HPV51 belongs to group I high-risk HPV (hrHPV) genotypes with a high prevalence of infection in numerous epidemiological studies, although its occurrence varies across geographical regions. To better understand the presence of variants and genetic variation of HPV51, this study aimed to perform a phylogenetic analysis of the E6, E7 and L1 regions to detect the hrHPV variants circulating in women referred to colposcopy in two different Italian regions (Lombardy and Sardinia). Cervical samples were tested using Anyplex™ II HPV HR Detection. HPV51 positive samples were further analysed using previously described PCR protocols to obtain sequences of E6, E7 and L1. A positivity rate for HPV51 of 7.4% (26/351) and 13.6% (11/81) was found in Lombardy and Sardinia, respectively. The majority (34 out of 35) of the analyzed sequences clustered into the A lineage and only one sequence was grouped into B lineage. L1 capsid gene showed the presence of different mutations but none under positive selective pressure. Three nucleotide polymorphisms T6311G, A6312T and G6313A related to the two aminoacidic mutations V264G and G265S were found among all analysed sequences. This study contributes to implement data regarding the molecular epidemiology of HPV but additional analysis on a larger number of sequences is necessary to better understand the role of HPV variants in cervical lesions development.

With the widespread application of artificial intelligence technology in various industries, users' attention to privacy and data security has increased significantly. Federated learning, as a new technology paradigm combining privacy-enhanced computing and artificial intelligence, resolves the contradiction between data security and open sharing. This paper presents the benefits of federated learning in terms of privacy, real-time processing, model robustness, compliance and cross-industry applications. At the same time, when combined with Edge AI technology, federated learning promotes the decentralisation of intelligent systems, improving data privacy protection and model accuracy. This paper also discusses the application cases of federated learning in the medical field, through local data processing and model training, effectively protecting user privacy, realizing medical data sharing and model optimization, and promoting the development of artificial intelligence.

Background: Colorectal cancer (CRC) can significantly impact mental health, increasing suicide risk. Variables such as pain and threat perception may be crucial. This study aims to identify predictors of suicide risk in individuals with CRC. Methods: A total of 71 participants (76.06% men) aged 27 to 88 years (M = 65.18, SD = 12.02) were assessed using the SF-36 for pain, the Brief Illness Perception Questionnaire (B-IPQ) for threat perception, the Hospital Anxiety and Depression Scale (HADS) for emotional distress, and the Plutchik suicide risk scale for suicide risk. Descriptive, comparative, and correlational analyses were performed, followed by a linear regression analysis. Results: Nearly 20% of participants exhibited high suicide risk. There was a moderate to high association between suicide risk and the perception of threat, pain, and emotional distress. The linear regression model explained 39% of the variance in suicide risk, with threat perception, pain, and emotional distress as significant predictors. Conclusions: These results indicate the need for multidisciplinary care for individuals with CRC, including emotional support from health psychologists, and holistic, human-centered care from nursing and medical professionals. Future research is necessary to further explore these relationships and improve patient care strategies.

Photovoltaic (PV) systems, which are renewable energy sources, are increasingly being utilized in distributed generation. To maintain a stable energy balance, energy storage systems such as batteries (BAT) play a vital role. Electric vehicles (EVs) offer a promising solution with rechargeable battery systems for operation. The BATs must maintain their state of charge within design boundaries, despite intermittent PV and load power fluctuations, and advanced power control and management techniques are essential for their effective operation. The article evaluates an intelligent controller that uses a Sliding Mode Control adaptive deep learning algorithm Convolutional Neural Networks (SMC-CNN) and a unique Strategy for managing supervisory power. (SPMS) for photovoltaic systems with battery energy storage for better regulation of DC bus voltage. SMC-CNN offers exceptional resilience and seamless functionality, minimizing fluctuations in DC bus voltage in the control strategy design requirements. The primary goals are maintaining a consistent power supply and ensuring continuous service by preventing system components from exceeding capacity. This study aims to enhance the control of DC bus voltage in the PV and battery system, with the primary significance focusing on the following aspects. The advanced SPMS has been created, incorporating control system constraints to enhance SOC balancing speed and reduce fluctuations in DC bus voltage. Power flow management involves optimizing energy flow between the PV system, battery system, and load while minimizing battery capacity requirements. The proposed SMC-CNN and SPMS are demonstrated through real-time simulation using Matlab/Simulink, as demonstrated in comprehensive case studies.

(1) Background: Acute myocardial infarction in pregnancy (pAMI) is a rare event, often caused by non-classical factors rather than atherosclerosis. The management of such a complicationrequires a multidisciplinary team and it is important to bring together the specialities involved to ensure that these teams are coordinated and ready to respond. The management of pAMI poses unique challenges as it requires considering both maternal and fetal well-being. (2) Methods: We present the case of a 36-week pregnant woman who presented with antero-lateral ST elevation myocardial infarction (STEMI) complicated by cardiogenic shock. To ensure comprehensive decision-making, an emergency Pregnancy Heart Team meeting was convened, comprising interventional cardi-ologists, gynecologists, and anesthesiologists. The team prioritized interventional treatment for pAMI, according to ESC guidelines, and opted for primary percutaneous coronary intervention (PCI) due to the unstable maternal condition.; (3) Results: The patient underwent primary PCI as the chosen intervention for pAMI. A rapid response gynecology team closely monitored the procedure and was prepared to intervene in case of irreversible hemodynamic compromise leading to cardiac arrest. An emergency caesarean section was deemed necessary if cardiac ac-tivity was not restored within 4 minutes.; (4) Conclusions: Managing pAMI requires a multidis-ciplinary approach that balances the maternal and fetal well-being. In this particular case, the Pregnancy Heart Team decided to prioritize interventional treatment with primary PCI due to the unstable maternal condition. The presence of a closely monitored gynecology team ensured prompt action in case of complications.

This qualitative study explores how businesses are adapting their Supplier Relationship Management (SRM) strategies to address the challenges and capitalize on the opportunities presented by evolving e-commerce trends. Through in-depth interviews with key industry stakeholders, the research investigates the integration of advanced technologies such as artificial intelligence (AI), blockchain, and the Internet of Things (IoT) into SRM practices. Findings reveal that these technologies enhance efficiency, transparency, and responsiveness within supply chains, enabling businesses to navigate complexities such as supply chain dynamics, fluctuating consumer demand, and regulatory compliance. The study identifies effective strategies employed by businesses, including enhancing communication channels with suppliers, diversifying supplier bases, and investing in technological advancements. These strategies enable businesses to mitigate risks, improve collaboration, and drive innovation, thereby maintaining competitive advantage in the digital marketplace. Collaborative practices such as joint product development, shared risk management, and co-investment in technology emerge as critical drivers of successful SRM. Ultimately, this research contributes to a deeper understanding of SRM in the context of e-commerce, offering insights into how businesses can optimize their supply chain operations amidst technological disruptions and market fluctuations. The findings underscore the importance of proactive adaptation and strategic alignment with suppliers to foster resilient and agile supply chains. As e-commerce continues to evolve, businesses must leverage these insights to refine their SRM strategies and sustain growth in an increasingly competitive environment.

The present study is to address performance of the dairy supply chain and emphasizes the significance of reliability of the chain as a fundamental and critical attribute for fulfilling the safety requirements. In order to evaluate the performance of the dairy supply chain, the present study utilizes the reliability attribute, which is an essential and informative system performance indicator. The study considers not only the inputs and outputs but also internal activities and relationships between customers, manufacturers, and suppliers. To minimize calculations and resolve uncertainties and vagueness that may be experienced in the performance evaluation process, this study proposes the use of the Fuzzy Inference System (FIS) approach and evaluates the reliability at each level of the supply chain: supply, manufacturing, and distribution. Combining the reliability of different levels, the study finally calculates the reliability of the entire supply chain. The proposed methodology offers a practical approach for evaluating the reliability performance of a dairy supply chain and can be easily extended to other industries as well. To verify the proposed methodology, a real case in the Iranian dairy industry is chosen to be studied. Results indicate that the proposed methodology can effectively identify bottlenecks or weaknesses in the dairy supply chain and help develop effective strategies to address them. Analyzing factors influencing supply chain reliability can optimize operations, reduce costs, and improve the overall quality of dairy product quality delivered to consumers.

Advanced 1H Nuclear Magnetic Resonance (NMR) relaxometry and diffusometry methods and VIS-nearIR spectroscopy combined with pH, electric conductivity (EC) and totally dissolved solids (TDS) measurements were used to assess the properties of wastewater collected from a chicken slaughterhouse in each step of the treatment process (wastewater before treatment, biologically treated wastewater, chemically treated wastewater and discharged wastewater) and from sludge. The 1H NMR Carr-Purcell-Meiboom-Gill (CPMG) and Pulsed-Gradient-Stimulated-Echo (PGSE) decay curves recorded for all samples of wastewater were analyzed by inverse Laplace transform (ILT) to obtain the distributions of transverse relaxation times T2 and diffusion coefficient D. The VIS-nearIR total absorbance, T2-values, D-values, pH, EC and TDS parameters were used for statistical analysis in principal component analysis (PCA). The 1H T2-distributions measured for the slaughterhouse wastewater lie in two main regions reflecting the amount of dissolved solids or the distribution of undissolved solids mobility. The PCA analysis successfully differentiates between polluted and less polluted types of wastewater and sludge. The wastewater treatment applied by the slaughterhouse is efficient. The recommended methods for wastewater monitoring are the NMR T2- and D-distributions and EC, TDS and NMR-D diffusion coefficient. Finally, Machine Learning AI-algorithms are used to provide prediction maps of wastewater treatment stage.

Improving photobioreactor performance for microalgae cultivation has attracted many researchers over the past years. One of the primary challenges associated with existing photobioreactors is the light penetration. An effective photobioreactor design should maximize light penetration, ensuring uniform illumination throughout the reactor. This study aims to assess the impact of light intensity on microalgal growth from the perspective of energy efficiency and productivity in two photobioreactors. A novel cactus-like and a cylindrical photobioreactor were designed and fabricated using 3D printing technology. These two photobioreactors were used to cultivate two strains of microalgae. The novel photobioreactor achieved a maximum biomass productivity of 0.99 g/L/d and a maximum energy efficiency of 0.3139 g/d/kWh. The cylindrical photobioreactor reached a maximum biomass productivity of 0.74 g/L/d and 0.2199 g/d/kWh of energy efficiency. The increase in biomass productivity can be linked to enhancements in the photobioreactor's surface-to-volume ratio and better light utilization.

(1) Background: The purpose of this study was to assess the external load demands in futsal, con-sidering both home and away matches and their outcomes, in order to plan microcycles throughout the season based on the external load of each match. (2) Methods: The external load of 10 players from a First Division team in the Spanish Futsal League was recorded. The total dura-tion of player involvement with the clock stopped was 18.15 ±7.04 minutes. The players' external load was monitored using OLIVER devices. To analyse the influence of the match outcome and location on the external load, a univariate general linear model (GLM) analysis was conducted. (3) Results: There are no differences between the variables, except for accelerations of 2 to 3 m/s² (m) per minute and the number of accelerations of 2 to 3 m/s² per minute. Despite not showing significant differences, there is a trend indicating a higher demand for external loads in away matches as well as in matches won. (4) Conclusions: These findings are important for planning microcycles and providing the appropriate dosage to each player to achieve optimal performance in matches.

(1) Background: donor-derived circulating free DNA (dd-cfDNA) is an innovative biomarker with great potential for the early identification and prevention of graft damage; (2) Methods: Prospective study to analyze dd-cfDNA plasma levels in 30 kidney transplant patients during their post-transplant follow-up (15 days, 3, 6 and 9 months), to determine if the result could be of interest in the identification of possible adverse events, specially allograft rejection. In addition, the aim is also to verify the obtained data on sensitivity, specificity, NPV and PPV; (3) Results: Plasma levels of dd-cfDNA could be considered a novel biomarker of graft rejection after first term post-transplant up to several months before its clinical presentation, mainly in TCMR or ABMR. In this study, it appears to have no positive predictive value for borderline rejection or TCMR IA. Our results show a low NPV of the technique because other pathologies or biological post-transplant complications can also affect dd-cfDNA levels and they must be considered in the interpretation of the result.; (4) Conclusions: dd cfDNA could allow, together with other additional biomarkers in the context of a future score, avoid invasive biopsies in most cases, mainly in the case of suspected TCMR or ABMR.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Pullulan is a kind of natural polymer, which is widely used in medicine and food because of its solubility, plasticity, edible, non-toxicity and good biocompatibility. It is of great significance to improve the yield of pullulan by genetic modification of microorganisms. It was previously reported that Aureobasidium melanogenum TN3-1 isolated from honey-comb could produce high-yield of pullulan, but the molecular mechanisms of its production of pullulan had not been completely solved. In this study, the reported strains of Aureobasidium spp. were further compared and analyzed at genome level. It was found that genome duplication and genome genetic variations might be the crucial factors for the high yield of pullulan and stress resistance. This particular phenotype may be the result of adaptive evolution, which can adapt to its environment through genetic variation and adaptive selection. In addition, the TN3-1 strain has a large genome, and the special regulatory sequences of its specific genes and promoters may ensure a unique characteristics. This study is a supplement of the previous studies, and provides basic data for the research of microbial genome modification in food and healthcare applications.

The article adds new policy insights to the way in which formal teaching methods of environmental stewardship education areas are evaluated in Tuvalu. We aimed to answer three questions: 1. What are the formal policies shaping environmental stewardship education in Tuvalu? 2. Are national educational and environmental policies mutually consistent? and 3. Are these national policies consistent with regional and global policies? These questions were addressed using a study of Tuvaluan online-available documentary assessments of national policies, frameworks, and curricula in conjunction with those obtained from the Education Department. Our findings revealed limitations and weaknesses regarding the provisions of environmental stewardship education at the national scale, including misaligned curricula, policy documents, and formal educational provisions with Tuvalu’s national environmental policy. We also found inconsistencies with regional and global policies such as the Pacific Islands Framework for Nature Conservation, the Framework for Resilient Development in the Pacific, and international strategic plans for biodiversity and climate change. These cross-scalar policy weaknesses and limitations highlight the need for the Tuvaluan government to align educational and environmental policies at different scales. We recommend a multi-pronged strategy where modes of informal environmental education can support and complement formal government policymaking on education and the environment.

A superior variant of dried jujube in China is ‘Huizao’ (HZ) jujube. Nonetheless, detailed evaluations of the texture quality of HZ fruits have been the subject of few studies. Texture is a significant indicator of the sensory and processed quality of a fruit. Here, we differentiate and characterize the texture quality of HZ fruits from the four primary producing regions in southern Xinjiang, as well as develop a system for assessing the texture quality of HZ fruits. Furthermore, five texture indices of HZ fruits from 109 plantations were exhaustively evaluated utilizing principal component analysis, Pearson correlation analysis, and hierarchical clustering analysis. Consequently, by the 10th, 30th, 70th, and 90th percentiles, each index was classified into five grades—lower, medium, high, and higher. Correlation investigation indicated strong relationships between the springiness, chewiness, cohesiveness, gumminess, and hardness of HZ fruits. Springiness, hardness, and adhesiveness are essential indicators that influence the texture of HZ fruits. We used clustering analysis to separate the six texture indices into three major categories (hard factor, stick-elastic factor, and adhesive factor), with indices representing hardness, springiness, and adhesiveness, respectively. Furthermore, according to the factor molecules, the texture quality of HZ fruits in the four production areas was evaluated as Bazhou (1.24) > Hotan (0.773) > Kashi (-0.577) > Aksu (-0.852). RDA analysis of six texture quality parameters and 24 climate conditions identified higher mean temperature (TEM) and lower relative humidity (RHU) as the primary factors contributing to the improved texture quality of HZ fruits in Xinjiang. This study identified the texture quality characteristics of HZ fruits in four major producing areas of Southern Xinjiang, and it offered a theoretical foundation for optimizing the dominant producing areas and regional production of HZ varieties in Xinjiang.

Mortality in children accounts for 15% of all AIDS-related deaths globally, with a higher burden among Cameroonian children (25%), likely due to poor virological response. We sought to evaluate viral suppression (VS) and its determinants in a nationally representative paediatric and young adult population receiving antiretroviral therapy (ART). A cross-sectional and multicentric study was conducted among Cameroonian children (

Conventional tutoring approaches are confronted with limitations such as restricted availability, inconsistent pedagogical quality, and scalability con-straints. Furthermore, the exclusive use of Large Language Models (LLMs) like ChatGPT in education has its shortcomings, including the potential for incorrect responses and the lack of customized guidance aligned with specific course con-tent. This research proposes an innovative intelligent chatbot tutoring system, in-tegrating the Retrieval Augmented Generation (RAG) approach with a custom LLM. The developed system aims to overcome the limitations of traditional tu-toring and general-purpose LLMs by providing accurate, contextually relevant, and personalized assistance, thereby enhancing student understanding and en-gagement. The system, powered by an intelligent agent, retrieves relevant information from curated academic sources, incorporates interactive features for user feedback, and utilizes machine learning algorithms for ongoing performance enhancement, ensuring a robust and effective tutoring experience. The anticipated outcome is an enriched educational experience for university students, advance-ment in personalized learning, and improved student engagement, retention, and academic performance. Through continuous research and refinement, it is expected that the intelligent chatbot tutor will assume an important role in enhancing and supporting the educational journey of students.

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: Blood pressure (BP) is characterized by a circadian rhythm (Circr), with lower nighttime values, called dipping. Non-dipping is associated with higher CVD risk. The Circr of urinary sodium excretion (NaCle), peaking during the day, is linked to BP patterns. Physical ac-tivity (PA) is known to improve BP control and enhance the dipping phenomenon, but its possi-ble effect on NaCle remains unclarified. Objectives: This study aimed to investigate the correla-tion between PA and the Circr of NaCle and to determine if the relationship is independent of age, sex, BP values, dipping pattern, and salt intake. Methods: A cross-sectional analysis was conducted using data from the Ticino Epidemiological Stiffness Study, involving 953 participants in Switzerland. Data collection included standardized questionnaires, blood samples, 24-hour urine collections, and ambulatory BP monitoring. Participants were categorized into sedentary, partially active, and active. The effect of PA, NaCl intake, and dipping on the day/night NaCle ratio, was assessed with multivariable linear regressions. Results: Participants median age 49 years, with 78% having normal BP values and 47% exhibiting a dipping pattern. 51% were classi-fied as sedentary and 22% as partially active. The median NaCl intake was 7.9 g/day. The youngest subjects had a higher hourly NaCle ratio compared to older subjects. Higher NaCl in-take correlated with increased BP, phenomenon more pronounced in men and younger subjects. The hourly day/night NaCle ratio positively correlates with dipping; however, PA did not show a significant correlation with the NaCle ratio. Conclusion: This study indicates that while the day/night NaCle ratio correlates with the dipping pattern, PA is unrelated to the circadian rhythm of renal sodium handling. The beneficial effects of PA on BP and cardiovascular health thus appear to be mediated through mechanisms other than NaCle. These are explorative find-ings only, but relativize the need for further investigations on the topic.

Leishmaniasis represents a severe global health problem. In the last decades, there have been significant challenges in controlling this disease due to the unavailability of licensed vaccines, the high toxicity of the available drugs, and an unrestrained surge of drug-resistant parasites, and human immunodeficiency virus (HIV)–Leishmania co-infections. Leishmania spp. preferentially invade macrophage lineage cells of vertebrates for replication after subverting cellular functions of humans and other mammals. These early events in host–parasite interactions are likely to influence the future course of the disease. Thus, there is a continuing need to discover a simple cellular model that reproduces the in vivo pathogenesis. Acanthamoeba spp. are non-mammalian phagocytic amoeba with remarkable similarity to the cellular and functional aspects of macrophages. We aimed to assess whether the similarity reported between macrophages and Acanthamoeba spp. is sufficient to reproduce the infectivity of Leishmania spp. Herein, we analyzed co-cultures of Acanthamoeba castellanii or Acanthamoeba polyphaga with Leishmania infantum, Leishmania amazonensis, Leishmania major, and Leishmania braziliensis. Light and fluorescence microscopy revealed that the flagellated promastigotes attach to the A. castellanii and/or A. polyphaga in a bipolar and or random manner, which initiates their uptake via pseudopods. Once inside the cells, the promastigotes undergo significant changes, which result in the obligatory amastigote-like intracellular form. There was a productive infection with a continuous increase in intracellular parasites. However, we frequently observed intracellular amastigotes in vacuoles, phagolysosomes, and the cytosol of Acanthamoeba spp. Our findings corroborate that Leishmania spp. infects Acanthamoeba spp. and replicates in them but does not cause their rapid degeneration or lysis. Overall, the evidence presented here confirms that Acanthamoeba spp. have all prerequisites and can help elucidate how Leishmania spp. infect mammalian cells. Future work exposing the mechanisms of these interactions should yield novel insights into how these pathogens exploit amoebae.

In 2023, we proposed the modified Delay and Doppler Profiler (mDDP) as an inter-carrier interference (ICI) countermeasure for underwater acoustic OFDM mobile communications in a multipath environment. However, the performance improvement in computer simulation and pool experiments was not significant. In a subsequent study, the accuracy of the Channel Transfer Function (CTF), which is the input for the mDDP channel parameter estimation, was considered insufficient. Then a 2-step mDDP was devised. This paper presents simulations of underwater OFDM communications using 1- to 3-step mDDPs. The simulation conditions are a two-wave multipath environment where the receiving transducer moves at a speed of 0.3 m/sec and is subjected to a Doppler shift in the opposite direction. As NumCOL, the number of taps in the multi-tap equalizer which removes ICI, was increased, Bit Error Rate (BER) of 0.016 at NumCOL = 1 was significantly reduced by a factor of approximately 40 to BER of 0.00041 at NumCOL = 41 for the 2-step mDDP.

This study investigated how the type and homogenisation parameters of the feed mixture affect the efficiency of the encapsulation process and the microcapsule properties of phenol-rich grape pomace extract (GPE) during the spray drying process with goat whey protein (GW) as wall material. GPE was obtained by solid-liquid extraction of grapes with 50% ethanol. Effects of ultrasonic homogenisation parameters (UB): temperature: 30-50 °C; time: 5-30 min; stabilisation time after homogenisation: 15-45 min, and homogenisation parameters on a magnetic stirrer (MS): temperature (25-50 °C), time (10-60 min) and homogenisation speed (600-1200 rpm) were tested using response surface methodology (RSM) and Box-Behnken design. After selecting the optimal homogenisation conditions, the spray drying process parameters were optimised in the same way, namely: inlet air temperature (160-190 °C), GW fraction (0.5-3.5) and feed flow (6-10 mL/ min). The results showed that GW has a high potential as a wall material in the spray drying process, especially for the purpose of protecting polyphenolic compounds from GPE.

The potential of generalized machine learning models developed for crop water estimation was examined in the current study. Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), and Random Forest (RF) are three ensembled machine learning models that were developed using all of the data from a single location from 1976 to 2017 and then immediately applied at eleven different locations without the need for any local calibration. For the test period of January 2018 to June 2020, the model's capacity to estimate the numerical values of crop water requirement (Pen-man-Monteith (PM) ETo values) was assessed. In comparison to the GBM and RF models, the XGBoost model outperformed them both marginally and significantly. The estimate's weighted standard error was smaller than 0.85 mm/day, and the model's effectiveness varied from 96% to 99% across various locations. The model's strong performance was indicated by the decreased noise-to-signal ratio. A real-time water management system at the regional level can be seamlessly linked with this type of model due to its accuracy in estimating crop water requirements and its capacity to generalize.

The Coronavirus disease 2019 (COVID-19) pandemic has significantly affected older adults. Identifying host COVID-19 susceptibility genes in elderly populations remains a challenge. Here, we aimed to identify host genetic factors influencing susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We genotyped 12 single nucleotide polymorphisms (SNPs) previously associated with the innate immune response in a total of 97 elderly (age >65 years) residents of three long-term care facilities located in the area of Barcelona, Spain. Individuals were PCR-tested during SARS-CoV-2 outbreaks between September and November 2020. SARS-CoV-2 PCR tests revealed infection in 81 residents. Importantly, the 16 uninfected residents remained SARS-CoV-2 seronegative until vaccination (January and February 2021). After adjusting for sex and age, we found that two SNPs were significantly associated with SARS-CoV-2 infection susceptibility: MMS19 nucleotide excision repair protein homolog (MMS19)/rs2236575 (p = 0.029) and interferon-induced helicase C domain-containing 1 (IFIH1)/rs1990760 (p = 0.034). No association with SARS-CoV-2 infection was found for the 10 additional genotyped SNPs, which included 4 SNPs on chromosome 12 in the gene encoding oligoadenylate synthetase (OAS). Our results indicate that MMS19 and IFIH1 genetic variants were associated with resistance to SARS-CoV-2 infection in a cohort of institutionalized seniors.

Reducing and time-shifting household energy demand is important for a sustainable transition of energy systems, and dynamic electricity pricing, like real-time pricing (RTP), is a popular instrument to incite households to change energy demand. However, the effect of such products relies on the assumption that dynamic price signals incorporate into everyday routines and rhythms. This paper investigates the flexibility of households’ everyday routines and rhythms. The study provides three insights based on 11 Danish household visits and interviews with electricity customers who are new to RTP. First, the interviews indicated confusion over terminology for dynamic pricing products and low interest in flexible energy demand. Second, everyday practices (already) appeared flexible but for other reasons than energy demand flexibility. Third, energy habits were important for providing meaning to everyday practices. In addition, the study shows that energy flexibility is not just about energy demand, but rather about all the other activities that form routines and rhythms in everyday life. We suggest 1) designing products that reflect ‘natural’ or ‘societal’ daily rhythms, 2) focusing on the engaged households, and 3) being aware that for some households, changes in pricing, including new payment schemes, might put extra pressure on already harried everyday routines.

Dengue (DENV) and Zika (ZIKV) virus continue to pose significant challenges globally due to their widespread prevalence and severe health implications. Given the absence of effective vaccines and specific therapeutics, targeting of the highly conserved NS5 RNA-dependent RNA polymerase (RdRp) domain has emerged as a promising strategy. However, limited efforts have been made to develop inhibitors for this crucial target. In this study, we employed an integrated in silico approach utilizing combinatorial chemistry, docking, molecular dynamics simulations, MM/GBSA, and ADMET studies to target the allosteric N-pocket of DENV3-RdRp and ZIKV-RdRp. Using this methodology, we designed lycorine analogs with natural S-enantiomers (LYCS) and R-enantiomers (LYCR) as potential inhibitors of non-structural protein 5 (NS5) in DENV3 and ZIKV. Notably, 12 lycorine analogs displayed a robust binding free energy (<-9.00 kcal/mol), surpassing that of RdRp-Ribavirin (<-7.00 kcal/mol) along with promising ADMET score predictions (<4.00), of which (LYCR728-210, LYCS728-210, LYCR728-212, LYCS505-214) displayed binding properties to both DENV3 and ZIKV targets. This study highlights the potential of non-nucleoside lycorine-based analogs with different enantiomers that may present different or even completely opposite metabolic, toxicological, and pharmacological profiles as promising candidates for inhibiting NS5-RdRp in ZIKV and DENV3, paving the way for further exploration for the development of effective antiviral agents.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.

The present study analyzes students' weather-related hazard and risk literacy in Greece, a climate change hotspot region in the Eastern Mediterranean. In this context, we examine the students' level in two core literacy variables, namely knowledge and competency. In addition, we explore how knowledge, attitudes and socio-demographic variables influence students' competencies related to weather and climate risk assessment and adaptability. A questionnaire-based survey was conducted on 474 students aged 12-16. The regression results showed that knowledge significantly affects the level of competency. Self-belief and confidence in science were the most influential among the attitudinal variables. We conclude by discussing educational and behavioural issues highlighted as essential to address with targeted policies and measures in formal education complemented by non-formal educational activities.

At the beginning of our observations, Humanity believed that it was the center of the universe, that the Earth was the center of the universe and that the sun was spinning around the Earth. Claude Ptolémée (100-168) made a mistake by modelling the movements in the geocentric referential. The model of the sun and planet movements was an illusion and all Humanity was wrong. Nicolas Copernic (1473-1543) showed the illusion and simplified the system by moving from the geocentric referential to the heliocentric referential. In the present paper, I would like to discuss about the possibility of making mistakes with quantum theory because it is not complete. I postulate that we are living in a virtual classical world that we consider as real. In my interpretation, the decoherence problem and wave function collapse do not exist at all, because we are the illusion, we are living in illusions, in mirages. It is impossible to observe the quantum world as it is, in our virtual classical referential, and we see the quantum world with a false vison of quantum reality because we are not yet in the real universal quantum referential whose I postulate the existence. I moved to this real universal quantum ref-erential because I am psychotic (schizophrenia) and saw that we are illusions. Schrödinger’s cat par-adox is an illusion as life and death are illusions. We must be very humble with quantum theory and we should not put ourselves in the center of the quantum world again particularly with our lives and deaths. I have completed quantum theory with seven postulates which led to a cosmological model based on bipolarity and schizophrenia. The theory explains well the recent observations of the James Webb spatial telescope. I make predictions with the theory which could be confirmed with the James Webb spatial telescope. If confirmed, the theory will become irrefutable. We would be collectively able to reach the quantum world by changing our minds and visions of life. I also explain how to go out of human suffering. This would be our Big Bang and our transformation into Zarathoustra, the Nietzschean surhuman.

This study explores the intricacies of supplier relationships and inventory optimization within high-technology industries, offering a comprehensive analysis of the strategic imperatives and operational challenges faced by firms in these sectors. By adopting a qualitative research methodology involving semi-structured interviews with supply chain professionals and documentary analysis, the study provides in-depth insights into the evolving dynamics of supply chain management. Findings reveal a marked shift towards collaborative and strategic supplier relationships, characterized by trust, transparency, and joint innovation initiatives. These partnerships are essential for enhancing operational efficiency, driving product development, and navigating market uncertainties. Additionally, the research underscores the critical role of advanced technologies, such as artificial intelligence and the Internet of Things, in optimizing inventory levels and improving supply chain visibility. The integration of these technologies facilitates precise demand forecasting and proactive inventory management, thereby reducing costs and enhancing service levels. However, the study also highlights significant challenges, including geopolitical uncertainties, supply chain disruptions, and cultural barriers, which necessitate robust risk management strategies and adaptive supply chain practices. Strategic implications for organizational leaders and policymakers include the need to invest in supplier development, embrace digital transformation, and enhance risk management frameworks to build resilient and agile supply chains. This study contributes valuable insights into the complex interplay between supplier relationships, inventory optimization, and technological integration in high-technology industries, offering actionable recommendations for practitioners and researchers seeking to drive innovation and maintain competitiveness in a dynamic global marketplace.

Pollution, urbanization and technological advancements have posed stress on the ecosystem and its matrices. Globally, pollutants are observed in all compartments of ecological communities which affect the integrity of the atmosphere, hydrosphere, lithosphere and biosphere. Xenobiotics bioaccumulate and biomagnify across trophic levels or webs. Heavy metals have been implicated in impacts towards biodiversity and environmental declination. In Nigeria, wastes issues are a cause of concern and landfilling or are waste disposal approaches that cause deleterious effects such as depauperation of diversity and species decline, prompting the non-invasive ecotoxicological hazard assessments. Feathers were used to assess concentration levels of 13 metals (Fe, Mn, Zn, Cu, Co, Cr, Cd, Pb, Ni, Al, B, Se and Hg) using fast atomic absorption spectrophotometer (FAAS), one-way ANOVA was used in comparing variations in mean concentrations across trophic levels, diversity indices and point count methods were used to estimate diversity and abundance. Four avian species were assessed Hirundo aethiopica (insectivore), Streptoptelia senegalensis (granivore), Turdus pelios (omnivore), and Anthus leucophrys. (insectivore). Observed concentrations of important metals like iron were high with the insectivores having the highest concentrations of iron (2.6985 ± 0.1975 ppm) and granivores having the lowest (2.0100 ± 0.3172 ppm). The insectivores had the highest concentrations for cadmium, cobalt and chromium (0.0005 ± 0.0005ppm), nickel (at 00.0012 ± 0.0017 ppm) and least was observed in the granivores (0.0003 ± 0.0006 ppm). Selenium concentrations were quite high in insectivores (0.0775 ± 0.0035 ppm) and lowest in granivores (0.0433 ± 0.0015 ppm) likewise mercury for insectivores (0.0280 ± 0.0010 ppm) and granivores (0.0213 ± 0.0015 ppm). From the study, it is apparent that landfills are sources of pollution and poor management of wastes can affect biota (causing effects such as asymmetry and bioaccumulation) and ecosystem balance. The observation of heavy metals in the feathers serve as good sentinels due to their trophic levels and could be signs for what could be yet to occur. The heavy metal concentrations were significantly different at p < 0.05.

Human serum albumin (HSA) corona formation at polymer microparticles of a spheroidal shape was studied using dynamic light scattering and laser Doppler velocimetry (LDV). Physicochemical characteristics of the albumin comprising, the zeta potential and the isoelectric point were determined as a function of pH for various ionic strengths. Analogous characteristics of the polymer particles were carried out. The adsorption of albumin on the particles was monitored by electrophoretic mobility measurements (LDV). The stability of the HSA functionalized particle suspensions under various pHs and their electrokinetic properties were determined. The deposition kinetics of the particles on mica, silica and gold sensors were determined in situ by optical microscopy, AFM and by the quartz microbalance (QCM) under diffusion and flow conditions. The obtained results were interpreted in terms of the coarse-grained random sequential adsorption model that allowed to estimate the range of applicability of QCM for determining deposition kinetics of virus and bacteria at abiotic surfaces.

Agile procurement has emerged as a transformative strategy for organizations striving to maintain competitiveness in a rapidly evolving marketplace. This qualitative research investigates the implementation, benefits, challenges, and outcomes of agile procurement practices in supply chain management. Through semi-structured interviews and case studies across diverse industries, this study explores how agile procurement enhances organizational adaptability and responsiveness. Key findings reveal that agile procurement enables organizations to swiftly adjust strategies in response to market fluctuations and customer demands, fostering increased customer satisfaction and loyalty. The integration of advanced technologies, including AI and blockchain, facilitates real-time data analysis, optimizing procurement processes and enhancing supply chain efficiency. Organizational culture emerges as a critical factor in successful agile procurement, with leadership support and a collaborative environment driving cultural change towards agility and innovation. Despite its benefits, challenges such as resistance to change and the need for significant technology investments are identified, requiring careful change management and strategic alignment. Case studies illustrate the versatility of agile procurement across sectors, showcasing its role in enhancing operational efficiencies, innovation capabilities, and overall supply chain performance. In conclusion, agile procurement offers organizations a strategic framework to navigate complexities and uncertainties effectively, capitalizing on market opportunities while mitigating risks. Embracing agile principles fosters a resilient organizational culture capable of adapting to dynamic market conditions. Future research should focus on further refining agile procurement strategies to address emerging challenges and sustain competitive advantage in the global marketplace.

1) Background- Coronary artery bypass grafting (CABG) is a common surgical intervention for patients with severe coronary artery disease. The Model for End-Stage Liver Disease (MELD) score has been widely used to predict mortality risk in patients with end-stage liver disease, but its utility in predicting postoperative outcomes in cardiac surgery patients is less well-established. 2) Methods-This retrospective study aims to investigate the association between preoperative MELD score and post-operative complications, length of hospital stay, and mortality in patients under-going coronary artery bypass grafting. This is a single-center, retrospective cohort study conducted at a tertiary care academic medical center. The study includes all adult patients who underwent elective coronary artery bypass grafting between January 2011 and December 2020. Preoperative MELD scores were calculated for each patient, and postoperative outcomes including major ad-verse cardiac events, length of hospital stay, and 30-day mortality was assessed. To ensure a homogeneous study cohort, we excluded patients who underwent emergent cardiac procedures or had incomplete data necessary for the calculation of MELD scores and assessment of postoperative outcomes. Data was extracted from the electronic medical records, including patient de-mographics, comorbidities, preoperative laboratory values, operative details, and postoperative outcomes. The study protocol was approved by the Institutional Review Board, and the require-ment for informed consent was waived due to the retrospective nature of the study.3) Results- This study reveals a statistical association between the MELD score calculated at admission and the length of hospital stay, duration in the ICU, patient age, and the duration of aortic clamping and extracorporeal circulation. Specifically, there is an exponential increase in the MELD score corre-lating with the rise in these factors, both collectively and individually, highlighting a significant relationship between the duration of extracorporeal circulation and aortic clamping time. 4) Conclusion-Patients with a high MELD score had an increased risk of postoperative complications and mortality compared to those with a low MELD score. Careful preoperative patient selection and optimization of the patient's clinical condition may improve outcomes in patients with advanced liver disease undergoing cardiac surgery.

(1) Background: In a society with an advancing aging rate, medical systems are coming under pressure due to an increasing flow of elderly patients with multiple somatic diseases, exacerbated by their fragile psychological and sociological backgrounds. We aimed to investigate the relationship be-tween frailty and loneliness in elderly people. Our research question was “Is there a link between the loneliness and frailty in elderly people?” (2) Methods: To assess the link between loneliness and frailty, we conducted a search accessing Index Medicus and PubMed; the timeframe of our research was from 2013 till 2023. Data regarding the study population, as well as loneliness and fragility assessments and approaches, were extracted. (3) Results: A positive relationship between loneliness and the appearance and progression of frailty in elderly people is argued for. (4) Conclusions: Maintaining a balance in the body’s functionality for as long as possible requires the diagnosis and periodic assessment of health status at any age and, due to the various socio-financial and emotional implications, is particularly imperative for elderly patients. Frailty can be prevented, and it appears that it could even be reversed if early diagnosis and appropriate interventions are made. Therefore, knowledge of relevant risk factors—most likely including loneliness—is an absolute necessity to slow down, stop, and even reverse the frailty process.

Postprandial plasma glucose between 4 and 7.9 hours is associated with the diagnosis of diabetes, diabetes mortality, and cardiovascular mortality. However, it is unknown whether 2-hour plasma glucose during the oral glucose tolerance test conducted in this postprandial period (4–7.9 hours), termed as 2-h PGOGTT@4–7.9h, can accurately classify diabetes diagnosis and predict mortality risks. This study aimed to address these questions using 2,347 adult participants. Diabetes was defined as HbA1c ≥6.5%, and the ability of 2-h PGOGTT@4–7.9h to classify diabetes was analyzed using receiver operating characteristic curves. Cox proportional hazards models were employed to estimate mortality hazard ratios (HRs) and 95% confidence intervals (CIs). The results showed that 2-h PGOGTT@4–7.9h could classify diabetes with 92% accuracy. Participants were followed up for a mean of 21.4 years. A 1-natural-log higher 2-h PGOGTT@4–7.9h was associated with an increased risk of mortality from diabetes (adjusted HR, 21.1; 95% CI, 9.2–48.0) and cardiovascular disease (adjusted HR, 1.47; 95% CI, 1.13–1.91). Simulation analysis indicated that future studies may require at least 100 participants to investigate 2-h PGOGTT@4–7.9h for diabetes diagnosis. In conclusion, 2-h PGOGTT@4–7.9h may be useful for diabetes classification and prediction of mortality risk.

Background and Objectives: To analyze survival in peritoneal and hemodialysis patients using chest radiography and biochemical parameters, determine dialysis etiologies and common mortality causes, reveal prognostic factors, and contribute to clinical practice. Materials and Methods: This retrospective cohort study was based on the analysis of data from 33 peritoneal dialysis and 37 hemodialysis patients who were followed and treated in our hospital between October 2018 and February 2020. Chest X-ray measurements (cardiothoracic index, pulmonary vascular pedicle width, right pulmonary artery diameter, diaphragmatic height) and biochemical parameters (urea, albumin, creatinine, parathormone, ferritin, hemoglobin, arterial blood gas, potassium) were analyzed to assess their impact on survival. Statistical analyses were performed using the Shapiro-Wilk, Wilcoxon signed rank test, Mann-Whitney U test, McNemar test, Kaplan-Meier survival analysis, Cox regression analysis, Spearman correlation test, Phi test, and ROC analysis. Results: The most common etiologies of dialysis were hypertension, type 2 diabetes mellitus, and urogenital disorders. The most common cause of death in peritoneal dialysis patients was peritonitis (38.5%), while in hemodialysis patients, it was cardiovascular diseases (47.4%). In chest X-ray measurements, pulmonary vascular pedicle width (p=0.003) and pulmonary artery diameter increased significantly (p=0.002) in hemodialysis patients, while pulmonary vascular pedicle width (p=0.028) and diaphragmatic height (p=0.004) increased significantly in peritoneal dialysis patients. No significant difference was found between the two groups in terms of biochemical parameters. Kaplan-Meier survival analysis showed that there was no significant difference in survival between peritoneal dialysis and hemodialysis methods (P>0.05). Significant correlations were found between both radiologic status and clinical status and between intact parathormone levels and pulmonary vascular pedicle width (p=0.016, p=0.024). In Cox regression analysis, age, intact parathormone levels, iPTH/PVPW ratio, and clinical status were found to be factors affecting survival (p

Group A rotaviruses (RVA) have been identified as the leading cause of neonatal calf diarrhea (NCD) In Yunnan, China, despite the limited documentation on this issue within the country. Given the significant impact on animal health and welfare, further attention is warranted to comprehend the prevalence and epidemiology of this disease. In this study, we isolated RVA strains from NCD clinical samples to support RVA epidemic study and further disease control in Yunnan. Material and Methods: Ten fecal samples were obtained from calves with a single episode of neonate calf diarrhea from a farmer during a severe NCD outbreak. For the diagnosis of Group A rotavirus (RVA) infection, fecal reverse transcription-polymerase chain reaction (RT-PCR) was employed as the primary method. Subsequently, RVA isolation was conducted on MA104 cells, with inoculates being pretreated with trypsin TPCK to enhance viral infectivity. The isolated RVA strain was further confirmed through RT-PCR and immunofluorescence assay. Results: RVA virus was isolated from clinical samples following six passages depended on trypsin treatment of inoculates. The sign of CPE detected consisted of increased cell granularity, obscure cell boundaries, cell rounding, and eventual degeneration and detachment of cells. Analysis of sequencing revealed that field isolates was of group A serotype. Phylogenetic analysis based on the ORF sequences of the VP4 and VP7 sequences segments indicated that the isolate was classified as the P[1] genotype. VP4 gene of strain YN-1 shares 75.2%-99.7% nucleotide identity of and 81.6%–99.7% amino acid identity with the complete VP4 sequences of the P[1]. The complete VP7 gene of YN-1 is 981 nucleotide long and encode 326 amino acids. The RotaC v2.0 analysis classified the sequence as the G8 genotype. The VP7 gene of strain YN-1 shares 88.5%-97.7% nucleotide identity and 94.2%-99.1% amino acid identity. Conclusion: This is the first study in China which reports the circulation of Group A NCD on cattle farms in the field. Our study constitutes a crucial and a necessary step allowing preventive and veterinary medicine to support RVA disease controls in Yunnan province, China.

Incidental findings (IFs) depicted in imaging tests during diagnostic evaluation of patients with cleft lip and/or palate (CL/P) can guide clinicians during treatment-planning procedures for effective, comprehensive cleft care. Evidence regarding IFs in different anatomical regions distant from the dentition are scarce. The aim of this study was to compare the prevalence of IFs in various anatomical areas between patients with non-syndromic CL/P and unaffected subjects. Orthopantomographs (OPT), lateral cephalometric (LC) radiographs and cone-beam computed tomography (CBCT) scans of 120 subjects (case group: n = 40, 18 females, age 14.5 ± 5.0 years; control group: n = 80, 36 females, age 14.6 ± 4.9 years) were examined and IFs were assessed by four observers. Significantly higher prevalence of IFs (p &lt; 0.001) was reported in the case group (97.5%) compared with the control group (62.5%). The most prevalent location of IFs in the case group was the maxilla (92.5%), followed by the nasal cavity (75.8%) and the mandible (63.2%), while in the control group, the highest rates of IFs occurred in the maxilla (43.8%), mandible (41.3%) and temporomandibular joint (TMJ) (14.7%). No gender-dependent pattern for IF occurrence was detected overall. Orofacial clefts may affect the mandible. However, the reported IFs were limited compared to those in the maxilla. In conclusion, individuals with CL/P are more likely to present with a range of IFs than their unaffected peers. Understanding the association between CL/P and IFs is critical for successful interdisciplinary treatment, raising awareness of the potential need for future dental care for cleft patients, and managing extra-dental aberrations. A systematic assessment of diagnostic records is required to eliminate the risk of overlooking clinically significant IFs.

This study investigates how organizations adapt their procurement practices in response to supply chain disruptions, aiming to enhance resilience and ensure operational continuity. Through qualitative research involving interviews with procurement professionals and industry experts, the study identifies key adaptive strategies employed by organizations, including supplier diversification, enhanced inventory management, digital transformation, supplier collaboration, and contingency planning. These strategies are explored in depth, highlighting their implementation challenges and the outcomes achieved. Despite facing obstacles such as financial constraints, technological barriers, and supplier resistance, organizations have demonstrated a proactive approach in leveraging these strategies to mitigate risks and improve supply chain resilience. The findings reveal that adaptive procurement strategies have led to significant outcomes, including strengthened supplier relationships, increased operational efficiency, better risk management, and competitive advantage. These outcomes underscore the strategic importance of agility, technological integration, collaborative partnerships, and effective leadership in responding to disruptions and maintaining competitiveness. The study also discusses implications for practice and policy, emphasizing the need for continued investment in technology, collaboration, and resilience-building initiatives across supply chains. Overall, this research contributes to the understanding of how organizations can adapt and innovate in the face of dynamic supply chain challenges, providing insights that can guide future research and inform strategic decision-making in procurement and supply chain management.

This work offers a new log generalized odd log-logistic exponential regression model for analyzing weekly dengue fever cases in 2022 with a location-systematic component. To achieve this, a data set of 49 observations of dengue fever cases in the Federal District of Brazil is employed. A review of the mathematical properties of the generalized odd log-logistic exponential distribution is provided, the maximum likelihood method is used to estimate the parameters, and, through Monte Carlo simulations, the accuracy of the estimators is investigated. The model's fit is assessed using global influence metrics and residual analysis. For the time scenario studied, the proposed regression identified factors that have an impact on dengue fever cases, which may contribute to improve disease control. Finally, several interpretations are addressed, and a discussion presents results that aid in better understanding the data set and future research on different data.

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

Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Sub-plots were treated with nitrogen (120 kg ha⁻¹) from farmyard manure and urea, including control, 33% FYM + 67% urea (MU), and 80% FYM + 20% urea (MF). Acidified hydrochar treatments H0 (no hydrochar) and H1 (with hydrochar, 2 t ha⁻¹) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear-1, thousand grain weight, and nitrogen content compared to shallow tillage. MU and MF improved growth parameters and yield over the control. Hydrochar effects varied; H1 enhanced certain yield components but reduced plant height and soil properties compared to H0. Canonical discriminant analysis linked deep tillage and MU/MF nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen manage-ment enhances maize productivity and soil health. However, hydrochar application requires op-timization. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. Future research should in-vestigate long-term impacts across diverse environments to validate these results.

Transportation plays an important role in urban development. Population growth and environmental burden have turned the efforts of cities globally towards smarter and greener mobility. Cooperative and Connected Automated Mobility (CCAM) serves as a concept with the power and potential to help achieve these goals building upon technological fields like Internet of Things, computer vision and distributed computing. However, its implementation is hindered by various challenges covering technical parameters such as performance and reliability in tandem with other issues, such as safety, accountability and trust. To overcome these issues, new distributed and decentralized approaches like blockchain and smart contracts are needed. This paper aims at identifying a comprehensive inventory of CCAM challenges and use it as a framework to describe methodologies using blockchain and smart contracts to address them. It provides a comparative analysis of the findings to draw useful conclusions and discuss future directions in CCAM and relevant blockchain applications. The paper contributes to intelligent transportation systems’ research by offering an integrated view of the difficulties in substantiating CCAM and providing insights on the most prominent blockchain and smart contract technologies that tackle them.

This paper investigates the safety profile of the Shingrix vaccine, focusing particularly on persistent adverse events post-vaccination. Shingrix, crucial for preventing shingles caused by the varicella-zoster virus, has shown efficacy in clinical trials but is associated with varying degrees of adverse reactions. This retrospective, cross-sectional survey-based study, spanning two years and involving 77 respondents who experienced severe adverse events after vaccination, reveals a spectrum of symptoms ranging from mild to severe, including reports of Guillain-Barré syndrome and neuropathy. These findings underscore the need for ongoing vigilance in vaccine safety monitoring and highlight the importance of personalized care approaches for managing post-vaccination adverse effects. The study aims to contribute to informed decision-making regarding shingles vaccination strategies and calls for continued research into the long-term safety and efficacy of Shingrix.

Sparkling wines elaborated by means Ancestral method, also called Pét-Nats, are nowadays gaining an increasing share of the market. However, the scientific information about these wines is very scarce. For that reason, the aim of this research was to compare the physicochemical composition and sensory attributes of a representative sampling of commercial sparkling wines elaborated by Ancestral and Traditional methods. Ancestral sparkling wines were more heterogenous than Traditional sparkling wines because some of them showed lower internal pressure, higher turbidity, higher colour intensity and less foamability. These differences would be probably because the ancestral elaboration protocol is not so well defined as in the case of Traditional sparkling wines. However, Ancestral method has the advantage of being able to work with riper grapes and with lower doses of sulphur dioxide.

Today, with the increase in population, technological developments, industrialization and urbanization, the problems related to waste management (WM) have become increasingly important to sustainably global clean environment. The gradual change in the quality of the elements that make up the environment, increasing environmental problems, and gaining global quality have caused societies to focus more on environmental problems. Waste management is a form of management that includes the prevention, non-prevention, reuse, recovery, and disposal of domestic, medical, hazardous, and non-hazardous wastes. In this study, it is aimed to prioritize critical success factors with the Analytical Hierarchy Process (AHP) in industrial waste management and to determine the most important critical success factor. The four main criteria and 23 sub-criteria were scored by the AHP method by five expert environmental engineers. Accordingly, after critical success factors were determined, survey questions were prepared to make employees rank these factors. While "national/local waste management strategies and policies" factor was the most important critical success factor according to experts, the most important critical success factor for employees was "enterprise waste management strategies and policies". In addition, differences in the priorities of CSFs were found in the opinions of employees in different sectors.

This research seeks to solve the multi-faceted problem of waste disposal by analyzing the application of waste plastic and tyre material within non-structural concrete to ensure more sustainability and less environmental degradation. Study focusses on material properties including specific gravity, water absorption and bulk density and characteristics of the concrete that is produced by the utilization of the above waste aggregates including workability, compressive strength, flexural strength and tensile strength. This paper employs secondary data collection and MATLAB in the analysis of the findings pointing to the fact that the mechanical properties reduce with the level of waste content yet emphasizing the green aspect of such materials. Thus, a complex and diverse effect is demonstrated by the life cycle assessments (LCA) for global warming, ozone depletion, terrestrial ecotoxicity, and acidification. Furthermore, the utilization of waste materials decreases the compressive, flexural, and tensile strength, but it provides distinct ecological benefits which prove the importance of proper mix proportions for concrete performance. The outcomes of this research will be useful for further investigation in the application of the concept as well as to call for the development of new ideas for the improvement of bonding of wastes to aggregates in concrete.

One of the main problems for managing global crises is to clarify and reduces drivers of systemic weaknesses to face complex emergencies. This study here analyzes the relation between public debt, healthcare expenditures and fatality rates in the presence of pandemic crises, such as COVID-19. Statistical evidence, based on a sample of European countries, here shows that high public debt over time reduces health expenditures and increases the vulnerability of countries to face emergencies, such as COVID-19 pandemic crisis. Regression analysis with a log-log model suggests that when European countries experience a 1% increase in healthcare expenditure per capita, in general they have a 1.2% reduction in the COVID-19 fatality rate. Main implications of this study to reduce the systemic risk and vulnerability to environmental threats are that countries must reduce public debt with good governance and institutions without reducing the allocation of economic resources to the healthcare sector in order to improve the preparedness to unforeseen emergencies and crises, such as pandemics, natural disasters, conflicts, and other environmental threats.

The prevalence of cardiac amyloidosis (CA), especially as a cause of heart failure, has significantly increased in recent years. Early detection and accurate assessment of the disease burden are crucial for initiating timely treatment and ensuring precise prognosis. CA primarily results from the infiltration of the myocardium by either immunoglobulin light chain fibrils (AL) or transthyretin fibrils (ATTR), leading to restrictive cardiomyopathy and eventual death if untreated. Over the past decade, advancements in diagnostic imaging and heightened clinical awareness have revealed a substantial presence of CA, particularly ATTR, among the elderly. These diagnostic improvements encompass echocardiography, cardiac computerized tomography scan, magnetic resonance imaging, and radionuclide scintigraphy with bone-avid tracers. Concurrently, significant progress has been made in therapeutic options, with new disease-modifying treatments now available that can dramatically alter the disease trajectory and improve survival rates when administered early. However, despite these advancements, there remains an urgent need for the early and accurate detection of CA to ensure that patients can fully benefit from these emerging therapies.

The velocity distribution of flow in an eccentric cylindrical annulus is determined in an attempt to investigate the vertical capillary rise in the channel. The radii ratio and the eccentricity at which a transition from monotone to oscillatory rise occurs, are determined. The results are shown to converge to the well-known limiting cases of concentric annuli and circular tubes.

A mathematical procedure enabling the transformation of an arbitrary tessellation of a surface into a bi-colored complete graph is introduced. Polygons constituting the tessellation are represented by vertices of the graphs. Vertices of the graphs are connected by two kinds of links/edges, namely, by a green link, when polygons have the same number of sides, and by a red link, when the polygons have a different number of sides. This procedure gives rise to a semi-transitive, complete, bi-colored Ramsey graph. The Ramsey number was established as R_trans (3,3)=5. Shannon entropies of the tessellation and graphs are introduced. Ramsey graphs emerging from random Voronoi and Poisson Line tessellations were investigated. The limits ζ=lim┬(N→∞)⁡〖N_g/N_r 〗, where N is the total number of green and red seeds, N_g and N_r, were found ζ=0.272±0.001 (Voronoi) and ζ= 0.47±0.02 (Poisson Line). The Shannon Entropy for the random Voronoi tessellation was calculated as S= 1.690±0.001 and for the Poisson line tessellation as S =1.265±0.015.

The Great Reset has been presented by the World Economic Forum (WEF) in response to the COVID-19 pandemic in 2022 as a model through which a “stakeholder economy” would achieve “resilient, equitable and sustainable” economic, social and environmental goals. A more equitable distribution of resources, better working conditions, and ecological transitions are included in a social, economic and environmental reform agenda. This article raises the question of whether the Great Reset project should be interpreted as a “realistic utopia” and what is its reform potential. In an attempt to answer the question of whether the Great Reset as a realist utopia is consistent with the current state of science and philosophy, the article re-examines the idea of utopia in the light of recent philosophical and scientific approaches, such as critical realism in philosophy, so-cial systems theory in sociology and complexity theory in science. A comparative conceptual analysis is carried out and discussed introducing the idea of a realist utopia in Rawls' theory of justice as fairness. In the final discussion, some doubts are raised about the logical coherence, rigor of scientific theorizing, policy prescriptions, and predictive potential of the Great Reset emerging paradigm. It is concluded that utopian projects of radical reform can become realistic when they offer explanations of the deep structural changes that underlie social and economic evolution, drawing from these explanations the policy implications and prescription that can support struc-tural changes, rather than from assumed long-term effects of exogenous shocks or “black swan” events such as the COVID-19 pandemic.

Multimodal knowledge graph completion necessitates the integration of information from multiple modalities (such as images and text) into the structural representation of entities to improve link prediction. However, most existing studies have overlooked the interaction between different modalities. To address this issue, this paper proposed a Transformer-based knowledge graph link prediction model (MM-Transformer) that fuses multimodal features. Different modal encoders are employed to extract structural, visual and textual features, and hybrid key-value calculations are performed on features from different modalities based on the Transformer architecture. The similarities of textual tags to structural tags and visual tags are calculated and aggregated respectively, and multimodal entity representations are modeled and optimized to reduce the heterogeneity of the representations. Experimental results demonstrate that, compared to the current multimodal state-of-the-art methods, the proposed method achieves significant performance improvements in knowledge graph link prediction tasks. This proves that the proposed method effectively addresses the problem of multimodal feature fusion in knowledge graph link prediction tasks.

This study examined the thermal reflective properties and mechanisms of composite inorganic coatings applied to various wall types. It evaluated the influence of these coatings on the thermal insulation and reflectivity of walls. The findings indicate that coating application markedly enhances the wall's thermal insulation capabilities and increases the heat flux reflection ratio. These results offer crucial theoretical backing and practical guidance for the future use of coating technologies in construction. By refining the coating formulations and application processes, the thermal insulation properties of walls can be further enhanced, thus making a significant contribution to building energy efficiency and environmental protection. Consequently, this research provides essential references and insights for advancing coating technology in the construction industry.

The major challenge in the current context of a rising world’s energy demand is to limit the global temperature increase for mitigating climate change. This goal requires a large reduction of CO2 emissions, mainly produced by power generation and industrial processes using fossil fuels. In this study, a novel methodology for K2CO3-doped Li4SiO4 sorbents production for CO2 capture at high temperature was adopted based on the Design of Experiments (DoE). Different synthesis (temperature and K2CO3 content) and adsorption conditions (sorption temperature and CO2 concentration) were systematically tested by Response Surface Methodology (RSM) to obtain predictive models of CO2 uptake and Li4SiO4 conversion. The results of RSM analysis evidenced a maximum adsorption capacity of 196.4 mg/g for a sorbent produced at 600 °C and with 36.9 wt% of K2CO3, tested at 500 °C and 4 vol% of CO2. Whereas at 50 vol% of CO2, the best uptake of 295.6 mg/g was obtained with a sorbent synthesized at 600 °C, containing less K2CO3 (17.1 wt%) and tested at higher temperature (662 °C). The obtained results highlight that K2CO3-doped Li4SiO4 sorbents can be tailored for maximizing CO2 capture at different operating conditions, making them suitable for use in industrial processes.

Most cervical cancer cases are a result of persistent high-risk Human papillomavirus (HPV) infections. Cervical cancer is prevalent in LMICs especially in SSA where it is second most prevalent cancer. In South Africa, it is the second most common cancer affecting women aged between 15 and 44 years. The host immune response has been shown as an important factor in controlling the progression or regression of high-risk HPV infection of the cervix to cervical cancer. The risk of cervical cancer is known to be influenced by the host's genetic diversity, particularly by immune response-regulating genes such as the Human Leukocyte Antigen (HLA) class I and II genes. HLA class I genes present viral peptides to CD8+ T cells which are restricted and pre-programmed for cytotoxic functions. There is very little known about the HLA genes of South African women and how these influence outcome of HPV infections. This review aims to understand the role and influence of HLA class I genes in HPV clearance, persistence, and CD8+ T cell mediated immunity in African women by examining existing literature in this area. Understanding this role can influence and inform therapeutic vaccine design that is population specific.

In marine ecosystems communication among microorganisms is crucial since the distance is significant if considered on a microbial scale. One of the ways used by microorganism cells to reduce this gap is the production of extracellular vesicles. Marine bacteria release extracellular vesicles (EVs), small membrane-bound structures of 50 to 250 nm diameter, into their surrounding environment. The vesicles contain various cellular compounds, including lipids, proteins, nucleic acids, and glycans. EVs may mediate the communication between microorganisms in aquatic environments thus influencing ecosystem function and determining the structure and composition of microbial populations. This review will focus on marine bacterial EVs analysing their structure, composition, functions, and applications.

In this letter, we propose a pattern-diversity antenna with different radiation patterns at two different frequency bands (f1 and f2) (f1: broadside radiation pattern, f2: conical radiation pattern). The proposed structure consists of a central circular antenna and two annular ring antennas; each of the three antennas has individual ports. Two of the ports exhibit orthogonal broadside radiation patterns; the other two ports exhibit orthogonal conical radiation patterns. Thus, they have polarization diversity characteristics. To improve isolation between ports, the inner part of the annular ring antennas is shorted via array, and the outermost port is positioned orthogonal to the other ports. Using this configuration, the isolation between ports was measured as -26.7 dB and -30.1 dB at the two frequency bands, respectively. Experimental results based on the fabricated prototype show that the proposed antenna achieves -10 dB bandwidths of 240 MHz (5.71~5.95 GHz) and 210 MHz (7.69~7.9 GHz) at f1 and f2, respectively.

As the number of end-of-life vehicles continues to grow, the field of separation technology for broken copper and aluminium parts of end-of-life vehicles has emerged as a significant area of research. As a key technology for the separation of non-magnetic non-ferrous metals, such as copper and aluminium, eddy current separation can achieve efficient separation of non-magnetic non-ferrous metals according to their differing conductivity and density. Nevertheless, further research is required in the separation of large-scale broken copper and aluminium parts of end-of-life vehicles. This paper presents a novel magnetic roller model comprising circumferential and axial periodic arrangements of permanent magnets. A single permanent magnet was constructed as an equivalent current model, and the magnetic scalar potential equations were solved using simulation tools. This allowed the distribution of the magnetic field outside the magnetic roller to be studied. The results demonstrate that the novel permanent magnet array magnetic roller can enhance the magnetic field intensity and action distance of the external magnetic field, which is more conducive to the separation of large-scale broken copper and aluminium parts of scrap cars. The findings of this research provide a theoretical foundation for the separation of scrap car broken copper and aluminium parts.

Finite-time control theory has been widely used as a mathematical tool to design robust controllers. By manipulating the finite-time convergence proof of this theory, we developed a new control design appropriately tuned for the finite-time control of the chaotic logistics system. In our experimental setup, the logistic equation is programmed into a PIC microcontroller, and a part of the controller was conceived using analog electronics. Because the system to be controlled is in the discrete-time domain, and the finite-time stability proof is stated in the continuous-time representation, our finite-time control approach is a good example for designing control algorithms in both time domain schemes. Hence, our experimental results support our main contribution. Pulse Width Modulation (PWM) is the signal format used to translate digital signals into continuous-time fields.

The process of oxygenic photosynthesis is primarily driven by two multiprotein complexes known as photosystem II (PSII) and photosystem I (PSI). PSII facilitates the light–induced reactions of water–splitting and plastoquinone reduction, while PSI functions as the light–driven plastocyanin-ferredoxin oxidoreductase. In contrast to the highly conserved structure of PSII among all oxygen–evolving photosynthetic organisms, the structures of PSI exhibit remarkable variations, especially for photosynthetic organisms that grow in special environments. In this review, we make a concise overview of the recent investigations of PSI from photosynthetic microorganisms including prokaryotic cyanobacteria and eukaryotic algae from the perspective of structural biology. All known PSI complexes contain a highly conserved heterodimeric core; however, their pigment compositions and peripheral light-harvesting proteins are substantially flexible. This structural plasticity of PSI reveals the dynamic adaptation to environmental changes for photosynthetic organisms.

This paper proposes a metaphysical framework for distinguishing between human and machine intelligence. It posits two identical deterministic worlds -- one comprising a human agent and the other a machine agent. These agents exhibit different information processing mechanisms despite their apparent sameness in a causal sense. Providing a conceptual modeling of their difference, this paper resolves what it calls “the vantage point problem” – namely, how to justify an omniscient perspective through which a determinist asserts determinism from within the supposedly deterministic universe.

Third and fourth-degree anal sphincter injuries are among the most severe traumas women can experience during childbirth, often leading to lifelong continence issues. Despite extensive research, current repair techniques are often inadequate, failing to provide long-term solutions. Women with previous severe injuries face a higher risk of recurrence in subsequent deliveries, making caesarean sections a safer option in many cases. The existing WHO classification system is outdated, as it doesn't account for injuries to muscles like the levator ani, which are crucial for continence. Effective repairs require skilled surgeons and often involve more than just fixing the sphincter. Smaller hospitals may not have the necessary expertise and resources for these complex repairs. Delaying repairs to allow specialists to perform them can be just as effective as immediate repairs. Comprehensive care that includes thorough anatomical knowledge and surgical skill is essential. As maternal age increases and birth rates decline, it's crucial for specialized centers to handle severe perineal injuries to ensure the best outcomes and long-term care for patients.

Patients who survived critical COVID-19 frequently reported post-acute sequelae of COVID-19 (PASC) such as psychosomatic and neurocognitive health problems. The goal of this study was to identify clinical risk factors and other predictors for such long-term consequences in severely ill COVID-19 patients. Adult COVID-19 intensive care unit (ICU) survivors from August 2020 to May 2021 were enrolled. A broad range of clinical, laboratory and chest computed tomography (CT) data was collected during ICU stay. The association between ICU predictors and psychosomatic, respiratory and neurocognitive assessments 12 months after ICU discharge was analyzed using univariate regression analysis. In 17 patients (mean age 58.9 ± 11.4 years), laboratory markers (CRP, lymphocytes, hemoglobin), ICU severity (SOFA, SAPS II, need for mechanical ventilation), complications (ARDS), and lung CT data (ground-glass opacity) were promising predictors of depressive and anxiety symptoms, fatigue, and sleep problems. Recovery of psychosomatic health such as fatigue, depression and anxiety correlated with lower levels of inflammation and high hemoglobin levels. ARDS, mechanical ventilation and worse SOFA and SAPS II scores were further risk factors for depressive and anxiety symptoms. Our study identified novel associations such as pulmonary ground-glass opacity being positively associated with depression, anxiety, fatigue, and insomnia levels.

This study investigates the effects of home-based Kakao health care breathing exercises and stretching on respiratory function and fatigue in COVID-19 cured patients. A total of 35 participants performed four movements of home-based breathing exercise and five respiratory muscle stretching exercises four times a week for four weeks. Respiratory function was measured using FVC, FEV1, FEV1/FVC, and PEF. Fatigue was assessed using the Fatigue Severity Scale (FSS). Data analysis was performed using Independent Samples and Paired Samples T-tests in SPSS 24, with a significance level set at p &lt; 0.05. After four weeks of Home based Kakao health care Breathing Exercise, there were significant increases in respiratory FVC, FEV1, FEV1/FVC, and PEF function values observed in the training group (T.G.) after the exercise intervention (p &lt; 0.05). Such an increase was observed when comparing these values with the pre-exercise measurements. In contrast, there was no statistically significant difference in respiratory function outcomes before and after exercise in the control group (C.G.) (p &gt; 0.05). The FSS scores were statistically significant within the training group (T.G.). (p &gt;0.05). The 4-week Kakao health care Breathing Exercise was found to be capable of improving some respiratory functions in COVID-19-recovered patients, but it showed no significant improvement in fatigue levels.

Developing effective cognitive training tools for older adults, specifically addressing executive functions such as planning, is a challenging task. It is of paramount importance to ensure the implementation of engaging activities, which must be tailored to the specific needs and expectations of older adults. Furthermore, it is essential to provide the appropriate level of complexity for the planning task. A human-centred approach was employed to address the issues identified in the design of the tool. Two pilot studies were conducted with older adults to fine-tune the training task and optimise its suitability for them. This also led to an enhancement of the underlying planning engine, transitioning from simple fast-forward planner (PDDL4J) to an advanced heuristic search planner (ENHSP). The results show that conducting user studies enabled the development of a cognitive training system that gradually increases the proposed difficulty levels of the planning task while maintaining usability and satisfaction among older adults. This highlights the importance of conducting user studies when implementing cognitive training tools for older adults.

Depression is one of the most prevalent mental disorders worldwide. This study examined the effect of a spiritual connectivity intervention on individuals with depression in a randomized waitlist control trial. Fifty-seven participants with mild or moderate depressive symptoms were randomly assigned to either the intervention group (n=28) or the waitlist control group (n=29). The intervention comprised eight weekly sessions focusing on divine connection, forgiveness and freedom, suffering and transcendence, hope, gratitude, and relapse prevention. The outcome measures included depressive symptoms, anxiety, hope, meaning in life, self-esteem, and social support. Participants completed self-administered questionnaires at baseline (week 0), post-intervention (week 8), and at a 3-month follow-up (week 20). Repeated-measures ANOVA and one-way ANCOVA were used to compare the within-group and between-group differences in the changes in outcome variables. Participants in the intervention group showed significant improvements in depression, anxiety, spiritual experience, hope, self-esteem, and perceived social support after the intervention. Effect size statistics showed small to large differences (Cohen’s d, 0.308 to -1.452). Moreover, 85.71% of participants in the intervention group also experienced clinically significant reductions in PHQ-9 scores from baseline to immediate post-intervention. This study highlights the effectiveness of a low-cost, accessible intervention suitable for community implementation by clergy and faith-based organizations.

The purpose of this study was to analyze the cross-linguistic influence of previously learned languages and working memory capacities on the vocabulary performance of two different typological languages. The objectives of this study were (1) to compare the working memory capacities of bilingual adults in relation to the vocabulary performance of two different languages never learned by the participants, and (2) to analyze to what extent the typology of previously learned languages influences working memory capaci-ties in relation to the vocabulary performance of French and Nahuatl. A group of 43 Mexican-Spanish college students participated in this experimental study. The participants completed a series of working memory tasks in Nahuatl and French. The results showed that working memory capacities were lower in Nahuatl than in French. Thus, a correlation was found between their first and second language and vo-cabulary performance in French. We can consider the influence of previously learned languages as a significant factor in vocabulary acquisition in accordance with the participants' working memory capacities.

This study investigates the implementation and performance benefits of using a MongoDB replica set compared to a single node setup. The primary objective was to evaluate the efficiency and reliability improvements provided by replication in a NoSQL database cluster. The research involved configuring a single node and a three-node replica set, followed by conducting performance tests using CRUD operations on both setups. The results indicated that while the single node exhibited faster write operations, the replica set significantly improved read performance and provided high availability and fault tolerance. The findings highlight the advantages of using a replica set for applications requiring robust data access and consistent performance under varying workloads.

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

Conversational artificial intelligence (AI) has shown strong capabilities in providing low-cost and timely interventions for a wide range of people and increasing well-being. Therefore, this study examined ChatGPT’s efficacy in conducting psychological counseling and its potential for providing accessible psychological interventions, especially in school settings. This study assessed the strengths and limitations of AI to inform future research. Data were generated from ChatGPT’s responses to 80 counseling questions that college students asked during a school counseling setting. All the responses generated during these simulated counseling sessions were then analyzed using three primary metrics—warmth, empathy, and acceptance—following APA guidelines. The analysis adopted several natural language processing methodologies for emotion detection and empathy measurement to quantify ChatGPT’s high efficacy in presenting the appropriate emotions and reactions for counseling. Some responses demonstrated randomness, which is crucial for consideration regarding the use of ChatGPT or relevant technology in psychological counseling. The Discussion section also highlights future directions in the application of conversational AI to enhance students’ mental health.

Rationale: Genetically modified (GM) foods have the potential to reduce food insecurity and address economic and environmental issues. Despite these benefits, GM foods continue to face significant criticism and there is limited information on public awareness and understanding of their nutritional and environmental health benefits in Nigeria. This study aims to fill this gap by investigating public knowledge and perceptions of GM foods in Victoria Island, Lagos. Methods: A convenience sampling method was used to recruit 369 respondents from Victoria Island, Lagos. Data were gathered using a structured questionnaire. The target population comprised employed adults either residing or working on Victoria Island. Statistical analyses were conducted to examine the relationship between sociodemographic factors and awareness of GM foods. Results: The study found that a majority of respondents (62.9%, n=232) were knowledgeable about GM foods and their associated issues. However, many believed that their community was not well-informed on the topic. Awareness of GM foods was significantly associated with sociodemographic factors such as marital status and education (P<0.01). Most respondents were well-informed about the environmental and health benefits of GM foods, with 61.8% believing that GM food production could sustainably reduce reliance on chemical pesticides, fertilizers, and other energy inputs, thus mitigating their ecological impacts. Additionally, most respondents did not feel that purchasing or consuming GM foods conflicted with their beliefs or would affect their food choices. Conclusion: The study concludes that while individual awareness of GM foods is relatively high, there is a perception that community awareness is low. Sociodemographic factors play a significant role in shaping public awareness and perceptions of GM foods. Recommendations: This includes government should actively educate the public on the ecological and health benefits of GM foods and address any safety concerns; Implement strict border controls and food labeling for GM products to protect consumer rights and preferences for organic foods, provide sufficient technical and financial assistance to farmers who participate in organic seed programs to enhance national food security. Significant Statement: This study highlights the importance of public education on GM foods and underscores the need for government intervention to ensure informed consumer choices and support for sustainable agricultural practices.

This qualitative study explores the transformative role of Supplier Relationship Management (SRM) in the context of e-commerce, focusing on the integration of digital technologies and evolving supplier interactions. As digital advancements such as artificial intelligence, blockchain, data analytics, cloud computing, and the Internet of Things (IoT) reshape traditional SRM practices, e-commerce companies are experiencing significant improvements in efficiency, transparency, and collaboration. This research employs semi-structured interviews, document analysis, and case studies to examine the impact of these technologies on SRM, identify key collaborative practices, and assess risk management strategies. Findings indicate that digital integration enhances decision-making, streamlines operations, and fosters deeper, trust-based supplier relationships. AI facilitates predictive analytics and automates processes, while blockchain provides transparency and reduces fraud. Data analytics supports informed sourcing decisions and risk mitigation, and cloud platforms improve real-time collaboration. IoT enhances supply chain visibility, allowing for better inventory management. Despite these benefits, challenges such as high implementation costs, integration difficulties, data privacy concerns, and security risks remain significant barriers. Collaboration practices, including joint development, shared resources, and coordinated marketing, contribute to innovation and mutual growth, emphasizing the need for effective communication and trust. Risk management strategies, such as scenario planning and supplier diversification, are crucial for maintaining supply chain resilience. Strategic alignment between e-commerce companies and suppliers, including goal congruence and capability matching, is essential for seamless coordination and competitive advantage. The study underscores the importance of a holistic approach to SRM, integrating technology, collaboration, risk management, and strategic alignment to navigate the complexities of supplier relationships in the digital age. These insights provide a framework for e-commerce companies to optimize their SRM practices and achieve sustainable growth in a dynamic marketplace.

Despite the diaphragm's direct connection with the heart through the phreno-pericardial ligament, little is still known about the role of this primary breathing muscle in the cardiovascular system. The purpose of the present study was to determine the relationship of diaphragm muscle thickness, thickening, and strength with selected cardiovascular parameters. Thirty participants who qualified for a three-week post-COVID physiotherapy program were examined. Diaphragm muscle thickness on the left and right sides was assessed using ultrasound. Blood pressure and heart rate were evaluated by an automatic oscillometric device, while the rest of the cardiovascular parameters were calculated using standardized formulas from the literature. We found a relationship between the left diaphragm dome thickening ratio and systolic blood pressure, pulse pressure, stroke volume, cardiac index, ejection fraction, and saturation level measured after the 6-minute walk test (6-MWT). Patients with better left diaphragm dome strength were characterized by a lower difference in systolic blood pressure, pulse pressure, stroke volume, cardiac output, cardiac power output, ejection fraction, cardiac index, and pressure-heart rate product between pre- and post-6-MWT measurements. There was no correlation between right diaphragm dome function and cardiovascular parameters. There was no association of left and right hemidiaphragm function with resting cardiovascular parameters. In conclusion, the strength of the left hemidiaphragm plays an important role in the regulation and modulation of cardiovascular parameters during physical exertion.

In the constantly growing field of wireless communication, antenna selection has a considerable influence on system performance, efficiency, and dependability. This paper gives a thorough comparison of patch antennas and dipole antennas, two of the most common forms used in wireless communication. Patch antennas are distinguished by their low profile, ease of production, and integration with microwave electronics, as opposed to dipole antennas, which have become known for their simplicity, omnidirectional emission patterns, and broad application. The discussion begins with an explanation of the basic concepts, design considerations, and operational characteristics of patch and dipole antennas. Key performance criteria including bandwidth, gain, radiation efficiency, polarization, and impedance matching are assessed using theoretical considerations and actual applications. Case studies from modern wireless applications, such as mobile communication, Wi-Fi networks, and Internet of Things devices, are used to demonstrate the strengths and limits of each antenna type in real-world circumstances.The comparative literature review additionally explores advanced strategies for improving the performance of patch and dipole antennas, such as the use of metamaterials, reconfigurable components, and new substrate materials. Comparative models and experimental findings illustrate the trade-offs between size, cost, and performance, assisting engineers and researchers in determining the best antenna type for certain applications.

In this study the distribution of heavy metal in the agricultural soils in the vicinity of 3 large mine-landfills around Kizhnica mine in Kosovo was investigated. The mining sector is one of the most important sectors of the economic development of Kosovo. The Kizhnica mine is one of the main ore producers in Kosovo. In addition to the positive aspects of production development it has its own side effects such as: industrial waste and the possibility of contamination of sur-rounding areas including the agricultural lands in the surrounding region. Ten sampling sites close to the Kizhnica mining complex were selected. These sampling sites have been characterized and evaluated as the most critical points, due to the anthropogenic influences of the discharge of industrial water from mining flotation and open tailing dumps in the Kizhnica. Concentration of Pb, Zn, Cu, As, Cd, Ni, Mn and Sb in selected samples was carried out by inductively coupled plasma–optical emission spectrometry (ICP–OES). Obtained data were used in order to generate geochemical maps and for calculatation the contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo). The statistical clustering analysis (CA), Pearson correlation coefficient (r) and air spatial distribution patterns using AERMOD View-Gaussian air dispersion model are used to perform evaluation within the area. The results demonstrated higher contents of the heavy metals in the vicinity of the mining area. It may be concluded that the heavy metal contents are impacted by anthropogenic nature of the contamination that confirms a current eco-logical threat of the mining activities in the region. Finally, a paper proposes the potential reas-signment of the deposed waste material into different combinations in construction in order to enhance the waste management and reduce the continued risk to: residents, lands and all living beings in the region.

It was previously reported that the peptide derived from LfcinB, R-1-R exhibited anti-Candida activity and this activity was enhanced in combination with an extract from the Bidens pilosa plant. However, the mechanism of action has not been studied. In the current study, a proteomic study was carried out, followed by a bioinformatic analysis and biological assays in both SC5314 strain and a fluconazole-resistant isolate of Candida albicans, after incubation with R-1-R. The proteomic data showed that after treatment with R-1-R in the two study strains, most of the differentially expressed proteins in comparison to controls were up-regulated. These proteins were mainly involved in membrane and cell wall biosynthesis, membrane transporters, oxidative stress, the mitochondrial respiratory chain, and response to DNA damage. Besides, the proteomic analysis of C. albicans parental strain SC5314 treated with R-1-R in combination with an ethanolic extract of B. pilosa was also undertaken. The proteins differentially expressed after this treatment were involved in similar functional processes as the proteins differentially expressed after treatment with R-1-R peptide alone, but at different levels and were mostly down-regulated. The biological assays allowed validation of the proteomic results, evidencing damage to the cell surface, generation of reactive oxygen species and decrease in mitochondrial membrane potential. The results provide information to begin to unlock the understanding of the complex antifungal mode of action of the R-1-R peptide, its combination with the extract, and possibly other derivatives of natural products.

Methylene blue has been electropolymerized on the surface of a stainless steel 316. The addition of sodium oxalate and working at a pH near 11 has allowed to obtain steel electrodes coated with electroactive polymer. This polymer shows electrochromic properties similar to those of the monomer, but also appears electroactivity at more positive potentials which is associated to the active centers in the bridges between monomeric units. The study by means of digital video electrochemistry has allowed on the one hand, to quantify the color changes on the entire surface of the stainless steel simultaneously and by means of the mean color intensities to separate the contribution to the overall polymer response of the active centers of the phenothiazine ring and of the inter-monomer bonds. A reduction mechanism for the polymer compatible with the pH variation of the observed electrochemical behavior is proposed.

Legionella bacteria can proliferate in poorly maintained water systems, posing risks to users. All Legionella species are potentially pathogenic but Legionella pneumophila (L. pneumophila) is usually the primary focus of testing. However, Legionella anisa (L. anisa) also colonises water distribution systems, is frequently found with L. pneumophila and could be a good indicator for increased risk of nosocomial infection. Anonymized data from three commercial Legionella testing laboratories afforded analysis of 565,750 water samples. Data covered July 2019 to August 2021, including the COVID-19 pandemic. Results confirmed L. anisa commonly colonises water distribution systems, being the most frequently identified non-L. pneumophila species. Proportions of L. anisa and L. pneumophila generally remained similar but increases in L. pneumophila during COVID-19 lockdown suggests static water supplies might favour its growth. Disinfection of hospital water systems was effective but re-colonization did occur, appearing to favour L. pneumophila, although L. anisa colony numbers also increased as a proportion of the total. While L. pneumophila remains the main species of concern as a risk to human health, L. anisa’s role should not be under-estimated, either as a potential infection risk or as an indicator of the need to intervene to control Legionella colonization of water supplies.

The nutritional composition of food for animal production can be completed using olive tree and plant by-products due to their high contents of bioactive compounds, such as pentacyclic triterpenes. Here, we present a novel application of near-infrared spectroscopy (NIRS) for the prediction of the total or individual [maslinic acid (MA), oleanolic acid (OA), and uvaol (UO)] pentacyclic triterpene concentrations in a feed additive obtained from a plant mixture. The oxygen radical absorbance capacity of these types of samples demonstrated the existence of a high antioxidant capacity. The conventional determination methods of pentacyclic triterpenes concentration are costly, labor-intensive, and not practical for analyzing several lines within a limited timeframe at the factory level. The optimal regression model developed in our work demonstrated high correlation values for the calibration and validation sets, along with a high residual prediction deviation value. The NIRS method can be applied directly to dried powder and avoids extraction and high-performance liquid chromatography (HPLC) analysis. Our results also demonstrate that NIRS can accurately quantify pentacyclic triterpenes even at low concentrations in food additives. It can be used at the factory level to directly determine the concentrations in the additive powder obtained at the same time that the powder is produced.

Background: The objective of this study was to evaluate, the clinical benefit of benralizumab in patients with uncontrolled severe asthma associated with chronic rhinosinusitis with nasal polyposis (CRSwNP). Methods: The study included patients with uncontrolled severe asthma associated with CRSwNP who started therapy with benralizumab. Pulmonary function, eosinophilia, IgE, comorbidity, changes in the Asthma Control Test (ACT), Asthma Control Questionnaire (ACQ), Visual Analogue Scale (VAS), Quality of Life (AQLQ), VAS (obstruction, drip, anosmia, facial pressure), SNOT-22, decrease or withdrawal of steroids and other medication, hospital admissions and emergency visits were analysed. The FEOS scale and EXACTO were employed in the assessment of response. Results: We analyzed 58 patients who completed minimal treatment at 12 months. After treatment with benralizumab, exacerbations were reduced by 82% (p

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.

Knee osteoarthritis (KOA) is a progressive and multifactorial disease that leads to joint pain, muscle weakness, physical disability, and decreased quality of life. In KOA, hyaluronic acid (HA) quantity and molecular weight (MW) are decreased, leading to joint pain due to increased wear of the knee articular cartilage. Arthrogenic muscle inhibition, which is usually found in patients with KOA, is associated with joint inflammation, pain, and swelling, also causing muscle atrophy, primarily of the anterior thigh muscles, and hindering the rehabilitation process. The aim of our work was to determine if a single HA infiltration could minimize the effects of arthrogenic muscle inhibition in patients with KOA in the short term, using isokinetic dynamometry to evaluate the strength of the knee extensor and flexor muscles of the thigh. Thirty patients with KOA who underwent both clinical and isokinetic assessment, and that received a single injection of HA, were retrospectively included. Our results showed that a single intra-articular injection of HA significantly reduces pain and improves joint function at four weeks, while non-statistically significant improvements were observed for the reference isokinetic parameter (maximum torque) at both 90°/s and 180°/s. Further high-quality studies are necessary to confirm the results of our study.

Epilepsy is a non-communicable neurological disease characterized by abnormal brain activity with conceivable peripheral implications. Few studies examine the role of peripheral and brain inflammation in the relationship between seizure predisposition and nonalcoholic fatty liver disease. Severe early-life infections leading to sepsis results in increased inflammation that can aggravate epilepsy and hepatic damage progression both associated with increased odds for hospital admissions in epileptic patients. Here, we examined the effect of early LPS challenge (1 mg/kg, i.p. at post-natal day3, PND3) in inducing hepatic damage in a genetic model of young epileptic WAG/Rij rats (PND45), evaluating the intra- and inter-gender differences on systemic and liver inflammation, hepatic lipid dysmetabolism and oxidative damage associated to mitochondrial functional impairment. First, epileptic rats exposed to LPS, regardless of gender, displayed increased serum hepatic enzymes and altered lipid profile. Early LPS challenge induced a major inflammatory and immune response in male epileptic rats than females in both serum and liver, increasing pro-inflammatory cytokines and hepatic immune cell recruitment. Conversely, LPS-insulted females showed a marked alteration in hepatic metabolic and lipid profile and the reduction in mitochondrial fatty acid oxidation. The two different gender-related mechanisms of LPS-induced liver injury converge in mitochondrial oxidative damage with intensified ROS production in both sexes, that notably induced a compensatory increase in antioxidant defense only in females. Our study with a translational potential points out that early postnatal infections predispose epileptic rats to develop or worsen hepatic disorders in a sex-dependent manner, amplifying inflammation, lipid dysmetabolism, and mitochondrial impairment.

The ACEtabular rim eXtension (ACE-X) implant is a custom-made 3-dimensional-printed titanium device designed for the treatment of canine hip dysplasia. Thirty-four dogs (61 hips) underwent ACE-X implantation, and assessments were conducted using computed tomography, force plate analysis, Ortolani’s test, and Helsinki Chronic Pain Index (HCPI) questionnaires at five intervals: pre-operative day, surgery day, 1.5-month, 3-month, and 12-month follow-up. Statistically significant increases in femoral head coverage with negative Ortolani subluxation test were observed immediately after surgery and persisted throughout the study. Osteoarthritis (OA) scores remained stable, but osteophyte size significantly increased between the surgery day and the 12-month follow-up, especially in hips with a baseline OA score of 2 compared to those with a score of 1. Force plate data showed no significant changes during the study. The HCPI demonstrated a significant decrease in pain score from pre-operative value to 6-week follow-up and gradually decreased over time. Major complications were identified in 6 hips (9.8%) of 4 dogs. In conclusion, the ACE-X implant effectively increased femoral head coverage, eliminated subluxation, and provided long-term pain relief with minimal complications, benefiting over 90% of the study population. The study supports the ACE-X implant as a secure and valuable treatment for canine hip dysplasia.

Electrochromic measurements have been performed throughout the full composition range of reactive magnetron-sputtered mixed Titanium oxide and Molybdenum oxide (TiO2-MoO3) to search for enhanced Coloration Efficiency (CE). Optical parameters and composition have been determined and mapped by using Spectroscopic Ellipsometry (SE). Scanning Electron Microscopy (SEM) with Energy-Dispersive X-ray Spectroscopy (EDS). EDS has been used to check the SE results as it was used in our earlier paper [N. T. Ismaeel et al, Materials 2023, 16(12), 4204] for (TiO2-SnO2). Ti and Mo targets were put separately from each other, and the Indium-Tin-Oxide (ITO) covered glass and Si-probes on a glass substrate (30 cm × 30 cm) were moved under the two separated targets (Ti and Mo) in a reactive Argon-Oxygen (Ar-O2) gas mixture. By using this combinatorial process, all the compositions (from 0 to 100%) were achieved in the same sputtering chamber after one sputtering process. The CE (the change of light transmission for the unit electric charge) of mixed metal oxides (TiO2-MoO3) that are deposited by reactive sputtering has been studied in an electrochemical cell. This paper aims to assess the results of investigations of such materials showing the enhanced electrochromic behavior compared to the pure materials and to enhance the Coloration Efficiency.

Background:Almost the entire country of Burkina Faso was endemic to onchocerciasis. Onchocerciasis control efforts thus brought the prevalence of O. volvulus to a level where the disease was no longer a public health problem and a national onchocerciasis control program was set up in 1991 to ensure surveillance and maintain the gains made. A resurgence of onchocerciasis cases has been observed in two regions (Comoé, South West) located around several river basins in the 2010-2011. In accordance with WHO guidelines, for the management of resurgent cases, CDTI was implemented in the affected areas of Comoé and Sud-Ouest regions. Methodology: We conducted an extensive analysis to determine the effects of CDTI on parasitological indices of onchocerciasis in these two areas and we also analyzed the data in relation to the location of the village in relation to the river to see if this was a factor in the decrease in prevalence. Results: A total of 43 villages in 6 health districts, i.e., 100% of the villages that participated in the epidemiological surveys before and after the implementation of CDTI in the Southwest and Cascade regions were included in the study. The key findings were that standardized microfilaria prevalence and CMFL decreased significantly after the implementation of CDTI in both regions. For the average of the two regions, the results for standardized microfilaria prevalence were -5.91 with a 95% confidence interval of (-9.67; -2.16) and for CMFL were -0.29 with a 95% confidence interval of (-0.57; -0.01). Our results showed also a decline in standardized microfilaria prevalence and CMFL in all villages involved in the study. Moreover, the drop in the trajectory of the curve representing the predicted standardized microfilaria prevalence of villages located within 5 km of the streams was greater than that of villages located more than 5 km from the streams. Conclusion: Our results thus show that the implementation of effective CDTI could stop the transmission of O. volvulus in these two regions. The main challenge for stopping transmission could be the migration of populations to neighboring countries and migration of the vector from one country to another, as Burkina Faso shares some river basins with neighboring countries.

Brain-to-brain communication (B2B-C) is rapidly expanding, integrating communication technology and neuroscience to enable direct neural data transfer between people. Nonetheless, because neural data is susceptible to noise, interference, and hostile attacks, guaranteeing the security and resilience of B2B-C systems continues to be difficult. This work aims to use Adversarial Neural Network Training (ANNT) to improve the security of B2B-C systems by using Steady-State Visually Evoked Potentials (SSVEP) EEG data. We use two large SSVEP datasets for a thorough analysis: Lee2019_SSVEP and Nakanishi2015. We use the Fast Gradient Sign Method (FGSM) to create adversarial instances and ANNT to train the model on clean and adversarially perturbed data. The system's accuracy and resilience are significantly improved by ANNT, as seen by the up to 17% increase in adversarial accuracy and the average 0.03 point improvement in the Area Under the Curve (AUC). This work demonstrates how ANNT may strengthen B2B-C systems against advanced cyberattacks, opening the door for dependable and safe neural communication technologies.

Objective: To explore the hot spots and development trends of community public health research. Methods: The literature related to this topic was searched in CNKI and PubMed databases, and the trend map of the number of articles was drawn according to the obtained data. The included literature were analyzed with Vosviewer software for keyword and author co-occurrence, and CiteSpace 6.3.R1 Basic software was used for mechanism co-occurrence, key emergence and clustering analysis, and timeline distribution map drawing. Results: 189 Chinese literature and 77 English literature were selected. The Chinese literature focused on “community public health service, emergency management, and community governance”, and the research trend was “community public health emergency management and community governance”; English literature focuses on “nursing education, health education, human qualitative research”. Conclusion: Although the Chinese and English literature shows that scholars in this field have different emphases, the primary community health is the key and difficult point to realize the national public health service project, and improving the basic public health service in the primary community is related to the health of all the people, so it is very important.

The existing methods of oil palm Fresh Fruit Bunch (FFB) evacuation from in-field to temporary collection point which typically apply medium to large tractors, often result in unexpected soil compaction. Meanwhile, smaller size equipment indicates low working capacity and unable to perform direct unloading to collection bin. This paper addresses the challenge of FFB evacuation by focusing on preventing soil compaction, increasing working capacity and enabling direct unloading to collection bin. For this purpose, a 6x6WD transporter prototype with a scissor lift mechanism was developed. With the design, the transporter could evacuate FFB in both steep mineral terrain and low ground pressure peatland, able to carry FFB with capacity of 750 kg and provide direct unloading into collection bin. The average field working capacity of the transporter was found to be 15 tons day-1. This research offers insights for future designs of medium-sized FFB transporters with advanced unloading mechanisms.

The use of Retrieval-augmented generation (RAG) using large language models (LLMs) has shown potential for addressing issues such as hallucinations and inadequately contextualized responses. A pivotal stage in the RAG process involves a retriever for retrieving chunks based on semantic similarity with the query. In this study, we advocate for and provide experimental evidence supporting integrating and maintaining questions and answers (QA) formatted databases to improve retrieved-context representations and response quality. Our experiments evaluate our approach on benchmark RAG datasets using standard evaluation metrics and provide comparative analyses against state-of-the-art retrieval methods, showing the potential of our approach.

Candidiasis is a significant fungal infection caused by various species of the genus Candida, posing health challenges to a wide range of animals, including Choloepus species (two-toed sloths). This review article aims to provide a comprehensive understanding of candidiasis in Choloepus sp., highlighting the etiology, epidemiology, pathogenesis, clinical manifestations, diagnosis, treatment, and prevention strategies.The article begins by examining the causative agents, primarily focusing on Candida albicans, which is the most commonly implicated species in candidiasis. The epidemiological aspects are discussed, emphasizing the prevalence of candidiasis in wild and captive Choloepus populations and identifying predisposing factors such as immunosuppression, stress, poor nutrition, and environmental conditions. Pathogenesis is explored, detailing the mechanisms through which Candida species invade host tissues and evade immune responses. Clinical manifestations in Choloepus sp. are described, including oral thrush, cutaneous lesions, and gastrointestinal infections, and their impact on the health and behavior of affected individuals. Diagnostic methods, including culture techniques, histopathology, and molecular assays, are reviewed to highlight their roles in accurately identifying Candida infections. The article also covers treatment options, focusing on antifungal therapies and supportive care tailored to the unique physiology of Choloepus sp. Finally, prevention and management strategies are discussed, emphasizing the importance of maintaining optimal husbandry practices, regular health monitoring, and early intervention to reduce the incidence and impact of candidiasis in Choloepus populations. This review underscores the need for further research to enhance our understanding of candidiasis and improve health outcomes for these unique and vulnerable animals.

This article examines illicit financial flows (IFFs) perpetuated in financial statements to develop a framework to curb IFFs. IFFs create opacity, impeding economic progress through investment deterrents and financial uncertainty. Through a comprehensive literature review and the synthesis of sets of qualitative propositions, the researchers previously developed a conceptual framework to address IFFs, and the purpose of the present article is to strengthen and validate the framework among stakeholders in the financial and audit sectors. Following a mixed inductive and deductive research approach and a qualitative methodological choice, the researchers conducted interviews among practitioners to enhance the framework, followed by a focus group to validate the framework. IFF challenges that emerged are tax evasion, for example, investments in untraceable offshore accounts, harming the economy, bitcoins not being subject to regulation everywhere in the world and being used by cryptocurrency criminals to transfer IFFs to nations with lax regulations. Internationally, IFF risks are also determined by geographical position, trade links and porous borders among countries emerged as further challenges, calling for entities to execute existing policies, improve tax enforcement methods, apply cross-border coordination, and practice financial reporting transparency aimed at combatting IFF practices. On the strength of these, the industry surveys significantly enhanced the conceptual framework.

Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability. Hence, detecting abnormal samples in the dataset can help clinicians make better decisions. In this study, we propose an unsupervised error detection method using patterns discovered by the Pattern Discovery and Disentanglement (PDD) model, developed in our earlier work. Applied to the large data, the eICU Collaborative Research Database for sepsis risk assessment, the proposed algorithm can effectively discover statistically significant association patterns, generate an interpretable knowledge base for interpretability, cluster samples in an unsupervised learning manner, and detect abnormal samples from the dataset. As shown in the experimental result, our method outperformed K-Means by 38% on the full dataset and 47% on the reduced dataset for unsupervised clustering. Multiple supervised classifiers improve accuracy by an average of 4% after removing abnormal samples by the proposed error detection approach. Therefore, the proposed algorithm provides a robust and practical solution for unsupervised clustering and error detection in healthcare data.

Historically, the military and non-religious, sub-continent’s intellectual elite Muslim men crafted state ideologies before partition, by actively contributing to sociocultural constructs prevalent to this day, in service of colonial patriarchal concepts. The purpose of this ideological collaboration has been to mould a Pakistani cis-gendered female child primarily into the ideal “Pakistan-Muslim” bride for marriage, carried out through her family and society. This has shaped the lives of cis-gendered female children in Pakistan through coerced, gendered control, implemented as prescriptive societal norms. These norms are rooted in colonial, patriarchal ideologies and are functions of capital and coercion intentionally perpetuated to erase her pluralistic identity, reducing her to a central resource within a family unit. To the military concept of nationalism, her mind and her body symbolize the unification and centralization of a statist ideology. Thus, the military state plays an essential role in shaping her purpose around the concept of nationalism. The intellectual elite, via the state, uphold colonial, patriarchal ideologies, where the primary identity of a cis-gendered female child is actualized through her marriage. The cis-gendered female child’s life is a vehicle to unify the state’s two-fold “Pakistani-Muslim” agenda, by implementing a ‘singular statist narrative’. A narrative that attempts to resolve two major tensions: First, it seeks to wipe out the possibility of a nation connecting with and exploring its own immense, internal ethnocultural diversity. It does this by imposing an imagined “homogenous Muslim” identity — which doesn’t exist — and is instead imported from multiple countries to reinforce a ‘singular statist narrative’, Second, it aims to control the mixing of local, sociocultural narratives by bridging any disjuncture between them by labelling colonial institutional patriarchy concepts as inherently “Pakistani”; in service of its preferred ‘singular statist narrative’.

Background: Infective endocarditis (IE) remains a difficult disease to diagnose and treat, with a persistently high mortality rate. There is a lack of recent data on IE in Bulgaria over the last decades. Methods: The study is retrospective, single centered, includes 270 patients diagnosed with IE, for the period 2005 - 2021. We compared the two periods 2005-2015 (n=119) and 2016-2021 (n=151) to find the characteristics changes. Results: The median age was 65 (23) years and 65.5% (177) were male. In the second period, there is a significant increase in age from 62 (29) to 67 (22), (p=0.023); Charlson comorbidities index (CCI) from 3 (3) to 4 (4), (p=0.000); cases with chronic kidney diseases (CKD) from 12.6% (15) to 36.9% (55), (p=0.001); coronary arterial diseases (CAD) from16.85% (20) to 29.1% (44), (p=0.018); atrial fibrillation (AF) from 10.9% (13) to 23.8% (36), (p=0.006). Injection fraction decreased significantly in the second period from 63 (14) to 59 (15), (p=0.000). Almost half of the patients 45.6% (123) had no known predisposing cardiac condition and 46.3 (125) had an unknown port of entry. IE was community-acquired in 173 (64.1%), healthcare-associated in 26.7% (72), and injection drug use related IE in 9.3% (25).The study population included 67.8% (183) native valve IE, 31.5% (85) prosthetic IE, and 0.74% (2) intracardiac device­related IE. The hemoculture were positive in 59.6%, and the most frequent pathogenic agent was Staphylococcus - 33.3 % ( aureus – 16.5 % and coagulase negative - 16.8 %). Only 20% of patients underwent early surgery. The all­cause 30 days mortality rate was 24.8%. There is no significant difference between the two periods in terms of the characteristics listed above. Conclusion: The profile of IE in Bulgaria has changed with increasing age and comorbidity, changing predisposing cardiac conditions and entry door. The most common pathogen was the Staphylococcus group. The 30 day mortality rate remains high.

Liberation war of Bangladesh was estimated to be held in financial year 1971 to gain independence from Pakistan. Bangladesh alone generated 70% of export return and in turn it received only 25%. The fabric mills of Bangladesh faced a slow increment from 11 to only 26 mills operating from 1947 till the fiscal year 1970. Nationalization of Urdu speaking language finally created outrage and turmoil among citizens of West and East Pakistan and generated war of Freedom Movement. This article mainly sheds light of different challenges faced by Bangladesh citizens such as genocide, women torture and communal disparity. Different factors such as economic turmoil political unrest and minor treatments were major reason behind the hate campaign of the liberation war. Thus, this article critically demonstrates the strategies adopted for mitigating challenges such as peaceful negotiation and maintenance of equality and similar priority to every citizen. This article critically evaluates the concept of hate campaign and Liberation War of Bangladesh. Its aim at analyzes ways incorporated by liberation war of Bangladesh for triggering hate campaigns along with different factors affecting hate campaigns. This study shed light on illustrating three different case studies including when government of Bangladesh undertook strict actions against mobs that tend to vandalize on Communal activities. In addition, second case study includes when social media platform Facebook formed a partnership with Asia foundation for combating online haters-based intolerance. Apart from that, third case study evaluating hate campaign on using social media platform it blocks two groups of people for hacking allegations.

To accurately determine the refractive error of the eye, sufficient relaxation of eye accommodation is essential, either through the fogging technique or pharmacological cycloplegia. This study aimed to evaluate the clinical information revealed after cycloplegia and assess how age and non-cycloplegic refractive status influence the classification of eye refractive error. We analyzed the records of 472 non-population-based subjects aged 3–28 years (mean ± SD: 9.1 ± 4.6) who attended a private ophthalmology practice from January 2018 to December 2020. Cycloplegia was induced with one drop of cyclopentolate 1% in each eye, and refraction was measured 30 ± 5 min later using an objective autorefractometer. The average spherical equivalent (SE) difference (mean ± SD) induced by cycloplegia was 0.72 ± 0.73 D, with the highest difference observed in the 3-5 years age group (1.18 ± 0.85 D). Gender had no significant effect on the SE values before or after cycloplegia (p &gt; 0.05). Cycloplegia caused a hyperopic refractive shift in 83% of participants, no shift in 12%, and a myopic refractive shift in 6%. This study highlights the importance of cycloplegia use in children and young adults.

Despite the known benefits of precision agriculture, the adoption is challenging due to the cost of investment and the farm sizes. Therefore, profitability is an important aspect to consider. This study aimed to evaluate the net returns, profitability, and investment efficiencies of PA by different economic farm sizes. The study was based on data retrieved from FADN and Eurostat. The study examined four countries (Poland, Germany, France, and Romania) under field crop farming using an investment cost of €35 941 - €71 883, and a 20% and 15% reduction in the cost of crop protection and fertilizer usage respectively without compromising productivity. There is a positive relationship between the adoption of PA and farm returns for larger-scale farms. The result of the profitability and analysis of investment efficiency using NPV showed a positive value for economic farm sizes of €100 000 and above. Hence, it is not economically advisable that all farmers use PA technologies with the hope that they will be profitable but with public support (subsidies) more farms will be able to use PA and be profitable. Also, an opportunity to meet the goal of the European Union Green Deal of minimizing emissions that cause climate change.