. Certain harmful bacteria, such as Porphyromonas gingivalis and Fusobacterium nucleatum, are specifically implicated in sustaining irritation and tumor progression through pathways including NF-κB and NLRP3 inflammasome. Additionally, the review explores how microbial byproducts, including short-chain fatty acids (SCFAs) and reactive oxygen species (ROS), contribute to DNA harm and disease advancement. Furthermore, the impact of reflux on microbiota composition and its role in esophageal carcinogenesis is evaluated. By combining epidemiological data with mechanistic understanding, this review underscores the potential to target microbiota-immune system interplay for novel therapeutic and diagnostic strategies to prevent and treat esophageal cancer.

Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are significant lightweight metal matrix composites extensively utilized in precision instruments and aerospace sectors. Nevertheless, the inclusion of rigid SiC particles exacerbates tool wear in mechanical machining, resulting in a decline in the quality of surface finish. This work undertakes a comprehensive investigation into the problem of tool wear in SiCp/Al composite materials throughout the machining process. Initially, a comprehensive investigation was conducted to analyze the effects of cutting velocity vc, feed per tooth fz, milling depth ap, and milling width ae on tool wear during high-speed milling under SCCO2-MQL (Supercritical Carbon Dioxide Minimum Quantity Lubrication) ultrasonic vibration conditions. Furthermore, a prediction model for tool wear was developed by employing the orthogonal test method and multiple linear regression. The model's relevance and accuracy were confirmed using F-tests and t-tests. Ultimately, through the utilization of a genetic algorithm, the milling parameters were optimized, resulting in the identification of the most optimal combination of parameters. Empirical findings suggest that the careful selection of milling parameters can significantly mitigate tool wear, extend the lifespan of the tool, and enhance the quality of the surface. This work serves as a significant point of reference for the processing of SiCp/Al composite materials.

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC. Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included. Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib. Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population

Smart City has emerged as the mainstream paradigm for urban governance innovation, sustainable development, and strategy upgrades, which is drawing attention from scholars worldwide. However, current frameworks for Smart City assessment remain incomplete and simplistic. In is paper, 30 national or provincial capitals in China were selected and we designed a tri-dimensional SPI model—Social, Physical, and Information Space—for smart city spatial development assessment. Utilizing methods such as entropy weighting, coupled coordination degree models, and the Dagum Gini coefficient, this study assesses the spatial development and coupled coordination of 30 cities from 2011 to 2019. Finally, by means of BP neural networks, the study examines the contribution of each indicator to the spatial coupled coordination. The results indicated that with a narrowing disparity in development speeds among different regions, the spatial coupled coordination development level of smart capitals in China has steadily increased, presenting a pattern of staggered distribution. Moreover, the IS subsystem plays the most significant role in coupled coordination. The significance of this research lies in its tri-dimensional spatial perspective of the spatial development and coupled coordination differences of the Smart City, providing evidence-based support for the regional layout and optimization in China.

Grain quality, cooking quality and nutritional quality traits are some of the major attributes that enhance uptake and utilisation of improved cowpea varieties. Therefore, there is need for a better understanding of the genetic variation and inter-relationships among these quality traits in cowpea to integrate them in cowpea breeding programs. The study was conducted to determine genetic variability among 306 cowpea genotypes for grain quality, cooking quality and nutritional quality traits and to understand the interrelationships among these traits for exploitation in breeding programs. The results showed highly significant differences (P

Despite extensive research on autism in children, much less attention has been given to the transition into adulthood. This study aims to address this gap by examining the dietary behaviors of young adults with autism during this critical transition period, highlighting the role of diet in enhancing their readiness for adulthood. Forty-seven participants (mean age 21.0 ± 1.1 years), both male and female, were involved in this study. Participants had various comorbidities, such as mood disorders, attention-deficit/hyperactivity disorder, depression, and anxiety disorders, for which they required medication. Dietary behavior was assessed using the Starting the Conversation: Diet survey, while transition readiness was measured with the Transition Readiness Sur-vey. T-test and regression analysis were utilized to evaluate the data. The results indicated that participants did not follow healthy eating habits, as reflected by the dietary scores (1.08 ± 0.07), and were not adequately prepared for adulthood, as shown by the transition readiness scores (3.19 ± 1.10). A statistically significant and negative correlation was found between dietary pat-terns and transition readiness (r = -0.51, p < 0.001), indicating an adverse relationship: transition readiness ratings decline as diet scores rise. Linear regression analysis revealed that dietary habits accounted for 26.20% of the variation in transition readiness, with the confidence interval for the coefficient of dietary habits being -2.89 to -0.95 (p = 0.002). The negative significant correlation between dietary scores and transition readiness scores shows that diet behavior significantly influences participants’ assessed readiness for transition.

Background: This study aimed to investigate the impact of the COVID-19 pandemic on breast reconstruction trends in the United States, focusing on implant-based and autologous techniques, as well as the timing of reconstruction (immediate vs. delayed). Methods: A retrospective analysis of data from the American Society of Plastic Surgeons' National Plastic Surgery Statistics from 2015 to 2022 was conducted. Annual trends in breast reconstruction procedures were analyzed, comparing the pre-pandemic (2015-2019) and pandemic (2020-2022) periods. Results: The total number of breast reconstructions increased from 106,338 in 2015 to 151,641 in 2022. The proportion of implant-based reconstructions decreased from 81.41% pre-pandemic to 76.51% during the pandemic (p < 0.001), with a notable rise in direct-to-implant procedures from 10.37% to 19.12% (p < 0.001). Autologous reconstructions increased from 18.59% to 23.49% (p < 0.001). Among autologous techniques, DIEP flaps remained the most popular. Immediate reconstruction rates increased from 72.61% pre-pandemic to 75.57% during the pandemic, while delayed recon-struction rates decreased from 27.39% to 24.43% (p < 0.001). Conclusions: The COVID-19 pandemic has significantly influenced breast reconstruction trends in the United States, with a shift towards autologous techniques, particularly DIEP flaps, and an in-crease in immediate reconstructions. These changes may reflect adaptations in surgical practice and decision-making processes in response to the unique challenges posed by the pandemic. Further research is needed to assess the long-term outcomes and patient satisfaction associated with these trends.

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from ten major Saudi banks, the research examines how different components of intellectual capital—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—influence key financial performance indicators such as Return on Equity (ROE) and Net Profit Margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effects models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size, financial leverage, GDP growth, inflation, and the impact of the COVID-19 pandemic. The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia's Vision 2030. The study's insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development.

Despite Low Power Wide Area Networks’ ability to offer an extended range, it might still encounter challenges with coverage blind spots in the network. This article proposes an innovative energy-efficient nature-inspired relay selection algorithm for LoRa-based LPWAN networks, serving as a solution for challenges related to poor signal range in areas with limited coverage. A behavior swarm-inspired approach has been utilized to select the relays’ localization in the network, providing network energy efficiency and radio signal extension. These relays help bridge communication gaps, significantly reducing the impact of coverage blind spots by forwarding signals from devices with poor direct connectivity with the gateway. The proposed algorithm considers critical factors for the LoRa standard, such as the Spreading Factor or device energy budget analysis. The simulation experiments validate the proposed scheme’s effectiveness in terms of energy efficiency under diverse multi-gateway topology scenarios involving thousands of devices. Specifically, it has been verified that the proposed approach outperforms the reference method in preventing the battery depletion of relays, which is vital for battery-powered IoT devices. Furthermore, for some large-scale problems, the proposed heuristic method achieves over twice the speed of the exact method with a negligible accuracy loss of less than 2%.

Food production is a complex matter, affecting people’s lives, organizations’ profits, and the well-being of the whole planet and has multifaceted ethical considerations surrounding its production, distribution, and consumption. This paper addresses the pressing need to confront ethical challenges within the food system, encompassing issues such as environmental sustainability, food security, and individual food choices for better oral and systemic health of all individuals around the globe. From agricultural practices to global trade and food waste, ethical implications are addressed across various domains, highlighting the interconnectedness of ethical decision-making in the food industry. Central themes explored include the ethical dimensions of food production methods, the impact of global trade on food ethics, and the role of individuals in making ethically informed food choices. Additionally, the paper dives into the spiritual and physical significance of food, particularly through the lens of oral health as a gateway to holistic well-being. Recognizing the complexity of the food ecosystem, the paper calls for serious interventions in legislation and economics to promote ethical protocols and techniques for sustainability reasons. It emphasizes the importance of ethical considerations in food safety management systems, regulatory frameworks, and quality standards. Moreover, the paper underscores the need for a comprehensive approach to address ethical dilemmas and moral values inherent in the food industry and oral health policies, advocating for the adoption of the precautionary principle and ethical decision-making frameworks. The article aims to serve as a call to action for stakeholders across the food industry and the healthcare sector, to prioritize ethical practices, promote transparency, rearrange economic parameters and work towards a more sustainable and equitable food system for inner and outer oral and systemic health and human sustainability for all.

Commuting is a vital travel channel for college students throughout their higher education career; nevertheless, excessive commute time negatively impacts students’ school satisfaction, academic achievement, health, and quality of life. Meanwhile, few studies have explored students’ commute time, covering a large population and scope. Therefore, this study analyzes the dwelling type that influences college and graduate students’ school commute times in the Seoul Metropolitan Area, using data from the 2016 Household Travel Diary Survey. This study uses spatial data on housing development to classify five dwelling types (i.e., new town, housing site development, Seoul, Incheon, and Gyeonggi-do). A multiple linear regression model empirically analyses students’ household and personal characteristics. The results reveal that dwelling type significantly affects students’ commute time. Specifically, Students living in Seoul have a shorter commute to school than those living in new towns. Socioeconomic characteristics have less effect on college and graduate students' school commute time. This study discusses the problem of excessive commuting of college and graduate students in new towns.

D-dimer testing in combination with clinical assessment is commonly used to diagnose suspected DVT and pulmonary embolism. However, as D-dimer levels are physiologically higher in elderly patients, this test loses clinical specificity in the setting of geriatric patients. The aim of our study was to investigate the changes in D-dimer levels with age and the specificity of the D-dimer test in the diagnosis of pulmonary embolism. 1617 elderly patients consecutively admitted to the Geriatric Emergency Care Department of the INRCA-IRCCS hospital between January 2013 and February 2014 and for whom D-dimer results were available were included. The D-dimer immunoturbidimetric assay was performed on a cs-2100i Sysmex Siemens using a conventional cut-off level of 500 µg/L. The median D-dimer level was 1200 [550-2990] µg/L FEU, and the percentage of patients with D-dimer levels below the conventional cut-off was only 22.1%. As expected, there was a significant age-related increase in D-dimer, even when sex was considered, and a significant decrease in the specificity of D-dimer assay with age. The most established use of D-dimer testing is in the diagnosis of deep vein thrombosis or pulmonary embolism. Our study confirms the need for an age-adjusted cut-off for D-dimer testing in geriatric patients.

Glass cleaning is one of the major cleaning tasks in malls, offices, and modern households where the human workforce is still used for cleaning. Manual cleaning on façade glasses is a less safe, tedious, ineffective, and complex process. With the advancement of robot technology, it is possible to use robots for glass cleaning to facilitate mankind and improve cleaning efficiency. This work presents the development of a vacuum-type glass cleaning robot for façade cleaning and its performance analysis. The developed square-shaped robot is controlled by an Arduino Mega microcontroller, equipped with vacuuming and cleaning technology. An adhesion mechanism on the wheels makes the robot move forward and backward on the glass. The robot runs on a 24-volt DC with a power rating of 75 watts. There are ultrasonic sensors to detect obstacles and help the robot navigate. The robot uses a random-walk mechanism and works continuously for 90 minutes effectively. The performance of the robot has been analyzed in terms of coverage area, repeatability, and dust collection efficiency.

In modern data analysis, working with diverse dataset formats is essential for ensuring compatibility across different software tools and platforms. However, manual conversion between formats can be time-consuming and error-prone. To address this challenge, we developed an interactive Shiny application that facilitates the seamless conversion of datasets between popular software formats such as CSV, Excel, SAS, SPSS, Stata, and RData. This user-friendly app enables users to upload datasets, select an output format, and download the converted file with a single click. The application also incorporates a real-time progress indicator, enhancing the user experience by showing conversion progress. Built with simplicity and efficiency in mind, the app is designed for researchers, data analysts, and practitioners who regularly handle multiple file formats in their workflows. Additionally, the app features a clean, intuitive interface with clear guidance, making it accessible even to users with minimal technical background. The development process, key features, and potential applications of this tool are discussed in this article.

High-wind structures were identified in the Cross-Calibrated Multi-Platform (CCMP) ocean wind vector reanalysis for comparison with winds measured by satellite radiometers and synthetical aperture radar (SAR) instruments from February to October 2023. The comparison aims to evaluate bias, uncertainty, and spatial correlations with the goal of enhancing the accuracy of ocean wind datasets during tropical cyclones (TCs). In 10°longitude×10°latitude blocks, each containing a TC, Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) winds are 6.5% and 4.8% higher than CCMP, while Advanced Scatterometer (ASCATB) is 0.8% lower. For extratropical cyclones, AMSR2 and SMAP also show stronger winds with a 5% difference, and ASCATB is about 0.3% weaker compared to CCMP. The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. Using empirically defined TC structural indices, we find that the TCs observed by CCMP are shifted in locations and lack a compact core region. A Random Forest (RF) regressor was applied to TCs in CCMP with corresponding SAR observations, nearly correcting the full magnitude of low bias in CCMP statistically, with a 15m/s correction in the core region. The hierarchy of importance among the predictors is as follows: CCMP wind speed (62%), distance of SAR pixels to the eye region (21%) and eye center (7%), and distance of CCMP pixels to the eye region (5%) and eye center.

In this paper we investigate the differential topological properties of a subclass of singular space--subcarteisan spaces. First, we get further result on partition of unity for differential spaces. Second, we establish the tubular neighborhood theorem for subcartesian spaces with constant structural dimension. Third, we generalize the concept of Morse functions on smooth manifolds to differential spaces. For subcartesian space with constant structural dimension, we provide examples of Morse functions; With the assumption that the subcartesian space can be embedded as a bounded subset of an Euclidean space, we prove that smooth bounded functions on this space can be approximated by Morse functions; We study the infinitesimal stability of Morse functions on subcartesian spaces. Classical results on Morse functions on smooth manifolds can be treated directly as corollaries of our results here.

The analysis of chemical warfare agents and their degradation products has become increasingly important for public and military safety in recent years. In the article, we drew attention to the possibilities of the HPLC-ICP-MS analytical technique, which has been relatively rarely used for identifying and quantitatively analyzing highly toxic and hazardous substances in environmental samples. This technique enables the identification and determination of minimal amounts (ppt range) of chemicals in various matrices. This fact is important for the analysis of chemical warfare agents and other highly harmful compounds, even small amounts of which can have serious consequences for living organisms. The article critically analyzes the results of scientific research on the identification and quantitative analysis of extremely toxic organophosphorus, organosulfur and organoarsenic substances, their derivatives and degradation products using high-performance liquid chromatography (HPLC) coupled with inductively coupled plasma mass spectrometry (ICP-MS).

This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we introduce a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

Researchers have explored primary colour-geometric shape associations since Kandinsky's correspondence theory. However, there is a gap in the literature regarding interior colour applications on surface shapes. To address this gap, an online study was employed to gather data with one hundred participants who were asked to choose their preferred colours for shapes on bedroom walls with follow-up questions on the colour-shape semantic associations, their preference of colours and shapes on bedroom walls independently in addition to their favourite colour, their favourite shape, and colour-shape pairs without interior context. The results revealed that colour-shape preferences in interiors differ from those found in psychology studies, other colour applications on bedroom walls, and other preferences, indicating that colour preference is context-dependent. Interestingly, the most popular colour for surface shapes on bedroom walls is purple, followed by brown and blue. The study contributes to the existing literature by providing colour charts for bedroom applications for professionals in the industry, their clients/users, and future studies.

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

According to the requirement of 20kg load of casting barrel, we design a three-dimensional model of the robot and analyze the three stages of liquid level change in the casting barrel during the casting process. Through the analysis, it is determined that the time and angle function is an implicit function, and it is impossible to find the analytical expression of time about angle. The kinetic function of the casting barrel is simulated by MATLAB, and it is found that the function image has mutation points, and when the original function is fitted and approximated by fifth-degree polynomial interpolation, the fifth-degree polynomial function image of the time versus the angular acceleration has a large amplitude of oscillation, especially the mutation points. A PID algorithm based on the discretization of the time and acceleration function is introduced for correction, and the results show that this method effectively reduces the oscillation amplitude of the image and improves the coincidence with the original function.

A novel approach was developed that combined LP-based row generation with optimization-based sorting to tackle computational challenges posed by budget allocation problems with combinatorial constraints. The proposed approach dynamically generated constraints using row generation and prioritized them using optimization-based sorting to ensure a high-quality solution. Computational experiments and case studies revealed that as the problem size increased, the proposed approach outperformed simplex solutions in terms of solution search time. Specifically, for a problem with 50 projects (N = 50) and 2,251,799,813,685,250 constraints, the proposed approach found a solution in just 1.4 seconds, while LP failed due to the problem size. The proposed approach demonstrated enhanced computational efficiency and solution quality compared to traditional LP methods.

There is currently an exponential growth in the electric vehicle market, which will require an increase in the electrical grid capacity to meet the demand of charging. If, on the one hand, the introduction of energy generation from renewable sources can be used to meet that requirement, the intermittent nature of some of these sources poses challenges to the required real time equilibrium between generation and consumption. The impossibility of controlling generation from some of these sources leads to the attempt of controlling and manage the consumption of electricity, according with the levels of generation. In this context, the emergence of smart grids has introduced mechanisms that guarantee a balance between consumption and generation of electricity. One of these mechanisms is the smart charging of electric vehicles. Effective smart charging relies on communication between the supply equipment and the electric vehicle, en-abling the adjustment of the energy transfer according with the generation levels. Thus, there is a necessity for a standardised system that guarantees this communication. In this context, the ISO 15118 standard, allows high level communication mechanisms, much beyond the basic control solutions offered by the IEC 61851-1 specification. In this context, this paper presents the development of a charge emulation system, based on the ISO 15118 communication protocol and discusses its application for demand response purposes.

Lithium-ion batteries (LIBs) have become the preferred battery system for portable electronic devices and transportation equipment because of their high specific energy, good cycling performance, low self-discharge and no memory effect. However, too low ambient temperature will seriously affect the performance of LIBs, almost cannot discharge at -40~-60 ℃. There are many factors affecting the low temperature performance of LIBs, among which the electrode material is an important factor. Thus it is urgent to develop electrode materials or modify existing materials with excellent low temperature LIBs performance. Carbon-based anode is a kind of LIBs candidate. In recent years, it has been found that the diffusion coefficient of lithium ion in graphite anode decreases more obviously at low temperature, which is one of the important bottlenecks limiting its low temperature performance. However, the structure of amorphous carbon materials is complex, amorphous carbon materials have good ionic diffusion properties, and its grain size, specific surface area, layer spacing, structural defects, surface functional groups and doping elements may have a greater impact on the low temperature performance of the material. In this work, the low temperature performance of LIBs is obtained by modifying the carbon-based material from the perspective of electronic modulation and structural engineering.

In European thought, the relationship among the fields of psychology, education, and health is both complex and obscured. Foucault’s acclaimed work, The Order of Things, offers a framework to evaluate their interconnection by identifying three distinct periods of European thought since the 16th century with respect to the ordering of phenomena—Renaissance, Classical and Modern. Theoretically dense and often difficult to decipher, the book’s categorization of language, value and being has been understandably underused, yet it provides deep insights into what have come to be known as psychology, education and health and remains invaluable in understanding the origin, limits and consequences of these fields. How Foucault’s analysis can be interpreted concerning the development of these areas as to each of the three periods of European thought is investigated. An approach based on narrative research appraises the analysis offered in the book. The results, presented for the first time in table form, compare these three periods, demonstrating a continuing practical value to Foucault’s insights. With the aid of the framework revealed by these tables, the boundaries and relationship of psychology, education and health become clear and their limitations—plus potential solutions to them—can be identified to mitigate anticipated negative consequences.

Reinforcement learning (RL) is an extensively applied control method for the purpose of designing intelligent control systems to achieve high accuracy as well as better performance. In the present article, the PID controller is considered as the main control strategy for brushless DC (BLDC) motor speed control. For better performance, the fuzzy Q-learning (FQL) method as a reinforcement learning approach is proposed to adjust the PID coefficients. A comparison with the adaptive PID (APID) controller is also performed for the superiority of the proposed method, and the findings demonstrate the reduction of the error of the proposed method and elimination of the overshoot for controlling the motor speed. MATLAB/SIMULINK has been used for modeling, simulation, and control design of the BLDC motor.

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

Breast cancer stands as a predominant health concern for women globally. As mammography is the primary screening tool for breast cancer detection, improving the detection of breast cancer at screening could save more lives. This mammography re-view paper provides a systematic review of computer-aided techniques during a specific time frame for the segmentation and classification of microcalcification, evaluating image processing, machine learning, and deep learning techniques. The systematic review is meticulously carried out, adhering closely to the preferred reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. This article focuses on mammographic breast cancer detection approaches based on automated systems, discussed chronologically from 1970 through 2023. This article encompasses the breadth of artificial intelligence-based methods from the most primitive to the most sophisticated models. Image processing and machine learning-based methods are compre-hensively reviewed. The evaluation of a deep learning architecture based on self-extracted features for classification tasks demonstrated outclass performance. Large-scale datasets required for a broader and in-depth analysis of novel methods for breast cancer detection are also discussed in this article. This research work is aligned with the United Nations' sustainability de-velopment goals.

Gene therapy is a medical approach capable of correcting genetic and epigenetic alterations in pathological conditions, including cancer. Different strategies have been pursued for cancer gene therapy, aiming to restore the function of tumor suppressor genes or inhibit oncogenes. These comprise the use of CRISPR/Cas9 gene editing technology and therapeutic oligonucleotides, such as microRNAs, anti-microRNAs, small interfering RNAs, DNAzymes, and epigenetic modifiers. However, despite great potential, their broad clinical use is hindered due to the lack of safe and efficient systems for targeted delivery to cancer cells. To this purpose, aptamers could represent an ideal tool. They are short single-stranded oligonucleotides that bind receptors selectively present or overexpressed on cancer cell membranes, often undergoing cell-specific internalization. Thanks to this last feature, numerous internalizing aptamers have been investigated as targeting moiety to deliver therapeutic oligonucleotides, viral vectors, and nanoparticle-based systems in preclinical studies. Here, we summarize the state-of-the-art of aptamer applications in cancer gene therapy, providing key examples and discussing their advantages, limitations, and clinical perspectives.

Fingerprints are essential for human identification and are valuable tools in criminal investigations. The pursuit of new materials for digital printing is expanding, with increasing interest in natural compounds such as bixin, sourced from annatto seeds. Despite its traditional use as a natural dye with medicinal properties, the potential of bixin in papilloscopy remains largely untapped. In this study, we meticulously extracted bixin from annatto seeds and meticulously developed composites incorporating zinc carbonate (bixin/ZnCO3) and kaolinite (bixin/kaolinite). UV-visible spectroscopy was used for characterization, and the extracted bixin showed absorption peaks at 429, 453, and 481 nm, which were very similar to standard peaks at 429, 457, and 487 nm. The two samples also had the same retention times (7.07 min) according to further liquid chromatography analysis. Sweat pores were easier to detect thanks to the effectiveness of the bixin/ZnCO3 and bixin/kaolinite composites in creating high contrast sebaceous and natural latent fingerprints. These results highlight the composites’ potential as novel and fascinating instruments for papilloscopy applications, which might also improve forensic investigations.

Epigenetic mechanisms, including histone post-translational modifications (PTMs), play a critical role in regulating pain perception and the pathophysiology of burn injury. However, the epigenetic regulation and molecular mechanisms underlying burn injury-induced pain remain insufficiently explored. Spinal dynorphinergic (Pdyn) neurons contribute to heat hyperalgesia induced by severe scalding-type burn injury through p-S10H3-dependent signaling. Beyond p-S10H3, burn injury may impact various other histone H3 PTMs. Double immunofluorescent staining and histone H3 protein analyses demonstrated significant hypermethylation at H3K4me1 and H3K4me3 sites and hyperphosphorylation at S10H3 within the spinal cord. By analyzing Pdyn neurons in the spinal dorsal horn, we found evidence of chromatin activation with a significant elevation in p-S10H3 immunoreactivity. We used RNA-seq analysis to compare the effects of burn injury and forma-lin-induced inflammatory pain on spinal cord transcriptomic profiles. We identified 98 DEGs for burn injury and 86 DEGs for formalin-induced inflammatory pain. A limited number of shared differentially expressed genes (DEGs) suggest distinct central pain processing mechanisms between burn injury and formalin models. KEGG pathway analysis supported this divergence, with burn injury activating Wnt signaling. This study enhances our understanding of burn injury mechanisms and uncovers converging and diverging pathways in pain models with different origins.

Background/Objectives: Resources to cope for maternity and women’s participation are essential modulators of maternal well-being. Therefore, it is relevant that the psychosocial factors of woman will be monitored during maternity to promote adequately healthcare. This study consisted in the design and the validation of two new tools that identify women's knowledge of obstetric healthcare rights (MatCODE) and perception of resource scarcity (MatER) during pregnancy, labor and early postpartum; Methods: The content validity was carried out using the Aiken's V coefficient and the content validity index (CVI-i) based on 5 experts. In addition, for the face validity of the pilot cohort was considered the INFLESZ scale. Finally, the questionnaires were applied to 185 women, which allowed to assess the construct validation by factorial and Rasch analysis. The divergent validity was also studied with validated psychological questionnaires; Results: MatCODE and MatER questionnaires received CVI-i and Aiken's V&gt;0.80 values, also the INFLESZ demonstrates acceptable semantic understanding. The analysis confirms the unidimensional of the questionnaires with fit values for MatCODE of RMSEA=0.113 [0.105; 0.122] and MatER of RMSEA=0.067 [0.063; 0.072]. The divergent validity showed significative and consistent correlations with the constructs assessed. In MatCODE was =0.95 and =0.94 and in MatER was =0.79 and =0.78; Conclusions: MatCODE and MatER are new useful tools monitoring maternal healthcare, with adequate psychometric characteristics in Spanish context.

A novel multicomponent glasses with nominal compositions of (50-x)MoO3:xWO3:25La2O3:25B2O3, x = 0, 10, 20, 30, 40, 50 mol% doped with 3 mol % Eu2O3 were prepared using a conventional melt quenching method. Their structure, thermal behavior and luminescent properties were investigated by Raman spectroscopy, differential thermal analysis and photoluminescence spectroscopy. Physical parameters as density, molar volume, oxygen molar volume and oxygen packing density were determined. Glasses are characterized with high glass transition temperature. Raman analysis revealed that the glass structure is built up mainly from tetrahedral (MoO4)2- and (WO4)2- units providing Raman bands of around 317 cm-1, 341-352 cm-1, 832-820 cm-1 and 928-935 cm-1. At the same time with the replacement of MoO3 with WO3 some fraction of WO6 octahedra are produced, which number increases with the increasing WO3 content. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (395 nm) excitation using the 7F0 →5L6 transition of Eu3+. PL emission gradually increases with increasing WO3 content evidencing that WO3 is more appropriate component than MoO3. The integrated fluorescence intensity ratio R (5D0 →7F2/5D0 →7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites.

The paper provides and comments on the results of studies of the effect of sandstone-based abrasives and quartz sand alone on the wear of martensitic surfaces of wear-resistant steels. The wear process was examined on a ring-on-ring test rig seeking to determine the mass decrement parameter which characterised wear. The tests were conducted for three sandstone varieties: Carboniferous, Permian, and Cretaceous, and they made it possible to determine that the most intense process of deterioration of wear-resistant steels took place in the presence of quartz sand grain, while less intense wear was observed in the case of sandstone-based abrasives. The mass decrement values established in the presence of the sandstones in question did not differ significantly between individual sandstone varieties. Based on a surface damage analysis, the basic damage mechanism was found to be micro-scratching, however, with regard to the sandstones examined, it was also determined that individual grains could be pressed into surface irregularities, as well as that films of soft hematite cement developed in the Permian sandstone and that inclusions of carbonaceous matter were formed in the Carboniferous sandstone. With reference to the wear process observations, a wear model was described for the surface of the steels examined in the presence of sandstone-based abrasives.

Many people, including Horadam, have studied the numbers $W_n$, satisfying the recurrence relation $W_n=u W_{n-1}+v W_{n-2}$ ($n\ge 2$) with $W_0=0$ and $W_1=1$. In this paper, we study the $p$-numerical semigroups of the triple $(W_i,W_{i+2},W_{i+k})$ for integers $i,k(\ge 3)$. For a nonnegative integer $p$, the $p$-numerical semigroup $S_p$ is defined as the set of integers whose nonnegative integral linear combinations of given positive integers $a_1,a_2,\dots,a_\kappa$ with $\gcd(a_1,a_2,\dots,a_\kappa)=1$ are expressed in more than $p$ ways. When $p=0$, $S=S_0$ is the original numerical semigroup. The largest element and the cardinality of $\mathbb N_0\backslash S_p$ are called the $p$-Frobenius number and the $p$-genus, respectively.

Training has a significative effect on physiology of blood coagulation both in humans and in horses. Several hemostatic changes have been reported after exercise in the horse but data available are inconclusive. The aim of this study was to investigate the platelet activation and primary platelet-related hemostasis modifications in young untrained Thoroughbred racehorses in the first 4-month timeframe incremental training period in order to improve knowledge on this topic. Twenty-nine clinically healthy, untrained, 2-year-old Thoroughbred racehorses. Never trained Thoroughbreds were followed during their incremental 4-month sprint exercise schedule. Blood collection was performed once a month (T-30, T0, T30, T60, and T90). Platelet aggregation was measured by light transmission aggregometer in response to various agonists: adenosine diphosphate (ADP), collagen and calcium ionophore A23187. Platelet function was evaluated using the Platelet Function Analyzer (PFA-100®) using collagen/ADP and collagen/adrenaline cartridges. Nitrite-nitrate (NOx) plasma concentrations were measured by a colorimetric assay to assess in vivo nitric oxide bioavailability. Platelet activation was investigated also through gene expression analyses (selectin P-SELP, ectonucleotidase CD39-ENTPD1, prostaglandin I2 synthase-PTGIS, endothelial nitric oxide synthase 3-NOS3). Differences among the time points were analyzed and mean±SEM were calculated. Significant modifications were identified compared with T-30 with increase of platelet aggregation (collagen:32.6±4.8 vs 21.6±4.9%; ADP: 35.5±2.0 vs 24.5±3.1%; A23187: 30±4.7 vs 23.8±4%) and a shorter closure time of C-ADP cartridges (75.6±4.4 vs 87.7±3.4 sec) that tended to return to baseline value at T90. NOx concentrations in plasma significantly increased after 30 days of training program compared with baseline. The first long-term training period induce platelet hyperactivity already after 30 days in untrained Thoroughbreds. Regular physical training blunts the negative effects of acute efforts on platelets activation.

The corrosion resistance of two cast CoCr based alloys, with different amounts of chromium and with different alloying elements in the bulk composition of the alloy, was assessed. Herewith, we investigated the corrosion behavior of Co21Cr8Mo7W and Co29Cr7W by open circuit potential (OCP), potentiodynamic polarization (PP) and electrochemical impedance spectroscopy (EIS) in 0.1 M phosphate buffer solution (PBS) at 37°C for long time immersion. After 1000 hours of immersion, the corrosion current density (icor), estimated from anodic polarization tests, is lower for Co21Cr8Mo7W (i.e. 49 nA cm-2) alloy compared to Co29Cr7W alloy (180 nA cm-2). As regards the corrosion potential (Ecor), a nobler value was observed for Co21Cr8Mo7W (i.e. -59 mV vs. Ag/AgCl) compared to Co29Cr7W (i.e. -114 mV vs. Ag/AgCl). These findings suggest a better corrosion resistance of the film formed on the alloy containing lower amount of Cr and two alloying elements, namely Mo and W. These results are promising ones in terms of medical applications because they open new strategies in obtaining alloys with lower content of chromium and with higher protective properties against corrosion attack.

Background: Lipoprotein lipase (LPL) deficiency is a genetic condition. Affected individuals typically develop symptoms before age 10 with severe hypertriglyceridemia. No pharmacological treatment has lowered triglyceride levels in LPL deficiency patients successfully. The purpose of this study is to report on clinical outcomes of patients with LPL deficiency who responded to dietary therapy with successful reduction of their triglyceride (TG) levels with a long-chain triglyceride (LCT)-restricted, medium-chain triglyceride (MCT)-supplemented diet. Methods: A single-center retrospective case review study of LPL deficiency patients who met the inclusion criteria and were evaluated at the Hospital of Sick Children between January 2000 to December 2022. Data collected include demographic and clinical data, biochemical profiles at diagnosis and after dietary treatment initiation, and molecular results. Results: The study included seven patients with a suspected diagnosis of LPL deficiency (hypertriglyceridemia > 20 mmol/L). Six patients had a confirmed molecular diagnosis of LPL deficiency, and one had a Glycogen storage disease 1a (GSD1a) diagnosis. After presenting with hypertriglyceridemia, an LCT-restricted and MCT-supplemented diet was initiated, resulting in immediate and sustained TG reduction in all LPL deficiency patients that adhered to the diet. Additionally, they all maintained excellent growth and development. LPL deficiency-related complications were not observed under the MCT-enriched diet, except for increased pancreatic enzymes in one patient after dietary error. As expected, the diet failed to treat hypertriglyceridemia in the GSD1 patient. Conclusions: The dietary restriction of LCT in combination with MCT supplementation was feasible and effective in the long-term management of patients with LPL deficiency. In our experience, this treatment eliminated LPL-related complications and led to good clinical outcomes.

Immersion in forest environments was shown to produce beneficial effects to human health, in particular psychophysical relaxation, so much that this practice is increasingly recognized as a form of integrative medicine. Limited evidence exists about both statistical significance and size of the effects conditioned on personal characteristics, as well as on the main external variables. The primary purpose of this study was to substantiate the very concept of forest therapy by means of the quantification and significance of the psychological effects, stratified by gender, age groups and place of residence. A preliminary qualitative analysis of the main determinants, in particular the method of conducting, the meteorological comfort and the concentration of volatile organic compounds in the forest atmosphere, was afforded. Seven forest therapy sessions were performed in late summer though early fall, resulting in 150 psychological self-assessment questionnaires administered before and after each session. The results were comparable or even better than others reported in the international literature. Moreover, preliminary evidence arose about different functionality towards specific psychological indexes conditioned at least on gender and age groups, as well as meteorological comfort, structured programs and, possibly, volatile organic compounds showed an impact on the outcomes.

Farm activities continued sand winning operations and the allocation of plots of land to prospective developers in Ghana pose a serious threat to the forest covers and lifespan of the Forest and game reserves. With all the positive add ups to the country from forests, Ghana has lost more than 33.7%(equivalent to 2,500,000 hectares) of its forest, since the early 1990s between 2005 and 2010, the rate of deforestation in Ghana was estimated at 2.19% per annum; the sixth highest deforestation rate globally for that period. This shows how important forest monitoring can be to the forestry commission in Ghana. Despite the frameworks which have been developed to help Ghana to protect and restore its forest resources, inadequate monitoring systems remain a barrier to effective implementation. In this study, Google earth engine was used to map and analyze the structural changes of forest cover using JavaScript to query and compute Landsat, MODIS and NOAA AVHRR satellite imageries of the study area (Ghana) with spatial resolutions 30m, 250m and 7km respectively. A supervised classification was performed on three multi-temporal satellite imageries and a total of six major land use and land cover classes were identified and mapped. By using random Forest-classification technique, from 1985 to 2018 recorded by NOAA AVHRR, forest cover has decreased by 66% and 2000 to 2018 recorded by Landsat and MODIS 61% and 47% respectively. A decrease in the forest has been as a result of anthropogenic activities in Ghana. A change detection analysis was performed on these images and it was noted that Ghana is losing forest reserves in every 5years. Overlay of the reserved forest of the 2000 and the classified map of 2018 shows vegetation changed during 2000-2018 remarkably. Therefore, forest-related institutions like the Forestry Commission can employ and use this monitoring system on Google Earth Engine for processing satellite images particularly Landsat, MODIS and NOAA AVHRR for forest cover monitoring and analysis for fast, efficient and reliable results.

Nutrition therapy is the best solution to human chronic diseases, especially beer and barley which play an important role in human health and civilization. We demonstrated the actional mechanism of functional ingredients in beer and barley to combat chronic diseases, based on PubMed, google, CNKI, and ISI Web of Science databases from 1997 to 2024. Beer is rich in functional ingredients that is a complex of barley malt and hops; the health effect of beer against 26 chronic diseases is highly similar to that of barley, due to molecular mechanism of polyphenols (phenolic acids, flavonoids), melatonin, minerals, bitter acids, vitamins, and peptides. The ancient German Beer Purity Law provides much scientific basis today, especially indirectly supporting the human one cell disease theory. Low purine beer can be produced by enzymatic and biological degradation and adsorption of purines as well as dandelion addition. Functional beer with low purine and high active ingredients made from Beer Purity and barley malt as well as functional foods addition will be the key and important development direction, such as ginger beer and ginseng beer, especially coix-lily beer at the ancestors ca. 9000 years ago. This review paper not only reveals the actional mechanism of beer overcoming human chronic diseases, but also provides scientific basis for the development of functional beer for the prevention and treatment of human chronic diseases.

Background: Painful spinal bone metastases (PSBMs) patients regularly receive palliative radiation therapy (RT) with response rates in about 2 of 3 patients. In this exploratory study, we evaluated the value of machine learning (ML) models based on radiomic, semantic and clinical features to predict complete pain response. Methods: Gross tumour volumes (GTV) and clinical target volumes (CTV) of 261 PSBMs were segmented on planning computed tomography (CT) scans. Radiomic, semantic and clinical features were collected for all patients. Random forest (RFC) and support vector machine (SVM) classifiers were compared using repeated nested cross-validation.Results: The best radiomic classifier was trained on CTV with an area under the receiver-operator curve (AUROC) of 0.62 ± 0.01 (RFC; 95% confidence interval). The semantic model achieved a comparable AUROC of 0.63 ± 0.01 (RFC), significantly below the clinical model (SVM, AUROC: 0.80 ± 0.01); and slightly lower than the spinal instability neoplastic score (SINS; LR, AUROC: 0.65 ± 0.01). A combined model did not improve performance (AUROC: 0,74 ± 0,01).Conclusions: We could demonstrate that radiomic and semantic analyses of planning CTs allowed for limited prediction of therapy response to palliative RT. ML predictions based on established clinical parameters achieved the best results.

This study proposes a novel hybrid machine learning approach for modeling of rainfall-induced shallow landslides. The proposed approach is a combination of an instance-based learning algorithm (k-NN) and Rotation Forest (RF), state of the art machine techniques that have seldom explored for landslide modeling. The Lang Son city area (Vietnam) is selected as a case study. For this purpose, a spatial database for the study area was constructed, and then, was used to build and evaluate the hybrid model. Performance of the model was assessed using Receiver Operating Characteristic (ROC), area under the ROC curve (AUC), success rate and prediction rate, and several statistical evaluation metrics. The results showed that the model has high performance with both the training data (AUC = 0.948) and the validation data (AUC = 0.848). The results were compared with those obtained from soft computing techniques i.e. Random Forest, J48 Decision Trees, and Multilayer Perceptron Neural Networks. Overall, the performance of the proposed model is better than those obtained from the above methods. Therefore, the proposed model is a promising tool for landslide modeling. The research result can be highly useful for land use planning and management in landslide prone areas.

Carbon nanodots (CNDs) have garnered significant attention as viable drug delivery vehicles in recent years, especially in the field of phytomedicine. Although there is much promise for therapeutic applications with phytomedicine, its effectiveness is frequently restricted by its low solubility, stability, and bioavailability. This paper offers a thorough synopsis of the developing field of phytomedicine drug delivery based on CND. It explores CND synthesis processes, surface functionalization strategies, and structural and optical characteristics. Additionally, the advantages and difficulties of phytomedicine are examined, with a focus on the contribution of drug delivery methods to the increased effectiveness of phytomedicine. The applications of CNDs in drug delivery are also included in the review, along with the mechanisms that underlie their improved drug delivery capabilities. Additionally, it looks at controlled release methods, stability augmentation, and phytomedicine loading tactics onto CNDs. The potential of polymeric carbon nanodots in drug delivery is also covered, along with difficulties and prospective directions going forward, such as resolving toxicity and biocompatibility issues. In summary, the present review highlights the encouraging contribution of CNDs to the field of drug delivery, specifically in enhancing the potential of phytomedicine for therapeutic purposes.

Keywords: Cocoa value chain; Fair trade; Chocolate; Sustainable development; SDGs

Background and Objectives: Most of the research of the BRCA1 inactivation is focused on monoallelic germline alterations and loss of heterozygosity in tumour. The aim of this study was to identify characteristic transcriptomic pattern of monoallelic somatic BRCA1 inactivation and estimate its impact to the event-free breast cancer survival prognosis. Materials and Methods: We conducted global transcriptome sequencing of breast cancer tissue samples to identify differentially expressed genes and signalling pathways associated with monoallelic somatic BRCA1 inactivation. The study group involved 36 patient samples categorized based on BRCA1 inactivation status. Subsequently, the differential gene expression and Kaplan-Meier analyses in the groups with and without monoallelic somatic BRCA1 inactivation were performed. Results: Kaplan-Meier analysis showed tendency for longer event-free survival in patients with monoallelic somatic BRCA1 inactivation, suggesting somatic BRCA1 inactivation is favourable prognostic. Differential gene expression analysis followed by the STRING tool enrichment analysis showed significant enrichment of proteins in the extracellular region and extracellular space. Conclusion: In this study we identified transcriptomic profile of differentially expressed genes TPSD1, FABP4, CARTPT and MMP9 as indicative for homologous recombination impaired tumours with tendency for better therapy results.

We developed an ovarian cancer-targeted drug delivery system based on a follicle-stimulating hormone receptor (FSHR) peptide. The lipophilic chemotherapeutic drug SN38 and the photosensitizer IR820 were loaded into the phospholipid bilayer of liposomes. Near-infrared laser irradiation stimulated the generation of reactive oxygen species, causing short-term reactive molecular species and spatial-temporal restricted photodamage to the biological targets. The reactive molecular species and spatial-temporal restricted photodamage enhanced the release and uptake of chemotherapy drugs and increased the sensitivity to chemotherapy drugs in ovarian cancer cells. FSH liposomes loaded with SN38 and IR820 (SN38/IR820-Lipo@FSH) were prepared using thin-film hydration-sonication. FSH peptide binding was analyzed using 1H NMR spectrum and Maldi-Tof. The average size and zeta potential of SN38/IR820-Lipo@FSH were 105.1 ± 1.15 nm (PDI: 0.204 ± 0.03) and −27.8 ± 0.42 mV, respectively. SN38/IR820-Lipo@FSH exhibited good drug-loading properties and the in vitro release was slow. FSH significantly increased the uptake of liposomes, inhibited cell proliferation, and induced apoptosis in A2780 cells. Moreover, SN38/IR820-Lipo@FSH exhibited good tumor-targeting ability and anti-ovarian cancer activity in vivo. The SN38/IR820-Lipo@FSH exhibited specific targeting to A2780 ovarian cancer cells. The combination of chemotherapy and photodynamic treatment based on an FSH peptide-targeted delivery system may be an effective approach to treating ovarian cancer.

The paper examines the possibility of increasing the wear and corrosion resistance of a CP-Ti surface by duplex plasma electrolytic treatment (borocarburizing and polishing). The structure and composition of diffusion layers, their microhardness, surface morphology and roughness, wear resistance during dry friction and corrosion resistance in Ringer's solution were studied. The formation of a surface hardened layer up to 200 m thick with a microhardness of up to 950 HV, including carbides and a solid solution of boron and carbon, is shown. Subsequent polishing makes it possible to reduce surface roughness and remove weak areas of the porous oxide layer, which is formed during high-temperature oxidation in aqueous electrolyte vapor during borocarburizing. Changing the morphology and structural-phase composition of the CP-Ti surface helps reduce weight wear by 3 times (the mode of frictional interaction changes from microcutting to oxidative wear) and corrosion current density by 4 times after borocarburizing in a solution of boric acid, glycerin and ammonium chloride at 950 °C for 5 minutes and subsequent polishing in an ammonium fluoride solution at a voltage of 250 V for 3 minutes.

Flap surgery is a common method used to cover defects following tumor ablation, trauma, or infection. However, insufficient vascularity in the transferred flap can lead to flap necrosis and failure. Proper postoperative monitoring is essential to prevent these complications. Recently, research has explored the use of infrared thermal imaging in plastic surgery, leading to its clinical application. This study investigates the use of a forward-looking infrared (FLIR) camera to monitor blood flow in flaps. In the study, 28 rats underwent reverse McFarlane flap surgery, and their flaps were analyzed using a FLIR thermal imaging camera seven days post-surgery. Additionally, thermal images of flaps were taken on postoperative days 0, 1, 2, 3, and 7 in 22 patients. The study focused on temperature differences between normal skin and the perforator compared to the average flap temperature. Results showed that the temperature difference was higher in the necrosis group and increased over time in cases of total necrosis. A lower perforator temperature compared to the flap's average indicated vascular compromise, potentially leading to flap failure. The FLIR camera, being contact-free and convenient, shows promise for understanding and inferring the clinical progression of flaps in postoperative monitoring.

Change Detection (CD) of aerial images refers to identifying and analyzing changes between two or more aerial images of the same location taken at different times. The CD is a highly challenging task due to the need to distinguish relevant changes, such as urban expansion, deforestation, or post-disaster damage assessment, from irrelevant ones, such as light conditions, shadows, and seasonal variations. Many CD papers have recently been published, where most of the papers that proposed a new model contained a comparison between their proposed and state-of-the-art (SOTA) models. While many recent studies propose new deep learning (DL) models for improving CD performance, their comparative analyses are often restricted, lacking comprehensive insights into the proposed models' real-world generalizability, robustness, and performance trade-offs across diverse change characteristics. This paper presents a novel generic framework to systematically benchmark and assess DL-based CD models through three parallel pipelines: 1) cross-testing models on diverse benchmark datasets to evaluate generalization, 2) robustness analysis against different image corruptions, and 3) multi-faceted contour-level analytics evaluating detection sensitivity to change size/complexity. The framework is applied to comparatively evaluate five state-of-the-art DL-based CD models - Changeformer, BIT, Tiny, SNUNet, and CSA-CDGAN. Extensive experiments unveil each model's strengths, limitations and biases, highlighting their relative proficiencies in generalizing across data distributions, resilience to noise corruption, and discriminative capabilities for changes of varying characteristics. The proposed benchmarking framework demonstrates significant potential for guiding the selection of suitable CD models tailored to specific application requirements by comprehensively evaluating their generalizability, robustness, and detection capabilities across diverse real-world scenarios. This systematic evaluation approach can drive future research into developing more robust and versatile CD solutions aligned with practical needs.

Abstract: The VSI represents a significant advancement in the assessment of gastrointestinal-specific anxiety among patients with Irritable Bowel Syndrome (IBS) and other Chronic Inflammatory Bowel Diseases (IBD). However, an Italian version of the instrument is not yet available for the reference population. This study utilized a national sample of 500 individuals, including healthy controls and patients with Ulcerative Colitis and Crohn's Disease, to test the validity and reliability of the Italian VSI. Using back-translation methodology to ensure translation fidelity, the research applied a questionnaire and the VSI through an online format to 500 participants. Data analysis revealed that the Italian VSI had excellent psychometric properties, demonstrating high internal consistency (Cronbach’s α = 0.95) and construct validity. The scale proved sensitive in detecting significant differences in visceral sensitivity among groups, highlighting its utility as a clinical and research assessment tool. Specifically, the Italian VSI exhibited a unidimensional factorial structure and maintained a strong correlation with other measures of anxiety and the severity of gastrointestinal symptoms, confirming its role in enhancing the understanding and management of IBS and IBD in Italy.

Salt stress is one of the major abiotic stresses that lead to crop yield reduction worldwide. Melatonin (MT), an endogenous hormone synthesized in plants, plays an important role in responding to abiotic stimuli such as drought, salinity, heat, cold, etc. However, the molecular mechanisms of MT-mediated abiotic stresses remain to be better understood. In order to explore the key genes and pathways of melatonin in alleviating salt stress, physiological and biochemical indicators as well as transcriptomics profile were conducted in alfalfa seedlings. The results showed that the germination rate, bud length and fresh weight of alfalfa seedlings added with melatonin were higher than those treated with salt alone. In addition, Malondialdehyde (MDA) and Superoxide anion (O2-) contents also displayed a decreasing trend. The activity and content of Superoxide dismutase (SOD)、peroxidase (POD) and Glutathione (GSH) increased to varying degrees. In order to further reveal the molecular mechanism of MT-mediated salt tolerance of alfalfa, transcriptome analysis was performed on alfalfa seedlings. 2,181 differentially expressed genes (DEGs) were obtained in the salt-treated group, including 780 upregulated genes and 1,401 down-regulated genes, while 4,422 DEGs were obtained in the MT group, among which 1,438 were upregulated and 2,984 were downregulated. By using GO functional annotation and KEGG pathway enrichment, we found that DEGs were mainly enriched in the biosynthesis of flavonoids, isoflavones, plant hormones, Glutathione (GSH), soluble sugars and other substances, as well as in the ABC transporter and MAPK signaling pathways. Among them, the DEGs in the MT group was more enriched in these pathways, suggesting that MT can combat salt stress by regulating the expression of genes related to phytohormone and antioxidant capacity, which has important reference value for the breeding of salt-tolerant alfalfa and other crops.

Chronic kidney disease (CKD) is a growing public health issue with significant morbidity and mortality rates. Traditional diagnostics, with about 70% accuracy, often delay CKD detection, highlighting the need for more efficient methods. Recent studies indicate a potential link between CKD and auditory health, yet this relationship remains underexplored due to methodological challenges and the complexity of establishing causality. Our research utilizes data spanning from 2000 to 2020 from the National Health and Nutrition Examination Survey (NHANES), covering 12,392 participants, including 2,060 diagnosed with CKD. Through meticulous analysis employing logistic regression and Mendelian randomization, we have unearthed novel insights into the bi-directional associations between hearing impairment and CKD. Furthermore, we developed and validated a machine learning model that surpasses traditional diagnostic approaches in terms of accuracy and predictive power. These findings highlight the innovative integration of auditory examinations with demographic data to enhance CKD detection. Our approach demonstrates the potential of machine learning in transforming diagnostic methodologies, thus offering a significant advancement in the field of nephrology and public health.

In Belgium, sex work was recently decriminalized to enhance street-based sex workers’ (SSWs) health. This qualitative study explores stakeholders' perceptions of the impact of the working environment on street-based sex workers’ occupational safety, health and well-being in Brussels. In-depth interviews with seven stakeholders directly involved with SSWs were conducted with data analyzed using qualitative content analysis. The analysis of study data resulted in one theme: “A power imbalance and a lack of concerted efforts among stakeholders are detrimental to the occupational safety, health, and well-being of street-based sex workers”. In Brussels, the majority of SSWs face various challenges due to structural vulnerabilities, thus limiting their choices regarding their work environment, and further compromising their health. Limited access to resources and severe constraints within their working environment contribute to a lack of safety and adverse health outcomes. A stigma mechanism fueled by ideology and personal interests prevent the enforcement of their rights regarding their working environment, safety and health promotion. The lack of involvement of key stakeholders, especially from the public sector, prevents the majority of SSWs in Brussels from benefiting from a sound working environment and the promotion of their health, safety and well-being.

Dynamic systems which underly controlled systems are expected to increase in complexity as robots, devices, and connected networks become more intelligent. While classical stable systems converge to a stable point (a sink), another type of stability is to consider a stable path rather than a single point. Such stable paths can be made of saddles which draw in trajectories from certain regions, and then push the trajectory toward the next saddle point. These are chains of saddles are called stable heteroclinic channels (SHCs), and can be used in robotic control to represent time sequences. While we have previously shown that each saddle is visualizable as a trajectory waypoint in phase space, how to increase the fidelity of the trajectory was unclear. In this paper, we hypothesized that the waypoints can be individually modified to locally vary fidelity. Specifically, we expected that increasing the saddle value (ratio of saddle eigenvalues) causes the trajectory to slow to more closely approach a particular saddle. Combined with other parameters that control speed and magnitude, a system expressed with an SHC can be modified locally, point by point, without disrupting the rest of the path, supporting their use in motion primitives. However, even more complex trajectory shape modifications are possible. While some combinations can enable a trajectory to better reach into corners, other combinations can rotate, distort and round the trajectory in the region of a corner. In our example, modifying select saddle values produced a 32% decrease in the trajectory error of a complex trajectory produced using this system. This is an effect not visible in previous 1D studies, that can lead to different learnable and tunable representations of dynamic systems.

In Mexico viticulture represents the second source of employment in the agricultural area after the fruit and vegetable sector. In developed countries, remote sensing is widely used for vineyard monitoring, however, this tool is barely used in developing countries of Iberoamerica. In this re-search, our overall objective is to characterize two vineyards in the state of Queretaro (Mexico) using Sentinel-2 and meteorological data, specifically spectral and thermal indices. Results showed that spectral indices obtained from Sentinel-2 bands have characterized adequately the phenolog-ical evolution of the different varieties of the vineyards. The Modified Soil-Adjusted Vegetation Index (MSAVI) was adequately used to discriminate the first stages of vineyards, while the Nor-malized Difference Vegetation Index (NDVI) was useful to monitor vineyards during the rest stages of vineyards. Thermal indices have shown that the best grape varieties were those that can adapt to both cooler and warmer temperatures, have a reasonable ripening period, and can produce wines with balanced acidity and flavors. In conclusion, the combination of meteorological (including thermal indices) and remote sensing data (NDVI and MSAVI) provide information for choosing the suitable grape variety for this region.

This paper presents geometric analyses of welded frames after free relaxing and vibratory stress relief (VSR). Respected frames were tested components of a prototype packaging machine. Two types of relaxation were carried out to remove stresses introduced as a result of welding process. One of the frame was subjected to free relaxing, while the other one to accelerated vibration relaxing. Detection of the frame geometry changes was performed using a photogrammetric system. In addition, an evaluation of the geometry change was conducted for fifteen variants of steel frame support. A comparative analysis of the geometric deviations of the frames after free and vibratory stress relief confirmed the assumption that the frame after vibration stress relief better reproduces the nominal dimensions. Nevertheless, it should be emphasized that after vibratory stress relief the frame is not subject to further deformation, which is a desirable effect. In the case of free relaxing, the frame undergoes dimensional changes in a random manner. In summary, carrying out accelerated vibratory stress relief allows control of spontaneous dimensional changes in the designed frame of a packaging machine resulting from spontaneous relaxation of stresses arising from the welding process. The shortening of the relaxation process of the welded frame is also an unquestionable advantage.

Control of autonomous robot motion in radial mass density field is presented. In that sense the robot motion is described as the function of the radial mass density parameters. The radial mass density field is between the maximal radial mass density and the minimal radial mass density. Between these two limited values one can use n points (n = 1, 2, . . . nmax) and calculate the related radial mass density for each point. The radial mass density is maximal at the minimal gravitational radius and minimal at the maximal gravitational radius. This conclusion is valid for Planck scale, but also for the scales that are less or higher of that one. Using the ratio of the Planck mass and Planck radius it is generated energy conservation constant with value κ = 0.99993392118. Further, in this theory it is possible to connect Planck’s and gravitational parameters as functions of the maximal (or minimal) radial mass density. In that sense the autonomous robot motion in radial mass density field is important for the control of the robot motion at micro and nano scales.

Fractals and multifractals are well-known trademarks of nonlinear dynamics and classical chaos. The goal of this work is to tentatively uncover the unforeseen path from multifractals and selfsimilarity to the framework of effective field theory (EFT). An intriguing finding is that the partition function of multifractal geometry includes a signature analogous to that of gravitational interaction. Our results also suggest that multifractal geometry may offer insights into the non-renormalizable interactions presumed to develop beyond the Standard Model scale.

_{Superconducting foams of YBa$_2$Cu$_3$O$_y$ (YBCO) are proposed as trapped field magnets or supermagnets. The foams with an open-porous structure are light-weight, mechanically strong and can be prepared in large sample sizes. The trapped field distributions were measured using a scanning Hall probe on various sides of an YBCO foam sample after field-cooling in a magnetic field of 0.5 T produced by a square Nd-Fe-B permanent magnet. The maximum trapped field (TF) measured is about 400 G (77 K) at the bottom of the sample. Several details of the TF distribution, the current flow and possible applicatons of such superconducting foam samples in space applications, e.g., as active elements in flux-pinning docking interfaces (FPDI) or as portable strong magnets to collect debris in space, are outlined.}

We propose a novel unsupervised semantic segmentation method for fast and accurate flood area detection utilizing color images acquired from Unmanned Aerial Vehicles (UAVs). To the best of our knowledge, this is the first fully unsupervised method for flood area segmentation in color images captured by UAVs, without the need of pre-disaster images. The proposed framework addresses the problem of flood segmentation based on parameter-free calculated masks and unsupervised image analysis techniques. First, a fully unsupervised algorithm gradually excludes areas classified as non-flood utilizing calculated masks over each component of the LAB colorspace, as well an RGB vegetation index and the detected edges of the original image. Unsupervised image analysis techniques, such as distance transform, are then applied, producing a probability map for the location of flooded areas. Finally, flood detection is obtained by applying the hysteresis thresholding segmentation. The proposed method is tested and compared with variations, and other supervised methods in two public datasets, consisting of 953 color images in total, yielding high-performance results, with 87.4% and 80.9% overall accuracy and F1-Score, respectively. The results and computational efficiency of the proposed method show that it is suitable for on board data execution and decision-making during UAVs flight.

The main purpose of this work was to tests of form and size of fatigue wear of the top layer of oil gear pump wheel (3PW-BPF-24). The object of tests was operated during a determined number of hours at strictly controlled operational and environmental parameters. A microscope of focal differentiation by Alicona InfiniteFocus G4 (with Focus-Variation optical measuring technology) was used for an identification, measurement and description of noticed superficial defects, which resulted from the fatigue process of the top layer and an earlier thermochemical treatment. The work was finished with an analysis of obtained results (based on the analysis of 3D scans) and conclusions concerning about optimization of the thermal treatment. Taking into consideration the presented results (suggestions) in the technology of improving strength properties of gear wheels (of this type oil pumps) may render it possible to obtain an appropriate fatigue endurance of the top layer, i.e. a minimization of observed superficial defects.

The aim of this paper is to establish a valid procedure for better understanding all the phenomena associated with the high-speed machining of Glass Fibre Reinforced Plastic (GFRP) composites. Both rectangular and circular specimens were machined at high speeds (up to 50 m/min) in order to understand what occurred for all values of fiber orientation angles during machining operations. An innovative testing methodology was proposed and studied to investigate the phenomenon of burr formation and thus understand how to avoid it during machining operations. To this end, the forces arising during the machining process and the roughness of the resulting surface, were carefully studied and correlated with the cutting angle. Additionally, the cutting surface and chip morphology formed during cutting tests were examined using a high-speed camera. Close correlations are found between the variations of the cutting forces' signals and the trends of the roughness and the morphology of the machined surface.

The work is devoted to the development of methods for constructing asymptotic formulas as x→∞ of a fundamental system of solutions of linear differential equations generated by a symmetric two-term differential expression of odd order. The coefficients of the differential expression belong to classes of functions that allow oscillation (for example, those that do not satisfy the classical Titchmarsh-Levitan regularity conditions). As a model equation, the 5th order equation i2p(x)y′′′′′+p(x)y′′′′′+q(x)y=λy, for which various cases of behavior of the coefficients p(x),q(x), is investigated. New asymptotic formulas are obtained for the case when the function h(x)=−1+p−1/2(x)∉L1[1,∞) significantly influences the asymptotics of solutions to the equation. The case when the equation contains a nontrivial bifurcation parameter is studied.

To enhance the performance of visual SLAM in underwater environments, this paper presents an enhanced front-end method based on visual feature enhancement. The method comprises three modules aimed at optimizing and improving the matching capability of visual features from different perspectives. Firstly, to address issues related to insufficient underwater illumination and uneven distribution of artificial light sources, a brightness consistency recovery method is pro-posed. This method employs an adaptive histogram equalization algorithm to balance the brightness of images. Secondly, a method for denoising underwater suspended particulates is introduced to filter out noise from the images. After image-level processing, a combined underwater acousto-optic feature association method is proposed, which associates acoustic features from sonar with visual features, thereby providing distance information for the visual features. Finally, utilizing the AFRL dataset, the improved system incorporating the proposed enhancement methods is evaluated for performance against the OKVIS framework. The system achieves better trajectory estimation accuracy compared to OKVIS and demonstrates robustness in underwater environments.

The high prevalence of human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma (OPSCC) is well-established, with p16 expression being a strong predictor. HPV-related tumors exhibit unique mechanisms targeting p16 and p53 proteins. However, re-search on HPV prevalence and the combined predictive value of p16 and p53 expression in head and neck cutaneous squamous cell carcinomas (HNCSCC), especially in Asian populations, is limited. This retrospective study surveyed 62 HNCSCC patients (2011–2020), excluding those with facial warts or other skin cancers. All patients underwent wide excision and biopsy. Immuno-histochemical staining for HPV, p16, and p53 yielded both positive and negative results. The relevance of each marker was investigated by categorizing the tumor locations into high-risk (Area H) and mid-risk (Area M) zones based on recurrence frequency. Of the 62 patients, 20 (32.26%) were male, with an average age of 82.27 years (26–103). Area H included 19 cases (30.65%), with the eyelid and lip being the most common sites (five cases, 8.06%). Area M in-cluded 43 cases (69.35%), with the cheek being the most common site (29 cases, 46.77%). p16 ex-pression was positive in 24 patients (38.71%), p53 expression in 42 patients (72.58%), and HPV in five patients (8.06%). No significant association was found between p16 expression and HPV presence (p > 0.99), with a positive predictive value of 8.33%. This indicates that p16, a surrogate marker of HPV in OPSCC, is not a reliable marker for HPV in HNCSCC. This study enhances our understanding of the relationship between HPV, p53, and p16 in HNCSCC in Asian populations and offers valuable insights for further research.

Critically ill patients treated in the intensive care unit (ICU) can present many abdominal conditions that need a prompt diagnosis and timely treatment because of their general frailty. Clinical evaluation and diagnostic tools like ultrasound or CT scan are not reliable or feasible in these patients. Bedside laparoscopy (BSL) is a minimally invasive procedure that allows surgeons to assess the abdominal cavity directly in the ICU, thus avoiding unnecessary exploratory laparotomy or incidence related to intra-hospital transfer. We conducted a review of the literature to summarize the state-of-the-art of BSL. Medline, The Cochrane Central Register of Controlled Trials (CENTRAL), and Scopus databases were utilized to identify all relevant publications. Indications, contraindications, technical aspects, and outcomes are discussed. The procedure is safe, feasible, and effective. When other diagnostic tools fail to diagnose or exclude an intra-abdominal condition in ICU patients, BSL should be preferred over exploratory laparotomy.

This paper proposes a design for a platform-based Multi-phase Interleaved Synchronous Buck Converter (MISBC) using Silicon (Si) based Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs). A custom platform was developed to compare the theoretical performance of a MISBC circuit simulated with Multisim and compared it with a prototype that was built at Western Sydney University. The work disclosed in this manuscript describes some steps adopted during the selection of each component and technical considerations taken during the design of the Printed Circuit Board (PCB). The platform designed has a maximum power output of 260 Watts, with a buck reduction of the nominal voltage from 97 Volts to 24 Volts at a maximum switching frequency of 50 kHz. This switching frequency is achieved with an open-loop circuit configuration coupled with synchronized signal generators, used to validate the dead band required between the activation of each MOSFET implemented in a half bridge configuration. A summary of the results based on the duty cycle required to achieve the buck voltage desired highlights the advantages of each operating mode of the MISBC circuit, where the theoretical performance is compared against the data acquired during functional evaluations of the prototype, allowing further interpretations towards the optimal control algorithm required to maximize the performance output of MISBC circuits.

The escalating demand for multifunctional and advanced materials for growing industries has turned scientific exploration to graphene-based hybrid filler polymer composites. The introduction of graphene with other fillers into polymer matrices results in astonishing properties and thus has gained significant attention in recent years. This study addresses the significance of graphene-based hybrid filler polymer composites in progressive materials science and engineering. The paper encloses some traditional and current preparation techniques employed in the fabrication of composites and a comprehensive review of successfully prepared graphene hybrid polymer composites with enhanced mechanical, thermal, and electrical properties reported in published research. The role of different factors, e.g., filler type, aspect ratios, filler-matrix compatibility, dispersion effects, homogeneity, filler orientation through polymer matrices, and curing conditions, are summarized. Finally, the applications in heavy industries, e.g., aerospace, electronics, energy storage, and automotive sectors were also analyzed. We hope this study will serve as a practical resource for new researchers and practitioners to understand and harness the full potential of these composites in various scientific and industrial fields.

This paper introduces a novel decision-making approach grounded in insights into human visual perception of change. Modern technologies such as internet of things (IoT) provide us with large amounts of sensor data that need to be processed in real time and decisions made with a high degree of accuracy and reliability. Artificial intelligence (AI) methods are welcome in this context and need to be upgraded to meet actual challenges. While modern computing capabilities facilitate rapid data processing, the real-time demands of vast sensor data necessitate swift responses across the cyber chain, often leading to compromises in solution quality to circumvent combinatorial search complexities. Determining the adequacy of a solution entails varied approaches, often relying on heuristic methodologies. We illustrate our original approach with an example of a selected detail of a differential evolution algorithm, where we have to make a decision to adopt the best solution so far. We propose an approach inspired by human perceptual features that exploits the Weber-Fechner law to emulate human judgements, and offers a promising way to improve decision making in AI applications and real-time requirements fulfillment. Our proposed methodology demonstrates applicability across diverse AI scenarios involving numerical data, effectively mirroring human perception abilities.

The diel variations of viruses (< 0.2 μm), picoplankton (0.2—2 μm; heterotrophic bacteria, Syn-echococcus spp., Prochlorococcus spp. and picoeukaryotes) and nanoplankton (2—20 μm; hetero-trophic nanoflagellates and pigmented nanoflagellates) were investigated for 2 days with about 4 hours of temporal sampling in spring 2024 in coastal surface waters of the subtropical western Pacific. A period of wind change associated with rain and increased turbulence, disrupted diel patterns of the overall microbial communities during the second cycle. The abundance of bacteria did not follow a consistent diel pattern, while viral abundance positively correlated with bacterial abundance. Synechococcus spp. and Prochlorococcus spp. grew during the light period and with peak abundance at night, exhibited marked diel variability, however, opposite patterns were observed in picoeukaryotes. According to Synechococcus spp. and Prochlorococcus spp. diel changes, nano-flagellate grazing could control their abundances and may explain temporally varying picocyanobacteria abundances. As we observed in the culture experiments, the results showed a significant increase in picoeukaryotic abundance from noon to nighttime, and a decrease in bacterial abundance during nighttime, to show the prey-predator cycle. Our study suggests picoeukaryotes could serve as bacteria predators by being mixotrophs. Future studies aiming to understand the interactions between prokaryotes and picoeukaryotes within marine microbial communities should take these differences into account.

(1) Background: The aim of the research was to present and emphasize the importance of magnetic resonance imaging (MRI) in diagnosing Achilles tendon (AT) ruptures by presenting case reports. (2) Materials and Methods: The sample of respondents included 7 patients (4 males and 3 females, 2 athletes and 5 non-athletes), aged 25 to 58 years, with AT injuries, who were examined and treated at the Institute for Treatment and Rehabilitation "Niška Banja", Niš, Serbia. Ankle examinations with MRI were conducted using the Esaote O-scan 0.3 T machine. The examinations were performed without the application of a paramagnetic contrast agent and without the use of anesthesia. Results: The MRI method's sensitivity and overall diagnostic accuracy were excellent, with 100% true positives. In our study, the method accurately detected the presence, location, and severity of AT injuries in all cases. MRI is an important and reliable method for detecting AT injuries, classifying them, monitoring the course of recovery, and assessing the effects of therapy. Conclusions: An unrecognized or delayed diagnosis of an AT injury can lead to chronic changes. Timely diagnosis (clinical examination, ultrasonography, magnetic resonance imaging) and appropriate treatment (conservative or operative) enable patients to return to normal activities, including sports. Unfortunately, the use of MRI is limited by restricted access and the cost of the examination.

This article discusses the application of thermal quality control methods for plant tissues. The purpose of the work is to determine the optimal parameters of thermal impact on a spherical-shaped plant control object, ensuring the detection of surface and subsurface defects. The authors of the work proposed mathematical models of the temperature field for a spherical body with defects and a flat sample when exposed to the thermal influence of a pulsed source. As a result of the use of mathematical models, the thermophysical characteristics of plant tissues of varying degrees of disease damage were obtained, which made it possible to simulate the temperature field of the control object and obtain an image of classified tissues. The developed recommendations made it possible to select the optimal parameters of the thermal effect on the test object.

This study, conducted with meticulous attention to detail, comprehensively examines the state of plants and their adaptation to Kazakhstan's extra-arid climatic zone of the Mangistau. It uses the collections of woody plants from the Mangyshlak Experimental Botanical Garden in Aktau as a case study and extrapolates the results to the entire region. The study area is arid and unsuitable for many plants, so examining physiological adaptation mechanisms and strategies for preserving plants in unfavourable conditions is crucial. The study employed a range of methods, including the measurement of the intensity of transpiration, leaf hydration, and the content of chlorophyll A, B, and carotenoids. These methods were chosen for their proven effectiveness in similar studies and their ability to provide accurate and reliable data. The samples were also assessed using a point system for resistance to drought, phytophagy, gas tolerance, salt tolerance, winter hardiness, and soil fertility. The results obtained and entered into the IEBG platform “DinTseR” to assess the value of the introduction using a diagnostic scale revealed a high variability (up to 51.7-52.2%) of physiological indicators of growth and development. The highest values of transpiration intensity were observed in deciduous trees and shrubs, rose varieties (205-243 mg/g fresh leaf mass per hour), leaf water content - in climbing plants (68.9%), chlorophyll A and B content - in deciduous plants, and plants - old trees, fruit trees and varietal roses (3.46-3.93 and 1.34-1.84%). Their concentration in coniferous species is almost two times lower (0.63%). A correlation was also made between various significant factors. Twenty regression equations and forecasts have been identified that can be used to diagnose and assess resistance, thereby reducing the cost of determining the introduction value in the conditions of Mangistau. These findings are essential in understanding and preserving the unique flora of the Mangistau region.

During the last decade, Bangladesh has been experienced a significant climatic anomalies which lead to an increase in magnitude and frequency of various climate relate extreme events. Climate scientists substantiate that global temperature and precipitation pattern is expected to change, which may result in consequential impact on agriculture, livelihood, and ecosystem. Bangladesh is therefore likely to face substantial challenges in the coming decades. In order to adequately understand this complex, dynamic phenomena, Analyzing historical Climate change scenarios as well as projecting its future trends is a great concern for researcher. This study aims to analyzes/ historical climatic data from (1901-2020), and predict future temperature and precipitation patterns in Bangladesh using CMIP6 data. Data used in this study (Observed data is from CRU TS 4.05 and future data is from CMIP6) have been acquired from WorldClim v2.1. Various methods including correlation, regression, standard deviation, correlation matrix, percentiles, cell statistics, and IDW interpolation were performed to analyze the trends, variability and spatial patterns of temperature and rainfall. This study revealed that Over the historical study period (1901-2020) Bangladesh has been experienced a significant warming trend with an average increase in temperature 2°C and with annual decline of the total precipitation 607.26 mm along with a shift towards drier conditions despite weak correlation with hotter years. Projected climate models represents that Bangladesh minimum temperature is expected to increase from 1°C to 4.4°C as well as maximum temperatures from 1°C to 4.1°C by 2100. Moreover, projected precipitation is expected to increase by 480.38 mm, with the biggest rises during monsoon months. Regional variations in temperature and precipitation are again expected, with the Southeast (SE) likely experiencing the most significant warming and the Northeast (NE) seeing the most substantial increase in precipitation.

Catastrophic mass flows originating from the high mountain cryosphere often cause hazard cascades. With increasing human activities in the alpine region and the sensitivity of glaciers, snow and permafrost to climate warming, the cryospheric hazard risks tend to be more active in the Tibetan Plateau(TP). The remoteness and inaccessibility of high mountain regions make the remote sensing technology the most effective approach for monitoring and investigating the cryospheric hazards. Exploring the evolution process and impact of ice avalanches and subsequent hazards are crucial to understand drivers and nature of mass flow process chain in order to prevent and mitigate potential hazard consequences. In this study, the glacier and ice-rock avalanches occurred in Arutso and Sedongpu basins in Tibet were investigated on the basis of Sentinel-2 time-series images and in-situ investigation, the evolution process of these events were reconstructed, and impacts and driving factors were analyzed. The massive Chamoli rock-ice avalanche occurred in February 2021 in the western Himalayas was also reviewed using using same methods. The study shows that Arutso glacier No. 53 (Arutso-53) avalanche completely melted away in July 2018 after two years from occurrence to final disappearance, while Arutso glacier No. 50 (Arutso-50) avalanche completely melted by the end of August 2023 after lasting for seven years. Four large-scale ice-rock avalanche and debris flow events in the Sedongpu basin in 2017 and 2018 not only had significant impacts on the river flow, landscape and geomorphologic shape in the basin, but also caused serious disasters in the basin and downstream. In March 2021, a small-scale ice-rock avalanche and debris flow event occurred again in the Sedongpu basin. The glacier and ice-rock avalanches occurred in Tibet area were mainly induced by climate warming, heavy precipitation and seismic activity, which acting on specific topographic and geomorphic structure of glacier properties in the high mountain regions. Catastrophic hazard events originating from the high-elevation glacier and ice-rock collapses in the mountain cryosphere and subsequent hazard cascades in the TP and Himalayas highlight the importance of mountain hazard monitoring, early warning systems and sustainable mountain development.

Introduction: Pulmonary hypertension (PH) in systemic sclerosis (SSc) can be caused by different pathophysiological mechanisms, including precapillary PH (pulmonary arterial hypertension), post-capillary PH (secondary to left heart diastolic dysfunction), or combined pre- and post-capillary PH. To unmask occult post-capillary PH, fluid loading with saline during right heart catheterization (RHC) is recommended. In the present study, we investigated the response to fluid challenge test (FCT) in patients with SSc who were referred for RHC due to their high likelihood of PH on screening echocardiography. Methods: Demographic data, clinical characteristics, echocardiographic and RHC data, and cardiac magnetic resonance imaging (CMR) results were obtained from the patients' hospital records or by contacting their rheumatologist. A positive FCT was defined as an increase in pulmonary capillary wedge pressure (PCWP) to more than18 mmHg with rapid saline infusion. Patients were followed for a median (IQR) of 15 (7-20) months. Results: Of the total 98 scleroderma patients 34 patients (29 female) were included. The mean age (SD) was 50.6(8.2) years. Baseline RHC data showed that 20 patients had no PH and 14 patients had mild precapillary PH (mPAH). Ten patients (50%) of the patients with no PH and 10 patients (71.4%) with mPAH had a significant increase in PCWP after a fluid loading. There was no statistically significant difference between the patients with positive and negative FCT in terms of the presence of LGE/inflammation on CMR examination. During follow-up, 3 patients died. Mortality was due to SSc-related complications in two patients. Conclusion: This study provides preliminary evidence that FCT may be a useful adjunct to baseline RHC testing to identify SSc patients with latent postcapillary PH. Further studies are needed to confirm these results and determine the optimal role of the fluid challenge test in the clinical management of SSc patients with suspected PH.

Aluminum (Al) toxicity and low phosphorus availability (LP) are the top two co-existing edaphic constraints limiting agriculture productivity in acid soils. Plants have evolved versatile mechanisms to cope with the two stresses alone or simultaneously. However, the specific and common molecular mechanisms, especially those on flavonoids and carbohydrate metabolism, are still unclear. Laboratory studies were conducted on two wheat genotypes, Fielder (Al-tolerant and P-efficient) and Ardito (Al-sensitive and P-inefficient), exposed to 50 μM Al and 2 μM Pi (LP) in hydroponic solutions. After 4 days of stress, wheat roots were analyzed via transcriptomic and targeted metabolomic techniques. A total of 2296 differentially expressed genes (DEGs, 1535 up and 761 down) under Al and 3029 DEGs (1591 up and 1438 down) under LP were identified in Fielder. Similarly, 4404 DEGs (3191 up and 1213 down) under Al and 1430 DEGs (1176 up and 254 down) under LP were identified in Ardito. The GO annotation analysis results that 4079 DEGs annotated to the metabolic processes term. These DEGs were significantly enriched in the phenylpropanoid, flavonoid, flavone and flavonol biosynthesis, and carbohydrate metabolism pathways by performing the KEGG enrichment analysis. The targeted metabolome analysis detected 19 flavonoids and 15 carbohydrate components in Fielder and Ardito under Al and LP. More responsive genes and metabolites were involved in flavonoid metabolism under LP than Al in the Fielder, while an opposite trend in the Ardito. In the carbohydrate metabolism pathway, the genes and metabolites were higher in Fielder than in Ardito. The combined transcriptome and metabolome analysis revealed that the flavonoid and carbohydrate genes and metabolites differed between Fielder and Ardito under Al and LP, which may be an important reason for Fielder’s high Al and LP resistance. The results of this study lay a foundation for pyramiding genes and breeding multi-resistance varieties.

In this study we have investigated the effect of the addition of Nb2O5 (up to 5 mol%) on the structure and luminescent properties of ZnO-B2O3 glass doped with 0.5 mol % Eu2O3 by using of infrared (IR), Raman and photoluminescence (PL) spectroscopy. Physical properties as molar volume, oxygen packing density and glass transition temperature were determined using the results of differential thermal analyisis (DTA) and Archimedes principle for density. IR and Raman spectra revealed that niobium ions incorporate into the base zinc borate glass as NbO4 trtraherda and NbO6 octahedra. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (392 nm) excitation using the sharp 7F0 - 5L6 transition of Eu3+. The integrated fluorescence intensity ratio R (5D0 → 7F2/5D0 → 7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites. The higher Еu3+ luminescence emission observed in zinc borate glasses containing 1÷5 mol% Nb2O5 compared to the Nb2O5-free zinc borate glass evidences that Nb2O5 is suitable component for modification of host glass structure and improving the emission intensity.

Recent technological advancements in conservation genetics and genomics have resulted in diverse tools for aiding conservation of species. The precision and resolution of high throughput sequencing technologies provide valuable insights to aid conservation decisions, but these technologies are often financially unfeasible or unavailable in resource constrained countries. Inter-Simple Sequence Repeat (ISSR) markers, when combined with sensitive automated detection systems, provide a simple, cheap means to investigate genetic diversity and discriminate closely related species. Here we apply this technology to assess genetic diversity and taxonomic delimitation in the Encephalartos eugene-maraisii species complex, a highly threatened, taxonomically dubious group of cycads in South Africa. Our analyses support taxonomic singularity of E. dyerianus, E. dolomiticus and E. eugene-maraisii. Relationships between E. nubimontanus and E. cupidus remain uncertain. E. middelburgensis samples showed no clustering but had poor amplification success. This study demonstrates the suitability of automated ISSR fingerprinting as a method for plant conservation studies, especially in resource-constrained countries, and we make recommendations as to how this methodology can be effectively implemented.

The spread of micro- (MPs) and nanoplastics (NPs) in the environment has become a significant environmental concern, necessitating effective removal strategies. In this comprehensive scientific review, we examine the use of magnetic nanoparticles (MNPs) as a promising technology for the removal of MPs and NPs from water. We first describe the issue of MPs and NPs and their impact on the environment and human health. Then the fundamental principles of using MNPs for the removal of these pollutants will be presented, emphasizing that MNPs enable selective binding and separation of MPs and NPs from water sources. Furthermore, we provide a short summary of various types of MNPs that have proven effective in the removal of MPs and NPs. These include ferromagnetic nanoparticles, MNPs coated with organic polymers, as well as nanocomposites and magnetic nanostructures. We also review their properties, such as magnetic saturation, size, shape, surface functionalization and stability, and their influence on removal efficiency. Next, we describe different methods of utilizing MNPs for the removal of MPs and NPs. We discuss their advantages, limitations, and potential for further development in detail. In the final part of the review, we provide an overview of existing studies and results demonstrating the effectiveness of using MNPs for the removal of MPs and NPs from water. We also address challenges that need to be overcome, such as nanoparticle optimization, process scalability, and the removal and recycling of nanoparticles after the completion of the process. This comprehensive scientific review offers an extensive insight into the use of MNPs for the removal of MPs and NPs from water. With improved understanding and the development of advanced materials and methods, this technology can play a crucial role in addressing the issue of MPs and NPs and preserving a clean and healthy environment.

As matrix representations of magic labelings of related hypergraphs, magic squares and their various variants have been applied to many domains. Among various subclasses, trimagic squares have been investigated for over a hundred years. The existence problem for trimagic squares with singly even orders and orders 16n has been solved completely. However, very little is known for the existence of trimagic squares with other even orders except for the only three examples and three families. We construct normal trimagic squares by using product constructions, row-square magic rectangles, and trimagic pairs of orthogonal diagonal Latin squares. We give a new product construction: For positive integers p, q, and r having the same parity other than 1, 2, 3, 6, if normal p × q and r × q row-square magic rectangles exist, then a normal trimagic square with order pqr exists. As its application, we construct normal trimagic squares of orders 8q^3 and 8pqr for all odd integers q not less than 7 and p,r ∈ {7, 11, 13, 17, 19, 23, 29, 31, 37}. Our construction can easily be extended to construct multimagic squares.

Software systems are often maintained by a group of experienced software developers, in order to ensure that faults which may bring the system down are less likely. Large turnover in organizations such as CERN makes it important to think of ways of onboarding newcomers on a technical project rapidly. This paper focuses on optimizing the way that people get up-to-speed on the business logic and technologies used on the project, using a knowledge-imbued large language model that is enhanced using domain-specific knowledge from the group or team’s internal documentation.

This study demonstrates the efficacy of structured pruning and architectural fine-tuning on the YOLOv7-tiny model for eye state detection, emphasizing optimization for real-time applications. Structured pruning significantly reduced the model's complexity and storage size while maintaining high detection accuracy, as evidenced by stable precision, recall, and mAP@.5 metrics across iterations. Further fine-tuning adjusted the model's width and depth, optimizing efficiency and processing speed without compromising performance. These optimizations yielded YOLOv7-tiny variants that are both computationally efficient and accurate, suitable for resource-constrained environments. The findings highlight the critical role of model optimization in deploying effective neural networks for specific detection tasks in real-time scenarios.

Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced stage WTs, of which 7 cases are chemotherapy-resistant. Our analysis revealed four genes (ALPK2, C16orf96, PRKDC, and SVIL) that correlated with chemotherapy resistance and reduced disease-free survival in ad-vanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemo-therapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profile of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.

Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to be more cost-effective, more accurate, and safer compared to traditional field observations, considering factors such as equipment cost, crew safety, and data collection efficiency. Consequently, there is a pressing need to develop more efficient methodologies for promptly, safely, and economically acquiring roadway geometry data. While image processing has previously been regarded as a time-consuming and error-prone approach for capturing these data, recent developments in computing power and image recognition techniques have opened up new avenues for accurately detecting and mapping various roadway features from a wide range of imagery data sources. This research introduces a novel approach combining image processing with a YOLO-based methodology to detect turning lane pavement markings from high-resolution aerial images, specifically focusing on Florida's public roadways. Upon comparison with ground truth data from Leon County, Florida, the developed model achieved an average accuracy of 87% at a 25% confidence threshold for detected features. Implementation of the model in Leon County identified approximately 3,026 left turn, 1,210 right turn, and 200 center lane features automatically. This methodology holds paramount significance for transportation agencies in facilitating tasks such as identifying deteriorated markings, comparing turning lane positions with other roadway features like crosswalks, and analyzing intersection-related accidents. The extracted roadway geometry data can also be seamlessly integrated with crash and traffic data, providing crucial insights for policymakers and road users.

As modern technologies, particularly home assistant devices, become more integrated into our daily lives, they are also making their way into the domain of energy management within our homes. Homeowners, now acting as prosumers, have access to detailed information in 15-minute or even 5-minute intervals, including weather forecasts, outputs from Renewable Energy Sources (RES)-based systems, appliance schedules and the current energy balance, which details any deficits or surpluses along with their quantities and the predicted prices on the Local Energy Market (LEM). The goal for these prosumers is to reduce costs while ensuring their home’s comfort levels are maintained. However, given the complexity and the rapid decision-making required in managing this information, the need for a supportive system is evident. This is particularly true given the routine nature of these decisions, highlighting the potential for a system that provides personalized recommendations to optimize energy consumption, whether that involves adjusting the load or engaging in transactions with the LEM. In this context, we propose a recommendation system powered by Large Language Models (LLM), Scikit-llm and Zero-Shot Classifiers, designed to evaluate specific scenarios and offer tailored advice for prosumers based on the available data at any given moment. Two scenarios for a prosumer of 5.9 kW are assessed using candidate labels, such as Decrease, Increase, Sell and Buy.

The objective of this research is to propose a utility function that calculates the possible level of satisfaction that a music consumer would achieve after listening to a song according to the emotional response obtained from a song. Assuming that the consumer's musical preferences are satisfied if the predominant emotions of his current emotional state increase; the probabilistic emotional-musical model (Lugos Abarca, 2023) is used to construct such a utility function. By posing a hypothetical scenario, realistic results were obtained, which guarantee, in principle, its use in theoretical practice. The originality of this research lies in proposing a mathematical tool to study, quantitatively, the decision making of a musical consumer influenced by his emotions. The main conclusion being its importance in the music industry, since the function could predict, theoretically, whether a song will be accepted or rejected by the consumer in comparison with the competition.

The growing interest in modern polymer materials targeted the research on complex plastic coatings and the possibilities of modifying their features and properties during manufacturing. Today's modern coatings, including polyurea and polyurethane, are among the most modern developed resins. Compared to other polymer coatings, they are distinguished by their versatility, strength, and durability. They undoubtedly represent the next step in the evolution of coatings. Advances in coating technology have also led to the development of spray, injection, and roto-cast application equipment, improving polyurea-based elastomers’ performance. For many years, there has been much interest in increasing the flame resistance of polymers. This is dictated by safety considerations and the increasing requirements for the flammability of plastics, the area of application of which is growing every year. This text attempts to provide an overview of current research on flame retardant composites. Particular attention was paid to polyurea (PU) and polyurea-based hybrids and the application areas of polyurea coatings. The paper defines flame retardants, discusses how they work, and presents types of flame retardants and the current trends of their usage in the production of plastics.

Resource pricing in cloud computing has become one of the main challenges for cloud providers. The challenge is determining a fair and appropriate price to satisfy users and resource providers. To determine a fair price, it is necessary to consider the conditions and needs of both parties: provider and user. This research tries to provide a pricing mechanism for cloud computing based on game theory. The proposed mechanism takes into account three factors including fault possibility, interaction between virtual machines, and energy consumption to reach a fair price. In the proposed game, the provider decides on the price of the virtual machine which can be offered to the user on each physical machine and the user decides between the virtual machines offered to run its application. The whole game is implemented as a function of the resource broker component. The proposed mechanism is simulated and evaluated using the CloudSim simulator. Its performance is compared with several previous recent mechanisms. According to the results, the proposed mechanism has been able to determine a more reasonable price for the user and the provider which increases the overall profitability of the cloud system.

This paper introduces a fuzzy logic-based autonomous ship-deck landing system for fixed-wing Unmanned Aerial Vehicles (UAVs). The ship is assumed to maintain a constant course and speed. The aim of this fuzzy logic landing model is to simplify the task of landing UAVs on moving ships in challenging maritime conditions, relieving operators from this demanding task. The designed UAV ship-deck landing model is based on a fuzzy system comprised of three interconnected subsystems. Each subsystem consists of three inputs and one output incorporating various fuzzy rules to account for external factors during ship-deck landings. Specifically, the Fuzzy Logic System (FLS) takes inputs such as the airspeed, the relative wind direction and speed, the range from the deck and the UAV's flight altitude. The FLS outputs provide data on the Speed of the UAV relative to the ship’s velocity, the Bank Angle, and the Angle of Descent of the UAV. The performance of the designed intelligent ship-deck landing system is evaluated using the standard configuration of MATLAB Fuzzy Toolbox.