Zika virus (ZIKV) co-circulates with several closely related flaviviruses which exhibit similar clinical manifestations thus, clinicians rely on molecular and serological techniques for diagnosis. Cross-reactivity of patient specimens to flaviviruses is a significant impediment to serological diagnosis in areas where multiple flaviviruses co-circulate. Furthermore, patient exposure history to any of these viruses could complicate serological response patterns which could result in over and/or underdiagnosis of ZIKV infection. Three strains of ZIKV, dengue serotypes 1-4, West Nile virus, Japanese Encephalitis virus, and Yellow Fever virus were evaluated for neutralizing properties against 3 monoclonal antibodies, 4 ZIKV-naïve patients with flavivirus exposure history, 5 patients with verified ZIKV exposure and unknown flavivirus exposure history, and 5 flavivirus-naive patients with ZIKV-only exposure. Patients naïve for ZIKV exposure effectively neutralized multiple strains of ZIKV. Overall, the prototype ZIKV isolate MR-766 did not behave like the other ZIKV isolated used in this study. MR-766 was neutralized more completely by polyclonal patient serum than recent ZIKV isolates. MR-766 was neutralized better than dengue virus in ZIKV-naïve patients with prior dengue exposure. MR-766 was neutralized significantly less than recent ZIKV isolates when treated with monoclonal antibodies. The data herein show that without RT-PCR, serological diagnosis may not be possible in areas where multiple flaviviruses are endemic.

A portable urea sensor for use in the fast flow condition was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. To generate a specific electrochemical sensor signal from urea, the urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes via chemical crosslinking using glutaraldehyde. The urease-immobilized membranes were assembled in a polydimethylsiloxane (PDMS) fluidic chamber, and a screen-printed carbon three-electrode system was used for electrochemical measurements. The success of urease immobilization was confirmed using fluorescence microscopy, scanning electron microscopy, and Fourier-transform infrared spectroscopy. The optimum concentration of urease for immobilization on the parylene-A-coated PTFE membranes was determined to be 48 mg/mL, and the optimum number of membranes in the PDMS chamber was found to be 8. Using these optimized conditions, we fabricated the urea biosensor and monitored urea samples under various flow rates ranging from 0.5 to 10 mL/min in the flow condition using chronoamperometry. To test the applicability of the sensor for physiological samples, we used it for monitoring urea concentration in the waste peritoneal dialysate of a patient with chronic renal failure, at a flow rate of 0.5 mL/min.

Original and improved version of the Hardy Cross iterative method with related modifications are today widely used for calculation of fluid flow through conduits in loops-like distribution networks of pipes with known node fluid consumptions. Fluid in these networks is usually natural gas for distribution in the municipalities, water in waterworks or hot water in district heating system, air in the case of ventilation systems in buildings or mines, etc. Since, the resistances in these networks depend of flow, problem is not linear like in electrical circuits, and iterative procedure must be used. In both version of the Hardy Cross method, in original and in the improved one, initial results of calculation in iteration procedure is not flow, but rather the correction of flow. Unfortunately, these corrections should be added to or subtracted from a flow calculated in previous iteration according to complicate algebraic rules. After the here presented node-loop method, final results in each of the iterations is flow directly rather than flow correction. In that way complex algebraic scheme for sign of flow correction is avoided, while the final results still remain unchanged. Numbers of required iterations for the same results are comparable with the improved Hardy Cross method.

Patterns of age and growth of a sedentary damsel fish Acanthochromis polyacanthus were tested over a latitudinal range of approximately 10 degrees (1,200 km) on the Great Barrier Reef, Australia. Within latitudes these patterns were also compared on reefs across a continental shelf that ranged in width from 52 to 128 km. Although variation in length-max, growth, age-max and the von-Bertalanffy metrics of L, and K were found within and among latitudes, greatest variation in some demographic characteristics were found across the shelf regardless of latitude. Fish were always smaller at inner shelf reefs and grew more slowly when compared to mid and outer shelf reefs. The oldest fish collected was 11 years old and, there were no consistent variation in age-max among distances from shore. On outer reefs, there was a linear relationship with age-max and latitude. This ‘tropical gradient’ of age only explained 34% of the variation, further this was not found when the oldest 10% of fish were considered. Fish only reached an age-max of 6 years on the southern-most reefs. There was a trend for a smaller L with latitude but, it was not significant and L did not vary predictably with water temperature. The sampling of MPAs did not confound the resultant patterns. Instantaneous mortality rates were 0.245-0.685, highest at inner reefs and showed no consistent MPA-related patterns. Our study suggested that the mid and outer shelf waters of the GBR appeared best suited for growth of A. polyacanthus. In conclusion, position on continental shelves and related local environmental conditions needs to be considered in spatial models of growth.

Software defect prediction is an important means to guarantee software quality. Because there are no sufficient historical data within a project to train the classifier, cross-project defect prediction (CPDP) has been recognized as a fundamental approach. However, traditional defect prediction methods using feature attributes to represent samples, which can not avoid negative transferring, may result in poor performance model in CPDP. This paper proposes a multi-source cross-project defect prediction method based on dissimilarity space ( DM-CPDP). This method first uses the density-based clustering method to construct the prototype set with the cluster center of samples in the target set. Then, the arc-cosine kernel is used to form the dissimilarity space, and in this space the training set is obtained with the earth mover’s distance (EMD) method. For the unlabeled samples converted from the target set, the KNN algorithm is used to label those samples. Finally, we use TrAdaBoost method to establish the prediction model. The experimental results show that our approach has better performance than other traditional CPDP methods.

The formability and failure behavior of TRIP steel blanks were investigated through various stress states. The forming limit diagram (FLD) at fracture is constructed both experimentally and numerically. Numerical studies are performed to evaluate the applicability of different damage criteria in predicting the FLD as well as complex cross-die deep drawing process. The fracture surface and numerical results revealed that the material failed in a different mode for different strain path. Therefore, Tresca model which is based on shear stress accurately predicted the conditions where shear had the profound effect on the damage initiation, whereas Situ localized necking criterion was able to calculate the conditions which localization was dominant.

This qualitative study explores the pivotal role of Supplier Relationship Management (SRM) in enhancing resilience within e-commerce supply chains. In an era marked by rapid digital transformation and global interconnectedness, the resilience of supply chains has become a strategic imperative for organizations striving to maintain operational efficiency and meet customer expectations. Through semi-structured interviews with supply chain managers, procurement officers, and strategic sourcing specialists across diverse industries, this research investigates the strategies, challenges, and outcomes associated with SRM practices. Findings reveal that effective communication and collaboration are fundamental to successful SRM, fostering trust, transparency, and responsiveness in supplier relationships. Strategic risk management through proactive identification and mitigation strategies enables organizations to navigate uncertainties such as economic fluctuations and geopolitical tensions. SRM implementation yields significant organizational benefits, including improved supply chain efficiencies, enhanced product quality, and increased customer satisfaction. However, challenges such as technological complexities, cultural differences among global suppliers, and regulatory compliance issues underscore the need for adaptive strategies and digital investments. The integration of digital technologies such as AI and blockchain enhances SRM effectiveness by enabling real-time data exchange, predictive insights, and decision-making capabilities. Ultimately, SRM emerges as a cornerstone of sustainable growth and competitive advantage in e-commerce, empowering organizations to optimize supply chain performance and resilience amidst dynamic market conditions.

This study explores the strategic importance of leveraging supplier relationships for competitive advantage in the e-commerce industry. Strong supplier relationships are crucial for enhancing operational efficiencies, cost management, quality assurance, innovation, sustainability, and overall supply chain resilience. Through collaborative partnerships, e-commerce companies can streamline logistics, reduce costs, ensure consistent product quality, and foster innovation through joint development initiatives. Ethical sourcing and sustainable practices play a pivotal role in supplier relationship management (SRM), aligning with consumer expectations and enhancing brand reputation. Advanced technologies such as AI, blockchain, and IoT further transform SRM practices by improving transparency, efficiency, and decision-making capabilities across the supply chain. The study also discusses challenges in managing global supplier relationships, emphasizing the importance of effective communication, cultural sensitivity, and strategic risk management. By addressing these challenges and nurturing trust-based relationships with suppliers, e-commerce firms can navigate market complexities and achieve sustainable growth. This research provides insights for e-commerce companies seeking to optimize their supplier relationships and maintain competitive advantage in a dynamic market environment.

Supplier diversity initiatives in procurement have emerged as strategic imperatives for organizations aiming to enhance competitiveness and foster socio-economic equity. This research investigates the impact of supplier diversity initiatives across various industries, analyzing implementation strategies, challenges, and outcomes through a mixed-methods approach. Qualitative data, including interviews with procurement professionals and case studies of exemplary organizations, reveal diverse approaches to implementing supplier diversity—from formalized programs with dedicated resources to ad hoc initiatives driven by regulatory compliance or social responsibility goals. Challenges identified include the identification and qualification of diverse suppliers, scalability issues, and internal resistance within procurement teams. Quantitative analysis of survey data highlights positive impacts on organizational performance metrics, such as procurement spend allocation towards diverse suppliers, supplier-driven innovation, and enhanced supply chain resilience. Best practices in successful supplier diversity programs underscore strategic alignment with overall procurement strategies, effective supplier relationship management, and strong leadership commitment. Socio-economic impacts encompass economic inclusion, community engagement, and skills development among diverse supplier networks, contributing to local economic growth and broader social benefits. Despite these benefits, challenges remain in measuring qualitative outcomes and overcoming systemic barriers to implementation. Cultivating an inclusive organizational culture and leveraging leadership support are crucial for sustaining supplier diversity efforts. Continued collaboration and innovation in supplier diversity practices are recommended to maximize benefits and drive meaningful socio-economic impact globally.

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

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

This research aims to explore the adoption and impact of green supply chain practices (GSCP) on sustainable development in Bangladesh. The study seeks to understand the current state of GSCP adoption across various industries, identify key drivers and barriers, assess the perceived benefits and challenges, and evaluate the overall impact on environmental sustainability, economic performance, and social well-being. The research employs a qualitative approach, utilizing interviews with key stakeholders, document analysis, and literature review to gather data and insights. Interviews were conducted with representatives from government agencies, businesses, civil society organizations, and academia to obtain diverse perspectives on GSCP adoption and its implications for sustainable development in Bangladesh. The findings reveal a mixed scenario of GSCP adoption across different industries in Bangladesh, with sectors such as textiles leading the way. Key drivers of GSCP adoption include regulatory pressures, market forces, corporate social responsibility initiatives, and financial incentives. However, organizations face significant barriers such as high upfront costs, lack of awareness and expertise, regulatory uncertainty, and supply chain complexity. Despite these challenges, GSCP offer various benefits, including environmental sustainability, economic performance, and social well-being. Successful initiatives demonstrate tangible impacts, highlighting the potential of GSCP to contribute to sustainable development. The research is limited by its qualitative nature and focus on selected industries and stakeholders. Future studies could employ quantitative methods and broader sampling to provide a more comprehensive understanding of GSCP adoption and its implications in Bangladesh. The findings provide actionable insights for policymakers, industry leaders, and other stakeholders to promote GSCP adoption and enhance sustainable development in Bangladesh. Strategies for overcoming barriers and maximizing benefits are outlined, emphasizing the importance of collaboration and capacity-building initiatives. GSCP adoption can have positive social implications by promoting ethical labor practices, improving working conditions, and fostering community engagement. By prioritizing sustainability, businesses can contribute to social well-being and inclusive growth. This research contributes to the literature on GSCP adoption and sustainable development in Bangladesh by providing empirical insights and practical recommendations. The study adds to the understanding of the drivers, barriers, benefits, and challenges associated with GSCP adoption, highlighting the importance of integrating environmental, economic, and social considerations in supply chain management.

The integration of supply chain analytics and Customer Relationship Management (CRM) systems represents a critical strategy for organizations seeking to enhance operational efficiency and customer-centricity in today's competitive business environment. This qualitative study investigates the motivations, strategies, challenges, and outcomes associated with integrating supply chain analytics with CRM systems across diverse industries. Motivations for integration include gaining a unified view of customer data, improving decision-making capabilities, enhancing operational efficiency, and ensuring strategic alignment across organizational functions. Strategies employed by organizations include cross-functional collaboration, investment in scalable technology platforms, and leadership commitment to drive successful integration initiatives. Despite the potential benefits, the integration process presents challenges such as data integration complexities, technical interoperability issues, and organizational resistance to change. Addressing these challenges requires robust technological solutions, effective change management strategies, and a proactive approach to data governance and security. The study identifies significant outcomes from integration efforts, including improved operational efficiency through streamlined processes and optimized resource allocation, enhanced customer insights leading to personalized experiences, and strengthened strategic decision-making supported by real-time analytics.

This study explores the dynamic interplay between supply chain integration and marketing strategies in achieving customer satisfaction. Through a qualitative approach involving semi-structured interviews with supply chain and marketing professionals, the research delves into how these traditionally distinct functions can be aligned to enhance operational efficiency and deliver superior customer experiences. Findings reveal that strategic alignment between supply chain management (SCM) and marketing fosters better coordination of product availability and service delivery, thereby meeting customer expectations consistently and enhancing brand loyalty. Information sharing and technological integration emerge as critical enablers, facilitating real-time data exchange and collaborative decision-making. The study also identifies challenges such as organizational silos, cultural resistance, and technological constraints that impede seamless integration, highlighting the need for proactive strategies to foster cross-functional collaboration. Additionally, the evolving roles of sustainability and customer-centricity are emphasized as key drivers for differentiating brands and achieving competitive advantage. By integrating sustainable practices and adopting a customer-centric approach, organizations can build stronger customer relationships and enhance their market position. The research underscores the importance of leadership support, investment in technology, and a collaborative organizational culture in overcoming integration barriers. The study’s findings provide actionable insights for organizations aiming to optimize their SCM and marketing strategies, drive innovation, and sustain growth in an increasingly complex and competitive business environment. This research contributes to the growing body of knowledge on supply chain and marketing integration, offering practical recommendations for achieving customer satisfaction and long-term success.

This qualitative research investigates the role of collaborative planning in synchronizing supply chain and marketing activities among multinational companies (MNCs). Collaborative planning integrates traditionally separate functions to enhance operational efficiency, customer responsiveness, and strategic alignment. The study employs semi-structured interviews with key informants from diverse MNCs across industries and geographies to explore practices, challenges, and outcomes associated with collaborative planning initiatives. Findings highlight the pivotal role of cross-functional collaboration and advanced technologies, such as artificial intelligence and big data analytics, in improving demand forecasting accuracy, optimizing inventory management, and enabling personalized marketing strategies. Challenges include organizational resistance, cultural barriers, and the complexity of aligning global strategies. Strategic outcomes encompass improved operational efficiency, cost savings, enhanced customer satisfaction, and strengthened competitive advantage. Moreover, the integration of sustainability goals underscores the importance of environmental responsibility and regulatory compliance in collaborative planning frameworks. The study also identifies emerging trends in digital transformation and agile supply chains shaping future practices. Overall, collaborative planning emerges as a strategic imperative for MNCs to navigate complexities, capitalize on opportunities, and sustain growth in a globalized marketplace.

Aligning supply chain and marketing functions is crucial for high-tech startups aiming to successfully launch new products in competitive markets. This qualitative research explores the strategies, challenges, benefits, and best practices associated with supply chain and marketing alignment in high-tech startups. Through a detailed analysis of case studies and semi-structured interviews with industry professionals, the study identifies key insights into how startups can effectively integrate these functions to enhance operational efficiency, market responsiveness, customer satisfaction, and risk management. The findings reveal that successful alignment requires the formation of cross-functional teams, leveraging integrated technologies like CRM and ERP systems, establishing regular inter-departmental communication, and developing joint performance metrics. These strategies foster collaboration and ensure that supply chain and marketing efforts are coordinated towards shared goals. However, startups face challenges such as differing departmental objectives, resource constraints, communication barriers, and technological limitations, which hinder effective alignment. Benefits observed from effective alignment include improved operational efficiency through streamlined processes, enhanced market responsiveness to adapt quickly to changing demands, increased customer satisfaction by delivering products that meet market expectations, and better risk management through proactive identification and mitigation of supply chain and market risks. Best practices identified include fostering a culture of collaboration, investing in technology for data integration and transparency, aligning strategic objectives across functions, and continuously monitoring and adjusting alignment strategies. Integration of broader elements such as sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management further enriches the alignment framework. This study contributes to a deeper understanding of how high-tech startups can strategically align their supply chain and marketing functions to achieve competitive advantage and sustainable growth in dynamic market environments.

This study explores the impact of supply chain visibility (SCV) on marketing strategies within the fast-moving consumer goods (FMCG) industry. In a rapidly evolving market characterized by complex supply chains and dynamic consumer demands, SCV offers a transformative capability by providing real-time data and insights into supply chain operations. Through semi-structured interviews with industry practitioners, the research identifies several key themes: enhanced demand forecasting, increased consumer trust through transparency, improved marketing agility, and the integration of advanced technologies. Findings suggest that SCV significantly improves the accuracy of demand forecasts by providing timely insights into inventory levels, production schedules, and market conditions. This enhanced forecasting aligns supply chain capabilities with marketing efforts, reducing stockouts and optimizing promotional activities. Moreover, SCV fosters consumer trust by enabling transparency regarding product sourcing and ethical practices, which can be effectively communicated in marketing campaigns to build brand loyalty. The agility provided by SCV allows companies to quickly adjust their marketing strategies in response to market disruptions and shifts in consumer preferences, making their campaigns more resilient and responsive. Advanced technologies such as IoT, blockchain, and analytics further enhance the benefits of SCV, providing deeper insights and more sophisticated capabilities for marketing. The study also highlights the importance of cross-functional collaboration between supply chain and marketing teams in leveraging SCV data effectively. Despite challenges such as the need for significant investment and organizational change, the advantages of SCV in enhancing marketing strategies and overall organizational performance are substantial. The research underscores SCV's critical role in shaping effective marketing strategies, offering FMCG companies a path to greater efficiency, agility, and consumer engagement in a competitive landscape.

This study investigates green logistics strategies adopted by businesses to enhance sustainability within their supply chains, particularly focusing on reducing carbon footprints and environmental impacts associated with transportation and distribution activities. Through qualitative analysis and interviews with supply chain managers, industry experts, and sustainability officers, this research provides insights into motivations, strategies, challenges, and benefits related to green logistics practices. Key findings highlight the critical role of aligning green logistics with corporate sustainability goals. Advanced technologies such as telematics, GPS tracking, and data analytics are instrumental in optimizing transportation routes, reducing fuel consumption, and minimizing emissions. Additionally, strategies like using eco-friendly vehicles, energy-efficient warehouse operations, and implementing reverse logistics are identified as effective means to mitigate environmental impacts. Collaboration and partnerships with suppliers, logistics providers, and stakeholders are essential for sharing best practices and fostering joint initiatives. Despite benefits such as cost savings and enhanced corporate reputation, challenges include high initial investments, the absence of standardized metrics for environmental impact, and regulatory complexities. However, regulatory compliance also acts as a driver for green logistics adoption and presents opportunities for improving sustainability performance. The integration of sustainability goals with logistics strategies underscores the interdisciplinary nature of sustainable supply chain management. This holistic approach encompasses aspects of entrepreneurship, emotional intelligence, marketing, and supplier relationship management.

This qualitative study investigates the adoption of Lean Principles in Supply Chain Management (SCM), aiming to explore the motivations, challenges, and outcomes associated with Lean implementation across diverse organizational contexts. Through semi-structured interviews and thematic analysis, insights were gleaned from stakeholders involved in SCM processes, revealing the critical role of organizational culture, leadership commitment, and strategic alignment in driving successful Lean initiatives. The findings underscore the importance of fostering a culture of continuous improvement, where employees are empowered to proactively identify and address inefficiencies. Leadership emerged as pivotal in setting the tone, providing resources, and championing Lean initiatives, while strategic alignment ensured integration with broader organizational goals and objectives. Operational practices and processes were central, highlighting the need for customization and contextual adaptation in Lean implementation. Despite the potential benefits, the outcomes and impact of Lean adoption varied depending on factors such as organizational maturity and industry context. The study also revealed broader cultural and organizational changes catalyzed by Lean adoption, fostering innovation, collaboration, and adaptability. In summary, this study contributes to our understanding of Lean adoption in SCM, offering practical insights for organizations seeking to enhance efficiency and competitiveness in today's dynamic business landscape.

Ethical sourcing practices play a pivotal role in addressing price inflation within renewable energy supply chains. This qualitative research investigates the multifaceted impacts of ethical sourcing, drawing insights from interviews with key stakeholders in the renewable energy sector. The study reveals that ethical sourcing enhances supply chain transparency, traceability, and resilience by mitigating risks associated with unethical practices such as labor exploitation and environmental degradation. Fair trade initiatives contribute to economic stability and reduce price volatility by ensuring fair compensation for producers and workers, fostering long-term relationships, and reinvesting premiums into community development projects. Sustainable sourcing practices align with consumer preferences for eco-friendly products, reduce the demand for virgin resources, and promote regulatory compliance and incentives, thereby stabilizing costs and reducing environmental impact. Socially responsible companies that prioritize fair labor practices and community support experience fewer disruptions and benefit from a more stable and productive workforce. Entrepreneurship and emotional intelligence among leaders drive the adoption and successful implementation of ethical sourcing practices, enhancing brand reputation, consumer trust, and market competitiveness. Despite challenges, such as higher implementation costs and supplier resistance, the long-term benefits of ethical sourcing outweigh the initial costs and contribute to sustainable supply chains. Collaboration, consumer education, and effective regulation are essential for promoting ethical sourcing across the renewable energy sector.

China’s leading development of a complete battery value chain for Electric Vehicles (EV) is restructuring the global automotive sector. The competitive advantage of China's EV battery industry lies on its firms’ core competency and political economic geography. Based on first-hand empirical material and data obtained from years of fieldwork in an EV battery cluster in South China, this paper identifies what the Chinese EV battery industry’s core competency is and details how it is built up from below. The current core competency of Chinese battery firms is their mass manufacturing capability to supply lithium-ion batteries vehicle manufacturers (OEMs) with stable and consistent quality as well as competitive prices. This competency is acquired by firms through technological learning at workshop level while taking use of their experiences accumulated in mass production of batteries for consumer electronics sectors. Furthermore, the rapid learning and accumulation of knowledge on battery manufacturing at large scale is also facilitated by the industrial cluster environment where firms are embedded. Supported and promoted by local government policies, Chinese EV battery clusters are composed of firms from different segments of a complete battery value chain. The findings illuminate the likely strategic strengths, weaknesses, and futures of the Chinese EV battery industry in global competition.

Procurement plays a central and defining role in the efficiency of supply chains. In recent years, the understanding and practice of procurement management have changed significantly due to increasing emphasis on and demand for agility and sustainability within supply chain management systems. Meanwhile, traditional supply chain systems, characterized by siloed processes, limited visibility, and inefficiencies due to manual interventions, can no longer cope with the current dynamic market conditions. Besides, the increasing requirements of sustainability, ethical sourcing, and environmental impact have intensified, making more responsible, transparent, and traceable procurement practices unnegotiable requirements for modern systems. In this paper, we examine the potential of emerging technologies and innovations such as blockchain, artificial intelligence, and the Internet of Things (IoT) in filling these gaps within the supply chain systems of enterprises in the US. The study employs a comprehensive review of relevant literature and case studies to discover and provide insights on how these technologies can improve procurement processes, optimize resource allocation and utilization, and improve sustainability. The findings of this study highlight the need for stakeholders to embrace technological advancements to effectively navigate the dynamic landscape of supply chain management.

This study presents a systematic review of the impact of Industry 4.0, digitalization, and information systems on the procurement function with a focus on the Portuguese reality. Despite global trends emphasizing digital transformation and innovation, the procurement practices in Portugal seem to lag. The adoption of cutting-edge technologies and the comprehensive integration of digital solutions within the procurement and supply chain management sector are yet to materialize fully in the Portuguese SME context. The benefits and obstacles of these technologies in transitioning procurement into a more strategic role are analyzed. By examining existing literature, critical factors for organizations to consider when implementing these technologies and the potential benefits are identified. The results indicate that digitalization has resulted in a data-driven approach to procurement, with the aid of advanced analytics and artificial intelligence for decision-making. Industry 4.0 has facilitated smarter factories, warehouses, and logistics operations with a focus on automation, connectivity, and real-time data. Procurement can more efficiently manage suppliers, track contracts, identify cost-saving opportunities, and increase sustainability with the aid of information systems. The study also highlights potential challenges for organizations. Overall, this study provides insightful findings on the role of digitalization in transforming procurement and the challenges and opportunities that organizations may face.

The only cases where exact distributions of estimates are known is for samples from exponential families, and then only for special functions of the parameters. So statistical inference was traditionally based on the asymptotic normality of estimates. To improve on this we need the {\it Edgeworth expansion} for the distribution of the standardized estimate. This is an expansion in $n^{-1/2}$ about the normal distribution, where $n$ is typically the sample size. The 1st few terms of this expansion were originally given for the special case of a sample mean. In earlier work we derived it for {\it any } standard estimate, hugely expanding its application. We call an estimate $\hat{w}$ of an unknown vector $w\in R^p$, a {\it standard estimate}, if $E\ \hat{w}\rightarrow w$ as $n\rightarrow \infty$, and for $r\geq 1$ the $r$th order cumulants of $\hat{w}$ have magnitude $n^{1-r}$ and can be expanded in $n^{-1}.$ Here we give another huge extension. We give the expansion of the distribution of {\it any smooth function} of $\hat{w}$, say $t(\hat{w})\in R^q,$ giving its distribution to $n^{-5/2}$. We do this by showing that $t(\hat{w})$, is a standard estimate of $t(w)$. This provides far more accurate approximations for the distribution of $t(\hat{w})$ than its asymptotic normality. %NOT USED: The building blocks of the Edgeworth expansions are the {\it cumulant coefficients } of the estimate. These cumulant coefficients are also needed for bias reduction, Bayes estimates and confidence regions. We give {\it chain rules} for the cumulant coefficients of $t(\hat{w})$ in terms of those of $\hat{w}$ and the derivatives of $t(w)$, up to those needed for 5th order Edgeworth expansions for $t(\hat{w})$ and its {\it tilted expansion}, useful for the tail of the distribution.

The influence of polysialic acid (PSA) and sialic acid (SA) on the gut microbial community composition and metabolites in healthy human was investigated using a bionic gastrointestinal reactor. The results indicated that PSA and SA significantly changed the gut microbiota and metabolites in different degrees. PSA can increase the relative abundances of Faecalibacterium and Allisonella, whereas SA can increase those of Bifidobacterium and Megamonas. Both can significantly increase the content of short-chain fatty acids. The results of metabolome analysis showed that PSA can upregulate ergosterol peroxide and gallic acid and downregulate the harmful metabolite N-acetylputrescine. SA can upregulate 4-pyridoxic acid and lipoic acid. PSA and SA affect gut microbiota and metabolites in different ways and have positive effects on human health. These results will provide reference for the further development of PSA- and SA-related functional foods and health products.

Keywords: Green human resource management1; Green supply chain management2; Regulation and legislation3; Sustainable development goals4.

Malaria is rare in Europe, but it is a medical emergency and programs for its control should ensure access to early diagnosis and prompt treatment within 24-48 h of the symptom’s onset. The consistent number of imported malaria cases and the risk of reappearance of autochthonous cases stimulated laboratories in non-endemic countries to evaluate diagnostic methods/algorithms: microscopy remains the gold standard, but with limitations. RDTs have greatly expanded the ability to diagnose malaria for rapid results due to simplicity and low cost, but they lack sensitivity and specificity. PCR-based assays provide more relevant information but need well-trained technicians. According to WHO global Technical Strategy for Malaria 2016-2030, the future direction for a rapid diagnosis is the development of Point-Of-Care Testing, which would be helpful for prompt/accurate treatment and for preventing the diseases spread. Despite the limitations of current diagnostic methods, they play important roles in dealing with the global malaria situation, including decreasing its incidence. Recently evidence suggested that Artificial Intelligence could be utilized for assisting pathologists in malaria diagnosis. Future studies need to be conducted to see whether this system can be used for routine malaria diagnostic procedures.

The improvement of agricultural low-carbon efficiency is an important path to promote the realization of the "double carbon" goal in the Yellow River Basin. In the context of rapid urbanization development, it is of great significance to explore whether the promotion of urbanization will affect the agricultural low-carbon efficiency. Based on the panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this paper uses super-DEA model, three-dimensional kernel density model and Markov chain model to measure and analyze the spatio-temporal evolution of agricultural low-carbon efficiency in the Yellow River Basin, on this basis, the panel Tobit model is used to analyze the relationship between urbanization and low-carbon efficiency in agriculture. The results show that: (1) The level of agricultural low-carbon efficiency in the Yellow River Basin is low and has not reached the effective state, showing a slow downward trend in general, among which, the agricultural low-carbon efficiency in the lower reaches is higher than that in the middle reaches, and the upper reaches is the lowest. (2) The agricultural low-carbon efficiency in the Yellow River Basin has a negative trend of transferring to the low level on the whole, and tends to maintain the original state level, and it is difficult to realize the leapfrog transfer between states. Agricultural low-carbon efficiency has obvious spatial spillover effect and "club convergence" phenomenon, high efficiency area has a positive driving effect on the neighborhood area, while low efficiency area has a negative impact on the neighborhood area. (3) The level of urbanization has a significant positive impact on the low-carbon efficiency of agriculture in the upper, middle and lower reaches of the Yellow River Basin, which plays an important role in promoting the green development of agriculture. Finally, based on the above research conclusions, relevant policy recommendations were put forward, in order to provide references for promoting the improvement of low-carbon agricultural efficiency and promoting high-quality agricultural development in the Yellow River Basin.

Renewable jet fuel (RJF) production has been recognized as a promising approach for reducing the aviation sector's carbon footprint. Over the last decade, commercial production of RJF has piqued the interest of airlines and governments around the world. However, RJF production can be challenging due to its dispersed supply resources. Furthermore, the production of RJF is more costly compared to producing conventional jet fuel. In this study, using a mixed integer linear program (MILP), we design an RJF supply chain network in which we obtain an optimized configuration of the supply chain and determine operational decisions required to meet RJF demand at airports. To accelerate commercialization of RJF production, we considered four different monetary incentive programs, which could cover the supply chain’s costs. This study is validated by employing the model to design an RJF supply chain in the Midwestern US. Results from this study are promising as they show the supply chain can achieve commercialization with partial financial coverage from the incentive programs. Based on the findings of this study, policymakers can devise policies to commercialize RJF production and accelerate its adoption by industry.

Grain supply is the lifeblood of a country, and the stability of the supply chain is a crucial prerequisite for ensuring national grain security. This paper draws on the definition of resilience in physics and economics. It takes supply chain fracture resilience, impact resilience, and synergy resilience as the secondary indicators. It constructs a comprehensive evaluation indicator system of the grain supply chain resilience, measures the resilience indicator of China's grain supply chain from 1996 to 2021, and analyzes the role of supply, cost, exchange rate, and other external shocks in influencing the resilience of China's grain supply chain on this basis. The study found that the overall level of China's total grain supply chain resilience has been growing year by year and can be divided into three stages: low-level stabilization stage, continuous growth stage, and high-level stabilization stage. Grain supply chain fracture resilience has been growing steadily, grain supply chain impact resilience fluctuation is more obvious, and grain supply chain synergy resilience has been changing more gently. In the inquiry of the impact of external shocks on the resilience of China's grain supply chain, it was found that world grain exports and the RMB exchange rate have a significant positive impact on China's grain supply chain resilience level, while the international oil price has a significant negative impact. Based on this, the paper puts forward suggestions for ensuring stable production and supply in the grain market, improving the structure of foreign trade in grain, and actively coping with international commodity price shocks.

Allergies are a common and increasing health problem affecting millions of people worldwide. In addition to genetic predisposition, this increase in allergic cases is attributed to air pollution, climate change, more time spent indoors, lack of physical activity, and alterations in eating habits. The Mediterranean diet (MD), which includes a lot of fruits and vegetables, whole grains, legumes, nuts, olive oil and fish has been linked to a variety of health benefits, including a lower risk of chronic and allergic diseases. The purpose of this paper is to explore the effects of the dietary components of the MD on food allergies. Electronic databases PubMed, Scopus, Science Direct, and EBSCO were used to conduct this systematic review up to March 2023. 696 studies were initially identified and nine were included (five human and four animal studies). The findings of this review showed an overall beneficial effect between the food components of the MD and food allergies. Although the results are promising, the limited number of studies highlights the need for more research.

World health is increasingly threatened by the growing number of spice-related food hazards. Further development of reliable methods for rapid, non-targeted identification of counterfeit ingredients within the supply chain is needed. ENEA has developed a portable, user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser and multivariate calibration. Following a study on the authenticity of saffron, the instrument was challenged with a more elusive adulterant, olive leaves in oregano. The results show that the reported method of laser sensing and chemometric analysis was able to detect adulterants at mass ratios of at least 20% in less than five minutes.

Locust is a pest that attacks human and animal food and endangers national security by threatening food security. Spraying is the easiest and fastest way to deal with them. But the easiest way is not always the best way. With chemical resistance, not only will permanent immunity from locust attacks not arise, but they will also become resistant to poisons. While we have to pay billions of dollars annually for this strategy, we will also cause water and soil pollution. Therefore, the research results of other researchers were used and modeled to measure the possibility of hunting invasive locusts to investigate the possibility and benefits of this action. So, this study was conducted in the field method. The obtained results indicate that it is possible to hunt invasive locusts. If traps are placed on time and in the right place, the possibility of preserving crops after the pest attack increases by 2.3 times more in protected fields than in unprotected fields. By hunting locusts, fields and even pastures are preserved, poisons are prevented from entering the food chain and ecosystem, part of the economic loss of farmers affected by the invasion of locusts will be compensated, and by providing animal feed through hunting locusts, water consumption will be reduced, soil erosion and energy consumption are saved.

Nowadays, frameworks and models are critical to enabling organizations to identify their current sustainability integration into business and to follow up on these initiatives over time. In this context, the maturity models offer a structured way of analyzing how a supply chain meets specific sustainability requirements and which areas demand attention to reach maturity levels. This study proposes a five-level maturity model to help supply chains identify their level of engagement with sustainability practices combining three perspectives: intra and inter-organizational sustainability practices, triple-bottom-line approach and critical areas for sustainability. All the steps followed in constructing the maturity model were based on a literature review, and case studies supported its improvement, application, and testing. The proposed model presents many advantages, such as being used as a self-assessment tool, a roadmap for sustainability behaviour improvement, and a benchmarking tool to evaluate and compare standards and best practices among organizations and supply chains.

Urban growth in various cities across the world, especially in developing countries, leads to land use change. Thus, predicting future urban growth in the most rapidly growing region of Nigeria becomes a significant endeavor. This study analyzes land use and land cover (LULC) change and predicts the future urban growth of the Lagos metropolitan region, using Cellular Automata (CA) model. To achieve this, the GlobeLand30 datasets from years 2000 and 2010 were used to obtain LULC maps, which were utilized for modeling and prediction. Change analysis and prediction for LULC scenario for 2030 were performed using LCM and CA_Markov chain modeling. The results show a substantial growth of artificial surfaces, which will cause further reductions in cultivated land, grassland, shrubland, wetland, and waterbodies. There was no appreciable impact of change for bare land, as its initial extent of cover later disappeared completely. Additionally, artificial surfaces/urban growth in Lagos expanded to the neighboring towns and localities in Ogun State during the study period, and it is expected that such growth will be higher in 2030. Lastly, the study findings will be beneficial to urban planners and land use managers in making key decisions regarding urban growth and improved land use management in Nigeria.

Water resource is considered as a significant factor in development of regional environment and society. Water consumption prediction can provide important decision basis for the regional water supply scheduling optimisations. According to the periodicity and randomness nature of the daily water consumption data, a Markov modified autoregressive moving average (ARIMA) model is proposed in this study. The proposed model, combined with the Markov chain, can correct the prediction error, reduce the continuous superposition of prediction error, and improve the prediction accuracy of future daily water consumption data. The daily water consumption data of different monitoring points are used to verify the effectiveness of the model, and the future water consumption is predicted, in the study area. The results show that the proposed algorithm can effectively reduce the prediction error compared to the ARIMA.

The concentration of all-trans-retinoic acid, the bioactive derivative of vitamin A, is critically important for the optimal performance of numerous physiological processes. Either too little or too much of retinoic acid in developing or adult tissues is equally harmful. All-trans-retinoic acid is produced by the irreversible oxidation of all-trans-retinaldehyde. Thus, the concentration of retinaldehyde as the immediate precursor of retinoic acid has to be tightly controlled. However, the enzymes that produce all-trans-retinaldehyde for retinoic acid biosynthesis and the mechanisms responsible for the control of retinaldehyde levels have not yet been fully defined. The goal of this review is to summarize the current state of knowledge regarding the identities of physiologically relevant retinol dehydrogenases, their enzymatic properties and tissue distribution, and to discuss potential mechanisms for the regulation of the flux from retinol to retinaldehyde.

The out-of-equilibrium dynamics of many body systems has recently received a burst of interest, also due to experimental implementations. The dynamics of both observables, such as magnetization and susceptibilities, and quantum information related quantities, such as concurrence and entanglement entropy, have been investigated under different protocols bringing the system out of equilibrium. In this paper we focus on the entanglement entropy dynamics under a sinusoidal drive of the tranverse magnetic field in the 1D quantum Ising model. We find that the area and the volume law of the entanglement entropy coexist under periodic drive for an initial non-critical ground state. Furthermore, starting from a critical ground state, the entanglement entropy exhibits finite size scaling even under such a periodic drive. This critical-like behaviour of the out-of-equilibrium driven state can persist for arbitrarily long time, provided that the entanglement entropy is evaluated on increasingly subsytem sizes, whereas for smaller sizes a volume law holds. Finally, we give an interpretation of the simultaneous occurrence of critical and non-critical behaviour in terms of the propagation of Floquet quasi-particles.

Irish beef farms have experienced poor viability longitudinally, with officially acknowledged ‘crisis’ levels in 2013. In response, beef Producer Organisation (PO) legislation was introduced. Through the lens of international evidence in the literature about how POs function, this paper presents an analysis of Irish stakeholders’ views in the context of a public consultation process. While stakeholders indicate the need for individual POs to collaborate, little emphasis is placed on other factors necessary for success: collaboration with other chain actors; and market differentiation of products. Stakeholders identified primary threats as poor engagement on the part of both farmers and processors/purchasers.

The increased consumption of high fat-containing foods has been linked to the prevalence of obesity and abnormal metabolic syndromes. Rhizopus oligosporus, a fungus in the family Mucoraceae, is widely used as a starter for homemade tempeh. Although R. oligosporus can prevent the growth of other microorganisms, it grows well with lactic acid bacteria (LAB). Lactobacillus plantarum can produce β-glucosidase, which catalyzes the hydrolysis of glucoside isoflavones into aglycones (with greater bioavailability). Therefore, the development of a soybean-based functional food by the co-inoculation of R. oligosporus and L. plantarum is a promising approach to increase the bioactivity of tempeh. In this study, the ameliorative effect of L. plantarum in soy tempeh on abnormal carbohydrate metabolism in high-fat diet (HFD)-induced hyperglycemic rats was evaluated. The co-incubation of L. plantarum with R. oligosporus during soy tempeh fermentation reduced the homeostatic model assessment of insulin resistance, HbA1c, serum glucose, total cholesterol, triglyceride, free fatty acid, insulin, and low-density lipoprotein contents and significantly increased the high-density lipoprotein content in HFD rats. It also increased the LAB counts as well as the bile acid, cholesterol, triglyceride, and short-chain fatty acid contents in the feces of HFD rats. Our results suggested that the modulation of serum glucose and lipid levels by LAB occurs via alterations in the internal microbiota, leading to the inhibition of cholesterol synthesis and promotion of lipolysis. Tempeh, produced with both L. plantarum and R. oligosporus, may be a beneficial dietary supplement for individuals with abnormal carbohydrate metabolism.

Although the signaling function of Na/K ATPase is been studied for decades, the chasm between the pumping function and the signaling function of Na/K – ATPase is still an open issue. This article explores the relationship between ion pumping and signaling with attention to the amplification of oxidants through this signaling function. Starting with some experimental observations published by our laboratories and others, we develop some predictions regarding cellular oxidant stress.

This ethnographic study investigates the cross-cultural challenges encountered in global supply chains, focusing on communication barriers, diverse business practices, trust-building, ethical and legal standards, and cultural competence. By embedding within the day-to-day operations of multinational corporations and conducting in-depth interviews with supply chain professionals, the research provides a nuanced understanding of the cultural dynamics that impact global supply chain management. The findings highlight that effective communication goes beyond language proficiency, requiring an understanding of varying communication styles and contextual nuances. Business practices shaped by cultural values such as power distance and uncertainty avoidance necessitate adaptive management strategies that balance local norms with global standards. Trust and relationship-building are critical, particularly in cultures where personal relationships underpin business transactions, demanding long-term investment in relationship-building activities. Ethical and legal standards vary significantly across regions, presenting challenges that require a nuanced approach to global governance. The study underscores the importance of cultural competence as a critical skill for supply chain professionals, enabling them to bridge cultural gaps and foster productive collaborations. Sustainability efforts, entrepreneurship, and innovation are also influenced by cultural factors, highlighting the need for culturally sensitive strategies. Emotional intelligence is identified as essential for managing cross-cultural interactions, with participants demonstrating high emotional intelligence more effectively navigating the emotional and social complexities of cross-cultural communication. The use of technology in managing cross-cultural challenges is acknowledged, but the findings suggest that it must be complemented by cultural competence. Overall, the study provides valuable insights for companies seeking to enhance their cross-cultural effectiveness, emphasizing the importance of cultural competence, communication, and relationship-building in achieving sustainable success in global supply chains.

This research presents the Cross-Cultural Intelligent Language Learning System (CILS), a novel approach integrating Artificial Intelligence (AI) into language education to enhance cross-cultural communication. CILS utilizes advanced AI technologies to provide adaptive, personalized learning experiences that cater to the unique linguistic and cultural backgrounds of each learner. By dynamically adjusting content and methodology, CILS significantly improves linguistic proficiency and cultural understanding, essential for effective global interactions. The implementation of CILS in platforms such as Busuu and HelloTalk has demonstrated marked improvements in engagement and communication skills among learners. Empirical studies validate the system's effectiveness in real-world settings, showing enhanced learner performance and increased intercultural competence. Additionally, the Technology Acceptance Model (TAM) applied confirms that the usability and perceived usefulness of AI-driven systems strongly influence learner acceptance and sustained use. This study not only underscores the potential of AI in transforming language education but also highlights the critical role of cultural sensitivity in designing educational technologies.

Accurately glacier mapping is crucial for understanding climate change impacts, but existing efforts may be biased due to overlooking spatial autocorrelation during map validation. To address this, we compared several widely used machine learning algorithms as gradient boosting machines (GBM), k-nearest neighbor (KNN) and random forest (RF) with parametric logistic regression (GLM) and an unsupervised remote sensing-based method (NDSI) for mapping Peru's glacier regions in a thoughtful experimental setup. Spatial and non-spatial cross-validation methods were used to evaluate model’s performance and compared with a fully independent test set. Performance differences of up to 18% were found between bias-reduced (spatial) and overoptimistic (non-spatial) cross-validation results when compared to independent test set, emphasizing the need to consider spatial autocorrelation when using machine learning for glacier mapping. K-nearest neighbors (KNN) was the overall best model across regions consistently demonstrating the highest performance followed by logistic regression (LR) and gradient boosting machines (GBM). Our novel validation approach, accounting for spatial characteristics, provides valuable insights for glacier mapping studies and future efforts on glacier retreat monitoring. Incorporating this approach improves the reliability of glacier mapping, guiding future national-level initiatives.

The nonlocality (superdiffusion) of turbulence is expressed in the empiric Richardson t3 scaling law for the mean square of the mutual separation of a pair of particles in a fluid or gaseous medium. The development of the theory of nonlocality of various processes in physics and other sciences based on the concept of Lévy flights resulted in the idea of Shlesinger and colleagues about the possibility of describing the nonlocality of turbulence using a linear integro-differential equation with a slowly falling kernel. The close approach developed by us made it possible to establish the closeness of the superdiffusion parameter of plasma density fluctuations moving across a strong magnetic field in a tokamak to the Richardson law. In this paper, we show the possibility of a universal description of the characteristics of nonlocality of transfer in a stochastic medium (including turbulence of gases and fluids) using the Biberman-Holstein approach to the transfer of excitation of a medium by photons, generalized to take into account the finiteness of the velocity of excitation carriers. This approach enables us to propose a scaling that generalizes Richardson's t3 scaling law to the combined regime of Lévy flights and Lévy walks.

Background: Frail elderly patients are exposed to suffering the consequences of heart diseases that are not managed timely such as receiving anticoagulation to prevent stroke associated to atrial fibrillation (AF). Referral to the cardiological outpatient department can be cumbersome as it often requires repeated visits. The aim of this project was to use AF as a showcase to develop and implement CardioShare, a shared-care model where primary care leads patient management, using an easy-to-use compact Holter monitor device with asynchronous remote support from cardiologists. Methods: This complex intervention has been developed during a feasibility phase, tested in a pragmatic cluster-randomization trial (primary care clinic as clusters) and its implementation potential evaluated with an escalation test. Mixed methods were used to evaluate the impact of the intervention, comprising quantitative observations, semi-structured interviews, and workshops. Results: Between February 2020 and December 2021, 314 patients (30% frail) were included of whom 75% had AF diagnosed/not found within 13 days. More than 80% in both groups avoided referral to cardiologists. Patients felt safe and primary care clinicians satisfied. In the escalation test, 58 primary-care doctors used CardioShare to manage 93 patients over three months with remote support from four hospitals in the Capital Region of Denmark. Conclusions: CardioShare was successfully implemented for AF evaluation in primary care.

At the highest level of endurance sports, the differences in finishing times are small, so equipment is constantly being constantly improved to enhance the athletes' performance. For instance, one dominant resistive force in connection with cross-country skiing is the friction between the skis and snow and since the 1930s, research designed to understand and reduce this friction has been ongoing. The mechanisms involved in ski-snow friction include compaction, micro-ploughing, adhesion, viscosity, and water-bridging. Of these, adhesive and viscous friction have been most studied, while much less is presently known about compaction, micro-ploughing, and water-bridging. At the macro-scale, the ski-camber profile plays a key role in determining whether, with respect to friction, a particular cross-country ski is suitable for use under a given set of conditions. Through its influence on where ski-snow contact occurs, this ski-camber profile has a profound impact on adhesive and viscous friction, micro-ploughing, the formation of water bridges, and the rate of compaction. Different contact zones with different apparent areas of contact and pressure have been found to be most suitable for different conditions. In addition, the micro-scale texture of the ski base is also an important determinant of ski-snow friction. Topographical measurements of this texture can be achieved with white-light interferometer and recent characterisation has focused on the mechanical properties of contact. In numerous tribological studies the interactions between features at different scales are modelled. In most tribological systems, features on several scales influence friction and ski-snow contact is certainly no exception. Accordingly, the current investigation was designed to evaluate the multi-scale properties of different combinations of two skis with two different base textures. The real area of contact and the average interfacial separation and total average reciprocal interfacial separation between the ski and snow were taken into consideration. We found that different macro- and micro-scale properties of the ski favour different mechanisms of friction. Both the profile of the ski camber and texture of the base play decisive roles in determining viscous friction. At the same time, the texture of the ski base exerts a greater impact on the average real contact pressure, real contact area and minimal average interfacial separation between the ski and snow than does the ski-camber profile.

Coronavirus disease (COVID-19) has had devastating impacts on the global economy and public health. This study aimed to assess the level of COVID-19 vaccine acceptance, hesitancy, and associated factors among staff and students of the Federal University of Health Sciences Otukpo, Benue State, Nigeria. A web-based cross-sectional survey was conducted between November 2021 and April 2022, and data were collected and analyzed using descriptive and inferential statistics. Of the 150 completed and analyzed questionnaires, the majority of respondents (80.0%) were between 16 and 45 years old. The study found that 58.4% of participants indicated vaccine hesitancy, with skepticism about the vaccine's fast production/rollout and fear of vaccine side effects being the most common reasons for hesitation. Respondents' age, religion, and category were significant factors influencing vaccine acceptance and hesitancy (P < 0.05). The university community has a high level of awareness of COVID-19 but low vaccine acceptance, resulting in high levels of vaccine hesitancy. The study recommends that policymakers and public health officials should prioritize testing and vaccination for job categories with higher risk of exposure to COVID-19. They should provide accurate information about COVID-19 testing and vaccination and implement workplace-based testing and vaccination programs. These interventions can help to increase COVID-19 testing and vaccination uptake among the university community and mitigate the spread of COVID-19.

Acute kidney injury (AKI) is a complication that can occur after cardiac surgery and requires ongoing research in light of the exponential expansion of technological advancements and knowledge in medicine. In this study, we aim to evaluate the outcomes of treated electives of emergency aortic disease with high serum creatinine levels (SCr). Methods: The cohort includes 183 patients, all of whom have an aortic disease and whose SCr levels were checked upon admission on the first day in the intensive care unit (ICU) and upon discharge from the hospital. We examined the correlation of SCr levels with in-hospital mortality and immediate mortality at least six months after discharge as well as with cross-clamp time and bypass time.Results: A high SCr level upon admission is a significant predictive factor of n-hospital mortality (p = 0.001) but not immediate mortality (p = 0.409). A statistically significant correlation was also observed between elevated SCr level on the first day of ICU and aortic disease (p = 0.041) but not immediate mortality (p = 0.119). We observed a significant correlation between aortic disease and in-hospital mortality (p < 0.001), but no correlation was found between high SCr level on the first day of ICU and immediate mortality (p = 0.119). The cross-clamp time is statistically significant correlated with elevated SCr level (p = 0.013) and in-hospital mortality (p = 0.001) but not immediate mortality (p = 0.847). Furthermore, the bypass time is negatively correlated with a high SCr level on the first day of ICU (p = 0.090), in-hospital mortality (p = 0.410), and immediate mortality (p = 0.625). We also found that aortic disease is not correlated with elevated creatinine levels at ICU discharge (p = 0.152) or long-term mortality (p = 0.106). Conclusions: Although this study only included a small portion of the elaborate aspects of surgical and medical management developed around cardiac patients who received invasive treatment, the conclusions reached are nevertheless clearly relevant, as evidenced by the significantly correlations uncovered. In order to manage AKI after AAS and improve the outcome, the SCr level could be used as a marker for renoprotective strategy. Moving forward, these results serve as a first step in motivating us to expand the range of our research, collect newly relevant data, and use it to benefit patients.

Most pathogens are capable of infecting multiple host species and such cross-species transmission (CST) can have dramatic consequences, as highlighted by recent disease emergence events affecting human, animal and plant health. Understanding the ecological and evolutionary factors that constrain or facilitate the ability of disease agents to infect and establish in a novel host is therefore a timely and important research area. Previous work across different pathogens, including rabies virus (RABV), found that increased evolutionary distance between hosts reduces the frequency of cross-species transmission and of permanent host shifts. However, whether this effect of host relatedness still holds for transmission among recently diverged hosts, and the importance of this effect relative to other predictors, is not well understood. We addressed this question by quantifying the CST frequency of RABV between North American bat species within the genus Myotis, using a multi-decade data set containing 128 nucleoprotein (N) sequences from ten host species. For comparison, we also conducted an equivalent analysis of a RABV dataset from North American bat species comprising nine genera. We found that at the within genus scale, host relatedness failed to explain the frequency of CST events. However, CST frequency increased with overlap in species’ host range. Moreover, we found evidence of CST occurring among a higher proportion of species, and CST more frequently resulting in sustained transmission in the novel host in the Myotis dataset compared to the multi-genus dataset. Our results suggest that among recently diverged species, the ability to infect a novel host is no longer restricted by physiological barriers but instead is limited by physical contact. Our results improve predictions of where future CST events for RABV might occur and clarify the relationship between host divergence and pathogen emergence.

Delayed diagnosis and a lack of adequate care for people with autism spectrum disorder (ASD) are related to worse outcomes and quality of life. This study aimed to identify the profile of service use, barriers to access care, and factors related to those barriers in Brazilian families with children with ASD. A total of 927 families with ASD children (3-17 years) from five Brazilian regions completed an online version of the Caregivers Needs Survey. Results showed that the most used services were behavioral interventions and pharmacotherapy, while the most used professionals were neurologists, nutritionists, speech therapists, psychiatrists, psychologists, and pediatricians. The main barriers included waiting lists, costs, and the absence of services or treatment. Service use varied according to age, the region of residence, the type of health care system used, and the parents/caregivers' education. Access to behavioral interventions was more frequent among users of the private system/health insurance and families whose caregivers had higher education. The absence of specialized services/treatments was less frequent among residents of state capitals and families whose caregivers had higher levels of education. This study highlights how families with children/adolescents with ASD in Brazil face significant barriers to access care related to sociodemographic factors.

Software reliability is an important characteristic for ensuring the qualities of software products. Predicting the potential number of bugs from the beginning of a development project allows practitioners to make the appropriate decisions regarding testing activities. In the initial development phases, applying traditional software reliability growth models (SRGMs) with limited past data does not always provide reliable prediction result for decision making. To overcome this, herein we propose a new software reliability modeling method called deep cross-project software reliability growth model (DC-SRGM). DC-SRGM is a cross-project prediction method that uses features of previous projects’ data through project similarity. Specifically, the proposed method applies cluster-based project selection for training data source and modeling by a deep learning method. Experiments involving 15 real datasets from a company and 11 open source software datasets show that DC-SRGM can more precisely describe the reliability of ongoing development projects than existing traditional SRGMs and the LSTM model.

In this paper a new approximate procedure is developed for calculating the inclination angle of the end points of statically determinate beams. The method is based on the topology comparison of simple (hinge-roller combination) supported beam and a resemblant cantilever beam. Assuming that the support reactions of the beam are active forces, the virtual displacements at the points of the reaction forces are calculated. Based on these values the inclination angle is calculated. Several examples are considered and the suggested in this paper, while the procedure is applied for various types of structures and loadings. The results, obtained by the suggested numerical procedure, are compared with analytical ones, and they are in good agreement.

Naive CD4+ T cells engage cognate peptide MHC-II complexes (pMHC-IIs) to differentiate and acquire one of several T helper (Th) fates whose specific trajectories are guided by a dynamic cytokine milieu that develops in response to antigenic entity. This physiological process is often erroneously conflated with a pathological one termed Th polarization. Using the SPIRAL model, we argue here that unlike Th fate choice, innate signaling alone is insufficient to initiate Th polarization in naive CD4+ T cells, that it instead develops from pre-existing memory CD4+ T cells that express cross-reactive TCRs, and that it inevitably leads to immunopathology.

To reduce the risk of infection of SARS-CoV-2 during the commute to the clinic or due to the contact with medical staff, The American College of Obstetricians and Gynecologists recommended ar-ranging part of the appointments in the form of “telehealth”. The aim of the study was to assess the access to medical care in pregnancy during the Sars-Cov-2 pandemic and the role of telehealth in implementation of prenatal care standards. This is a cross-sectional study. The study group in-cluded 618 women that were pregnant and or gave birth during the COVID-19 pandemic in Poland. The majority of participants experienced difficulties in access to medical care because of the pandemic. Correlation between this experience and the use of hybrid healthcare model was es-tablished. However, affiliation to public or private healthcare group was irrelevant. There was no relationship between healthcare (private/public or in-person/hybrid) and implementation of the prenatal care standards. To ensure safe access to prenatal care for pregnant women, recommen-dations for a hybrid pregnancy management model should be created with detailed information for which appointments patients must be present and which can be done remotely. To reduce movement risk and interpersonal contact, all visits during which tests and screenings take place should be done in-person. Other appointments can be arranged in the form of telehealth

The part transportation efficiency is a main factor of aircraft sortie generation rate. Part transportation is used to transport spare part from base to carrier. Transportation strategy depends on both demand on carrier and inventory in transportation base. The transportation time and stochastic demand will induce fluctuations of cost and inventory. Thus, a Takagi-Sugeno fuzzy system of dynamic part transportation is established considering transportation time and stochastic demand. And a novel Takagi-Sugeno fuzzy robust control is designed for dynamic part transportation, which will keep transportation cost and part inventory stable. First of all, a fuzzy model with stochastic demand and transportation time is proposed. Then, a novel robust control with cross rule groups is conducted according to production and transportation strategy, which will reduce fluctuations induced by strategies switch. Moreover, robust stability is guaranteed and part can be supplied in time under a low cost. Finally, simulation illustrates usefulness and quickness of the novel Takagi-Sugeno fuzzy robust control. Besides, the proposed method will be useful in other transportation electrification systems with delay time and uncertainty.

We report cross-shore profile evolution at Palanga, eastern Baltic Sea where short period waves dominate. Cross-shore profile studies began directly after a significant coastal erosion caused by storm “Anatoly” in December of 1999 and continued for a year. Further measurements were undertaken sixteen years later. Cross-shore profile ∆V(x) changes were described, and cross-shore transport rates Q(x) were calculated. A K-means clustering technique was applied to determine sections of the profile with the same development tendencies. Profile evolution was strongly influenced by the depth of closure which is constrained by a moraine layer and the presence of a groyne. The method used divided the profile into four clusters: the 1st cluster in the deepest water represents profile evolution limited by the depth of closure, and the 2nd and 3rd mostly are affected by processes induced by wind, wave and sea-water level changes. The most intensive sediment volume changes were observed directly after the coastal erosion. The largest sand accumulation was in the 4th profile cluster, which includes the upper beach and dunes. Seaward extension of the dune system caused a narrowing of the visible beach which has led to an increased sand volume (accretion) being misinterpreted as erosion

Background: The methods used in low- and middle-income countries (LMICs) household surveys have not changed in four decades; however, LMIC societies have changed substantially and now face unprecedented rates of urbanisation and urbanisation of poverty. This mismatch may result in unintentional exclusion of vulnerable and mobile urban populations. We compare three survey method innovations with standard survey methods in Kathmandu, Dhaka, and Hanoi, and summarize feasibility of our innovative methods in terms of time, cost, skill requirements, and experiences. Methods: We used descriptive statistics and regression techniques to compare respondent characteristics in samples drawn with innovative versus standard survey designs and household definitions, adjusting for sample probability weights and clustering. Feasibility of innovative methods was evaluated using a thematic framework analysis of focus group discussions with survey field staff, and via survey planner budgets. Results: We found that a common household definition excluded single adult (46.9%) and migrant headed households (6.7%), as well as non-married (8.5%), unemployed (10.5%), disabled (9.3%), and studying adults (14.3%). Further, standard two-stage sampling resulted in fewer single adult and non-family households than an innovative area-microcensus design; however, two-stage sampling resulted in more tent and shack dwellers. Our survey innovations provided good value for money and field staff experiences were neutral or positive. Staff recommended streamlining field tools and pairing technical and survey content experts during fieldwork. Conclusions: This evidence of exclusion of vulnerable and mobile urban populations in LMIC household surveys is deeply concerning, and underscores the need to modernize survey methods and practices.

HDPE (high-density polyethene) plastic waste is stronger, harder, and more resistant to high temperatures than other plastics. Using it as an additive in a concrete mixture is one solution to reduce this type of waste. We examined how HDPE-type plastics can be used as an additive material in the manufacture of concrete to improve its hardness, tensile strength and compressive strength. Using 156 samples, we aimed to identify the effect of HDPE plastic fibres on concrete of three qualities; B0, f'c10 MPa (low quality), and f'c25 MPa (medium and high quality). We added four compositions (2.5%, 5%, 10% and 20% by weight of cement) of HDPE plastic fibre to each quality of cement, with HDPE plastic fibre sizes of 1 x 1 cm, 0.5 x 2 cm or 0.25 x 4 cm. We found that the addition of 5% HDPE plastic fibre with a 0.5 x 2 cm cross-sectional shape to the f'c10 MPa concrete gives the best result, with increased tensile and compressive strength of the concrete.

Global severity maps of ongoing dengue epidemic and COVID-19 pandemic do not overlap. Countries with high dengue endemicity (>1.5 million cases/year) are observably less hit by COVID-19 in terms of infection, transmission and mortality. Based on non-overlap of dengue and COVID-19 severity maps and evidence of SARS-CoV-2 serological cross-reactions with dengue, we wonder whether immediate immunization of susceptible populations in Europe, North America and Asia (China, Iran) with available live-attenuated dengue vaccines, will cue the anti-viral immune response to thwart COVID-19 (viral interference). Risk of developing post-vaccination “Antibody-dependent Enhancement” is low as dengue is not endemic in the aforesaid regions.

Façade elements are a building component that satisfies multiple performance parameters. Among other things, “advanced façades” take advantage of hybrid solutions, such as assembling laminated materials. In addition to the enhanced mechanical properties that are typical of optimally composed hybrid structural components, these systems are energy-efficient, durable, and offer lighting comfort and optimal thermal performance, an example of which is the structural solution developed in collaboration with the University of Zagreb and the University of Ljubljana within the Croatian Science Foundation VETROLIGNUM project. The design concept involves the mechanical interaction of timber and glass load-bearing members without sealing or bonding the glass-to-timber surfaces. Following earlier research efforts devoted to the structural analysis and optimization of thus-assembled hybrid Cross-Laminated Timber (CLT)-glass façade elements, in this paper, special focus is given to a thermal and energy performance investigation under ordinary operational conditions. A simplified numerical model representative of a full-size building is first presented by taking advantage of continuous ambient records from a Live-Lab mock-up facility in Zagreb. Afterwards, a more detailed Finite Element (FE) numerical analysis is carried out at the component level to further explore the potential of CLT–glass façade elements. The collected numerical results show that CLT–glass composite panels can offer stable and promising thermal performance for façades similar to national and European standard requirements.

Facade elements are known to represent a building component with multiple performance parameters to satisfy. Among others, “advanced facades” take advantage of hybrid solutions, like the assemblage of laminated materials. In addition to enhanced mechanical properties that are typical of optimally composed hybrid structural components, these systems are energy-efficient, durable, and offer lightening comfort and optimal thermal performance. This is the case of the structural solution developed in joint research efforts of the University of Zagreb and the University of Ljubljana, within the Croatian Science Foundation VETROLIGNUM project. The design concept involves the mechanical interaction of timber and glass load-bearing members, without sealing or bonded glass-to-timber surfaces. Laminated glass infilled timber frames are recognized as a new generation of structural members with relevant load-carrying capacity (and especially the enhancement of earthquake resistance of framed systems), but also energy-efficient and cost-effective solutions.

This is a theoretical and empirical article. In the first part, an original definition of the cross-border market for cultural services has been developed, based on classic market definitions. The structure and conditions of functioning for this market have also been presented. The next part of the article discusses the supply side of the cross-border market of cultural services for the two twin towns: Cieszyn (Poland) and Český Těšín (Czech Republic). Next, based on the surveys conducted, the participation of residents of both towns in the most important cultural events organised by cultural institutions on both sides of the border was examined.

Limited observational studies have described the relationship between sleep duration and overall diet. The present study investigated the association between sleep duration at weekdays and empirically derived dietary patterns in a nationally representative sample of UK adults, aged 19-64 years old, participating in the 2008-2012 UK National Diet and Nutrition Survey Rolling Programme. Survey members completed between three to four days of dietary records. Sleep duration at weekdays was categorised into tertiles to reflect short, normal and long sleep duration. Social jetlag was calculated as the difference between sleep duration at weekends and weekdays. The association between sleep duration/ social jetlag and dietary patterns, derived by principal components analysis, was assessed regressing diet on sleep whilst accounting for the complex survey design and adjusting for relevant confounders. Survey members in the highest tertile of sleep duration had on average 0.45 (95% CI -0.78, -0.12) lower healthy dietary pattern score compared to middle tertile (p =0.007). There was an inverted u-shaped association between social jetlag and a healthy dietary pattern, such that when sleep at weekends exceeded weekday sleep by 1h 45min, scores for indicating a healthy dietary pattern declined (p =0.005). In conclusion, long sleep duration at weekdays and an increased social jetlag are associated with a lower healthy dietary pattern score. Further research is required to address factors influencing dietary patterns in long sleepers.

This work explores the use of Kuhn verdazyl radicals as building blocks in multifunctional molecular materials in an exemplary study, focusing on the magnetic and the electron transfer (ET) characteristics, but also addressing the question whether chemical modification by cross-coupling is possible. The ET in solution is studied spectroscopically whereas solid state measurements afford information about the magnetic susceptibility or the conductivity of the given samples. The observed results are rationalized based on the chemical structures of the molecules, which have been obtained by X-ray crystallography. The crystallographically observed molecular structures as well as the interpretation based on the spectroscopic and physical measurements are backed up by DFT calculations. The measurements indicate that only weak, antiferromagnetic coupling is observed in Kuhn verdazyls owed to the low tendency to form face-to-face stacks, but also that steric reasons alone are not sufficient to explain this behavior. Furthermore, it is also demonstrated that ET reactions proceed rapidly in verdazyls/verdazylium redox couples and that Kuhn verdazyls are suited as donor molecules in ET reactions.

Single valued neutrosophic set has king power to express uncertainty characterized by indeterminacy, inconsistency and incompleteness. Most of the existing single valued neutrosophic cross entropy bears an asymmetrical behavior and produce an undefined phenomenon in some situations. In order to deal with these disadvantages, we propose a new cross entropy measure under single valued neutrosophic set (SVNS) environment namely SN- cross entropy and prove its basic properties. Also we define weighted SN-cross entropy measure and investigate its basic properties. We develop a new multi attribute group decision making (MAGDM) strategy for ranking of the alternatives based on the proposed weighted SN-cross entropy measure between each alternative and the ideal alternative. Finally, a numerical example of MAGDM problem of investment potential is solved to show the validity and efficiency of proposed decision making strategy. We also present comparative anslysis of the obtained result with the results obtained form the existing solution strategies in the solution.

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 the complexities of managing suppliers for quality among Italian restaurant owners, investigating their perspectives, challenges, and strategic approaches in supplier management. Through semi-structured interviews with 15 restaurant owners across diverse regions of Italy, key themes emerged regarding supplier selection criteria, challenges in supplier management, strategies for ensuring quality, and the impact of external factors on supply chain dynamics. Findings reveal that authenticity, reliability, and sustainability are paramount in supplier selection, aligning with consumer expectations for genuine Italian ingredients and culinary excellence. Economic pressures, operational disruptions, and external influences, exacerbated by events like the COVID-19 pandemic, necessitate adaptive strategies such as cost-effective sourcing, rigorous quality control measures, and technological integration to maintain supply chain continuity and uphold quality standards. Strategic initiatives, including rigorous quality assurance protocols, digital procurement platforms, and collaborative partnerships with suppliers, enhance transparency, efficiency, and responsiveness in supply chain operations. Entrepreneurial initiatives and emotional intelligence play crucial roles in fostering innovative sourcing strategies and building trust-based relationships with suppliers, enhancing supply chain resilience and responsiveness to market demands. External factors, such as market dynamics and sustainability trends, underscore the need for continuous adaptation and strategic foresight in supplier management practices. The study contributes to understanding the intricate dynamics of supplier management in Italian cuisine, offering insights for enhancing operational efficiency, maintaining quality standards, and fostering sustainable supplier relationships in the food service industry.

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.

This study investigates the adoption of emerging technologies in procurement within supply chain management, focusing on the transformative potential of artificial intelligence (AI) and blockchain. Through a qualitative approach, involving semi-structured interviews with procurement professionals and technology experts, the study explores how these technologies enhance operational efficiency, optimize inventory management, and improve supply chain transparency and trust. AI-driven predictive analytics were found to significantly enhance demand forecasting, inventory optimization, and supplier performance evaluation, fostering data-driven decision-making and proactive risk management. Blockchain technology ensures secure and transparent transactions, facilitating compliance with ethical sourcing standards and reducing risks associated with counterfeit goods. Despite these benefits, organizations face substantial challenges in adopting these technologies, including data security concerns, integration complexities with existing IT infrastructure, and skills shortages in AI and blockchain expertise. Leadership commitment and organizational readiness are identified as crucial enablers for overcoming these barriers and driving successful technology adoption. The study also highlights the strategic importance of supplier relationship management, emphasizing how emerging technologies enhance real-time collaboration, performance insights, and contractual transparency. By addressing these challenges and leveraging technological innovations strategically, organizations can achieve sustainable growth, resilience, and competitive advantage in an increasingly digital and interconnected global economy. The findings contribute to advancing knowledge on procurement innovation and offer valuable insights for organizations seeking to navigate the complexities of technology-driven procurement practices. Future research directions may explore the long-term impact of technology adoption on supply chain dynamics, sustainability initiatives, and organizational performance.

This qualitative study explores the role of supply chain partnerships in enhancing brand value through collaborative marketing efforts. By analyzing diverse cases from industries including consumer electronics, apparel, automotive, and food and beverage, the research examines how different forms of partnerships—strategic alliances, co-marketing, joint ventures, and supplier integrations—contribute to brand value. The study employed a multiple case study design, incorporating semi-structured interviews, document analysis, and participant observations to gather data. The findings reveal that these partnerships enable companies to leverage complementary strengths, resulting in enhanced innovation, product quality, sustainability, market reach, and ethical standards. Collaborative marketing strategies such as joint product launches, sustainable branding campaigns, and co-developed customer programs are identified as key drivers of brand value, effectively increasing brand awareness, customer loyalty, market share, and perceived quality. Despite challenges like coordination complexity, goal misalignment, cultural differences, and cost management issues, the benefits realized—such as improved brand image, faster time-to-market, and reduced costs—demonstrate the substantial value of effective supply chain partnerships. The study underscores the importance of strategic alignment between supply chain activities and brand objectives, highlighting that successful partnerships foster deeper consumer engagement and stronger market positions. This research provides actionable insights for companies seeking to optimize their supply chain collaborations to enhance brand value, offering a foundation for future studies and practical applications in supply chain management and marketing. The findings contribute to a deeper understanding of how supply chain partnerships can be strategically managed to drive brand excellence in a competitive market environment.

The integration of supply chain data analytics with marketing strategies has become increasingly critical for organizations seeking to enhance customer insights and competitive advantage in today's dynamic business environment. This qualitative research explores the intersection of these two disciplines, focusing on implementation strategies, benefits, challenges, and future directions. Through semi-structured interviews with industry experts and stakeholders, key themes emerged, highlighting the importance of cross-functional collaboration, technological integration, and robust data governance in achieving effective integration. The study identifies significant benefits, including enhanced customer insights, improved operational efficiencies, and competitive advantage through personalized marketing strategies and optimized supply chain management. However, challenges such as data silos, technological complexities, and regulatory compliance issues pose barriers that require strategic solutions and organizational commitment. Future directions point towards the continued evolution of predictive analytics, AI-driven solutions, and sustainability integration, shaping the future landscape of supply chain management and marketing. Proactive engagement with regulatory frameworks and ethical considerations will be crucial in navigating these challenges and building trust with consumers. Ultimately, this research contributes to a deeper understanding of how organizations can leverage data analytics to drive strategic decision-making, enhance customer relationships, and achieve sustainable growth in an increasingly data-driven economy.

This qualitative research explores the intricate relationship between cultural influences on supply chain practices and their implications for marketing strategies. Cultural dimensions such as individualism versus collectivism, uncertainty avoidance, and contextuality significantly shape decision-making processes, risk management strategies, and relationship dynamics within global supply chains. Through semi-structured interviews with supply chain managers, marketing executives, and cultural experts across diverse industries and regions, this study investigates how cultural values impact supply chain operations and consumer engagement strategies. Key findings highlight that collectivist cultures prioritize consensus-building and long-term relationships, fostering trust and collaboration among supply chain partners. In contrast, individualist cultures emphasize efficiency and accountability but may face challenges in relationship building. Risk management practices vary with cultural orientations towards uncertainty, influencing the adoption of structured versus flexible approaches to mitigate disruptions. In terms of marketing implications, the study underscores the importance of cultural sensitivity in crafting effective strategies. High-context cultures require marketing messages that resonate emotionally through implicit communication and cultural symbolism, while low-context cultures prefer clear, direct messaging focusing on product benefits. The study concludes by advocating for cultural competence as a strategic imperative for global businesses, enabling them to leverage cultural diversity for innovation and competitive advantage. It emphasizes the need for continuous adaptation to cultural nuances and market dynamics to foster inclusive collaboration and achieve sustainable growth in a globalized economy.

This qualitative research explores the intricate relationship between cultural influences on supply chain practices and their implications for marketing strategies. Cultural dimensions such as individualism versus collectivism, uncertainty avoidance, and contextuality significantly shape decision-making processes, risk management strategies, and relationship dynamics within global supply chains. Through semi-structured interviews with supply chain managers, marketing executives, and cultural experts across diverse industries and regions, this study investigates how cultural values impact supply chain operations and consumer engagement strategies. Key findings highlight that collectivist cultures prioritize consensus-building and long-term relationships, fostering trust and collaboration among supply chain partners. In contrast, individualist cultures emphasize efficiency and accountability but may face challenges in relationship building. Risk management practices vary with cultural orientations towards uncertainty, influencing the adoption of structured versus flexible approaches to mitigate disruptions. In terms of marketing implications, the study underscores the importance of cultural sensitivity in crafting effective strategies. High-context cultures require marketing messages that resonate emotionally through implicit communication and cultural symbolism, while low-context cultures prefer clear, direct messaging focusing on product benefits. The study concludes by advocating for cultural competence as a strategic imperative for global businesses, enabling them to leverage cultural diversity for innovation and competitive advantage. It emphasizes the need for continuous adaptation to cultural nuances and market dynamics to foster inclusive collaboration and achieve sustainable growth in a globalized economy.

This qualitative investigation delves into the intricate interplay of cultural factors within supply chain integration, aiming to elucidate how diverse cultural dimensions shape communication dynamics, decision-making processes, and collaborative efforts among global supply chain practitioners. Employing a phenomenological approach, the study explores the lived experiences and subjective perceptions of supply chain managers and professionals, providing nuanced insights into the profound impact of national culture, organizational culture, digital technologies, and sustainability considerations on supply chain operations. Key findings highlight the significant influence of national culture, as conceptualized by Hofstede's cultural dimensions, on supply chain interactions. These dimensions—such as power distance, individualism versus collectivism, uncertainty avoidance, and masculinity versus femininity—play crucial roles in shaping how individuals perceive authority, manage risks, negotiate agreements, and engage in collaborative practices across diverse cultural contexts. Cultural norms and values deeply influence both intra-organizational dynamics and inter-organizational relationships within global supply chains. Organizational culture emerges as a pivotal determinant of supply chain integration success. Cultures characterized by transparency, trust, inclusivity, and a commitment to continuous improvement create environments conducive to effective cross-border collaboration. Conversely, organizations with conflicting or ambiguous cultural norms face challenges in aligning goals, fostering mutual understanding, and maintaining open communication channels with international partners. The study underscores the transformative role of digital technologies in enhancing supply chain management practices. Technologies such as blockchain, artificial intelligence, and the Internet of Things improve supply chain visibility, optimize operations, and enhance decision-making processes, strengthening resilience against disruptions. The adoption and integration of these technologies depend on organizational readiness, technological capabilities, and cultural acceptance within supply chain networks. Cultural factors influence the adoption pace, implementation strategies, and utilization patterns of digital technologies, emphasizing the need for strategic alignment between technological investments and cultural norms to maximize their potential benefits. Furthermore, sustainability considerations are critical in shaping cultural values and priorities within supply chain networks. Organizations increasingly recognize the importance of environmental sustainability, ethical sourcing practices, and corporate social responsibility in shaping their reputations, stakeholder relationships, and long-term business goals. Cultural factors significantly influence organizations' approaches to sustainability, guiding their strategic decisions and operational practices.

The gut has been a focus of chronic disease research. The gut microbiota produces metabolites that act as signaling molecules and substrates, closely influencing host health. Indigestible oli-gosaccharides (NDOs), as a common dietary fiber, play an important role in regulating the structure and function of gut microbiota. Their mechanism of action is mainly attributed to their carbon source as specific probiotics, producing related metabolites, and regulating the gut mi-crobial community. However, due to the selective utilization of oligosaccharides, some factors such as the types and structures of oligosaccharides have different impacts on the composition of microbial populations and the production of metabolites in the colon ecosystem. This review systematically describes the key factors influencing the selective utilization of oligosaccharides in microorganisms and elaborates how oligosaccharides affect the host's immune system, inflam-mation levels and energy metabolism by regulating microbial diversity and metabolic function, which in turn will affect the onset and progress of chronic diseases, especially diabetes, obesity, depression and intestinal inflammatory diseases, constipation. In this review, we re-examine the interaction mechanisms between gut microbiota and its associated metabolites and diseases, and explore new strategies for promoting human health and combating chronic diseases through di-etary interventions.

This qualitative research investigates the intricate relationship between market dynamics and supply chain sustainability in the renewable energy sector. Amidst the global energy transition, renewable energy has emerged as a crucial player in mitigating climate change and fostering sustainable development. However, ensuring the sustainability of renewable energy supply chains presents complex challenges shaped by various market forces. Through semi-structured interviews and thematic analysis, this study explores how policy frameworks, technological innovation, market competition, consumer preferences, and investor demands influence sustainability practices across the renewable energy supply chain. The findings highlight the critical role of supportive policy environments, technological advancements, and stakeholder collaboration in driving sustainability performance and mitigating risks within renewable energy supply chains. Furthermore, the study identifies challenges such as supply chain complexity, regulatory compliance, and stakeholder engagement, underscoring the need for collaborative efforts and multi-stakeholder partnerships. By addressing these challenges and leveraging opportunities, stakeholders can advance sustainability goals, mitigate climate change impacts, and foster a more resilient and equitable renewable energy sector. The research contributes to a deeper understanding of market dynamics and supply chain sustainability in the renewable energy sector, offering insights for policymakers, industry stakeholders, and sustainability practitioners to inform evidence-based decision-making and drive positive change.

In the past few years, cloud-based additive manufacturing has shown its application and potential in industries. For this reason, when the demand for cloud-based additive products increases, efficient scheduling of related tasks becomes more important to achieve optimized duration. This research proposes a Heuristic Scheduling Algorithm (HSA) for use in Cloud-Based Additive Manufacturing (CBAM) with an approach to Critical Chain Buffer Management (CC/BM). This research aims to schedule and optimize the time in cloud-based additive manufacturing, in addition to the parts production process, it also includes the steps of receiving online orders and informing the manufacturing unit and sending them to the customer. The HSA proposed in this research consists of three phases 1- Buffer sizing, 2- Additive manufacturing and logistics scheduling, and 3- Buffer controlling. To evaluate, the performance of the algorithm is simulated. The finding shows that the proposed HAS can effectively solve the CBAM scheduling problem.

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

This review deals with the developmental origins of extraocular, jaw and laryngeal muscles, the expression, regulation and functional significance of myosin heavy chains (MyHCs) they express and changes in MyHC expression during phylogeny. Myogenic progenitors from mesoderm in the prechordal plate and branchial arches specify craniofacial muscle allotypes with different repertoires for MyHC expression. To cope with very complex eye movements, extraocular muscles express 11 MyHCs, ranging from the superfast extraocular MyHC to the slowest, non-muscle MyHC IIB. They have distinct global and orbital layers, singly- and multiply-innervated fibres, longitudinal MyHC variations, and palisade endings that mediate axon reflexes. Jaw-closing muscles express the high-force masticatory MyHC, cardiac or limb MyHCs depending on the appropriateness for the acquisition and mastication of their food. Laryngeal muscles express extraocular and limb muscle MyHCs but shift towards slower MyHCs in large animals. During postnatal development, MyHC expression of craniofacial muscles is subject to neural and hormonal modulation. The primary and secondary myotubes of developing EOMs are postulated to induce, via different retrogradely transported neurotrophins, the rich diversity of neural impulse patterns that regulate the specific MyHCs they express. Thyroid hormone shifts 2A MyHC towards 2B in jaw, laryngeal muscles and possibly extraocular muscles.

“All diseases originate in the gut.” Hippocrates (400 BC) A healthy gut microbiome via the gut-brain-axis (GBA) elevates heart rate variability (HRV), a general measure of health and well-being. A dysbiotic gut microbiome, low in biodiversity and butyrate producers, alters tryptophan metabolism with release of proinflammatory cytokines, predominantly TNF-α, IL-6, and IL-1β. These also characterize chronic inflammation, oxidative stress, and a multitude of diseases, all exhibiting low HRV. Gut dysbiosis upregulates IFN-γ and with it IDO (indoleamine 2,3 dioxygenase). Tryptophan pivots from serotonin synthesis to that of IDO induced kynurenine, increasing the kynurenine to tryptophan ratio (KTR). An elevated KTR is positively linked to neurodegenerative and autoimmune diseases and negatively linked to HRV. Elevated IDO activity is not only enzymatic but also an intracellular signal transducer potentiated by TGF-β. This cytokine is the primary determinant of the TME. Also proposed is the gut-lung dysbiosis concept and consequent degradation of ACE2 (richest in lungs and gut). Leaky gut induced autoantibodies related to G-protein coupled receptors (GPCRs) in combination with increased Ang II further potentiate oxidative stress. Aldosterone and paroxysmal orthostatic tachycardia syndrome (POTS) paradoxes are highlighted in the context of GPCR and gut dysbiosis, and the role of Candida is explored. The triple play of a prebiotic (d-mannose), probiotic (bifidobacteria and lactobacilli), and postbiotic (butyrate) might improve intestinal barrier integrity, oppose entry of GPCR antigens, suppress the inflammatory cytokine triad, balance IFN-γ and TGF-β, suppress oxidative stress, depress KTR, elevate HRV, and extend lifespan and its quality.

Hydrogen sulfide (H2S) is an environmental toxicant of health concern. The brain is a major target in acute H2S poisoning. This study was to test the hypothesis that acute and subchronic ambient H2S exposures alter the brain metabolome. Male 7-8 week-old C57BL/6J mice were exposed by whole-body inhalation to 1000 ppm H2S for 45 min and euthanized at 5 min or 72 h for acute exposure. For subchronic study, mice were exposed to 5 ppm H2S 2 h/day, 5 days/week for 5 weeks. The brainstem was removed for metabolomic analysis. Enrichment analysis showed the metabolomic profiles in acute and subchronic H2S exposures matched with those of cerebral spinal fluid from patients with seizures or Alzheimer’s disease. Acute H2S exposure decreased excitatory neurotransmitters, aspartate and glutamate, while the inhibitory neurotransmitter, serotonin, was increased, which may explain H2S-induced loss of consciousness. Branched-chain amino acids and glucose were increased by acute H2S exposure. Subchronic H2S exposure within OSHA guideline surprisingly decreased serotonin altering central nervous system. In subchronic H2S exposure, glucose was decreased while polyunsaturated fatty acids, inosine, and hypoxanthine were increased. Collectively, these results provide important mechanistic clues of acute and subchronic ambient H2S poisonings and show that H2S alters brainstem metabolome.

(1) Background: The stylohyoid syndrome, known as classical Eagle Syndrome (cES), is characterized by calcificatication of the stylohyoid chain with numerous nonspecific symptoms, mainly pain. This study introduces Minimally Invasive Cervical Styloidectomy (MICS). (2) Methods: MICS was performed on sixty-five patients diagnosed with classical Eagle syndrome. Patients underwent meticulous differential diagnosis. Surgical plans were established based on the findings from neck angioCT. (3) Results: The healing process was uneventful without significant complications. The overall success rate was 97.0%, with a follow-up of a minimum of six months. In one case, the surgery did not yield the desired improvement. In one case, a partial relapse of symptoms was observed. (4) Conclusions: MICS is a straightforward and efficient surgical treatment technique for stylohyoid syndrome.

The objective of this study was to apply simulation and computational intelligence techniques using artificial intelligence and genetic algorithm for economic and environmental optimization of the reverse network (manufacturers, waste managers and recyclers in São Paulo, Brazil) of waste electrical and electronic equipment (WEEE) to promote circular economy. For the economic evaluation, the reduction of: fuel, drivers, insurance, depreciation, maintenance and charges was considered and for the environmental evaluation, the environmental impact was measured in the abiotic, biotic, water, land, air and greenhouse gases compartments. It is concluded that the optimized structure of the WEEE reverse chain for São Paulo, Brazil reduced the number of collections, making the most of the cubage. It also generated economic and environmental gains, contributing to the strategic actions of the circular economy. Thus, the proposed simulation allows replication in organizational practice, mainly to meet the 2030 agenda on reducing the carbon footprint generated in transport in large cities. Thus, this study can guide companies on structuring the reverse WEEE chain in São Paulo, Brazil for economic and environmental optimization, a relevant aspect considering the exponential generation of WEEE, requiring the implementation of the national solid waste policy, and subsequently the signature of the electronics sector agreement in São Paulo.

In recent years, there has been a wave of research on complex networks. The purpose of this paper is to study the graph theoretic mathematical properties of random cyclooctatetraene chain. We obtain the explicit analytical expressions for the variances of the Gutman index, Schultz index, multiplicative degree-Kirchhoff index and additive degree-Kirchhoff index of a random cyclooctatetraene chain with $n$ octagons, which plays a crucial role in the research and application of topological indices.

Cross-species investigations on cancer invasiveness are a new approach that identified new biomarkers potentially useful for improving tumor diagnosis and prognosis in clinical medicine and veterinary science. In this study, we combined proteomic analysis of four experimental rat malignant mesothelioma (MM) tumors with analysis of ten patient-derived cell lines to identify common features associated to mitochondrial proteome rewiring. The comparison of significant abundance changes between invasive and non-invasive rat tumors rat tumors gave a list of 433 proteins, including twenty-six proteins reported to be exclusively located in mitochondria. Next, we analyzed the differential expression of genes encoding the mitochondrial proteins of interest in five primary epithelioid and five primary sarcomatoid human MM cell lines, and the most impressive increase was observed in the expression of the long-chain acyl coenzyme A dehydrogenase (ACADL). To evaluate the role of this enzyme in the migration/invasiveness, two epithelioid and two sarcomatoid human MM cell lines derived from patients with the highest and lowest overall survival were studied. Interestingly, sarcomatoid vs epithelioid cell lines were characterized by higher migration and fatty oxidation rates, in agreement with ACADL findings. These results suggest that evaluating mitochondrial proteins in MM specimens might identify tumors with higher invasiveness.

Nuclear magnetic resonance (NMR) techniques are widely used to identify pure substances and probe protein dynamics. Edible oil is a complex mixture composed of hydrocarbons, which have a wide range of molecular size distribution. In this research, low field NMR (LF-NMR) relaxation characteristic data of various sample oils were analyzed. We also suggest a new method for prediction size of edible oil molecules using LF-NMR relaxation time distributions. According to the relative molecular mass, carbon chain length, transverse relaxation time of different sample oils, combined with oil viscosity and other factors, the relationship between carbon chain length and transverse relaxation time rate was analyzed. Various oils and fats in the mixed fluid are displayed, reflecting the composition information of different oils. To study the correlation between the rotation correlation time and molecular information of oil molecules. The molecular composition of the resulting fluid determines its properties, such as viscosity and phase behavior. The results show that low-field NMR can obtain information on the composition, macromolecular aggregation, and molecular dynamics of complex fluids. Measurements of grease in the free fluid state show that the relaxation time can reflect the intrinsic properties of the fluid. It is shown that the composition characteristics and states of complex fluids can be measured by low-field nuclear magnetic resonance.

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the SIR-type epidemiological model that we developed for viral diseases with long-term immunity memory pandemic. This is a large-scale model containing 15 nonlinear ODE equations, and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions.

The evolution towards Industry 4.0 is driving the need for innovative solutions in the area of network management, considering the complex, dynamic and heterogeneous nature of ICT supply chains. To this end, Intent-Based networking (IBN) which is already proven to evolve how network management is driven today, can be implemented as a solution to facilitate the management of large ICT supply chains. In this paper, we first present a comparison of the main architectural components of typical IBN systems and, then, we study the key engineering requirements when integrating IBN with ICT supply chain network systems while considering AI methods. We also propose a general architecture design that enables intent translation of ICT supply chain specifications into lower level policies, to finally show an example of how the access control is performed in a modelled ICT supply chain system.

Short chain quinones (SCQs) have been identified as potential drug candidates against mitochondrial dysfunction, which is largely dependent on their reversible redox characteristics of the active quinone core. We recently synthesized a SCQ library of > 148 naphthoquinone derivatives and identified 16 compounds with enhanced cytoprotection compared to the clinically used benzoquinone idebenone. One of the major drawbacks of idebenone is its high metabolic conversion in the liver, which significantly restricts is therapeutic activity. Therefore, this study assessed the metabolic stability of the 16 identified naphthoquinone derivatives 1-16 using hepatocarcinoma cells in combination with an optimized reverse-phase liquid chromatography (RP-LC) method. Most of the derivatives showed significantly better stability than idebenone over 6 hours (p < 0.001). By extending the side-chain of SCQs, increased stability for some compounds was observed. Metabolic conversion from the derivative 3 to 5 and reduced idebenone metabolism in the presence of 5 were also observed. These results highlight the therapeutic potential of naphthoquinone-based SCQs and provide essential insights for future drug design, prodrug therapy and polytherapy, respectively.

The early diagnosis of mastitis represents an essential factor for a prompt detection of the animal for further actions. In fact, if not culled, infected cows must be segregated from the milking herd and milked last, or milked with separate milking units. Besides microbiological analysis, the somatic cell count (SCC) commonly used as predictor of intramammary infection, frequently lead to a misclassification of milk samples. To overcome these limitations, more specific biomarkers are continuously evaluated. Total amino acid content increases significantly in mastitic milk compared to normal one. Bovine mastitis can arise as a result of infection of the mammary gland by Staphylococcus aureus. Multiplication of this bacterium within the mammary gland is required for infection to persist. S. aureus requires branched-chain amino acids (BCAAs: isoleucine, leucine, valine) for protein synthesis, branched-chain fatty acids synthesis and environmental adaptation by responding to their availability via transcriptional regulators. The importance of BCAAs for S. aureus physiology necessitates that it either synthesize them or scavenge them from the environment. Increase of BCAAs in composite milk has been postulated to be linked to mammary infection by S. aureus. In the present work, we demonstrated, by a direct ion-pairing reversed-phase method based on the use of the evaporative light-scattering detector (IP-RP-HPLC-ELSD), applied to 65 composite cow milk samples, a correlation between the concentration of isoleucine and leucine and S. aureus load.

Bayesian analysis for masked data under competing risk frameworks is studied for the purpose of assessing the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval of time for the remaining subjects. Such data, known as partly interval-censored data, usually result from periodic inspection. Dirichlet and Gamma processes are assumed as priors for masking probabilities and baseline hazards. The Markov Chain Monte Carlo (MCMC) technique is employed for the implementation of the Bayesian approach. The effectiveness of the proposed model is tested through numerical studies, including simulated and real data sets.

Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.

Traditional urban design often overlooks the synchronisation of human and ecological connectivities, typically favouring corridors for ecological continuity. Our study challenges this convention by introducing a computational design approach, Meta-Connectivity, leveraging the deep generative models performing cross-domain translation to integrate human-wildlife landscape connectivity in urban morphology amidst the planetary urbanisation. Utilising chained Pix2Pix models, our research illustrates a novel meta-connectivity design reasoning framework, combining landscape connectivity modelling with conditional reasoning based on deep generative models. This framework enables the adjustment of both human and wildlife landscape connectivities based on their correlative patterns in one single design process, guiding the re-materialisation of urban landscapes without the need for explicit prior ecological or urban data. Our empirical study in East London demonstrated the framework's efficacy in suggesting wildlife connectivity adjustments based on human connectivity metrics. The results demonstrate the feasibility of creating an innovative urban form in which the land cover guided by the connectivity gradients replaces the corridors based on simple geometries. This research thus presents a methodology shift in urban design, proposing a symbiotic approach to integrating disparate yet interrelated landscape connectivities within urban contexts.

Exosomes are produced by all cell types, their biogenesis is of endosomal origin, originating as a result of cell membrane invagination. Furthermore, physiochemical characteristics are important prerequisites for their commercial application. The representative size range of exosomes is 50-200 nm. Whereas, comparative to animal cell, exosomes from plant cell sources have a relatively larger size range, moreover, exhibit broader therapeutic potential. In this review study, we have briefly discussed the research potential of plant-derived exosomes. Including their earlier studies on biogenesis, characterization, isolation methods, and possible therapeutic applications. Additionally, we have quoted targeted drug delivery for targeted therapies and have provided insights of methods for customizing exosomes produced from plants with various drugs. Most-importantly, here we have embodied exosomes from plant sources are natural nano-inducers possessing the ability for inter-kingdom communication, resulting in cross-kingdom regulations.

In the rapidly evolving landscape of mobile applications, the demand for efficient and user-friendly platforms for services like motorcycle rentals is rising, particularly in urban areas. This paper presents the development of a Motorcycle Rent Application using Agile Methodology, tailored for the Android platform and developed with Flutter. Agile is iterative and adaptive approach, emphasizing continuous improvement and customer feedback, was crucial in managing the project's dynamic requirements. Flutter, with its single code base for multiple platforms and hot reload feature, significantly expedited development and enhanced the application's responsiveness and user interface. The project successfully implemented features such as user registration, motorcycle listing, rental booking, and payment integration, resulting in a seamless user experience. This study demonstrates the effectiveness of combining Agile Methodology with Flutter to create high-quality, responsive mobile applications that meet modern user expectations.

This paper proposes a non-extensive entropy econometric technique to predict energy efficiency at province (NUT-2) level based on imperfect knowledge of the national overall efficiency in the sectors of industry, transport, households and services. The model is applied to the polish case. As acknowledged in recent literature, non-extensive entropy model should remain a valuable device for econometric modelling even in the case of low frequency series since outputs provided by the Gibbs-Shannon entropy approach correspond to the Tsallis entropy limiting case of the Gaussian law when the Tsallis q-parameter converges to unity. Therefore, we set up a q-Tsallis-Kullback-Leibler entropy criterion function with a priori consistency moment and model data constraints, including province energy intensity (known with uncertainty), regional climate differentiation and regular conditions. The model outputs continue to conform to empirical expectations. In spite of the close to unity q-Tsallis parameter, this Tsallis related approach reflects higher stability for parameter computation in comparison with the Shannon-Gibbs entropy econometrics technique. The proposed technique can be applied in different EU countries and elsewhere for example in the context of experimental official statistics.

Efficient thermal management of modern electronics requires the use of thin films with highly anisotropic thermal conductivity. Such films enable the effective dissipation of excess heat along one direction while simultaneously providing thermal insulation along the perpendicular direction. In this study, we investigate the thermal conductivity of bilayer graphene (BLG) sheets using non-equilibrium molecular dynamics, examining both in-plane and cross-plane thermal conductivities. The in-plane thermal conductivity of 10 nm × 10 nm BLG with zigzag and armchair edges at room temperature is found to be around 204 W/m.K and 124 W/m.K, respectively. The in-plane thermal conductivity of BLG increases with sheet length. For all sizes, BLG with a zigzag edge exhibits higher thermal conductivity than that of the armchair edge, with this difference becoming more pronounced as the lengths of the sheets increase. In addition, increasing temperature from 300 K to 600 K decreases the in-plane thermal conductivity of a 10 nm× 10 nm zigzag BLG by about 34%. Similarly, the application of a 12.5% tensile strain induces a 51% reduction in its thermal conductivity compared to the strain-free values. Armchair configurations exhibit similar responses to variations in temperature and strain, but with less sensitivity. Furthermore, the cross-plane thermal conductivity of BLG at 300 K is estimated to be 0.05 W/m·K, significantly lower than the in-plane results by approximately four orders of magnitude. The cross-plane thermal conductance of BLG decreases with increasing temperatures, specifically, at 600 K, its value is almost 16% of that observed at 300 K.