Maternal and child nutrition has been a critical component of health, sustainable development, and progress in low- and middle-income countries (LMIC). While a decrement in maternal mortality is an important indicator, simply surviving pregnancy and childbirth does not imply better maternal health. One of the fundamental obligations of nations under international human rights law is to enable mothers and teenage girls to endure pregnancy and delivery as an aspect of their enjoyment of reproductive and sexual health and rights and live a dignified life. The aim of this study was to discover the correlation between the Maternal Observation and Motivation (MOM) program and m-Health support for maternal and newborn health. A Comparative study was done among 109 pregnant mothers (study group-94; control group-102 mothers) with not less than 20 weeks of gestation. Maternal outcomes such as Hb, weight gain and newborn results like birth weight and crown- heel length was obtained on the baseline, 28 and 36 weeks of gestation. Other secondary data collected were abortion, stillbirth, low birth weight, major congenital malformations, twin or triplet pregnancies, physical activity and maternal wellbeing. The MOM intervention included initial face to face education, three in-person visits and eight virtual health coaching by WhatsApp. The baseline data on Hb of the mothers show that 31(32.98%) vs 27(28.72%) of the study and control group had anaemia, which improved to 27.66% and 14.98% among study group mothers at 28 and 36 weeks of gestation (p<0.001). The weight gain (p< 0.001), level of physical activity (p< 0.001), and maternal wellbeing (p< 0.01) also had significant differences after the Intervention. Even after controlling for potentially confounding variables, the maternal food practices regression model revealed that birth weight was directly correlated with consumption of milk (p 0.001), fruits (p 0.01), and green vegetables (p 0.05).As per the physical activity and maternal wellbeing regression model, the birth weight and crown heel length were strongly related with the physical activity and maternal wellbeing of mothers at 36 weeks of gestation (p <0.05). Combining the MOM intervention with standard antenatal care is a safe and effective way to improve maternal welfare while upholding pregnant mothers' human rights.

A radical, albeit pragmatic protocol for experimental access to putative String/M-theoretic, Einstein Unified Field Mechanical (UFM) additional dimensionality (XD) of the brane-bouquet bulk is presented. If successful, results demonstrate the existence dimensionality beyond the metric of observed physical reality provided by the Standard Model (SM) of particle physics and Cosmology. Quantum Mechanics (QM), as well-known is incomplete and further, should no longer be considered the basement of reality; meaning, Locality and Unitarity – the fundaments of quantum theory are an insufficient basis for extending the representation of reality. A seminal model of Tight Bound States (TBS) below the lowest Bohr orbit in the hydrogen atom, proposed by Vigier, is extended to a Kaluza-Klein-like (KK) cyclical tier of XD hyperspherical cavities defined within a manifold of uncertainty (MOU) of finite radius up to the semi-quantum limit, predicting, within its domain, new spectral lines in Hydrogen. The proposed protocol for this process, with phase modifications, provides efficacy of large-scale additional dimensionality (LSXD) of the brane bulk; XD-LSXD incursion duality accesses nonlocal Einsteinian UFM phenomena, leading to myriad new classes of technological innovation.

Considering the fault "N-1" checksum and the power flow, the single-phase power flow model is further transformed into a three-phase power flow model, and the asymmetry of the three-phase power flow is measured by the three-phase unbalance factor. The calculation model is linearized by the second-order cone relaxation and the Big-M method. At the same time, the load response and distribution network reconstruction are used to improve the reliability of the power supply network to cope with the power failure. The relationship between power supply capability and power flow constraints, main transformer capacity and distributed power parameters is analyzed by IEEE 33-node three-phase power distribution system. The feasibility of the proposed model and the accuracy of the second-order cone relaxation are verified by numerical examples, which provides a technical reference for distribution network planning.

Formation of Fe- and Mg-rich smectite and zeolite under alkaline conditions is concerned as secondary minerals after alkaline alteration of bentonite in a repository of radioactive wastes. It might be crucial for safety assessment whether smectite will be formed or not as secondary minerals after alkaline alteration of bentonite. In present paper, Fe- and Mg-rich smectite which are currently interacting with hyperalkaline groundwater was found at Narra in Palawan, Philippines. Mineralogical and geochemical investigation was conducted to understand formation process of smectite and factors determined secondary mineral species. Our study revealed a certain amount of smectite may have been produced under hyperalkaline conditions, altered from amorphous or poorly crystalline material such as M-S-H and F-S-H. Key factor which decides smectite or zeolite as secondary minerals after alkaline alteration of bentonite might be whether nuclei of M-S-H and/or F-S-H will be formed or not. This might be decided by the presence of dissolved Mg2+ and Fe2+ in the system. Our suggested formation process of smectite under alkaline conditions is analogue with generally-accepted model of smectite formation that might have been occurred on early Mars.

The rapid evolution of digital payment systems has significantly transformed the retail industry, reshaping how transactions are processed and enhancing the overall shopping experience. This research explores the adoption of digital payment technologies in retail settings, focusing on the motivations, challenges, benefits, and impacts associated with their implementation. Retailers are increasingly driven by the need to meet consumer demands for convenience and speed, as well as to gain a competitive edge in a saturated market. Digital payment systems, including mobile wallets, contactless payments, and online payment gateways, have become essential tools for retailers seeking to streamline operations and improve customer satisfaction. The study highlights several key findings, including the challenges related to technical integration, security concerns, and cost implications. Technical difficulties in integrating new payment systems with existing point-of-sale infrastructure, coupled with the need for robust security measures, present significant obstacles. Despite these challenges, the long-term benefits of digital payments, such as increased transaction volumes, higher average transaction values, and valuable data insights, often outweigh the initial investment and ongoing costs. The research also underscores the positive impact of digital payments on customer behavior, noting improvements in transaction speed, convenience, and overall satisfaction. Furthermore, the findings reveal variations in the impact of digital payment systems across different retail settings, including large department stores, independent retailers, and e-commerce businesses. The ability to tailor digital payment solutions to the specific needs of each retail environment is crucial for maximizing benefits and ensuring successful implementation. Overall, the study provides a comprehensive understanding of the role of digital payment systems in modern retail and offers insights into the future trajectory of these technologies.

This qualitative study explores the role of Supplier Relationship Management (SRM) in optimizing inventory within the context of e-commerce. Through semi-structured interviews with e-commerce managers and supply chain experts, the study investigates the strategies, challenges, and outcomes associated with SRM practices. Key findings highlight the critical importance of strategic partnerships with suppliers, emphasizing trust, transparency, and goal alignment as foundational elements for effective SRM. Participants underscored the transformative impact of technological advancements, including advanced analytics and blockchain technology, in enhancing supply chain visibility, optimizing inventory levels, and improving operational agility. However, the study also identifies challenges in SRM implementation, such as cultural differences, regulatory compliance, and geographical distances, which require proactive management strategies. Innovation emerges as a key driver of competitive advantage in e-commerce, facilitated through collaborative R&D initiatives and co-innovation with suppliers. Strategic alignment with organizational goals is crucial for integrating SRM practices with broader business objectives, including operational efficiency and risk mitigation. Recommendations include adopting integrated SRM strategies that leverage technological innovations while maintaining a focus on relationship-building and sustainability. Enhanced supplier performance monitoring, proactive risk management, and the integration of sustainable practices are proposed to strengthen supplier relationships and enhance supply chain resilience. By addressing these insights, e-commerce firms can optimize inventory management, drive innovation, and achieve sustainable growth in the digital economy.

This study investigates the critical role of Supplier Relationship Management (SRM) in enhancing the e-commerce user experience. In an increasingly competitive digital marketplace, effective SRM practices are essential for optimizing supply chain operations and meeting customer expectations. The research employs a qualitative approach, combining semi-structured interviews with industry stakeholders, extensive literature review, and case studies to explore various dimensions of SRM. Key findings reveal that strategic supplier selection criteria, including quality, cost efficiency, reliability, innovation, and sustainability, are pivotal in ensuring a robust and adaptable supply chain. Effective communication practices, such as transparency, frequent updates, and digital tools, foster strong supplier relationships and enable timely issue resolution. Performance management strategies, centered on KPI monitoring and continuous improvement, support operational excellence and customer satisfaction. Risk management practices, including diversification, contingency planning, and advanced analytics, are crucial for mitigating disruptions and ensuring supply chain resilience, as highlighted by the challenges posed during the COVID-19 pandemic. Technological integration with blockchain, AI, IoT, data analytics, and automation enhances efficiency, transparency, and decision-making capabilities in SRM. Furthermore, the study underscores the evolving integration of sustainability and ethical sourcing into SRM strategies, reflecting broader corporate responsibility goals. Ultimately, this research contributes to understanding how effective SRM strategies drive competitive advantage in e-commerce by enhancing supply chain reliability, responsiveness, and customer-centricity. As e-commerce continues to evolve, adapting and innovating SRM practices will be vital for companies aiming to sustain growth and meet the dynamic demands of global markets.

This qualitative study explores the dynamics of Supplier Relationship Management (SRM) and its impact on innovation within the e-commerce sector. Through in-depth interviews and documentary analysis of three case study firms known for their innovative practices, the study examines how collaborative SRM practices influence innovation outcomes, organizational resilience, and competitive advantage in dynamic market environments. Key themes include the pivotal role of trust, transparency, and joint problem-solving in fostering effective SRM relationships, enabling knowledge sharing and co-development of innovative products and services. Innovation outcomes observed encompass product innovation, process improvements, and technological advancements facilitated by close collaboration between e-commerce firms and their suppliers. Challenges such as managing supplier diversity, navigating regulatory complexities, and mitigating geopolitical risks highlight the complexities and strategic imperatives of SRM implementation in global supply chains. The study also emphasizes the transformative role of digital technologies, including real-time data exchange, predictive analytics, and agile supply chain management, in enhancing SRM effectiveness and innovation capabilities. Strategic alignment with organizational goals and market strategies further enhances the impact of SRM, enabling firms to prioritize innovation initiatives, allocate resources effectively, and sustain growth amidst economic uncertainties. The findings contribute to theoretical understanding and practical insights into SRM strategies that promote innovation excellence and competitive positioning within e-commerce. The implications for practice underscore the importance of fostering collaborative supplier relationships, investing in digital transformation, and adopting proactive strategies to manage risks and regulatory compliance.

This qualitative study explores Supplier Relationship Management (SRM) in the context of digital transformation within e-commerce businesses, focusing on the implications of emerging digital technologies. Through semi-structured interviews and documentary analysis, the study examines how organizations leverage technologies like artificial intelligence (AI), blockchain, and Internet of Things (IoT) to enhance SRM practices. Findings reveal that digitalization enables improved operational efficiencies, real-time data analytics, and expanded supplier networks through platforms such as Amazon Business and Alibaba. Strategic shifts are noted towards collaborative supplier relationships, emphasizing joint innovation, technology co-investment, and shared risk management strategies. However, the implementation of digital SRM strategies presents challenges, including data privacy concerns, integration complexities, cybersecurity threats, and regulatory compliance issues. Organizations must navigate these challenges by developing robust governance frameworks and cybersecurity protocols to protect sensitive information and ensure regulatory adherence. Key performance indicators (KPIs) such as supplier performance, cost savings, innovation impact, risk management effectiveness, and sustainability integration are critical for evaluating the success of digital SRM initiatives. Strategically, businesses are advised to prioritize leadership commitment, cross-functional collaboration, and continuous learning to optimize digital SRM practices effectively. Future research should explore emerging trends in digital SRM, investigate technological impacts on supplier dynamics and organizational performance, and examine ethical considerations in digitalization. By integrating these insights into strategic decision-making, businesses can enhance supplier relationships, mitigate operational risks, and achieve sustainable growth in the global marketplace.

This qualitative research investigates the influence of Corporate Social Responsibility (CSR) on Supplier Relationship Management (SRM) within the e-commerce sector. Through semi-structured interviews and secondary data analysis, the study explores motivations, challenges, impacts, and strategic outcomes of integrating CSR practices into supplier relationships. Motivations for adopting CSR include ethical considerations, regulatory compliance, and meeting stakeholder expectations, reflecting a strategic alignment with corporate values and societal demands. Challenges such as resource constraints, regulatory complexities, and cultural differences highlight operational hurdles and strategic considerations e-commerce firms face in implementing CSR initiatives effectively. The study reveals that CSR enhances trust, collaboration, and risk mitigation within e-commerce supply chains through transparent communication, shared values, and ethical practices. Strategically, CSR contributes to enhanced brand equity, competitive advantage, and long-term value creation by differentiating firms in competitive markets and attracting socially conscious consumers and investors. However, economic trade-offs, stakeholder divergence, and operational complexities require firms to adopt adaptive strategies that balance short-term financial goals with long-term sustainability objectives. The findings suggest avenues for future research exploring longitudinal impacts of CSR on supplier relationships, cross-sectoral comparisons, and technological advancements in CSR-driven SRM practices. Practically, e-commerce firms should prioritize strategic alignment of CSR initiatives with core business objectives, engage stakeholders in CSR strategy development, and embrace continuous improvement to foster ethical conduct, stakeholder trust, and sustainable business practices.

Supplier Relationship Management (SRM) plays a pivotal role in enhancing delivery performance within the e-commerce sector, yet understanding its nuanced impacts remains crucial for optimizing operational efficiencies and customer satisfaction. This qualitative research explores the intricate dynamics of SRM in e-commerce, focusing on strategic alignment, technological integration, trust, collaboration, and risk management as key determinants of delivery reliability. Through in-depth interviews and thematic analysis, the study reveals that strategic alignment of supplier capabilities with firm objectives is fundamental for maintaining a responsive and synchronized supply chain. Technological integration, including AI-driven analytics and blockchain applications, emerges as critical for real-time monitoring and adaptive decision-making, thereby improving delivery accuracy and efficiency. Trust and collaboration are identified as essential pillars for building resilient supplier relationships, fostering transparent communication and joint problem-solving. Effective risk management practices, such as supplier diversification and contingency planning, mitigate disruptions and ensure consistent delivery performance. Despite these benefits, challenges such as technological adoption barriers, cultural differences, communication complexities, resource constraints, and supplier reliability issues persist, necessitating strategic interventions. Recommendations include investing in advanced SRM technologies, promoting cultural understanding, enhancing communication protocols, allocating adequate resources, and fostering collaborative initiatives with suppliers. These strategies aim to overcome challenges and optimize SRM practices, ultimately enhancing delivery performance and competitiveness in the e-commerce landscape.

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 period of the COVID-19 pandemic resulted in a rapid development of innovative education methods, in particular using e-learning and remote work tools. The effects of this development are also post-pandemic changes in formal teaching regulations, in particular in higher education, allowing classes and lectures to be carried out with Blended Learning or Flipped Classroom methods. This paper provides information about a case study of implementing ICT technologies with elements of the mentioned methods in one of the subjects at a technical university. The implemented tools and solutions in the field of e-learning and interactivity are presented, along with information regarding their perception by students during two academic years in the post-COVID-19 period. The analysis of results of these information and student evaluations indicates their generally positive approach to such innovations in the educational path, and at the same time shows significant challenges for teachers to increase the attractiveness and effectiveness of the teaching process and the development of practical, technical skills of students.

This study explores the intricate dynamics of customer-centric supply chains and the pivotal role of marketing innovations in enhancing efficiency and customer satisfaction. Employing a qualitative research methodology, semi-structured interviews were conducted with key stakeholders in supply chain management across various industries, providing rich insights into the practices and perceptions related to customer-centric strategies. The findings highlight the centrality of understanding and anticipating customer needs, which necessitates a cultural shift within organizations to prioritize customer satisfaction at all levels. Digital marketing tools, data analytics, e-commerce platforms, and social media emerged as critical enablers of these customer-centric supply chains, facilitating real-time insights, direct customer engagement, and personalized experiences. The integration of these technologies has led to more accurate demand forecasting, optimized inventory levels, and enhanced agility and responsiveness in operations. Furthermore, the study underscores the importance of collaboration and partnership within the supply chain network, emphasizing joint initiatives and strong relationships with stakeholders as key drivers of improved resource utilization and service levels. Sustainability, entrepreneurship, and emotional intelligence also play significant roles in shaping effective customer-centric supply chains. Sustainable practices meet growing consumer demands for environmental and social responsibility, while an entrepreneurial mindset fosters continuous innovation and competitiveness. Emotional intelligence among leaders and employees enhances trust, conflict resolution, and collaboration, contributing to a positive organizational culture and superior customer satisfaction. Overall, this study provides comprehensive insights and actionable recommendations for businesses seeking to navigate the complexities of customer-centric supply chain management and leverage marketing innovations to achieve sustainable competitive advantage.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

This study investigated the presence, distribution, and antimicrobial resistance profiles of extend-ed-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae in a dairy herd located in Northern Italy. A questionnaire was administered, and the feces of clinically healthy pre-weaned dairy calves, their mothers, and the cows treated for mastitis, waste milk, water, and environmental samples, were collected and inoculated on Chromagar ESBL™ medium. The questionnaire identi-fied several risk factors including administration of waste milk to male calves, lack of routine cleaning of calf feeding and housing equipment, and blanket dry cow therapy. Escherichia coli was identified by MALDI-TOF MS in the feces of 28 of 37 (75.67%) calves, 2 of 3 (66.67%) treated cows, 8 of 14 (57.15%) environmental samples, and the waste milk. Six of 14 (42.85%) environmental samples were also positive for ESBL Acinetobacter baumannii, while all fecal samples were negative. ESBL production was confirmed for all E. coli isolates based on the double disk susceptibility test (DDST), while none were carbapenemase producers. Upon minimal inhibitory concentration (MIC) analysis, all of them showed multiple resistances and were categorized as multi-drug resistant (MDR). This study confirms the widespread presence of MDR, ESBL-E. coli in dairy calves and highlights their diffusion in the farm environment.

The symmetries of a Riemann surface $\Sigma \setminus \{a_i\}$ with $n$ punctures $a_i$ are encoded in its fundamental group $\pi_1(\Sigma)$. Further structure may be described through representations (homomorphisms) of $\pi_1$ over a Lie group $G$ as globalized by the character variety $\mathcal{C}=\mbox{Hom} (\pi_1,G)/G$. Guided by our previous work in the context of topological quantum computing (TQC) and genetics, we specialize on the $4$-punctured Riemann sphere $\Sigma=S_2^{(4)}$ and the \lq space-time-spin' group $G=SL_2(\mathbb{C})$. In such a situation, $\mathcal{C}$ possesses remarkable properties (i) a representation is described by a $3$-dimensional cubic surface $V_{a,b,c,d}(x,y,z)$ with $3$ variables and $4$ parameters, (ii) the automorphisms of the surface satisfy the dynamical (non linear and transcendental) Painlev\'e VI equation (or $P_{VI}$), (iii) there exists a finite set of $1$ (\mbox{Cayley-Picard})+$3$ (\mbox{continuous platonic})+$45$ (\mbox{icosahedral}) solutions of $P_{VI}$. In this paper we feature on the parametric representation of some solutions of $P_{VI}$, (a) solutions corresponding to algebraic surfaces such as the Klein quartic and (b) icosahedral solutions. Applications to the character variety of finitely generated groups $f_p$ encountered in TQC or DNA/RNA sequences are proposed.

This study employed e-Vol DX cone beam computed tomography (CBCT) software to assess dentin remnants in the furcation area of mesial canals in mandibular molars during root canal retreatment (RCR). Four groups (Reciproc®, ProTaper Next®, Race Evo®, Protaper Gold®) were subjected to RCR, and CBCT images were captured before (T1) and after (T2) treatment. Measurements of remaining dentin thickness at 1 mm and 3 mm below the furcation were scrutinized. Results revealed no significant differences in mean thicknesses of mesiobuccal (MB) and mesiolingual (ML) canals at 1 mm and 3 mm from the furcation pre-treatment (T1). Post-treatment (T2) showed analogous findings, with no significant differences in mean thicknesses. However, disparities surfaced between MB and ML canals at both distances, both before and after retreatment. In essence, the evaluated instruments exhibited safety in RCR, implying their appropriateness for use in critical areas of mandibular molars without inducing excessive wear. This study underscores the instruments' reliability in navigating danger zones during RCR, contributing valuable insights for dental practitioners handling complex root canal scenarios in mandibular molars.

The goal of the current study was to discover a novel potential probiotic strain of Lactobacillus spp. with anti-Escherichia coli activity from locally produced yogurt in Tongi, Gazipur, Bangladesh, compare its antagonistic activity with a commercial probiotic mixture of several strains, and approve a novel method for confirming the viability and relative abundance of the microbial community in a probiotic mixer. We carried out 16S sequencing, 16S metagenomics, Transmission Electron Microscopy (TEM) analysis, and other in vitro laboratory experiments to reach this objective. The strain TY-11 was identified as Lactobacillus delbrueckii subsp. indicus (16S sequence accession number OQ652026). It was gram-positive, anaerobic, lactose fermenting, and round-ended rod that typically measured 0.7 to 1.3 µm by 2.2 to 9 µm. In addition to having seven probiotic characteristics, it also showed an antagonistic impact on six different pathogens, but what's more noteworthy is that E. coli was the pathogen it inhibited most strongly (inhibition zone diameter was 18.88±0.18 mm). The most important and ground-breaking finding of this work was determining the probiotic features of a new probiotic strain, TY-11, whose antibacterial activity was virtually as effective as that of the probiotic combination with three different strains. Furthermore, the results of 16S high throughput sequencing and the conventional plate count method demonstrated a strong correlation (0.999) at the genus level, indicating that the use of both of these approaches in combination may be a practical way to assess the relative abundance of the microbial community and their viability in commercially available probiotic blends.

A systematic and comprehensive review of critical applications of Blockchain Technol-ogy with Differential Privacy integration lies within the privacy and security enhancement. This paper aims to highlight the research issues in the e-health domain (e.g., Electronic Medical Rec-ords) and to review the current research directions in Differential Privacy integration with Blockchain Technology.(1) Background: The current state of the art in the e-health domain is identified as follows: (a) healthcare information poses a high level of security and privacy concerns due to its sensitivity; (b) due to vulnerabilities surrounding the healthcare system, a data breach is common and presents a risk for attacks by an adversary; and (c) the current privacy and security apparatus needs further fortification. (2) Methods: The methodology uses a systematic literature review (SLR) to identify and select relevant research papers and academic journals in DP and BT. (3) Results: The results are categorized into: e-Health Record Privacy, Real-Time Health Data, and Health Survey Data Protection to identify inherent issues with Differential Privacy integra-tion with Blockchain and technical challenges.(4) Conclusion: This review thoroughly surveyed and summarized Differential Privacy mechanisms in EMR privacy, real-time health data, and health survey data protection while highlighting challenges.

The manuscript presents a novel approach to designing and fabricating a stretchable patch antenna designed for strain sensing and wireless communication of sensing data at the same time. The challenge lies in combining flexible and stretchable textile materials with different physical mor-phologies, which can hinder adhesion among multiple layers when stacked up, resisting the overall stretchability of the antenna. The proposed antenna design overcomes this challenge by incorpo-rating a lattice hinge pattern in the non-stretchable conductive e-textile, transforming it into a stretchable structure. The innovative design includes the longitudinal cuts inserted in both the patch and the ground plane of the antenna, allowing it to stretch along in the perpendicular direction. Implementing the lattice hinge pattern over the conductive layers of the proposed patch antenna in combination with a 2 mm thick Polydimethylsiloxane (PDMS) substrate achieves a maximum of 25% stretchability compared to its counterpart antenna without lattice hinge design. The stretchable textile antenna resonates around a frequency of 2.45 GHz and exhibits a linear resonant frequency shift when strained up to 25%. This characteristic makes it suitable for use as a strain sensor. Ad-ditionally, the lattice hinge design enhances the conformability and flexibility of the antenna compared to a solid patch antenna. The realized antenna gains in the E and H-plane were measured as 2.21 dBi and 2.34 dBi, respectively. Overall, the presented design offers a simple and effective solution for fabricating a stretchable textile patch antenna for normal use or as a sensing element, opening up possibilities for applications in communication and sensing fields.

The E-learning system has achieved great development after the pandemic. In this work, we proposed three artificial intelligence-based enhancements to our linguistic interactive E-learning system from different aspects. Compared with the original phonetic transcription exam system, our enhancements include an MFCC+CNN-based disordered speech classification module, a Transformer-based Grapheme-to-Phoneme converter, and a Tacotron2-based IPA-to-Speech speech synthesis system. This work not only provides a better experience for the users of this system but also explores the utilization of artificial intelligence technologies in the E-learning field and linguistic field.

Background and Objectives: Gastric cancer (GC) is one of the most commonly diagnosed cancer and the fourth cause of cancer death worldwide. Personalised treatment improves GC outcomes. A molecular classification is needed to choose the appropriate therapy. A classification that uses on-slide biomarkers and formalin-fixed and paraffin-embedded (FFPE) tissue is preferable to comprehensive genomic analysis. In 2016, Setia et al. proposed an on-slide classification, however this is not in widespread use. We propose a modification of this classification that has six subgroups: GC associated with Epstein-Barr virus (GC EBV+), GC with mismatch repair deficiency (GC dMMR), GC with epithelial-mesenchymal transformation (GC EMT), GC with functional loss of p53 due to mutation (GC p53m), CG with intact p53 (GC p53wt) and GC not otherwise specified (GC NOS). This classification also has provision for biomarkers for current or emerging targeted therapies (Her2, PD-L1 and Claudin18.2). Here we assess the implementation and feasibility of this inclusive working classification. Materials and Methods: We constructed a tissue microarray library from a cohort of 79 resection cases from FFPE tissue archives. We used a restricted panel of on-slide markers (EBER, MMR, E-cadherin, beta-catenin and p53), defined their interpretation algorithms, and assigned each case to a specific molecular subtype. Results: GC EBV(+) cases were 6%, GC dMMR cases were 20%, GC EMT cases were 14%, GC p53m cases were 23%, GC p53wt cases were 29% and GC NOS cases were 8%. Conclusions: This working classification uses markers that are widely available in Histopathology and are easy to interpret. A diagnostic subgroup is obtained for 92% of the cases. The proportion of cases in each subgroup is in keeping with other published series. Widescale implementation appears feasible. A study using endoscopic biopsies is warranted.

An accurate flux measurement of low-energy charged particles trapped in the magnetosphere is necessary for space weather characterization and to study the coupling between the lithosphere and magnetosphere, which allows for the investigation of the correlations between seismic events and particle precipitation from Van Allen belts. In this work, the project of a CubeSat space spectrometer, the Low-Energy Module (LEM), is shown. The detector will be able to perform an event-based measurement of the energy, arrival direction, and composition of low-energy charged particles down to 0.1 MeV. Moreover, thanks to a CdZnTe mini-calorimeter, the LEM spectrometer also allows for photon detection in the sub-MeV range, joining the quest for the investigation of the nature of Gamma-ray bursts. The particle identification of the LEM relies on the ΔE−E technique performed by thin silicon detectors. This multipurpose spectrometer will fit within a 10 × 10 × 10 cm3 CubeSat frame, and it will be constructed as a joint project between the University of Trento, FBK, and INFN-TIFPA. To fulfil the size and mass requirements, an innovative approach, based on active particle collimation, was designed for the LEM; this avoids the heavy/bulky passive collimators of previous space detectors. In this paper, we will present the LEM geometry, its detection concept, the results from the developed GEANT4 simulation, and some characterisations of a candidate silicon detector for the instrument payload.

E-commerce is a rapidly evolving global trend that is having a significant impact on consumer behavior and business strategies. Despite its growing impact, e-commerce adoption by Moroccan firms remains low and research on this topic in this context is scarce. This study aims to fill this gap by investigating the main determinants influencing e-commerce adoption by Moroccan firms. We use logit, probit, and conditional mixed process-probit models to identify the critical factors driving e-commerce adoption. Our results reveal five key findings. First, newer firms that are more open to innovation and change are more likely to adopt e-commerce. Second, firms with a higher proportion of highly educated employees are more likely to adopt e-commerce. Third, the digital skills of new employees do not directly influence the likelihood of e-commerce adoption. Fourth, being listed on digital platforms increases the likelihood of e-commerce adoption. Finally, there is a positive relationship between firms engaged in innovation activities and e-commerce adoption. These findings highlight the need for additional investment in promoting modern organizational practices, reskilling workers, and implementing advanced technologies to facilitate effective e-commerce integration among Moroccan SMEs. By addressing these challenges, Moroccan firms can harness the full potential of e-commerce and contribute to the country’s economic growth and digital transformation.

Composites of Ag and TiO2 nanoparticles on cotton fabrics were synthetized in-situ by sono-chemical and hydrothermal methods achieving the successive formation of Ag-NPs and Ti-NPs directly on the fabric. The impregnated fabrics were characterized by ATR-FTIR spectroscopy, high resolution microscopy (HREM), scanning electron microscopy coupled with Ener-gy-dispersive X-ray spectroscopy (SEM-EDS), Raman, photoluminescence, UV-vis and DRS spectroscopies and by tension tests. Results showed the successful formation and impregnation of NPs on the cotton fabric, with a negligible leaching of NPs after several washing cycles. The photocatalytic activity of supported NPs was assessed by the degradation of methyl blue dye (MB) under solar and UV irradiation revealing improved photocatalytic activity of the Ag-TiO2/cotton composites due to a synergy of both Ag and TiO2 nanoparticles. This behavior is attributed to a diminished electron-hole recombination effect in the Ag-TiO2 cotton samples. The biocide activity of these composites on the growth inhibition of Staphylococcus aureus (Gram+) and Escherichia coli (Gram-) was confirmed, revealing interesting possibilities for the utilization of the functionalized cotton fabric as protective cloth for medical applications.

Background: Studies exploring the possible protective effect of coffee and tea consumption on dementia showed inconsistent results so far. We aimed to investigate whether consumption of tea and different types of coffee at midlife are associated with dementia later in life and, whether sex or ApoE4 influence such association. Methods: We included 7381 participants from the Norwegian HUNT Study. Self-reported questionnaires assessed daily consumption of coffee and tea at baseline. After 22 years, individuals 70 years or older were screened on cognitive impairment. Results: General coffee consumption and tea consumption was not associated with dementia risk. Compared to daily consumption of 0-1 cups of coffee, daily consumption of ≥8 cups of boiled coffee was associated with increased dementia risk in women (OR:1.83, 95% CI: 1.10-3.04, p-value for trend=0.03) and daily consumption of 4-5 cups of other types of coffee was associated with a decrease in dementia risk in only men (OR 0.48, 95% CI: 0.32-0.72, p-value for trend =0.05). Furthermore, the association between boiled coffee and increased dementia risk was only found in ApoE4 non-carriers. Differences by sex or ApoE4 carrier status were not supported by strong statistical evidence for interaction. Conclusion: Type of coffee may play a role in the direction of the association between coffee-drinking habits and dementia later in life.

With the diversified development of media forms, livestreaming e-commerce has become a new sales model. Unlike the traditional sales model, this paper constructs a three-party game model composed of manufacturers, social media influencers and consumers based on the livestreaming model. It explores the equilibrium strategy selections of each participant in the supply chain system. In analyzing the evolutionary game stability of each participant, this paper obtains the equilibrium strategy and stability factors by analysis of the income and expenditure matrix. It uses the simulation model to analyze reasons for strategy selections of different game participants in the livestreaming e-commerce model. The results show that the strategies of manufacturers, social media influencers and consumers' selections have different impacts on their decision-making mechanism, and man-ufacturers are more sensitive to consumers' active participation in livestreaming e-commerce.

The novel coronavirus (SARS-CoV-2) is a human pathogen recently emerged in China, causing a global pandemic of severe respiratory illness (COVID19). SARS-CoV-2 makes entry into human cells through its spike (S) protein that binds to cell surface receptors. Widespread of SARS-CoV-2 has been attributed to high affinity of S protein to its receptor. A homology model of the receptor binding domain of SARS-CoV-2 S protein (RBD) was built. RBD- receptor docking and published molecular dynamics data were used to map the key RBD-receptor interaction hotspot (RBDhp) on the RBD. Primary virtual screening was carried out against RBDhp using more than 3300 compounds approved by U.S Food and Drug Administration (FDA) and other authorities for human use. Compounds that bind to hpRBD with a binding energy ≤ - 6.5 kcal/mol were subjected to secondary screening using a recently published cryo EM (2.9 Å) structure of RBD. A cardiac glycoside (dgitoxin), two anthracyclines (zorubicin and aclarubicin), a tetracycline derivative (rolitetracycline), a cephalosporin (cefoperazone) and a food dye (E-155) were predicted to be most potent inhibitors of RBD – receptor interaction. An anti-asthmatic drug (zafirlukast) and several other drugs (itrazol, fazadinium, troglitazone, gliquidone, Idarubicin, Oxacillin) were found to be high affinity binders that may have a potential to inhibit RBD – receptor interaction.

This study assesses the development of professional skills in university students using serious games (SG), from a sustainability perspective. The Sustainable Development Goals (SDGs) were set by the United Nations’ 2030 Agenda for Sustainable Development. Universities are strategic agents in the transformation process towards sustainability. This way, they should be committed to promoting such sustainable values in the students through curricular sustainability, implementing active methodologies and SG for that purpose. Transversal skills are essential for the development of future graduates. The objective of this study was to assess which professional skills should be developed through the SG called The Island, to improve the degree of student satisfaction with the incorporation of a sustainable curriculum. The data were obtained using a questionnaire, and then analysed using linear regression models, with their inference estimated through the goodness of fit and ANOVA. The first results indicated that the implementation of the SG promoted a strengthening of the students' sustainable curriculum through the development of those skills. It was concluded that the key to success in education for sustainable development is improving the development of strategic thinking, collaborative thinking, and self-awareness, in addition to encouraging systemic, critical, and problem-solving thinking.

Replacement of fee-for-service with capitation arrangements, forces physicians and institutions to minimize health care costs, while maintaining high-quality care. In this report we describe how patients, their families (and caregivers) can work with members of the medical care team to achieve these twin goals of maintaining (and perhaps improving) high-quality care and minimizing costs. We describe how increased self-management enables patients and their families/caregivers to provide electronic patient-reported outcomes (i.e., symptoms, events) (ePROs) as frequently as the patient or the medical care team consider appropriate. These capabilities also allow greater reliance on the use of mobile technologies (mHealth) to provide ongoing assessments of physiologic measurements/phenomena. Remote surveillance of these communications allows longer intervals between (fewer) visits of patients to the medical-care team when this is appropriate and earlier interventions when that is appropriate. Systems are now available that alert medical care providers to situations when interventions might be needed.

Suicidal behaviour remains difficult to predict and prevent, even for experienced mental health care professionals. The known distal risk factors for suicidal behaviour are not sufficiently specific to fully understand the complex dynamic processes that precede a suicide attempt. Real-time mobile monitoring data can be used to analyse proximal risk mechanisms within the suicidal process. At the same time smartphone-based safety planning and self-monitoring may enhance a patient’s self-management skills thereby increasing their capacity to respond to a suicidal crisis and to become more aware of crisis symptoms. The current paper describes the theoretical and conceptual rationale for the CASPAR study which applies an innovative approach to the study of suicidal processes. It uses basic science approaches to inform the implementation of an innovative suicide prevention intervention. We aim to develop and implement mobile safety plan in conjunction with real-time monitoring in order to both directly implement suicide prevention interventions and to study the ongoing dynamics of individual suicidal behaviour by applying network analysis.

According to many research groups, high glucose induces over production of superoxide anions, and reactive oxygen species (ROS) in general is the link between high glucose levels and the toxicities seen at cellular levels. Respiratory complex anomalies could lead to the production of ROS. Calcium [Ca2+], at physiological levels serves as a second messenger in many physiological functions. Accordingly, mitochondrial calcium [Ca2+]m overload leads to ROS production which could be lethal to the mitochondria through various mechanisms. The F1F0-ATPase (ATP syn-thase or complex V) is the enzyme that is responsible for catalyzing the final step of oxidative phosphorylation. It does so by coupling the translocation of protons in the mitochondrial in-termembrane space and shuttling them to the mitochondrial matrix for ATP synthesis to take place. Mitochondrial complex V T8993G mutation specifically blocks the translocation of protons across the intermembrane space thereby blocking ATP synthesis leading to Neuropathy, Ataxia and Retinitis Pigmentosa Syndromes (NARP). This study seeks to explore the possibility of [Ca2+]m overload mediating the pathological roles of high glucose in defective respiratory chain mediated mitochondrial stress. The NARP cybrids are the in vitro experimental models for the cells with F1FO-ATPase defects, these cells harbor 98% of mtDNA T8993G mutation. Their coun-terparts 143B osteosarcoma cell lines are the parental cell lines used for comparisons. We uncov-ered that, NARP cells mediated and enhanced the death of the cells (apoptosis) when incubated with hydrogen peroxide (H2O2) and high glucose respectively as depicted by the MTT assay of cell viability. Furthermore, using the fluorescence probe-coupled laser scanning confocal imag-ing microscopy, NARP cells significantly enabled mitochondrial reactive oxygen species (mROS) formation and enhanced the depolarization of the mitochondrial membrane potential (ΔΨm). Elucidating the mechanisms of sugar enhanced toxicity on mitochondria would help in the fu-ture to alleviate the symptoms of patients associated with (NARP) syndromes.

This investigation introduces an efficient method for assessing the reliability of semi-rigid steel frame connections in existing buildings, explicitly targeting the Top Angle and Seat Pad (TA-SP) semi-rigid connection commonly used in Australian cities' high-rise buildings. The moment capacity of these connections was examined through parameter power model testing, meticulously considering the bending, shear, and prying forces actions to determine the weakest elements in the connection system. A plastic hinge model was applied to ensure computational efficiency and accuracy in assessing the connections' ultimate strength. Comparatively, the finite element (F.E) method M−θ curves were introduced to scrutinise the nonlinear behaviour of the connection, providing validation for the predicted analytical approach. Further emphasis was placed on identifying the reliability of the weakest elements in the connection system, employing the First-Order and Second-Order Reliability Methods models to estimate their reliability index. The correlation between the model's failure probability and a percentile error was also explored, utilising Monte Carlo simulation reference for refined validation. Novel formulas and methodologies were introduced to compute the locked-chain-series system reliability, which accounts for the inherent material and geometric variability. The findings highlight the critical significance of the weakest element in determining the overall reliability of the existing TA-SP connection.

This study explores the influence of cultural differences on Supplier Relationship Management (SRM) within global e-commerce, examining communication styles, trust-building, negotiation strategies, and strategic alignment across diverse cultural contexts. Through qualitative research including interviews with e-commerce professionals, the study identifies how cultural factors shape SRM practices and outcomes, highlighting the importance of cultural sensitivity and adaptive strategies in fostering effective supplier relationships. Findings underscore the significance of communication preferences, trust norms, and strategic orientations in navigating cultural complexities to enhance operational efficiency and mitigate risks in global markets. Practical implications suggest integrating cultural dimensions into SRM frameworks, prioritizing cultural competence development, and leveraging cultural diversity for innovation and collaboration. Future research directions include exploring digitalization's impact on cross-cultural SRM and longitudinal studies on evolving cultural dynamics in global business. By advancing understanding in this area, e-commerce firms can enhance resilience, maintain competitive advantage, and achieve sustainable growth in the global marketplace.

This study explores the transformative impact of e-commerce technologies on supply chain management within the retail sector. Through a thematic analysis of current literature and qualitative research findings, the study examines how technologies such as real-time monitoring, predictive analytics, AI, blockchain, and IoT are reshaping inventory management, procurement, logistics, and customer service. The research highlights significant improvements in operational efficiency, decision-making, and customer experience driven by these technologies. However, challenges such as system integration complexities, cybersecurity risks, and regulatory compliance issues are also identified. The study emphasizes the strategic adoption and integration of e-commerce technologies to enhance supply chain resilience, sustainability, and competitiveness. Insights from the analysis underscore the evolving role of technology in driving innovation and efficiency across supply chain functions, while also necessitating careful management of risks and complexities. Looking forward, the study discusses future trends including AI advancements, IoT connectivity, and blockchain applications, which are poised to further revolutionize supply chain dynamics. By addressing these trends and challenges strategically, retailers can leverage e-commerce technologies to optimize operations, mitigate risks, and meet evolving consumer demands in a digital-first marketplace.

This qualitative research explores the transformative role of Artificial Intelligence (AI) in Supplier Relationship Management (SRM) within the e-commerce sector. SRM is critical for e-commerce platforms to maintain efficient supply chains, optimize supplier interactions, and ensure competitive advantage in a dynamic marketplace. AI technologies offer advanced capabilities such as predictive analytics, machine learning algorithms, and natural language processing, which revolutionize traditional SRM practices by enhancing decision-making accuracy, mitigating supply chain risks, and fostering personalized supplier relationships. Through semi-structured interviews with 20 e-commerce professionals and industry experts, this study investigates AI's impact on supplier selection, operational efficiencies, and strategic supplier relationships. Findings highlight AI's ability to streamline supplier evaluation processes, improve demand forecasting accuracy, and optimize inventory management strategies. AI also facilitates personalized supplier engagement through sentiment analysis and real-time insights, promoting collaboration and trust. Ethical considerations, including algorithmic bias and data privacy, emerge as significant concerns in AI adoption for SRM. Addressing these challenges is crucial to maintaining stakeholder trust and ensuring responsible AI deployment. Furthermore, technological integration barriers and organizational readiness are identified as critical factors influencing successful AI implementation. Looking forward, the study underscores the potential of AI to drive innovation and competitiveness in e-commerce SRM, emphasizing the importance of ethical AI practices, technological infrastructure investments, and organizational preparedness for sustainable growth.

Supplier Relationship Management (SRM) tools play a crucial role in enhancing efficiency and competitiveness within e-commerce supply chains. This qualitative research explores the effectiveness of SRM tools in optimizing procurement processes, mitigating risks, and fostering collaborative partnerships with suppliers. The study employs semi-structured interviews with key stakeholders in diverse e-commerce sectors to gather insights into the implementation and outcomes of SRM tools. Findings reveal that technological advancements, including AI, blockchain, and data analytics, facilitate real-time communication, decision-making, and supply chain visibility, thereby enabling organizations to achieve cost savings and operational efficiencies. Enhanced supplier relationships through SRM tools contribute to collaborative innovation, faster product development cycles, and improved customer satisfaction. However, challenges such as technological complexity, regulatory compliance, and supplier resistance necessitate strategic management and investment in cybersecurity and compliance frameworks. The research underscores the importance of executive sponsorship, stakeholder engagement, and continuous improvement in driving successful SRM implementations.

Digital health has added numerous promising solutions to enhance the health and wellness of people with neurocognitive disorders (NCDs) and their informal caregivers: (1) Background: It is important to get a comprehensive view of currently available technologies, their outcomes, and conditions of success to inform recommendations regarding digital health solutions for people with NCDs and their caregivers. This environmental scan was performed to identify the features of existing digital health solutions relevant to the targeted population. This work reviews currently available digital health solutions and their related characteristics to develop a decision support tool for older adults living with mild or major neurocognitive disorders and their informal caregivers. This knowledge will inform the development of a decision support tool to assist older adults and their informal caregivers in their search for adequate digital health solutions according to their needs and preferences, based on trustable information.; (2) Methods: We conducted an environmental scan to identify digital health solutions from a systematic review and targeted searches in grey literature covering the regions of Canada and Europe. Technological tools were scanned based on a preformatted extraction grid. We assessed their relevance based on selected attributes and summarized findings; (3) Results: We identified 100 available digital health solutions. The majority (56%) were not specific to NCDs. Only 28% provided scientific evidence of their effectiveness. Remote patient care, movement tracking, and cognitive exercises were the most common purposes of digital health solutions. Most solutions were presented as decision aid tools, pill dispensers, apps, web, or a combination of these platforms. (4) Conclusions: This environmental scan allowed the identification of current digital health solutions for older adults with mild or major neurocognitive disorders and their informal caregivers. Findings from the environmental scan highlight the need for additional approaches to strengthen digital health interventions for the well-being of older adults with mild and major NCDs and their informal and formal healthcare providers.

Salidroside, a valuable phenylethanoid glycoside, is obtained from plants belonging to the Rhodiola genus, known for its diverse biological properties. At present, salidroside is still far from large-scale industrial production due to the lower titer and higher process cost. In this study, we constructed a biosynthetic pathway from L-tyrosine to salidroside in Saccharomyces cerevisiae. To increase sali-droside production, we for the first time constructed an in vivo UDP-glucose regeneration system that sucrose synthase GmSUS worked in conjunction with UDP-glucose transferase RrUGT33 to improve the UDP-glucose availability with inexpensive sucrose as the consumed substrate. Finally, the molar conversion rate of L-tyrosine could reach 95%. To further reduce the cost, co-culture with E. coli that synthesized L-tyrosine de novo resulted in an 81% reduction in the final substrate cost per 1 kg of salidroside compared to the initial cost. The final titer of salidroside obtained 3.8 g/L and was the highest titer achieved at the Shake-Flask-Level in the existing reports. And this marked the first successful synthesis of salidroside in an in situ enhanced UDP-glucose system using sucrose. This accomplishment laid a robust groundwork for further investigations into the synthesis of other notable glycosides and natural compounds.

The successful advancement of xenotransplantation has led to the development of highly sensitive detection systems for the screening for potentially zoonotic viruses in donor pigs and preventing their transmission to the recipient. To validate these methods, genetically modified pigs generated for xenotransplantation, numerous minipig and other pig breeds have been tested, thereby increasing our knowledge concerning the pig virome and the distribution of pig viruses. Of particular importance are the porcine cytomegalovirus, a porcine roseolovirus (PCMV/PRV) and the hepatitis E virus genotype 3 (HEV3). PCMV/PRV has been shown to reduce the survival time of pig transplants in non-human primates and was also transmitted in the first pig heart transplantation to a human patient. Here, we determined the sensitivities of our methods to detect PCMV/PRV, HEV3, porcine lymphotropic herpesvirus - 1 (PLHV-1), PLHV-2, PLHV-3, porcine circovirus 2 (PCV2), PCV3, PCV4 and porcine parvovirus 1 (PPV1) efficiently and used the methods to screen indigenous Greek black pigs. Since porcine endogenous retroviruses (PERVs) of type A and B are integrated in the genome of all pigs, but PERV-C is not, the animals were screened for PERV-C and PERV-A/C. Our detection methods were sensitive and detected PCMV/PRV, PLHV-1, PLHV-1, PLHV-3, PVC3 and PERV-C in most animals. PPV1, HEV3, PCV4 and PERV-A/C were not detected. These data are of great interest since the animals are healthy and very resistant to diseases.

The treatment of critically ill patients remains an evolving and controversial issue. Mechanical circulatory support through a percutaneous approach for the management of cardiogenic shock has taken place in recent years. The combined use of IABP and Impella 2.5 device may have a role to play for this group of patients. A simulation approach may help with a quantitative as-sessment of the achievable degree of assistance. In this paper, we analyse the interaction be-tween Impella 2.5 pump applied as LVAD and IABP using the numerical simulator of the cardi-ovascular system developed in our laboratory. Starting with pathological conditions reproduced using literature data, the simulations were performed setting different rotational speeds for the LVAD and driving the IABP in full mode (1:1) or partial mode (1:2, 1:3 and 1:4). The effects in-duced by drug administration during the assistance were simulated too. The haemodynamic pa-rameters under investigation were: mean aortic pressure, systolic and diastolic aortic pressure, mean pulmonary arterial pressure, mean left and right atrial pressure, cardiac output, cardiac index, left and right ventricular end-systolic volume, left ventricular end-diastolic volume and mean coronary blood flow. The energetic variables considered in the study were: left and right ventricular external work and left and right atrial pressure-volume area. The outcome of our simulations shows that the combined use of IABP and Impella 2.5 achieves adequate support in the acute phase of cardiogenic shock compared to each standalone device. This would allow fur-ther stabilisation and transfer to a transplant centre should escalation of treatment be required.

Understanding surface water evaporation in tropical catchments is pivotal for effective water management, but limited research exists on stable isotopic (δ2H and δ18O) assessment of water evaporation losses. Our study bridges that gap, examining stable isotopes in meteoric water and surface waters across tropical regions, both humid and semi-arid. Using the Craig-Gordon model, we calibrated evaporation-to-inflow (E/I) ratios, identifying distinct E/I variations between seasons and regions. Notably, the semi-arid region consistently exhibited higher E/I ratios due to climatic characteristics. By integrating the Hamiltonian Monte Carlo and the No-U-Turn Sampler, we were able to quantify uncertainties in isotopic and meteorological parameters, resulting in E/I estimates within 68% and 95% confidence intervals. Our Bayesian model insights are critical for freshwater resource optimization and hydrological modeling in tropical regions.

With the rise of internet technology and the growth of mobile communications, the global economy has undergone a significant transformation, shifting towards digital and soft markets. As a result, great efforts have been made to establish virtual marketplaces that provide customers with an exceptional shopping experience. One crucial aspect of this new paradigm is marketing, which has led to the emergence of a new stage known as E-marketing. In E-marketing, understanding customer behavior is of utmost importance. Marketing teams and companies are eager to gain insights into how different customer segments react to their products. Marketing strategies are now developed based on customer information such as financial status, location, age, gender, and more. As a result, the abundance of customer data generated by these new commerce technologies has surpassed the capabilities of traditional data analysis methods. To extract valuable knowledge from this vast amount of data, data mining technologies have come into play. Techniques such as clustering, classification, and prediction are utilized to mine marketing data and uncover hidden patterns and trends. The impact of data mining on E-marketing has been the subject of analysis in this study. A questionnaire-based review was conducted to collect the necessary data, which was then analyzed using SPSS 23 software. The study's results demonstrate that data mining can significantly enhance the performance of E-marketing by providing intelligent and efficient predictions of customer behaviour. Moreover, this technology offers similar advantages for end-customers as well. By leveraging the power of data mining, companies can gain valuable insights, tailor their marketing efforts, and ultimately provide better products and services to their customers in the digital marketplace.

NUSES is a planned space mission aiming to test innovative observational and technological approaches related to the study of low-energy cosmic rays, gamma rays and high-energy astrophysical neutrinos. Two scientific payloads will be hosted onboard the NUSES space mission: Terzina and Zirè. Terzina will be an optical telescope readout by SiPM arrays, for the detection and study of Cerenkov light emitted by Extensive Air Showers generated by high-energy cosmic rays and neutrinos in the atmosphere. Zirè will focus on the detection of protons and electrons up to a few hundred MeV and to 0.1-10 MeV photons and will include the Low Energy Module (LEM). The LEM will be a particle spectrometer devoted to the observation of fluxes of low-energy electrons in the 0.1-7 MeV range and protons in the 3-50 MeV range along the Low Earth Orbit (LEO) followed by the hosting platform. The detection of Particle Bursts (PBs) in this Physics channel of interest could give new insight into the understanding of complex phenomena such as eventual correlations between seismic events or volcanic activity with the collective motion of particles in the plasma populating van Allen belts. With its compact sizes and limited acceptance, the LEM will allow the exploration of hostile environments such as the South Atlantic Anomaly (SAA) and the inner van Allen belt, in which are expected electron fluxes of the order of 106−7 cm−2 sr−1 s−1. Concerning the vast literature of space-based particle spectrometers, the innovative aspect of the LEM resides in its compactness, within 10x10x10 cm3, and in its “active collimation” approach dealing with the problem of multiple scattering at these very low energies. In this work, the geometry of the detector, its detection concept, its operation modes and the hardware adopted will be presented. Some preliminary results from the Monte Carlo simulation (Geant4) will be shown.

To study and monitor the adverse health consequences from using electronic cigarettes, a user’s puff topography, which are quantification parameters of the user’s vaping habits, plays a central role. In this work, we introduce a topography sensor to measure the mass of total particulate matter generated in every puff and to estimate the nicotine yield. The sensor is compact and low-cost, and is integrated into the electronic cigarette device to promptly and conveniently monitor the user’s daily puff topography. The topography sensor is comprised of a photometric sensor and a pressure sensor. The photometric sensor measures the mass concentration of the aerosol, based on scattering of near-infrared light from airborne particles, while the pressure sensor measures the flow rate. The topography sensor was experimented under various conditions with a wide range of atomizer power, puff duration, and inhalation pressure. The sensor’s accuracy was validated by comparing the sensor’s readings with reference measurements, and the results matched closely with the trends reported by existing studies on electronic cigarettes. An example application of tracking a user’s puff topography was also demonstrated. Our topography sensor holds great promise in mitigating health risks of vaping, and in promoting quality control of electronic cigarette products.

The importance of measuring sustainability in tourism has been significantly advancing in recent years, following the need to manage the impact of tourism on territories and hosting communities. It was further boosted by the pandemic, where sustainability has been defined as one of the central elements to restart global tourism. The ETIS model, developed by the European Commission, is a point of reference based on self-assessment, data collection and analysis by the destinations themselves. The application of ETIS toolkit has faced many challenges, especially at sub-national level, mostly related to the lack of available and updated data to feed the model. The hypothesis explored by the authors is to solve the implementation issues, developing an indicator based on the use of the Sentiment Analysis to frame e-reputation and tourism satisfaction, and further combining it with other open data sources. The Tourism Sustainability Index (TSI) can provide a scalable and geo-referenced evaluation of tourism sustainability, measuring the four pillars and sub-components referenced to ETIS criteria, applicable to any tourism destination. Results show that the TSI can be seen as a consistent and valid tool for destinations to analyze sustainability, monitor its evolution through time periods and sub-areas, and compare it to other benchmark or competitive areas.

BackgroundIt is unclear what underpins the large global variations in the prevalence of fluoroquinolone resistance in gram-negative bacteria. We tested the hypothesis that different intensities in the use of quinolones for food-animals plays a role. MethodsWe used Spearman’s correlation to assess if the country-level prevalence of fluoroquinolone resistance in human infections with Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa was correlated with the use of quinolones for food producing animals. Linear regression was used to assess the relative contributions of country-level quinolone consumption for food-animals and humans on fluoroquinolone resistance in these 4 species. ResultsThe prevalence of fluoroquinolone resistance in each species was positively associated with quinolone use for food-producing animals (E. coli [ρ=0.55; P<0.001], K. pneumoniae [ρ=0.58; P<0.001]; A. baumanii [ρ=0.54; P=0.004]; P. aeruginosa [ρ=0.48; P=0.008]). Linear regression revealed that both quinolone consumption in humans and food animals were independently associated with fluoroquinolone resistance in E. coli and A. baumanii. ConclusionsReducing quinolone use in food-producing animals may help retard the spread of fluoroquinolone resistance in various gram negative bacterial species.

Studies have shown that aerosols generated from flavored e-cigarettes contain Reactive Oxygen Species (ROS), promoting oxidative stress-induced damage within pulmonary cells. Our lab investigated the ROS content of e-cigarette vapor generated from disposable vape bars, a product exempt from the Federal Drug Enforcement Agency’s (FDA) 2020 flavor ban. Specifically, we analyzed vape bars belonging to multiple flavor categories (Tobacco, Minty Fruit, Fruity, Minty/Menthol, Desserts, and Drinks), manufactured by various vendors and of various nicotine concentrations (0-6.8%). Aerosols from these flavored vape bars were generated by a single puff aerosol generator and individually bubbled through a fluorogenic solution to detect and semi-quantify ROS in H2O2 equivalents generated by the vape bars. We compared and contrasted the ROS levels generated by each flavor as an indirect determinant of oxidative stress potential by these disposable vape bars. Our results showed that ROS concentration (μM) of aerosols produced from the vape bars varied significantly between different flavors and a function of nicotine concentration. Likewise, our results suggest that flavoring chemicals and nicotine concentration play a role in alerting ROS production in e-cigarette aerosols. Our study provides insight into the differential health effects of flavored disposable vape bars and the need for their regulation.

A significant attention has been made to the accurate detection of diabetes which is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the IoT e-healthcare environment. Internet of Things (IOT) has emerging role in healthcare services which delivers a system to analyze the medical data for diagnosis of diseases applied data mining methods. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a IOT based diagnosis system using machine learning methods, such as preprocessing of data, feature selection, and classification for the detection of diabetes disease in e- healthcare environment. Model validation and performance evaluation metrics have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning Decision Tree algorithms, such as Ada Boost and Random Forest are also used for feature selection and compared the classifier performance with wrapper based feature selection algorithms also. Machine learning classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the Decision Tree algorithm based on selected features improves the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high as compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and GL, DPF, and BMI are more significantly important features in the dataset for prediction of diabetes disease. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would be effectively detected diabetes disease and can easily be deployed in IOT wireless sensor technologies based e-healthcare environment.

Exploring the dynamic behavior of cellular metabolism requires a standard laboratory method that guarantees rapid sampling and extraction of the cellular content. We propose a versatile sampling technique applicable to cells with different cell wall and cell membrane properties. The technique is based on irreversible electroporation with simultaneous quenching and extraction by using a microfluidic device. By application of electric pulses in the millisecond range, permanent lethal pores are formed in the cell membrane of Escherichia coli and Saccharomyces cerevisiae, facilitating the release of the cellular contents; here demonstrated by the measurement of glucose-6-phosphate and the activity of the enzyme glucose-6-phosphate dehydrogenase. The successful application of this device was demonstrated by pulsed electric field treatment in a flow-through configuration of the microfluidic chip in combination with sampling, inactivation, and extraction of the intracellular content in a few seconds. Minimum electric field strengths of 10 kV/cm for E. coli and 7.5 kV/cm for yeast S. cerevisiae were required for successful cell lysis. The results are discussed in the context of applications in industrial biotechnology, where metabolomics analyses are important.

Immunosensors have been widely developed to use antibodies to detect a pathogen of interest; it is interesting to look at the effect of nonspecific antibody binding to E. coli using electrochemical methods. IgG antibody not specific to E. coli O157:H7 was crosslinked onto a screen-printed carbon electrode. The presence of E. coli at 4, 4 × 10², 4 × 10⁵, and 4 × 10⁸ CFU/mL on the electrode surface was detected via linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). Current transfer at both electrodes was reduced as the concentration of bacteria increased; however, the calibration of number of cells to decreased current was nonlinear for IgG-modified electrodes. The nonlinearity is confirmed by EIS measurements which showed highest impedance at 4 CFU/mL E. coli when impedance should be the lowest. FESEM images showed higher binding of cells when IgG is present compared to electrodes with reduced graphene oxide (rGO) alone. Electrodes with rGO alone show less attachment of E. coli, with EIS showing a linear calibration profile, while LSV shows not much difference in current values for all concentrations aside from the highest concentration. These results suggest that nonspecific binding can provide false signals in electrochemical measurements, and it is crucial to provide proper controls.

The aim of the study was to determine the possibility of suppression of the prostaglandin synthesis by new derivatives of N-phenylanthranilic acids; they inhibit the activity of the microsomal prostaglandin E synthase-1 (mPGES-1) enzyme using the method of a flexible molecular docking. For the docking studies the crystallographic structural models with high resolution from Protein Data Bank were used: mPGES-1 in the complex with glutathione (pdb code 4AL0). A flexible molecular docking was carried out using the Molecular Operating Environment (MOE) software package. According to the results of the docking studies four scoring functions were calculated (Affinity dG Scoring, Alpha HB Scoring, London dG Scoring, GBVI/WSA dG Scoring). The values of the scoring functions calculated indicate the thermodynamic probability and energy favorability of forming complexes between molecules of the substances under research and the specified receptor, in which arrangement of ligands in the active site of the receptor and residues of amino acids of side chains are of similar geometry and types of binding of the known inhibitors of mPGES-1 determined on the basis of the crystallographic studies.

The theory of Ismail's non-extensive maximum entropy solution (NME) is described in detail. It is used as an inductive inference technique for heavy-tailed queues with a non-robust mean queue length and a non-extensive "long-range" interaction. In our novel method, we substitute the non-robust mean queue length for the conventional Pollaczeck-Khinchin mean queue length. In other words, the new non-extensivity parameter q will be included in the resulting state probability function. Numerical portraits are provided to capture the influential effect of the derived formalism, , on the stable M//1 queue with heavy tails. More potentially, some applications of Hurst Exponent to social computing and connected health are provided. Conclusion with some challenging open problems and possible future research pathways are given.

In this paper, the new optical wave solutions of truncated M-fractional perturbed Kundu-Eckhaus model with full non-linearity are obtained by utilizing the expa function technique and modified extended tanh expansion function technique. The solutions are in the form of dark soliton, bright soliton, singular solitons and other form of solutions. The gained solutions are helpful for the further development of concerned model. The obtained results have also been presented graphically in both two-dimensional and three-dimensional formats to discuss the dynamical features as well as the parametric dependence of the constructed solutions. The study offers a highly spectacular and acceptable techniques to combine various intriguing wave demonstrations for more sophisticated models of the modern day.

The Subtropical Front (STF) plays a key role in the ecology of Chilean jack mackerel Trachurus murphyi. Nonetheless, there are few remote sensing studies of the STF in the open Southeast Pacific Ocean, and almost all of them have been conducted by satellite oceanographers in Russia and Ukraine to support respective large-scale fisheries of jack mackerel in this region. We reviewed these studies that documented long-term seasonal and interannual variability of the STF from sea surface temperature (SST) and sea surface height (SSH) data. We also mapped the STF from satellite sea surface salinity (SSS) data of the SMOS mission (2012-2019). The Subtropical Front consists of two fronts -- North and South STF about 500 km apart -- that border the Subtropical Frontal Zone (STFZ) in-between. The STF is density-compensated, with spatially divergent manifestations in temperature and salinity. In the temperature field, the STF extends in the WNW to ESE direction in the Southeast Pacific. In the salinity field, the STFZ appears as a broad frontal zone, extending zonally between 30-35°S across the entire South Pacific. Three major types of satellite data – SST, SSH, and SSS – can be used to locate the STF. The SSH data is most advantageous with regard to the jack mackerel fisheries owing to the all-weather capability of satellite altimetry and the radical improvement of the spatial resolution of SSH data in the near future. Despite the dearth of dedicated in situ studies of the South Pacific STFZ, there is a broad consensus regarding the STFZ being the principal spawning and nursing ground of T. murphyi as well as a major migration corridor between Chile and New Zealand.

The present research focuses on the endogenous development theory and investigates the relationship between economic growth (dependent variable) and renewable energy consumption, technological innovation, and export diversification (independent variables) in seven emerging economies known as the E-7. Previous studies have examined these factors individually but have not explored their combined impact on the E-7 economies. Therefore, this study contributes to the existing literature on the effects of renewable energy consumption, technological advancement, and export diversification on economic development. The study analyses the dynamic connection among these variables in seven selected emerging countries: Brazil, China, Indonesia, India, Mexico, Russia, and Turkey. Panel data from 1990 to 2022 is utilized, and various methodologies, including panel cointegration, the PMG-ARDL estimator, and robustness tests such as FMOLS and DOLS, are employed. Empirical inferences are drawn using the Dumitrescu-Hurlin Panel Causality (DHC) test, and the long-run relationships among the variables are validated using the Westerlund residual cointegration tests. The results from the PMG-ARDL estimator show that renewable energy consumption, technological advancement, and export diversification have a significant and positive impact on economic expansion, confirming the validity of the endogenous growth model in the E-7 countries. The control variable of the financial sector has a positive but insignificant effect on economic growth, while trade openness has a negative and significant effect. The DHC test results indicate a neutral feedback effect of renewable energy consumption on economic growth. The findings also reveal a unidirectional causal relationship between technological innovation and economic growth. Overall, these findings provide valuable insights for economic policymakers in the E-7 countries. By removing barriers to renewable energy consumption, technological innovation, and export diversification, policymakers can promote sustainable economic development.

Abstract: Background: chronotype is generally defined as the variability of the phase angle of en-trainment, while the latter reflects the relationship between the timing of a certain rhythm (e.g., sleep-wake cycle) and the timing of an external temporal cue. Individuals can be placed on a spectrum from "morning types" (M types), to "evening types" (E types). E-chronotype has been proposed as a transdiagnostic risk factor for psychiatric conditions and associated with psycho-pathological dimensions. Eveningness seems correlated with both suicidal ideation (SI) and suicidal behavioral (SB), through several possible mediating factors. Immunological alterations also have been linked to later chronotypes and SI/SB. Objective: This narrative review aims to summarize the evidence supporting the possible association between chronotypes and suicide, with the eventual mediating role of neuroinflammation and several psychopathological dimensions. Material and methods: A search of literature (2003-2023) was conducted, using various databases: PUBMED, EMBASE, Scopus, UpToDate, PsycINFO, Cochrane Library. English-language articles were col-lected and screened for eligibility. Results: Despite the apparent absence of a direct correlation between E-chronotype and suicidality, E-chronotype promotes a chain of effects that could be in-volved in an increased risk of SB, in which with neuroinflammation possibly play an intriguing role and some psychopathological dimensions may stand out.

Familial dysbetalipoproteinemia (FD) is a highly atherogenic genetically-based lipid disorder with the underestimated actual prevalence. In the recent years, several biochemical algorithms have been developed to diagnose FD using available laboratory tests. However, there is not enough data on their use in real-world clinical implementation. We studied the applicability of the most accessible biochemical algorithms to diagnose FD in clinical practice. We also investi-gated the prevalence of FD in one of the European regions of Russia based on a population sample. In this study there was detected a high prevalence of FD: 1 in 151. We demonstrated that the diagnostic algorithms of FD including a diagnostic apoB levels require correction, taking into account the characteristics of the distribution of apoB levels in the population. At the same time a triglycerides cutoff ≥1.5 mmol/L may be a useful tool in identifying subjects with FD. We also analyzed the presence and pathogenicity of APOE variants associated with the autosomal dominant FD in a large research sample.

The worldwide prevalence of type 2 diabetes (T2D) and prediabetes is rapidly increasing, particularly in children, adolescents, and young adults. Oxidative stress (OxS) has emerged as a likely initiating factor in T2D. The role of natural antioxidant products in combating T2D is best evaluated in the context of the complex physiological processes that modulate T2D-OxS such as glycemic control and exercise. The role of natural antioxidant compounds such as vitamin E in T2D must likewise be considered beyond their roles as inhibitors of OxS. In addition to antioxidant properties, vitamin E vitamers (tocopherols and tocotrienols) also exhibit distinct abilities to regulate cellular signal transduction pathways important to T2D progression. Most research on the role of vitamin E in T2D or prediabetes has been limited to tocopherols (Ts) but emerging trials with tocotrienols (T3s) show promise. Minimizing factors that induce chronic damaging OxS and maximizing natural antioxidant protective factors may provide a means of preventing or slowing T2D progression. This “optimal redox” (OptRedox) approach also provides a framework in which to discuss the potential benefits of natural antioxidant factors such as antioxidant products. Since early, effective intervention is critical, the OptRedox strategy would be optimally effective if implemented in the pediatric population.

It is unclear how important it is to reduce fluoroquinolone consumption in the general population to prevent the spread of fluoroquinolone resistance in Neisseria gonorrhoeae (bystander selection). Methods We assessed bystander selection by using Spearman’s correlation to assess if the country-level prevalence of fluoroquinolone resistance in N. gonorrhoeae was correlated with the prevalence of fluoroquinolone resistance in four other gram-negative species - Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa. Results Fluoroquinolone resistance in N. gonorrhoeae was positively associated with homologous resistance in all 4 species - A. baumanii. (ρ=0.61, P=0.0003, E. coli (ρ=0.67, P<0.0001), K. pneumoniae (ρ=0.52, P=0.0004) and P. aeruginosa (ρ=0.40, P=0.0206). Positive associations were also found between the national prevalence of fluoroquinolone resistance and fluoroquinolone consumption in the general population in the preceding year for 4 of the 5 species. Conclusions Gonococcal fluoroquinolone resistance can be productively viewed as being part of a syndemic of fluoroquinolone resistance. Strengthening antimicrobial stewardship programs may help retard the spread of fluoroquinolone resistance in N. gonorrhoeae.

The popularity of electronic cigarettes in the United States and around the world has led to a startling rise in youth nicotine use. The Juul e-cigarette was introduced in the U.S. market in 2015 and had captured approximately 13% of the U.S. market by 2017. Unlike many other contemporary electronic cigarette companies, the founders behind the Juul® e-cigarette approached their product launch like a traditional high-tech start-up company, not like a tobacco company. This article presents a case study of Juul’s corporate and product development history in the context of US regulatory actions. The objective of this article is to demonstrate the value of government-curated archives as leading indicators which can (a) provide insight into emergent technologies and (b) inform emergent regulatory science research questions. A variety of sources were used to gather data about the Juul e-cigarette and the corporations that surround it. Sources included government agencies, published academic literature, non-profit organizations, corporate and retail websites, and the popular press. Data was disambiguated, authenticated, and categorized prior to being placed on a timeline of events. A timeline of four significant milestones, nineteen corporate filings and events, twelve US regulatory actions, sixty four patent applications, eighty seven trademark applications, twenty three design patents and thirty two utility patents related to Juul Labs and its associates is presented spanning the years 2004 thought 2020. This work demonstrates the probative value of findings from patent, trademark, and SEC filing literature in establishing a premise for emergent regulatory science research questions which may not yet be supported by traditional archival research literature. The methods presented here can be used to identify key aspects of emerging technologies before products actually enter the market, this shifting policy formulation and problem identification from a paradigm of being reactive in favor of becoming proactive. Such a proactive approach may permit anticipatory regulatory science research and ultimately shorten the elapsed time between market technology innovation and regulatory response.

There is much interest in effective copper chelators to correct copper dyshomeostasis in neurodegenerative and oncological diseases. In this study, a recombinant fusion protein for expression in E. coli cells was constructed from glutathione-S-transferase (GST) and the N-terminal domain (ectodomain) of human high affinity copper transporter CTR1 (hNdCTR1), which has three metal-bound motifs. Several biological properties of the GST-hNdCTR1 fusion protein were assessed. It was demonstrated that in cells, the protein was prone to oligomerization, formed inclusion bodies and displayed no toxicity. Treatment of E. coli cells with copper and silver ions reduced cell viability in a dose- and time-dependent manner. Cells expressing GST-hNdCTR1 protein demonstrated resistance to the metal treatments. These cells accumulated silver ions and formed nanoparticles that contained AgCl and Ag0. In this bacterial population, filamentous bacteria with length about 10 μm were often observed. The possibility for the fusion protein carrying extracellular metal binding motifs to integrate into the cell’s copper metabolism and its chelating properties are discussed.

This research article provides an unconditional proof of an inequality proposed by \textit{Srinivasa Ramanujan} involving the Prime Counting Function $\pi(x)$, \begin{align*} (\pi(x))^{2}<\frac{ex}{\log x}\pi\left(\frac{x}{e}\right) \end{align*} for every real $x\geq \exp(547)$, using specific order estimates of the \textit{Mertens Function}, $M(x)$. The proof primarily hinges upon investigating the underlying relation between $M(x)$ and the \textit{Second Chebyshev Function}, $\psi(x)$, in addition to applying the meromorphic properties of the \textit{Riemann Zeta Function}, $\zeta(s)$ with an intention of deriving an improved approximation for $\pi(x)$.

Heterosis of growth traits in economic fish has benefited the production of aquaculture for many years, yet its genetic and molecular basis has been remained obscure. Nowadays, a new germplasm of hybrid Jinhu grouper (Epinephelus fuscoguttatus♀ × E. tukula♂), exhibiting paternal-biased growth heterosis, has provided an excellent model for investigating the potential regulatory mechanisms of heterosis. We integrated transcriptome and methylome to unravel the changes of gene expression, epigenetic modification, and subgenome dominance in Jinhu grouper compared with maternal E. fuscoguttatus. Integration analyses showed that the heterotic hybrids showed lower genomic DNA methylation levels than the purebred parent, and the up-regulated genes were mostly DNA hypomethylation. Furthermore, allele-specific expression (ASE) detected paternal subgenome dominance regulated paternal-biased heterosis, and paternal bias differentially expressed genes (DEGs) were wholly up-regulated in the muscle. Muti-omics results highlighted the role of lipid metabolism, particularly “Fatty acid synthesis”, “EPA biosynthesis”, and “Signaling lipids”, in Jinhu grouper heterosis formation. Coherently, our studies have proved that the eicosapentaenoic acid (EPA) of Jinhu grouper was greater than that of maternal E. fuscoguttatus (8.46% vs 7.46%). Finally, we constructed a potential regulatory network for control of the heterosis formation in Jinhu grouper. Among them, fasn, pparg, dgat1, igf1, pomca, fgf8a, and fgfr4, were identified as key genes. Our results provide new and valuable clues for understanding paternal-biased growth heterosis in Jinhu grouper, taking a significant step towards the molecular basis of heterosis.

This qualitative study investigates the management of supplier risks in e-commerce through relationship management strategies, focusing on trust-building, communication practices, digital technology integration, risk assessment methodologies, challenges, innovation initiatives, and ethical considerations. The research aims to provide nuanced insights into how e-commerce companies navigate the complexities of global supply chains to mitigate operational, financial, and reputational risks associated with supplier relationships. Through semi-structured interviews with 20 key stakeholders in the e-commerce sector, data were collected and analyzed using thematic analysis. The findings underscored the foundational role of trust in establishing resilient supplier relationships, facilitated by transparent communication, consistent performance evaluation, and mutual respect for contractual obligations. Effective communication practices, supported by digital platforms and technologies such as AI, blockchain, IoT, and cloud computing, enhanced operational transparency and decision-making capabilities across supply chains. The study identified diverse approaches to risk assessment, from qualitative evaluations to quantitative models utilizing predictive analytics and scenario planning. However, participants highlighted challenges including geopolitical uncertainties, trade disruptions, regulatory changes, and cultural barriers, necessitating adaptive strategies and diversified sourcing options. Innovation initiatives such as joint product development and technology adoption were crucial in enhancing supply chain agility and competitive advantage. Ethical considerations emerged as a critical aspect, influencing supplier selection criteria, CSR initiatives, environmental sustainability practices, and labor standards compliance. Integrating ethical guidelines into supplier contracts reinforced corporate values and enhanced brand reputation. Overall, this study contributes practical implications for e-commerce practitioners seeking to enhance supply chain resilience, mitigate supplier risks, and sustain competitive advantage in a dynamic global marketplace.

This qualitative study explores the relationship between supply chain responsiveness (SCR) and customer loyalty within the e-commerce sector. E-commerce has revolutionized global commerce, driven by technological advancements and shifting consumer behaviors. Central to e-commerce success is the ability to meet customer expectations swiftly and reliably, necessitating agile supply chain management (SCM) practices. SCR in e-commerce encompasses the capacity to adapt to dynamic market demands, minimize disruptions, and enhance customer satisfaction through efficient logistics, inventory management, and last-mile delivery. Through in-depth interviews with customers, e-commerce platform managers, and supply chain practitioners, this study investigates key themes, challenges, strategies, and impacts associated with SCR and customer loyalty. Findings reveal that customers prioritize fast order fulfillment, reliable service quality, personalized experiences, and trustworthy interactions, all of which significantly influence their loyalty and advocacy behaviors. Challenges identified include inventory management complexities, logistical hurdles in last-mile delivery, and the need for effective supplier communication. Strategic approaches to enhance SCR include leveraging data analytics for demand forecasting, adopting agile SCM practices, integrating customer feedback into service improvements, and fostering collaborative relationships with suppliers. These strategies not only optimize operational efficiency but also cultivate enduring customer relationships based on satisfaction, trust, and loyalty. The study concludes that improved SCR practices lead to increased customer satisfaction, repeat purchases, and positive word-of-mouth, thereby strengthening competitive advantage and sustainability in the e-commerce marketplace.

A novel educational platform called Shared Modeling and Simulation Environment (SMSE) was initiated in the ERASMUS+ “CybPhys” project. It integrates the Jupyter platform, including Ju-pyter Notebooks, for e-learning in the STEM field. A novel platform enhances e-learning by combining Moodle with Jupyter's capabilities to create virtual labs. A survey was conducted in the spring of 2023 among bachelor and master students of Chernihiv National Polytechnic Uni-versity aimed to gather feedback from students using SMSE in their e-learning process. Two student groups were involved: one of them consisted of students using SMSE in both the autumn and spring semesters and another represented the students starting with SMSE in the spring se-mester. The survey based on the adjusted Technology Acceptance Model (TAM) was conducted to understand the acceptance of this e-learning approach. A comprehensive analysis of students’ answers based on the TAM approach revealed the inside of the process of transformation of stu-dents’ perceptions during the acquisition of the SMSE platform. Our research demonstrates that SMSE effectively merges Moodle's online learning capabilities with Jupyter notebooks, provid-ing a flexible and interactive learning experience for both in-class and remote students. It pro-vides a web-based, multifunctional e-learning environment that combines a variety of tools and technologies, giving students the possibility to be involved in all sorts of teaching activities, such as lectures, exercises, simulations, etc., through the use of one single online environment.

The COVID-19 pandemic was declared in March 2020 and is still ongoing. The course of the epidemic remains uncertain, and mutations in the coronavirus, as well as the emergence of new variants of concern, make it possible that there will be periodic surges in the number of cases. Moreover, it is not clear how quickly and to what extent the effectiveness of vaccination will decline as the virus continues to mutate. One possible solution to combat the rapidly mutating coronavirus is the development of pan-coronavirus vaccines that stimulate the production of antibodies against conserved elements of the virus. Another approach could be the creation of safe vaccine platforms that can be rapidly adapted to deliver new, specific antigens in response to viral mutations. Recombinant probiotic microorganisms that can produce viral antigens by inserting specific viral DNA fragments into their genome show promise as a platform and vector for mucosal vaccine antigen delivery. With a well-established safety profile and the ability to transform into vaccine candidates, probiotic bacteria have significant research potential. The authors of this study have developed a convenient and universal technique for inserting the DNA sequences of pathogenic bacteria and viruses into the gene that encodes the pili protein of the probiotic strain E. faecium L3. The paper presents data on the immunogenic properties of two E. faecium L3 vaccine strains, which produce two different fragments of the coronavirus S1 protein, and provides an assessment of the protective efficacy of these oral vaccines against coronavirus infection in Syrian hamsters.

The pharmacokinetic profile of fat-soluble vitamins A, E, K1, and D3 co-administered with liquid paraffin or water in an experimental rat model was investigated. Animals received a solution of the four vitamins orally through a probe, followed 10 minutes later by the administration of either the liquid paraffin product dissolved in water (Emuliquen Simple®) or water (control). Vitamin formulations were 20, 50, 0.30 and 0.10 mg/kg for vitamins A, E, K1, and D3, respectively. Blood samples were collected before dosing and at 0.17, 1, 2, 4, 8, and 24 hours post-dosing. Vitamin concentrations were quantified by liquid chromatography coupled with mass spectrometry. No relevant differences in the absorption of vitamins in terms of AUC0-last (area under the curve up to the last measurable concentration) or Cmax in the absence or presence of co-administration of the liquid paraffin product were observed. The difference of these parameters between the treatment groups for all vitamins was in the range of bioequivalence (≤ 20%). The liquid paraffin-based laxative product did not interfere with the absorption of vitamins A, E, K1, and D3 that are ingested in the diet, which is clinically relevant due to the high prevalence of functional constipation in children and adults.

As digital technologies rapidly integrate into Health Professions Education (HPE), gaining a comprehensive understanding of cyberethics becomes crucial. This scoping review aimed to explore the pedagogy of cyberethics within HPE, with an emphasis on its definitions, conceptualizations, theoretical foundations, and interventions. Drawing from 37 documents spanning 2012-2022, primarily originating from the U.S. and encompassing both peer-reviewed and grey literature, the study highlighted a significant gap in the explicit definition and conceptualization of cyberethics. Additionally, the evident lack of specific theoretical frameworks in the majority of these documents could hamper the progression and replicability of research. Among the reviewed articles, only four introduced cyberethics educational interventions, indicating a substantial avenue for future research. While the study utilized comprehensive search methods, limitations such as language biases and the potential omission of pertinent documents were present. Future investigations should broaden the cyberethics discourse to encompass emerging technologies and their ethical implications within HPE. Crafting comprehensive, culturally sensitive, and inclusive guidelines is pivotal in nurturing ethical digital practices in the health care community.

The Internet of Things (IoT) was born from the fusion of virtual and physical space and became the initiator of many scientific fields. Economic sustainability is the key to further development and progress. Today, the need for electronic commerce has become an economic priority in the transition period between Industry 4.0 and Industry 5.0. Unlike mass production in Industry 4.0, customized production in Industry 5.0 should reach its true potential in vertically organized management and decision-making systems. The authors focused their research on e-commerce based on the three-level vertical IoT environment and the edge, fog, and cloud computing. The paper presents hands-on machine learning (ML) algorithms to facilitate the transition from a flat to a vertical e-commerce concept. The authors also propose practical ML algorithms for a few e-commerce types: consumer-consumer relationships and consumer-company-consumer relationships. These algorithms are mainly composed of convolution neural networks (CNN), natural language understanding (NLU) and sequential pattern mining (SPM), reinforcement learning (RL for agent training), algorithms for clicking on the item prediction, consumer behavior learning, etc. All presented concepts, algorithms, and models are described in detail.

This review is devoted to present the history of CARDIOSIM© software simulator platform, which was developed in Italy to simulate the human cardiovascular and respiratory system. The first version of CARDIOSIM© was developed at the Institute of Biomedical Technologies of the National Research Council in Rome. The first platform version published in 1991 ran on PC with disk operating system (MS-DOS) and was developed using the Turbo Basic language. The last version runs on PC with Microsoft Windows 10 operating system; it is implemented in Visual Basic and C++ languages. The platform has a modular structure consisting of seven different general sections, which can be assembled to reproduce different pathophysiological conditions. The software simulator can reproduce the most important circulatory phenomena in terms of pressure and volume relationships. It represents the whole circulation using a lumped-parameter model and enables the simulation of different cardiovascular conditions according to Starling’s law of the heart and a modified time-varying elastance model. Different mechanical ventilatory and circulatory devices have been implemented in the platform including thoracic artificial lung, ECMO, IABP, pulsatile and continuous right and left ventricular assist devices, biventricular pacemaker and biventricular assist devices. CARDIOSIM© is used in clinical and educational environment.

Hypercytokinemia, or cytokine storm, is one of the severe complications of viral and bacterial infections, involving the release of abnormal amounts of cytokines, resulting in a massive inflammatory response. Cytokine storm is associated with COVID-19 and sepsis high mortality rate by developing epithelial dysfunction and coagulopathy, leading to thromboembolism and multiple organ dysfunction syndrome. The anticoagulant therapy is an important tactic to prevent thrombosis in sepsis and COVID-19, but recent data show the incompatibility of modern direct oral anticoagulants and antiviral agents. It seems relevant to develop dual-action drugs with antiviral and anticoagulant properties. At the same time it was shown that azolo[1,5-a]pyrimidines are heterocycles with a broad spectrum of antiviral activity. We have synthesized a new family of azolo[1,5-a]pyrimidines and their condensed polycyclic analogs by cyclocondensation reactions and direct CH-functionalization and studied their anticoagulant properties. Five compounds among 1,2,4-triazolo[1,5-a]pyrimidin-7-ones and 5-alkyl-1,3,4-thiadiazolo[3,2-a]purin-8-ones demonstrated higher anticoagulant activity than the reference drug, dabigatran etexilate. Antithrombin activity of lead compounds was confirmed using lipopolysaccharide (LPS) treated blood to mimic conditions of cytokine release syndrome. The studied compounds affected only the thrombin time value, reliably increasing it 6.5–15.2 times as compared to LPS-treated blood.

The history of health records (later also called medical records), including ones regarding individual patients, is thousands of years old. It finds it roots in the first ancient civilisations. Up until the 19^th century the records’ purpose was mainly an educational one. In the 19^th and 20^th century they started becoming significant in other roles as well, including those not strictly limited to medicine. In particular, to account for medical procedures, insurance proceeds or legal action. Currently we are living in a revolutionary era when it comes to health records, in which their character has changed from a “paper-based” to an electronic one. This paper presents the development of health records from the ancient to modern times, mainly in Europe and North America. Other cultures and civilisations, including China and India, are not discussed. An analysis of available sources was conducted, inter alia digital versions of manuscripts up to hundreds of years old. The analysis was based on PubMed and Google Scholar (several key words, all the available sources). Sources published in non-international languages (e.g. Dutch) were also investigated. Overall, approximately 600 articles were analysed, 158 of which were used and cited in this paper. The conclusions drawn from the analysis are as follows: (1) Health records, priorly used mostly for educational purposes, for about 100 years now have acquired a fully formal status. (2) We are currently facing the most revolutionary changes regarding the transformation of paper-based records into electronic ones. (3) The consequences of this process include systematic applications of solutions within the area of e-health, which allow us to make medical services more flexible, improve the health of individual patients and entire populations and potentially limit expenditure. (4) In the light of the ongoing COVID-19 pandemic, introducing electronic health records could be beneficial in terms of limiting the potential sources of contamination (physical copies of health records), saving time and resources, and improving the network of communication between medical centres.

We investigate the shear quasinormal modes (QNMs) in the context of electron stars, focusing on the Lifshitz geometry and exploring the behavior in the small star limit. The study begins by analyzing the shear sector modes in the infrared (IR) Lifshitz limit, where the geometry approaches that of a pure Lifshitz space. We derive and solve the differential equations governing the shear modes, revealing the asymptotic behavior in terms of the Lifshitz exponent. In the special case of integer values of the exponent, we obtain analytic corrections to the solutions to extract hydrodynamical QNMs. We then explore the cases with a Lifshitz exponent equal to or greater than three, providing analytical corrections to the Lifshitz IR solutions. A special case with an exponent of two is also considered, leading to modified solutions. The study extends to finding hydrodynamical QNMs, emphasizing the role of the Lifshitz geometry. Further investigations involve the flux with real and complex frequencies, considering the off-shell Lagrangian and deriving conserved flux expressions. Our analysis focuses on the exterior of the star, modeled by the Reissner-Nordström-AdS geometry. The small star limit is examined, revealing interesting features in the behavior of fermionic excitations. In summary, we provide a detailed exploration of shear quasinormal modes in electron stars, shedding light on their behavior in Lifshitz geometry, small star limits, and the interplay between real and complex frequencies. Our findings contribute to our understanding of the dynamics of electron stars and their gravitational properties.

It has been more than a century since Erlang published his paper in 1909. The classical queueing system for the M/D/c queue has been investigated by many authors. The key is to find the roots of an equation using explicit or numerical methods. We present an alternate form of explicit solution(s) of this/these root(s) using the Lambert-W function in this paper. In addition, the unsaturated probabilities of the number of customers in the system is derived explicitly in terms of this/these root(s). Finally, the mean number of customers in the system and the mean queueing delay are obtained from these probabilities. The exact queueing delay formula for the M/D/c queue is expressed in closed-form in terms of the root(s). Numerical results show that they are in excellent agreement with the numerical results published by Seelen, Tijms and Van Hoorn.

The aim of this article is to establish a new class of unified integrals associated with the generalized Lommel-Wright functions, which are expressed in terms of Wright Hypergeometric function.Some integrals involving trigonometric,generalized Bessel function and Struve functions are also indicated as special cases of our main results.further, with the help of our main results and their special cases, we obtain two reduction formulas for the Wright hypergeometric function.

Effective management of supplier relationships is crucial for e-commerce companies to navigate complex supply chain dynamics and mitigate risks associated with supplier disputes. This qualitative study explores the strategies and challenges involved in resolving supplier disputes through relationship management in the context of e-commerce. Through semi-structured interviews with supply chain managers, procurement officers, and executives from diverse e-commerce firms, the study investigates key themes including communication strategies, trust-building initiatives, negotiation dynamics, technological integration, organizational culture, and global supply chain alignment. Findings reveal that clear and transparent communication plays a foundational role in preventing misunderstandings and fostering collaboration with suppliers. Trust-building initiatives, such as consistency in commitments and transparency in business dealings, are essential for cultivating resilient supplier relationships. Negotiation strategies emphasizing principled negotiation and collaborative problem-solving facilitate the resolution of disputes while preserving long-term partnerships. Technological integration through data analytics, automation, and digital platforms enhances operational efficiency and decision-making capabilities in managing supplier relationships. Organizational culture characterized by collaboration, innovation, and leadership commitment to strategic alignment with global supply chains promotes resilience and responsiveness to market dynamics. Challenges including power dynamics, operational constraints, and cultural differences underscore the importance of proactive risk management and cultural sensitivity in supplier relationship management. This study contributes actionable insights for practitioners to enhance supplier relationship management practices, navigate disputes effectively, and foster sustainable competitive advantage in e-commerce. By integrating these findings into strategic planning, e-commerce firms can strengthen supplier partnerships, optimize supply chain performance, and mitigate risks in a dynamic business environment.

To delve into the structure-function relationship of transmembrane proteins (TMPs), robust protocols are needed to produce them in a pure, stable, and functional state. Among all hosts that express heterologous TMPs, E. coli has the lowest cost and fastest turnover. However, many of the expressed in E. coli TMPs are misfolded. Several strategies have been developed to either direct the foreign TMPs to E. coli’s membrane or retain them in a cytosolic soluble form to overcome this deficiency. Here, we summarize protein engineering methods to produce chimera constructs of the desired TMPs fused to either signal peptide or precursor maltose binding protein (pMBP) to direct the entire construct to the periplasm, therefore depositing the fused TMP in the plasma membrane. We further describe strategies to produce TMPs in soluble form by utilizing N-terminally fused MBP without signal peptide. Depending on its N- or C-terminus location, a fusion to apolipoprotein A-I can either direct the TMP to the membrane or shield the hydrophobic regions of the TMP, maintaining the soluble form. Strategies to produce G-protein coupled receptors, TMPs of Mycobacterium tuberculosis, HIV-1 Vpu, and other TMPs are discussed. This knowledge could increase the scope of TMPs’ expression in E. coli.

This study aimed to assess the microbiological quality of set of fruits and vegetables sold on stalls in the streets and open markets of Dakar, the capital city of Senegal. Samples purchased in seven sites were analyzed to isolate E. coli, Salmonella spp. and Vibrio spp. Some primary samples with a positive microbiological culture were subjected to DNA extraction and subsequent metagenomic analysis. A total of 240 fresh fruit and vegetable samples were collected including lettuce (n=40), tomatoes (n=40), mango slices (n=40), onion slices (n=40), mint leaves (n=40), strawberries and grapes (respectively n=20). Of these samples, 50.83% (122/240) and 60.41% (145/240) was contaminated with Escherichia coli and Vibrio spp. respectively, while Salmonella was not isolated in any product. Levels of contamination with both E. coli (1.3 103 to 6 106 CFU/g) and Vibrio spp. (4.55 102 to 8.73 106 CFU/g) were significantly above the thresholds acceptable for human consumption. The most contaminated samples were lettuce with a prevalence of 98% (39/40) for E. coli and for Vibrio spp. followed by mint leaves with 100% (40/40) and 93% (37/40) of the samples containing for E. coli and Vibrio spp. respectively. Out of 46 samples sequenced, metagenomic analysis revealed high contamination rates for E. coli, Vibrio spp. and Salmonella spp. with 100%, 67.39% and 93.47% of prevalence respectively. On the other hand, the alpha diversity analysis shows a high bacterial diversity in lettuce and mint leaf samples while beta diversity analysis highlighted the presence of two major clusters. Our results stress the need of a surveillance system that extends this investigation to a national scale while increasing the number of sampling sites and products analyzed.

The purpose of this research was to analyze the moderating effect of clean energy innovation on the relationship between corporate carbon footprint and corporate profits in those industrial sectors associated with high demand for fossil fuels in which it is "hard to abate" CO₂e emissions. It used a longitudinal research design, in particular a panel study under a structural equation modeling (SEM) approach, based on partial least squares. For the longitudinal moderation analysis, this research employed the Bayesian method by defining a multiple-indicator latent growth curve model (B-LGC model). A global sample was used consisting of 7,827 firm-year observations between 2015 and 2021 corresponding to 167 international firms. The results revealed a very significant impact of the corporate carbon footprint on corporate profits. Likewise, the results showed that innovations in clean energy, when measured as the consumption of renewable energy, positively moderates the relationship between the greenhouse gas emissions from the value chain associated with Scope 3 of the Greenhouse Gas (GHG) Protocol, and the gross profit margin obtained. Besides the academic contribution represented by the moderating effect of clean energy innovation, these findings imply that a more detailed understanding of the emissions of the entire value chain (Scope 3 CO₂e) by executives and managers of high emitting CO₂e companies represents an effective mechanism to obtain higher profits, create competitive advantages and, at the same time, achieve a net zero emissions strategy. More importantly, public policy makers will be able to use these results to revise CO₂e-related policies paying more attention to the Scope 3 CO₂e emissions produced by these companies, to formulate regulatory and control mechanisms that stimulate clean energy innovation.

Geomagnetic induced current (GIC) is a ground end manifestation associated with the space weather perturbations that should be greatly taken into account by the society. Although the GICs implication to the power system is not regular, it can cause large scale of system failure. In equatorial, the power system is considered safe since the most intense of geomagnetic storm happened in high latitude. However, the internal damage due to GICs which finally led to the South African power system failure has totally changed the normal perception. Therefore, a preliminary investigation on the GICs activity in equatorial region is performed to understand the space weather impact to the power system. Time derivative of the horizontal magnetic field component (dB/dt) is done to indicate the GICs activity value based on Faraday’s law. All the reported power failures are compiled to produce the threshold value of dB/dt, which possibly cause the harmful effect to the system. Then, dB/dt analysis is extended to show the pattern of GICs activity in function of magnetic latitude and local time. The results reveal that power network in equatorial region has possibly suffered by GIC. Plus, high number of intense GIC activity in this region occurred during dayside.

Genetic variations at the Apolipoprotein E (ApoE) and microtubule-associated protein tau (MAPT) loci have been implicated in multiple neurogenerative diseases, but their exact molecular mechanisms are unclear. In this study we performed transcript level linear modelling using the blood whole transcriptome data and genotypes of the 570 subjects in the Parkinson’s progression markers initiative (PPMI) cohort. ApoE, MAPT haplotypes and two SNPs at the SNCA locus (rs356181, rs3910105) were used to detect expression quantitative trait loci eQTLs associated with the transcriptome and differential usage of transcript isoforms. As a result, we identified 151 genes associated with the genotypic variations, 29 cis and 122 trans eQTL positions. Profound effect with genome-wide significance of ApoE e4 haplotype on the expression of TOMM40 transcripts was identified. This finding potentially explain in part the frequently established genetic association with the APOE e4 haplotypes in neurodegenerative diseases. Moreover, MAPT haplotypes had significant differential impact on 23 transcripts from the 17q21.31 and 17q24.1 loci. MAPT haplotypes had also the largest (256) and smallest (-178) effect sizes measured as beta values on two different transcripts from the same gene (LRRC37A2). Intronic SNP in the SNCA gene, rs3910105, differentially induces expression of three SNCA isoforms. In conclusion, this study established clear association between well-known haplotypic variance and transcript specific regulation in the blood. APOE e4 and MAPT H1/H2 haplotypic variants are associated with the expression of several genes related to the neurodegeneration.

This paper presents an overview of the smart electro-clothing systems (SeCSs) targeted at health monitoring, sports benefits, fitness tracking, and social activities. Technical features of the available SeCSs, covering both textile and electronic components, are thoroughly discussed and their applications in the industry and research purposes have been highlighted. In addition, it also presents the developments in the associated areas of wearable sensor systems and textile-based dry sensors. As it became evident during the literature research, such a review on SeCSs covering all relevant issues has not been presented before. This paper will be particularly helpful for new generation researchers investigating the design, development, function and comforts of the sensor integrated clothing materials.

Given the rise in the number of cases and their recurrences, Urinary Tract Infections (UTI) are one of the major burdens on public healthcare worldwide. Rapid, inexpensive and selective detection of Uropathogenic E. coli (UPEC), a major contributor to UTIs, is the need of the hour for effective treatment, given the rise of antibiotic-resistant bacteria due to improper diagnosis. Here we present a rapid, real-time, selective and label-free detection of UPEC using an integrated sensing platform based on Crossed Surface Relief Gratings (CSRGs) as nanoplasmonic sensors. Detection is achieved due to the unique Surface Plasmon Resonance (SPR)-based light energy exchange attributed to the CSRGs, allowing real-time sensing in a very narrow bandwidth of the incident light to pass where the SPR energy conversion occurs. The sensing ability of the platform is experimentally demonstrated by the detection of bulk Refractive Index (RI) changes, with a bulk sensitivity of 382.2 nm/RIU and a resolution in the order of 10-6 RIU. We demonstrate selective capture and detection of clinical concentration of UPEC, as opposed to other gram-negative bacteria, in real-time, a first for CSRGs. This work is particularly important for effective treatment of UTIs, allowing point-of-care diagnosis for economically disadvantaged regions around the world.

The arrival of new developments in the field of power electronics circuit’s applications in power systems builds new control strategy to improve voltage quality for power grid by overcome interruptions. Wind energy resources are unconventional resources and get advanced problems to power grid when it is connected. Uncertainty of load sharing, peak energy management, climatic conditions, wind velocity and wind energy injected into power grid leads many of power quality problems on power grid based on the existing guidelines specified in IEC-61400 standard. This system plans efficient operation of DFIG to eliminate the voltage collapse and mismatch frequency to power grid. The DFIG connected diode rectifier and rotor side converter wind generator works as an Efficient Static Synchronous Compensator (E-SATCOM) for supplying the demand of reactive power for power grid to mitigate PQ problems. The benefit of using a combined controller was verified by simulink/Matlab and its simulated results used Doubly Fed Induction Generator (DFIG), wind Turbine. This simulation results gives good quality transient and stable state response to manage and support reactive power for both symmetrical and unsymmetrical faults in connection of grid codes to provide continuous quality of power supply, multiple wind generators are required for 140 bus power grid.

The greenhouse gases and air pollution generated by extensive energy use have exacerbated climate change. An electric-bus (e-bus) transportation system favors reducing pollution and carbon emissions. This study analyzed the minimization of construction costs for an all battery-swapping public e-bus transportation system. A simulation was conducted according to existing timetables and routes. Daytime charging was incorporated during the hours of operation; the two parameters of the daytime charging scheme were the residual battery capacity and battery-charging energy during various intervals of daytime peak electricity hours. The parameters were optimized using three algorithms: particle swarm optimization (PSO), a genetic algorithm (GA), and a PSO–GA. This study observed the effects of optimization on cost changes (e.g., number of e-buses, on-board battery capacity, number of extra batteries, charging facilities, and energy consumption) and compared the plug-in and battery-swapping e-bus systems. The results revealed that daytime charging can reduce the construction costs of both systems. In contrast to the other two algorithms, the PSO–GA yielded the most favorable optimization results for the charging scheme. Finally, according to the cases investigated and the parameters of this study, the construction cost of the plug-in e-bus system was lower than that of the battery-swapping e-bus system.

Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) have revolutionised e-learning by creating personalised, adaptive, and secure environments. However, challenges such as privacy, bias, and data limitations persist. E-FedCloud aims to address these issues by providing more agile, personalised, and secure e-learning experiences. This study introduces E-FedCloud, an AI-assisted adaptive e-learning system that automates personalised recommendations and tracking, thereby enhancing student performance. It employs federated learning-based authentication to ensure secure and private access for both course instructors and students. Intelligent Software Agents (ISAs) evaluate weekly student engagement using the Shannon Entropy method, classifying students into either engaged or not-engaged clusters. E-FedCloud utilises weekly engagement status, demographic information, and an innovative DRL-based early warning system, specifically ID2QN, to predict the performance of not-engaged students. Based on these predictions, the system categorises students into three groups: risk of dropping out, risk of scoring lower in the final exam, and risk of failing the end exam. It employs a multi-disciplinary ontology graph and an attention-based capsule network for automated, personalised recommendations. The system also integrates performance tracking to enhance student engagement. Data is securely stored on a blockchain using the LWEA encryption method.

To develop a modern plague vaccine, we used hypo-endotoxic Yersinia pestis bacterial ghosts (BGs) with combinations of genes encoding the bacteriophage ɸX174 lysis-mediating protein E and/or holin-endolysin systems from λ or L-413C phages. Expression of the protein E gene resulted in the BGs that retained the shape of the original bacterium. Co-expression of this gene with genes coding for holin-endolysin system of the phage L-413C caused formation of structures resembling collapsed sacs. Such structures, which have lost their rigidity, were also formed as a result of the expression of only the L-413C holin-endolysin genes. Similar holin-endolysin system from phage λ containing mutated holin gene S and intact genes R-Rz coding for the endolysins caused generation of mixtures of BGs that had (i) practically preserved and (ii) completely lost their original rigidity. The addition of protein E to the work of this system shifted the equilibrium in the mixture towards the collapsed sacs. The collapse of the structure of BGs can be explained by endolysis of peptidoglycan sacculi. Immunizations of laboratory animals with the variants of BGs followed by infection with a wild-type Y. pestis strain showed that bacterial envelopes protected only cavies. BGs with peptidoglycan maximally hydrolyzed had a greater protectivity compared to BGs with preserved peptidoglycan skeleton.

The present study was aimed to evaluate the levels of oxidative stress markers in breast diseases by measuring the 8-hydoxy-2-deoxyguanosine (8-OHdG), vitamin A, vitamin C, vitamin E and total antioxidant status (TAS) alterations in relation to cell proliferation activity and disease progression. Significant increases in the level of oxidative damage marker 8-OHdG and cell proliferation activity were observed in breast carcinoma patients in comparison to benign and normal controls, which were accompanied by significant decrease in non enzymatic antioxidants and TAS concentrations. 8-OHdG and cell proliferation level were negatively correlated with non enzymatic antioxidants viz., Vitamin A, Vitamin C, vitamin E level and total antioxidant activity. Altered levels of biomarkers of oxidative stress and cell proliferation activity amongst the malignant, benign and controls suggest a correlation of increased oxidative stress and cell proliferation activity in the progression of disease in breast carcinoma patients. Among the oxidative stress markers and cell proliferation index, decreased level of vitamin A, vitamin C, vitamin E, TAS and increased level of 8-OHdG, cell proliferation index emerged as best predicted biomarkers for subjects with malignancy and benign breast disease.

The literature lacks consensus on the minimum microbial density required for diagnosing urinary tract infections (UTIs). This study categorized the microbial densities of urine specimens from symptomatic presumptive UTI patients and correlated them with detected levels of immune response biomarkers NGAL, IL-8, and IL-1β. The objective was to identify changes in immune response at different microbial densities and determine an optimal threshold for diagnosing symptomatic UTIs. Midstream clean-catch urine samples were analyzed for microbial identification and quantification using SUC and M-PCR, while NGAL, IL-8, and IL-1β levels were measured with ELISA. NGAL, IL-8, and IL-1β levels were all significantly higher in symptomatic subjects with microbial densities ≥ 10,000 cells/mL by M-PCR (p < 0.0069) or equivalent CFUs/mL by SUC (p < 0.0104) compared to samples with no detectable microbes. With both PCR and SUC, a consensus of two or more elevated biomarkers correlated well with microbial densities > 10,000 cells/mL or CFU/mL, respectively. The association between ≥ 10,000 cells and CFU per mL with elevated biomarkers in symptomatic patients suggests that this lower threshold may be more suitable for diagnosing UTIs. These findings challenge the widely used threshold of 100,000 CFU per mL, which may overlook many active UTI cases.

C-type lectin CD209/DC-SIGN and CD209L/L-SIGN proteins are distinct cell adhesion and pathogen recognition receptors that mediate cellular interactions and recognize a wide range of pathogens including, viruses such as SARS, SARS-CoV-2, bacteria, fungi and parasites. Pathogens exploit CD209L family proteins to promote infection and evade the immune recognition system. CD209L and CD209 are widely expressed in SARS-CoV-2 target organs and can contribute to infection and pathogenesis. CD209L family receptors are highly susceptible to alternative splicing and genomic polymorphism, which may influence virus tropism and transmission in vivo. The carbohydrate-recognition domain (CRD) and the neck/repeat region represent the key features of CD209L family proteins that are also central to facilitating cellular ligand interactions and pathogen recognition. While, the neck/repeat region is involved in oligomeric dimerization, the CRD recognizes the mannose containing structures present on specific glycoproteins such as those found on the SARS-CoV-2 spike protein. Considering the role of CD209L and related proteins in diverse pathogen recognition, this review article discusses the recent advances in the cellular and biochemical characterization of CD209 and CD209L and their roles in viral uptake, which has important implications in understanding the host-pathogen interaction, the viral pathobiology and driving vaccine development of SARS-CoV-2.

This study investigates the factors influencing the choice of online and offline shopping trips and their impacts on urban transportation, environment, and economy in Tehran, Iran. A questionnaire survey was conducted to collect data from 1,000 active e-commerce users who made successful orders in both online and offline services in the last 20 days of 2021 in areas 2 and 5 of Tehran. A deep neural network model was developed to estimate the type of shopping trip based on 10 indicators, such as age, gender, car ownership, delivery cost, product price, etc. The performance of the model was compared with three other algorithms: MLP, decision tree, and KNN. The results showed that the deep neural network model had the highest accuracy of 95.63%. The most important factors affecting the choice of shopping trips were delivery cost, delivery time, and product price. This study provides insights for transportation planners, e-commerce managers, and policymakers to design effective strategies for reducing transportation costs, pollutant emissions, urban traffic, and increasing user satisfaction and sustainable development.

Background: Metastatic oral squamous cell carcinoma (OSCC) is associated with poor patient prognosis. Metastasis is a complex process involving various proteins, tumor cell alterations including changes caused by the epithelial-to-mesenchymal transition (EMT) process, and interactions with the tumor microenvironment (TME). In this study, we investigate a combined protein marker system consisting of connexin 43 (Cx43), EMMPRIN (CD147), E-cadherin and vimentin during the invasive metastatic process of OSCC and the possibility of using this system for prognosis prediction. Methods: The protein expression profiles of Cx43, EMMPRIN, E-cadherin and vimentin were investigated by immunohistochemistry in tissue samples from 24 OSCC patients. The metastatic process was mapped through different regions of interest (ROI) of adjacent healthy oral mucosa (OM), center of primary OSCC, invasive front (IF), and local cervical lymph node metastases (LNM). Disease-free survival (DFS) and overall survival (OS) were the primary clinical endpoints. Results: Significant changes in the expression profiles of the different marker proteins were detected between the different ROIs (all p values &lt; 0.05). Multivariable Cox regression analysis revealed a significant effect of increased EMMPRIN expression towards IF on DFS (p = 0.019) and OS (p = 0.023). The combined predictive analysis showed a significant predictive value of the marker system for DFS (p = 0.0017) and OS (p = 0.00044). Conclusions: The combined marker system was able to significantly predict patient prognosis. An increase in EMMPRIN expression towards IF showed the strongest effect and could be an interesting new antimetastatic therapy approach.

Excessive intracellular glucose in insulin independent tissues including nerve, nephron, lens and retina invites mishandling of metabolism of glucose resulting in a background of increased oxidative stress, advanced glycation end products (AGE) formation, lipid peroxidation and failure of antioxidant defense systems in type 2 diabetes mellitus (T2DM). All these detrimental biochemical anomalies ultimately attack biological membranes and especially capillary beds of retina and glomerulus of kidney, resulting in break-down of inner blood-retinal i.e. initiation of diabetic retinopathy (DR). If these disarrays are corrected to a large extent, development of DR can be avoided or delayed. In this prospective clinical trial, 185 patients with T2DM who received B-vitamins, vitamin-C, and E along with anti-diabetic medication for five years, demonstrated a slower rate of the development of DR and reduced abnormal biochemical mediators like reactive oxygen species (ROS), malondialdehyde (MDA), AGE, and vascular endothelial growth factor (VEGF) compared to 175 T2DM individuals who were treated with only anti-hyperglycemic drugs.

Myr47 lipopeptide consisting of hepatitis B virus (HBV) pre-S1 domain (myristoylated 2-48 peptide) is a commercialized effective anti-HBV drug, preventing the interaction of HBV with sodium taurocholate cotransporting polypeptide (NTCP) on human hepatocytes, of which the activity requires both N-myristoylation residue and specific amino acid sequence. Meanwhile, we recently reported that Myr47 reduces the cellular uptake of HBV surface antigen (HBsAg, subviral particle of HBV) in the absence of NTCP expression (Somiya; et al. Virology 2016, 497, 23–32). In this study, we analyzed how Myr47 reduces the cellular uptake of lipid nanoparticles (including liposomes (LPs) and HBsAg) without NTCP expression. By using Myr47 mutants lacking the HBV infection inhibitory activity, they could reduce the cellular uptake of LPs in an N-myristoylation-dependent manner whereas in an amino acid sequence-independent manner. Moreover, Myr47 and its mutants could reduce the interaction of LPs with apolipoprotein E3 (ApoE3) in an N-myristoylation-dependent manner regardless of their amino acid sequences. From these results, N-myristoyl residue of lipopeptides generally could interfere the LPs/HBsAg-ApoE3 complex formation, thereby reducing the cellular uptake of LPs/HBsAg. When lipid nanoparticles are used as a DDS (drug delivery system) nanocarrier, the surface modification with lipopeptides may be a new method to inhibit unwanted cellular uptake of DDS nanocarriers by non-target cells.

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (?-ω) model, can suffer from significant errors over croplands (in average between -9.4K and + 12.0K for Single Channel Algorithm SCA; -8K and + 9.7K for Dual-Channel Algorithm DCA) if the vegetation scattering albedo (omega) is treated as a constant and the temporal variations are not accounted. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer ?-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). The validation was performed from 14 May to 13 December 2015 over 61 Climate Reference Network sites (SCRN) classified as croplands. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics on croplands are better represented by a time-dynamic single scattering albedo.

This study examines the role of using algorithmic HRM to make strategic decisions pertaining to HR activities in organizations. The study develops a scale to measure algorithmic HRM usage in its first phase, and in the second phase, it finds that algorithmic HRM having significant impact on the strategic HR decision making that helps and enables organization in creating the competitive advantage. Utilizing the author’s LinkedIn profile, 234 final participants considered for this research. Collected data analyzed by applying PLS SEM. It evaluates the mediation role of the HR strategic decision making, and the HR digital maturity as a moderator in seeing the impact of algorithmic HRM on the competitive advantage of the firm. The study finds a strong relationship between the algorithmic HRM usage and competitive advantage, a significant relationship between algorithmic HRM usage and the strategic HR decision making, and lastly, a significant relationship between strategic HR decision making and the competitive advantage. The moderating role of HR digital maturity was found to be insignificant in this research which paves the way for further research. This research, the model, and its findings contribute to the theory and implicate the practicality of algorithmic HRM. It's one of few papers that address the algorithmic HRM usage in the transitioning economy like Saudi Arabia.

Historically, viral hepatitis is a considerable public health problem in Central Asian countries, which may have worsened after dissolution of the Soviet Union. However, up-to-date seroepidemiological studies are lacking. The aim of the present study was, therefore, to provide current estimates of seroprevalence of viral hepatitis in Kyrgyzstan, one of the economically least developed countries in the region. We conducted a population-based cross-sectional study in 2018 in the capital of Kyrgyzstan, Bishkek (n=1075). Participants, children and adults, were recruited from an outpatient clinic. Data were collected during face-to-face interviews. A blood sample (6 ml) was collected from each participant and tested with ELISA for the presence of serological markers for five viral hepatitides (A, B, C, D and E). Poststratification weighting was performed to obtain nationally representative findings. The overwhelming majority of the study participants were positive for anti-HAV (estimated seroprevalence, 75.3%; 95% confidence interval: 72.5–77.9%). The weighted seroprevalence estimates of HBsAg, anti-HCV and anti-HDV were 2.2% (1.5–3.3%), 3.8% (2.8–5.1%), and 0.40% (0.15–1.01%), respectively. Anti-HEV seropositivity was 3.3% (2.4–4.5%). Of the 33 HBsAg positive participants, five (15%) were anti-HDV positive. Our study confirms that Kyrgyzstan remains a high endemic country for hepatitis virus A and C infections. However, seroprevalences of HBV and HDV were lower than previously reported, and based on these data, the country could potentially be reclassified from high to (lower) intermediate endemicity. The observed anti-HEV seroprevalence resembles the low endemicity pattern characteristic of high-income countries.