Cross-laminated timber (CLT) possesses both good shape stability and the possible two-way force transfer ability due to its crosswise lamination. However, the transverse layers in CLT are prone to rolling shear failure under an out-of-plane load. An innovative multi-layer composite laminated panel (CLP) was developed by combining structural composite lumber (SCL) and dimension lumber to overcome the rolling shear failure while maintaining high mechanical performance and aesthetic appearance of natural wood. The mechanical properties of 5-layer CLP consisted of laminated strand lumber (LSL) and dimension lumber with different layups were evaluated by both static and modal tests. The results showed that the shear resistance, bending stiffness and moment resistance of CLP were up to 143%, 43% and 87% higher than their counterparts of regular CLT, respectively. The failure modes observed in both shear and bending tests indicated that the use of LSL in transverse layers could eliminate the potential rolling shear failure in CLT. With the lamination properties from components tests as inputs, the validity of shear analogy method was assessed by test results. The mechanical properties can be well predicted by shear analogy method except for the bending moment resistance of CLP and CLT with either rolling failure in the cross layer or tension failure in the bottom layer.

Background: Disparity in adult mortality (AM) with reference to social dynamics and health care has not been sufficiently examined. This study aimed to identify the gap in the understanding of AM in relation to religion, political stability, economic level, and universal health coverage (UHC). Methods: A cross-national study was performed with different sources of data, using the administrative record linkage theory. We created a new data set using data from the 2013 World Bank data catalogue by region, The Economist (Political instability index 2013), Stuckler David et al. (Universal health coverage, 2010), and religious categories of all UN country members. Descriptive statistics, a t-test, an ANOVA followed by a post hoc test, and a linear regression were used where applicable. Result: The average AM rate for males and females was 0.20 ± 0.10 and 0.14 ± 0.10, respectively. AM was significantly higher in economically weak countries, countries with political instability, countries with traditional religion, without achievement of UHC, and Sub-Saharan Africa (p<0.01). There was high disparity of AM between countries with and without UHC (F = male: 61.89, female: 51.85, p<0.001) and between groups with low and high income (F = male: 36.33, female: 42.39, p<0.001). UHC and political stability would significantly reduce AMR by > 0.41 in both sexes and high economic status would reduce male AMR by 0.44, and female AMR by 0.70, in relation to countries without UHC, with political instability, and low economic status. Conclusions: Disparities in AM can be reduced after the achievement of UHC and economically productive activities for those adults affected by conflict and political unrest.

Compared to traditional multi-robot path planning problems, multi-chain robot path planning (MCRPP) is more challenging because it must account for collisions between robot units and between the bodies of a chain and the leading unit during towing. To address MCRPP more efficiently, we propose a novel algorithm called Multi-Train Safe Interval Path Planning (MT-SIPP). Based on safe interval path planning principles, we categorize conflicts in the multi-train planning process into three types: travel conflicts, waiting conflicts, and station conflicts. To handle travel conflicts, we use an improved k-robust method to ensure trains avoid collisions with other trains during movement. To resolve waiting conflicts, we apply a time correction method to ensure the safety of positions occupied by trains during waiting periods. To address station conflicts, we introduce node constraints to prevent other trains from occupying the station positions of trains that have reached their target stations and are stopped. Experimental results on three benchmark maps show that the MT-SIPP algorithm achieves about a 30% improvement in solution success rate and nearly a 50% increase in the maximum number of solvable instances compared to existing methods. These results confirm the effectiveness of MT-SIPP in addressing the challenges of MCRPP.

In response to the escalating climate-related catastrophes of recent decades and their significant impacts on global transportation systems, this study explores the concept of resilience bonds as a novel financial tool for enhancing supply chain sustainability. The research applies a case study from China to demonstrate the application of resilience bonds in funding infrastructure projects that aim to enhance the sustainability and resilience of supply chain networks. The study examines the market mechanisms and valuation models of resilience bonds, assessing their potential to mitigate risks associated with transportation failures and to reduce economic losses from unexpected disruptions. By applying empirical data, the research quantitatively evaluates the impact of resilience bonds on the sustainability and reliability of transportation systems. The findings show that resilience bonds can significantly contribute as a sustainable solution to enhance supply chain resilience and sustainability, offering insightful alternatives for financing resilient infrastructure projects. This study not only supports policymakers, investors, and business leaders in understanding innovative funding mechanisms but also makes a significant contribution to resilience financing for sustainable transportation within supply chains, especially in the context of global disruptions.

Supply chain transparency plays a crucial role in shaping consumer perceptions and building brand trust in today's competitive marketplace. This qualitative study explores the impact of supply chain transparency on consumer behavior, focusing on its influence on brand trust and purchase decisions. Through semi-structured interviews with 30 participants, the research examines consumer attitudes towards transparency, highlighting key factors that influence trustworthiness and credibility perceptions of brands. The findings reveal that consumers prioritize brands that demonstrate openness about their sourcing, production practices, and ethical standards, viewing transparency as a critical indicator of corporate responsibility and integrity. Factors such as product safety, environmental sustainability, and labor practices within supply chains emerge as significant concerns driving consumer preference for transparent brands. Demographic insights indicate that younger consumers and those with higher education levels exhibit heightened sensitivity to transparency issues, underscoring a generational and educational divide in consumer expectations. Moreover, income levels influence the perceived importance of transparency, with higher-income participants showing greater preference for brands that prioritize ethical and sustainable practices. Challenges associated with supply chain transparency, including information overload and concerns about greenwashing, highlight the complexities brands face in effectively communicating their ethical commitments to consumers. The study concludes by advocating for strategic transparency initiatives that integrate sustainability, technology-enabled verification, and stakeholder engagement to build consumer trust and competitive advantage. By addressing these insights, brands can navigate the evolving landscape of consumer expectations and regulatory requirements, fostering long-term relationships based on trust and ethical business practices.

This qualitative study investigates how supply chain disruptions affect brand loyalty by analyzing consumer experiences during crises. Through in-depth interviews with diverse participants, the research explores the nuanced factors shaping consumer perceptions and behaviors when supply chains face challenges. Findings reveal that trust is pivotal, with transparent communication and consistent updates fostering consumer confidence and loyalty. Brand reputation emerges as crucial, influencing perceptions of reliability and ethical conduct during disruptions. Effective crisis management strategies, including agility and proactive communication, mitigate negative impacts on brand loyalty. Consumer decision-making is influenced by the availability of substitutes and perceptions of disruption severity, highlighting the importance of brand resilience and continuity. Emotional responses, such as frustration and anxiety, significantly influence consumer loyalty, underscoring the role of empathetic engagement and support from brands. Aligning with consumer expectations and delivering on promises are essential for sustaining loyalty and reducing the risk of consumer defection. The study concludes that navigating supply chain disruptions requires brands to prioritize trust, reputation, crisis management, consumer-centric strategies, emotional intelligence, and alignment with consumer expectations. These insights contribute to a deeper understanding of consumer behavior in crisis contexts and provide strategic implications for brands seeking to enhance resilience and maintain loyalty in dynamic market environments.

Brand communication and supply chain management are critical components of value co-creation in B2B markets, yet their interplay and implications remain underexplored in current literature. This qualitative study investigates how these elements synergistically contribute to mutual value creation among businesses. Through semi-structured interviews with senior executives and managers from diverse industries, key insights were gleaned regarding the strategic alignment of brand communication strategies with supply chain practices. Findings underscore the importance of authenticity, transparency, and consistency in brand messaging to build credibility and foster stakeholder trust. Supply chain management emerged as pivotal in supporting effective brand communication, facilitated by advancements in AI, blockchain, IoT, and cloud computing, enhancing operational efficiency and responsiveness across global networks. Entrepreneurship and emotional intelligence were identified as crucial drivers of innovation and collaboration within B2B contexts, augmenting organizational agility and resilience. Furthermore, the integration of sustainable practices within supply chain operations was found to enhance brand reputation and mitigate risks associated with environmental and ethical considerations. The study highlights actionable insights for practitioners, emphasizing the strategic integration of brand communication and SCM capabilities to navigate complexities, capitalize on emerging opportunities, and foster sustainable growth. This research contributes to a deeper understanding of the multifaceted dynamics shaping B2B interactions and provides a foundation for future research endeavors. By aligning brand communication strategies with SCM practices and leveraging technological advancements, businesses can enhance competitive advantage, cultivate enduring relationships with stakeholders, and achieve sustainable success in a dynamic global marketplace.

Consumer trust in supply chain certifications plays a pivotal role in shaping contemporary consumer behavior and marketing effectiveness. This qualitative research investigates consumer perceptions of supply chain certifications and their impact on purchasing decisions and brand loyalty. Through semi-structured interviews and focus group discussions with 30 participants, the study explores themes such as credibility, transparency, perceived value, and the influence of certifications on consumer trust. Findings reveal that consumers value certifications that signal ethical sourcing practices and sustainability commitments, viewing them as assurances of product quality and social responsibility. Credibility and transparency in certification processes emerged as critical factors influencing consumer trust, while perceived benefits such as environmental sustainability and fair labor practices positively influenced purchase intentions. Moreover, certifications were found to enhance brand loyalty by aligning with consumers' ethical values and beliefs. However, the study identifies challenges including high certification costs, complexity in compliance, and consumer skepticism, which hinder broader adoption and effectiveness of certifications. The implications of these findings suggest that businesses can enhance consumer trust and market competitiveness by investing in rigorous certification standards, clear communication strategies, and sustainable practices. Addressing barriers through improved transparency and consumer education is crucial for maximizing the impact of certifications on ethical consumption. Future research directions include longitudinal studies on certification impacts and comparative analyses across industries and global markets to further enrich understanding of consumer behavior and certification influences.

The dynamic and unpredictable nature of modern supply chains necessitates the development of resilient systems capable of withstanding various disruptions. This qualitative study examines the impact of collaborative practices on supply chain resilience, providing an in-depth analysis of their contributions to the robustness and adaptability of supply chains. Through extensive interviews with industry professionals, including supply chain managers, logistics coordinators, and strategic planners, the study identifies key collaborative practices—such as information sharing, joint decision-making, and coordinated response strategies—that significantly enhance resilience. These practices facilitate proactive risk management, improve response times during disruptions, and foster innovation through shared knowledge and resources. Thematic analysis of the collected data reveals that strong relationships among supply chain partners and integrated approaches that leverage each participant's strengths are crucial for effective risk mitigation and recovery. Additionally, the study underscores the role of technology in enabling real-time information sharing and decision-making, which are essential for effective collaboration. The findings highlight the importance of investing in robust collaborative networks and adopting supportive technologies to enhance communication and coordination. This research contributes to the existing body of knowledge by offering a nuanced understanding of how strategic implementation of collaborative practices can build more resilient supply chains. It provides practical recommendations for businesses seeking to improve their resilience, emphasizing the qualitative aspects of collaboration and its impact on supply chain management. Overall, this study presents a comprehensive exploration of how collaboration can bolster supply chain resilience, offering valuable insights for practitioners and scholars focused on creating stable and sustainable supply chain operations in the face of growing uncertainties.

This qualitative research explores the impact of digital transformation on supply chain collaboration, delving into its implications for organizational dynamics, processes, and outcomes. Through in-depth interviews with key stakeholders in diverse industries, insights are gathered into how digital technologies reshape collaboration within supply chains. Findings reveal a shift towards greater connectivity, visibility, and agility enabled by digital platforms and ecosystems, fostering innovation and value creation. However, challenges such as data security, organizational silos, and trust issues hinder the realization of collaborative potential. The study underscores the importance of embracing digital technologies, fostering a collaborative culture, and prioritizing trust and transparency to unlock the full benefits of digital collaboration. Moving forward, future research should focus on exploring evolving dynamics, identifying best practices, and developing frameworks for effective implementation in diverse organizational contexts. By leveraging digital transformation, organizations can enhance their supply chain capabilities, strengthen competitiveness, and drive sustainable growth in an interconnected, digitalized world.

Supply chain risk management (SCRM) is a critical aspect of contemporary business operations, necessitated by the complex and interconnected nature of global supply chains. This qualitative research delves into the intricacies of SCRM through in-depth interviews with industry experts, aiming to unravel the multifaceted nature of supply chain risks and the strategies employed for mitigation. Key themes emerged, including the diverse sources of risks encompassing operational, financial, environmental, and geopolitical factors, highlighting the need for a comprehensive approach to risk management. Challenges such as limited visibility, resource constraints, and organizational silos were identified, underscoring the importance of addressing these barriers to enhance SCRM effectiveness. Strategies for risk mitigation encompassed technological investments for enhanced visibility and predictive capabilities, collaboration and information sharing among supply chain partners, and the integration of sustainability principles into risk management practices. Leadership, organizational culture, and continuous learning emerged as critical factors in driving effective SCRM practices, emphasizing the need for proactive and adaptable approaches to navigate evolving risks. Overall, this study contributes to the existing body of knowledge on SCRM by providing valuable insights for practitioners and academics, and underscores the importance of holistic and proactive approaches to enhance supply chain resilience and agility in today's dynamic business environment.

This qualitative research study explores the multifaceted impacts of digital transformation on supply chain processes within contemporary business environments. Through in-depth interviews with industry professionals, the study investigates the implications of digitalization for visibility, collaboration, resilience, and innovation within supply chains. The findings highlight the opportunities presented by digital technologies for enhancing operational efficiency, mitigating risks, and creating value across supply chain networks. However, the study also underscores the challenges and barriers that organizations face in their digital transformation journey, including integration complexity, data security, and organizational culture. The research emphasizes the importance of strategic investments in digital capabilities, change management, and organizational culture to capitalize on the opportunities presented by digital transformation while addressing the associated challenges. By doing so, organizations can build agile, resilient, and competitive supply chains capable of thriving in an increasingly digitalized and interconnected world.

Although the neurofilament light chain (NfL) is used as a biomarker for neurodegenerative decline, its use in surgery- and anaesthesia-induced acute cognitive dysfunction remains controversial. We aimed to synthesise the evidence to explore the potential of NfL as an established biomarker for perioperative neurocognitive disorders (PND). We systematically searched the PubMed, EMBASE, MEDLINE, Cochrane Library electronic databases, and Cochrane Central Registry of Clinical Trials. Our results show that CSF NfL levels positively correlated with blood NfL levels (r = 0.63; 95% confidence interval [CI], 0.42-0.77). The pooled standardised mean difference (SMD) showed a significantly higher preoperative CSF NfL levels (SMD = 0.27; 95% CI, 0.07-0.47) and both pre- and postoperative blood NfL levels (SMD = 0.53, 95% CI, 0.40-0.66 and SMD = 0.58, 95% CI, 0.43-0.73) in the postoperative delirium (POD) group. Postoperative blood NfL levels were significantly elevated in both POD group (SMD = 0.49; 95% CI, 0.34-0.64) and no-POD group (SMD = 0.67; 95% CI, 0.53-0.81). Our meta-analysis indicates that NfL may serve as a potential biomarker for POD, and elevated preoperative blood NfL levels could be a risk factor for POD. Further studies are needed to confirm the association of CSF/blood NfL levels with other PND types.

The study examines projected changes in dry- and wet-spell probabilities in West Africa using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. The results show an increase in the probability of having a dry day, a dry day preceding a wet day and a dry day preceding a dry day, and a decrease in the probability of wet days in the Sahel region under anthropogenic forcing scenarios RCP4.5 and RCP8.5. The decrease in wet days is stronger in the far future and under the RCP8.5 scenario (up to -30%). The study also finds that the probability of consecutive dry days (lasting at least 7 days and 10 days) is expected to increase in the Western Sahel, the Central Sahel, and the Sudanian Area under both scenarios, with stronger increases in the RCP8.5 scenario. In contrast, the decrease is expected over the Guinea Coast, with the changes more important under the RCP4.5. These changes in dry- and wet-spell probabilities are important for water management decisions and risk reduction in the energy and agricultural sectors. The study also highlights the need for decision-makers to implement mitigation and adaptation policies to minimize the adverse effects of climate change.

Effective management of the medicine supply chain is crucial for ensuring the availability of essential medicines and supplies in public health facilities. This study aimed to determine the utilization of the electronic logistic management information system (e-LMIS) in public health facilities and its implications for the medicine supply chain. A mixed-methods approach, combining both quantitative and qualitative data collection methods was used. The study was conducted in 106 healthcare providers from 35 public health facilities in Singida District. Six key informants were interviewed in a qualitative method. Of 106 participants, (62.3%) said they were somehow competent in e-LMIS utilization. In in-depth interviews, respondents underscored the system's utility for tracking stock levels, procurements, and managing orders. Staff shortage and lack of customized training were mentioned as major challenges, hindering efficiency in managing drug supplies. This study highlighted the positive impact of e-LMIS on various aspects of the medicine supply chain, including the timely submission of orders and enhanced inventory management. Sustained management support and regular utilization of the e-LMIS system are crucial for building and maintaining competence among healthcare providers, thereby optimizing the medicine supply chain and ultimately improving healthcare delivery.

The article delves into the intricate phase transitions of 1-Octadecanol and n-Nonadecane within a binary system, unveiling dynamic structural changes under varying conditions. Through Fouri-er-transform infrared (FTIR) analysis, specific molecular vibrations were identified, shedding light on the molecular composition and interactions. The study highlights the challenges in detecting subtle phase transitions and emphasizes the individuality of molecular behaviours in closely related compounds. The findings underscore the complexity of phase transitions in binary systems and advocate for a nuanced approach to studying molecular structures and behaviours. Addi-tionally, the research contributes valuable insights into the molecular dynamics of Organic Polymer Functional Adsorption Materials, offering implications for synthetic waxy layers in plant epidermis.

With the increasing of China's international status and the acceleration of the process of global economic integration, the internationalization strategy of Chinese enterprises is getting deeper and deeper. This paper analyzes the problems and challenges faced by the international supply chain management of Chinese bamboo weaving and creative products, and puts forward a set of supply chain management model that ADAPTS to the international development. Firstly, the concept, connotation and types of supply chain management are sorted out through literature review. Secondly, this paper analyzes the current situation of international supply chain management of bamboo editing and creative products, and points out the existing problems. Thirdly, based on the theory and practice of international supply chain management, this paper puts forward a set of supply chain management model suitable for the international development of bamboo editing and creative products. Finally, taking a bamboo weaving and creative products enterprise as an example, the application effect of the supply chain management model is empirically analyzed. The results show that the supply chain management model can effectively reduce the cost and improve the efficiency, and is conducive to the international development of bamboo editing and creative products.

Understanding the implications of organic acids in animal diets on physiological markers is critical for developing viable strategies for improving overall health and performance. The aim of this study was to evaluate the influence of dietary organic acids inclusion on rabbits’ growth performance and physiological status by determining blood and intestine development indicators. Forty weaned rabbits aged 28-d randomly assigned into 2 groups and fed with standard compound diet (SCD) and SCD + 0.2% organic acids mixture (butyric, propionic, sorbic; OAM). Growth performance was evaluated between 28-77 d of age, physiological status at 77 d of age. OAM’s rabbits final body weight, ADG, DFI, growth rate indicators were higher, but FCR lower compared to SCD (P &lt; 0.05). OAM increased total protein and albumin levels in blood plasma; reduced pH, increased DM, achieved greater viscosity in caecum’s content (P &lt; 0.05). Compared to SCD better gut development observed in OAM, as total intestinal weight was significantly higher (P &lt; 0.05). Acetic and propionic acids concentrations were increased, but butyric reduced in OAM caecum’s content (P &lt; 0.05). OAM had significant effect on the most caecum histomorphometric parameters: increased villus height, crypt depth and their ratio (P &lt; 0.05). According to our results OAM can improve rabbits’ growth performance, nutrient intake, and feed digestibility by significantly improving physiological status.

The study focuses on the impact of new methods for inhibiting malolactic fermentation in white wines on their analytical and sensory properties. Enological preparations with different mecha-nisms of effect were tested: fumaric acid, chitosan, Estaan (a preparation based on tannin inhibi-tion), medium-chain fatty acids (MCFA), sulphur dioxide and a control variant where malolactic fermentation (MLF) was performed. The samples underwent analysis through HPLC (high-performance liquid chromatography) to determine concentrations of malic and lactic acid, as well as biogenic amines. GC (gas chromatography) analysis was used to monitor volatile sub-stances, alongside sensory evaluation. The study demonstrated a significant influence of indi-vidual enological preparations on the aromatic profile of the examined wines. The SO2 and MCFA variants exhibited the highest concentrations of volatile substances within the esters group, spe-cifically isoamyl acetate, 1-hexyl acetate and phenylethyl acetate. Conversely, the fumaric acid and Estaan variants displayed the lowest concentrations of these esters. The most notable disparities were observed in acetoin concentration, with the MCFA variant exhibiting the lowest values. Additionally, the chitosan variant showed higher concentrations of putrescine and spermidine compared to the MCFA and fumaric acid variants, which presented the lowest levels.

In contrast to its traditional form, in which large, powerful companies were solely and exclusively responsible for supplies, manufacturing, and distribution, the supply chain has undergone substantial change over the past half-century. Today, nearly all supply chain processes are outsourced, thanks to the efforts of innovative, modern companies. The degree of risk associated with contemporary supply chains is greater than the majority of supply chain managers acknowledge, according to an accumulation of studies, analysts, and news outlets. Vulnerabilities within the supply chain remain a significant challenge for numerous organizations. Inadequate management of these risks—which include, but are not limited to, natural disasters, acts of terrorism, cyber assaults, the credit crisis, pandemic scenarios, and war—could lead to significant declines in profitability, productivity, revenue, competitive advantage, and other metrics. Concerns regarding the risk assessment of the supply chain remain unresolved. The objective of this article is to present a risk evaluation framework that can be effectively implemented in the assessment of supply chain risks. This study makes a fundamental contribution to the body of knowledge by providing supply chain managers with a practical instrument for assessing their processes, irrespective of the mathematical underpinnings or the diverse variables employed in risk assessment. A case study from an automotive EMS production is used to compare the outcomes of multiple aggregation methods; the conclusions are then validated by risk and FMEA specialists from the same factory.

Today’s intruders usually send attacking commands to a target system through several stepping-stone hosts, in order to reduce the chance of being detected. With stepping-stone intrusion (SSI), the intruder’s identity is hidden behind a long interactive chain of hosts and very hard to detect. An effective approach for SSI detection (SSID) is to estimate the length of the chain. This type of method is called network-based SSID. Most existing network-based SSID worked effectively only when intruders’ session manipulation was not present. These known SSID algorithms are either weak to resist intruders’ chaff-perturbation manipulation or having very limited capability in resisting attacker’s session manipulation. This paper develops a novel network-based SSID algorithm resistant to intruders’ chaff-perturbation by using packet crossover. Our proposed SSID algorithm is simple and easy to implement as the number of packet crossovers can be easily computed. We conduct rigorous technical proofs to verify the correctness of our proposed algorithm. The experimental results show that our proposed SSID algorithm works effectively and perfectly in resisting intruders’ chaff-perturbation up to 50% chaff rate.

To solve the benefit allocation problem between the subjects of the supply chain of general contracting projects. The Cobb-Douglas function is applied to establish the benefit distribution model when the two cooperate in the supply chain system, analyze the optimal benefit situation of one-time cooperation between the two parties under two modes of egoistic decision and collectivistic decision as well as the benefit distribution problem of multiple cooperation, and conduct numerical simulation to calculate the functional relationship between each decision variable and the contribution degree of the general contractor under different effort cost coefficients. The results show that：In the case of one-time cooperation between general contractors and subcontractors, regardless of the decision mode, the degree of effort of both parties is positively related to their own contributions and negatively related to each other's contributions; the overall benefit of the supply chain system is positively proportional to the degree of contribution of the general contractor and inversely proportional to the share of benefit distribution of the subcontractor; in multiple cooperation, the equilibrium result of both parties achieving Pareto optimality at each stage is that both parties choose to cooperate.

Background: Understanding the factors that influence the market entry, exit, and stability of community pharmacies (i.e., market dynamics) is important for stakeholders ranging from patients to health policymakers and small business owners to large corporate institutions. The purpose of this article is to provide an update to a 15-year ecological comparison for the market dynamics of Minnesota community pharmacies from 2002 to 2017 [1]. Objectives: The first objective was to update the 15-year study [1] by describing the market dynamics of community pharmacies for each county in the state of Minnesota every five years over a 20-year period (i.e., 2002-2022). The second objective was to update the 15-year study by describing the number and proportion of community pharmacies for each county in the state of Minnesota every five years over a 20-year period (i.e., 2002-2022) by (1) ‘Business Organization Structure’ and (2) ‘Pharmacy Type.’ The third and fourth objectives were new for the 2022 study. In response to evolutionary trends in the pharmacy market, objective three described the number of Minnesota licensed pharmacies located in-state and out-of-state between 2002 and 2022. Objective four described the primary type of service provided by licensed pharmacies categorized as out-of-state in 2002 and in 2022. Methods: Data were obtained from the Minnesota Board of Pharmacy, US Census Bureau, and Minnesota State Demographic Center for 2002, 2007, 2012, 2017, and 2022. Descriptive statistics were used to tabulate and summarize the findings and test associations between study variables. Results: Over the 20-year study period, the total number of community pharmacies in Minnesota remained steady. Findings for 2022 were similar to those for 2017 regarding the effects of population density and metropolitan designation on the market dynamics of community pharmacies and regarding the organizational structures and types of pharmacies. The findings revealed significant growth in the number of proportion of pharmacies licensed in Minnesota that were located out-of-state. In 2002, there were 283 of these pharmacies (19% of the total). By 2022, this grew to 960 (46% of the total). Over that 20-year period, the number of mail order and medical supply service pharmacies rose from 196 to 413. The number of specialty pharmacy distributors rose from 37 to 230 and the number of compounding pharmacies rose from 33 to 202. Discussion: The findings confirmed the shift over the past 20 years from traditional retail convenience models to healthcare access models based on population health metrics. National scalability was another detected shift in order to have profitable margins for some services and was feasible due to advances in technologies. Conclusion: The findings showed that community pharmacy distribution in Minnesota’s 87 counties shifted between 2002 and 2022 from traditional retail convenience models to healthcare access models based on population health metrics and to nationally scalable models based on economic pressures. This signals the need for not only new approaches for tracking community pharmacy market dynamics but also adjustments by community pharmacies to remain relevant in a new environment of patient care services.

Polyglycolic acid (PGA) is a promising polymer in the packaging field owing to excellent hydrolysis, heat resistance and gas barrier properties, but there are limited in application due to poor toughness. For this reason, a covalently bonded chain extender is introduced to increase compatibility with flexible polymers. However, covalent bonds are unfavorable for application to degradable plastics because of require a lot of energy for reverse reactions. Therefore, it is intended to effectively control the ductility of blending plastics by using a novel ionic chain extender having a relatively weaker non-covalent bond than the existing covalent bond. Polycaprolactone (PCL), which has biodegradability and flexibility, was selected as a blending polymer. For comparison, a covalently reactive chain extender (G-CE) and a non-covalently ionic chain extender (D-CE) were synthesized and compounded to blending plastics. Each chain extenders were improved the compatibility between PGA and PCL, and the ductility of the PGA/PCL blending plastics were greatly enhanced with non-covalently bonding D-CE than with covalently bonding G-CE. At this time, the ductility of PGA/PCL blending plastic without CE is 7.2%, the ductility of 10D with D-CE is 26.6%, and the ductility of 10G with G-CE is 18.45%. Therefore, it was confirmed that the novel ionic chain extender inducing non-covalent bonds improves the compatibility between PGA and PCL and is more advantageous in enhancing ductility through a reversible reaction.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

Given the recent emergence of Rift Valley Fever (RVF) in Rwanda and its profound impact on livelihoods and health, improving RVF prevention and control strategies is crucial. Vaccinating livestock is one of the most sustainable strategies to mitigate the impact of RVF on health and livelihoods, yet vaccine supply chain constraints severely limit the effectiveness of vaccination programs. In the human health sector, unmanned aerial vehicles, i.e., drones, are increasingly being used to improve supply chains and last-mile vaccine delivery. We investigated perceptions on whether delivering RVF vaccines by drone in Rwanda might help to overcome logistical constraints in the vaccine supply chain. We conducted semi-structured interviews with stakeholders in the animal health sector and Zipline employees in Nyagatare District in the Eastern Province of Rwanda and used content analysis to identify key themes. We found that stakeholders in the animal health sector and Zipline employees believe that drones could improve RVF vaccination in Nyagatare. The main benefits study participants identified included decreased transportation time, improved cold chain maintenance, and cost savings.

Research focused on succinate dehydrogenase (SDH) and its substrate, succinate, culminated in the 50’s accompanying the rapid development of research dedicated to bioenergetics and intermediary metabolism. This allowed to uncover the implication of the SDH in both the mitochondrial respiratory chain and the Krebs cycle. Nowadays this theme is experiencing a real revival following the discovery of the role of SDH and succinate in a subset of tumors and cancers in human. The aim of this review is to enlighten the many questions yet unanswered, ranging from fundamental to clinically oriented aspects, up to the danger of the current use of SDH as a target for a sub class of pesticides.

Objectives: This meta-analysis was designed to assess the effect of addition of a bead-beating step during DNA extraction to effectively isolate Trichuris trichura DNA for quantitative Polymerase Chain Reaction (qPCR)-based diagnosis. Abstract was reported according to PRISMA-DTA abstract checklist. Methods: Eligibility criteria: qPCR-based molecular studies comparing the inclusion of bead-beating step during the DNA extraction from stool samples with extraction without the step were included in the analysis. Information sources: Studies using real patient samples in community settings were included. PubMed and Google search engine were searched in December 2019. Risk of bias and applicability: Risk of bias and applicability were assessed using QUADAS-2 checklist. Synthesis of results: Odds ratio for individual studies were combined to estimate Random Effects Model odds ratio. Additional literature were searched to discuss biochemical nature of helminth eggs. Results:Included studies: A total of six independent sub-studies were gathered from two published original articles. Division of the two major studies into six sub-studies was indispensable due to natures of the study carried. 128 of total 192 samples (in all studies) were positive for Trichiuris trichiura when bead-beating was used during DNA extraction compared to 108/192 when bead-beating was excluded. Combined odds ratio was 1.66 (95% CI: 1.059 to 2.602). Biochemical nature of helminth eggs was discussed. Discussions: Strengths and limitations: Though only two article were included in the study, six exclusive individual sub-studies were analyzed. Inherent differences in the background prevalence of helminth in study population could impact sensitivity of qPCR. Interpretation: It was found that the inclusion of the bead-beating step during DNA extraction significantly increased the sensitivity of the test.

Fatty acids and glucose are the main bioenergetic substrates in mammals that are alternatively used during the transition between fasting and feeding. Impairment of mitochondrial fatty acid oxidation causes mitochondrial myopathy leading to decreased physical performance. Here, we report that haploinsufficiency of ADCK2, a member of the aarF domain-containing mitochondrial protein kinase family, in human is associated with liver dysfunction and severe mitochondrial myopathy with lipid droplets in skeletal muscle. In order to better understand the etiology of this rare disorder, we generated a heterozygous Adck2 knockout mouse model to perform in vivo and cellular studies using integrated analysis of physiological and omics data (transcriptomics-metabolomics). The data show that Aldh2+/- mice exhibits impaired fatty acid oxidation, liver dysfunction, and mitochondrial myopathy in skeletal muscle resulting in lower physical performance. Significant decrease in CoQ biosynthesis was observed and supplementation with CoQ partially rescued the phenotype both in the human subject and mouse model. These results indicate that ADCK2 is involved in organismal fatty acid metabolism and in CoQ biosynthesis in skeletal muscle. We propose that patients with isolated myopathies and myopathies involving lipid accumulation be tested for possible ADCK2 defect as they are likely to be responsive to CoQ supplementation.

Durum wheat is an important food crop in the world and an endemic species of sub-Saharan Africa (SSA). In the highlands of Ethiopia and the oases of the South Sahara this crop has been cultivated for thousands of years. Today, smallholder farmers still cultivate it on marginal lands to assure production for their self-consumption. However, durum wheat is no longer just a staple crop for food security but it has become a major cash crop. In fact, the pasta and couscous industry currently purchase durum grain at prices 10 to 20% higher than bread wheat. Africa as a whole imports over € 4 billion per year of durum grain to provide the raw material for its food industry. Hence, African farmers could obtain a substantial share of this large market by turning their production to this crop. Here, the achievements of the durum breeding program of Ethiopia are revised to reveal a steep acceleration in variety release and adoption in the last decade. Furthermore, the variety release for Mauritania and Senegal is described to show how modern breeding methods could be used to deliver grain yields above 3 t ha^-1 in seasons of just 92 days of length and daytime temperatures always above 32°C. This review describes the ability of releasing durum wheat varieties adapted to all growing conditions of SSA, from the oases of the Sahara to the highlands of Ethiopia. This potential area of expansion for durum wheat production in SSA is not linked to any breeding technology, but rather it remains dependent on the market ability to purchase these grains at a higher price to stimulate farmer adoption. The critical importance of connecting all actors along the semolina value chain is presented in the example of Oromia, Ethiopia, and that success story is then used to prompt a wider discussion on the potential of durum wheat as a crop for poverty reduction in Africa.

Global financial investments in energy production and consumption are significant since all aspects of a country's economic activity, and development require energy resources. In this paper, we assess the investment trends in the global energy sector during, before and after financial crises of 2008 using two data sources: (1) Dealogic database providing cross‐border mergers and acquisitions (M&As), and (2) fDi Intelligence fDi Markets database providing greenfield (GF) foreign direct investments (FDIs). We highlight the changing role of China and compare its M&A and GF FDI activities to those of the United States, Germany, UK, Japan and others during this period. We analyze the investments along each segment of the energy supply chain of these countries to highlight the geographical origin and destination, sectoral distribution, and cross‐border M&As and GF FDI activities. Our paper shows that while energy accounts for nearly 25% of all GF FDI, it only accounts for 4.82% of total M&A FDI activity in the period 1996-2016. China's outbound FDI in the energy sector started its ascent around the time of the global recession and had accelerated in the post-recession phase. In the energy sector, the development of China's outbound cross‐border M&As is similar to USA or UK, located mostly in the developed countries in the west, while their outbound GF investments are spread across many countries around the world. Also, China's outbound energy M&As are concentrated in certain segments (extraction, and electricity generation) while their GF covers all segments of the energy supply chain.

Secondary transportation of raw and comminuted forest products is a major component in forest harvesting operations in terms of economics, public perception, and safety. Consequently, there is a substantial amount of literature on this topic. The existing literature has dealt with many of the technical aspects of transportation with a majority of them focusing on improving supply chain issues; However, there are only few specific to secondary transportation issues in general. This annotated bibliography will help practitioners, researchers, and stakeholders gain a better understanding of the existing literature from 2000 to 2015. To this end, we began by classifying the selected literature into six themes: cost, roads and routes, trucking, efficiency & safety, other modes of transportation, and supply chain & optimization. Woody biomass for bioenergy production was the most researched forest product with respect to transportation. About one-third of the articles were presented in the context of supply chain modeling and optimization. More than half of the studies originated from Europe while the United States had the most publications for any given country. The most articles (16) were published in 2013. Biomass and Bioenergy published the highest number of articles (29) during the timeframe.

Agavins consumption has lead to accelerate body weight loss in mice. We investigated the changes on cecal microbiota and short chain fatty acids (SCFA) associated to body weight loss in overweight mice. Firstly, mice were fed with standard (ST5) or high fat (HF5) diet for 5 weeks. Secondly, overweight mice were shifted to standard diet alone (HF-ST10) or supplemented with agavins (HF-ST+A10) or oligofructose (HF-ST+O10), five more weeks. Cecal contents were collected before and after supplementation to determine microbiota and SCFA concentrations. At the end of first phase, HF5 mice showed a significant increase of body weight, which was associated with reduction of cecal microbiota diversity (PD whole tree; non-parametric t-test, P < 0.05), increased Firmicutes/Bacteroidetes ratio and reduced SCFA concentrations (t-test, P < 0.05). After diet shifted, HF-ST10 normalized its microbiota, increase its diversity and SCFA levels, whereas agavins (HF-ST+A10) or oligofructose (HF-ST+O10) led to partial microbiota restoration, with normalization of the Firmicutes/Bacteroides ratio as well as higher SCFA levels (P < 0.1). Moreover, agavins noticeably enriched Klebsiella and Citrobacter (LDA > 3.0); this enrichment has not been reported previously under a prebiotic treatment. In conclusion, agavins or oligofructose modulated cecal microbiota composition, reduced extent of diversity and increased SCFA. Furthermore, identification of bacteria enriched by agavins, opens opportunities to explore new probiotics.

This paper proposes a re-conceptualization of the port supply chain as a smart service system, according to the theory of the Service science. Starting from a short literature review about the port supply chain approach and the Service science, a new comprehensive framework is provided to better understand the seaport dynamics and the creation of competitive port supply chains. The methodology used is the case study approach. The authors examined the port of Salerno (Italy), and re-conceptualized it as a smart port service systems. Both theoretical and practical implications are provided to enrich the literature about the port supply chain and to support the port operators.

For offshore wind power generation, accessibility is one of the main factors that has great impact on operation and maintenance due to constraints on weather conditions for marine transportation. This paper presents a framework to explore the accessibility of an offshore site. At first, several maintenance types are defined and taken into account. Next, a data visualization procedure is introduced to provide an insight into the distribution of access periods over time. Then, a rigorous mathematical method based on finite state Markov chain is proposed to assess the accessibility of an offshore site from the maintenance perspective. A five-year weather data of a marine site is used to demonstrate the applicability and the outcomes of the proposed method. The main findings show that the proposed framework is effective in investigating the accessibility for different time scales and is able to catch the patterns of the distribution of the access periods. Moreover, based on the developed Markov chain, the average waiting time for a certain access period can be estimated. With more information on the maintenance of an offshore wind farm, the expected production loss due to time delay can be calculated.

Multimodal emotion classification (MEC) involves analyzing and identifying human emotions by integrating data from multiple sources, such as audio, video, and text. This approach leverages the complementary strengths of each modality to enhance the accuracy and robustness of emotion recognition systems. However, one significant challenge is effectively integrating these diverse data sources, each with unique characteristics and levels of noise. Additionally, the scarcity of large, annotated multimodal datasets in Bangla limits the training and evaluation of models. In this work, we unveiled a pioneering multimodal Bangla dataset, MAViT-Bangla (Multimodal Audio Video Text Bangla dataset). This dataset, comprising 1002 samples across audio, video, and text modalities, is a unique resource for emotion recognition studies in the Bangla language. It features emotional categories such as anger, fear, joy, and sadness, providing a comprehensive platform for research. Additionally, we developed a framework for emotion recognition that employs a cross-modal attention mechanism among unimodal features. This mechanism fosters the interaction and fusion of features from different modalities, enhancing the model’s ability to capture nuanced emotional cues. The effectiveness of this approach was demonstrated by achieving an F1-score of 0.64, a significant improvement over unimodal methods.

：Non-Euclidean data, such as social networks, and citation relationships between documents, has node information and structural information. Graph Convolutional Network(GCN) can automatically learn node features and association information between nodes. The core ideology of the graph convolutional network is to aggregate node information by using edge information, thereby generating a new node feature. In the process of updating node features, there are two core influencing factors. One is the number of neighboring nodes of the central node, the other is the contribution of the neighboring nodes to the central node. Due to the previous GCN methods not simultaneously considering the numbers and different contributions of neighboring nodes to the central node, we design the Adaptive Attention Mechanism(AAM). To further enhance the representational capability of the model, we utilize Multi-Head Graph Convolution(MHGC). Finally, we adopt cross-entropy(CE) loss function to describe the difference between the predicted results of node categories and the ground truth (GT). Combined with backpropagation, this ultimately achieves accurate node classification. Based on AAM, MHGC and CE, we contrive the novel Graph Adaptive Attention Network (GAAN). Experiments show that the classification accuracy has achieved outstanding performances on Cora, Citeseer and Pubmed datasets.

Juvenile Polyposis Syndrome (JPS) is a rare autosomal dominant disorder characterized by multiple juvenile polyps in the gastrointestinal tract, often associated with mutations in genes such as Smad4 and BMPR1A. This study explores the impact of Smad4 knockout on the development of intestinal polyps using Collaborative Cross (CC) mice, a genetically diverse model. Our results reveal a significant increase in intestinal polyps in Smad4 knockout mice across the entire population, emphasizing the broad influence of Smad4 on polyposis. Sex-specific analyses demonstrate higher polyp counts in knockout males and females compared to their WT counterparts, with distinct correlation patterns. Line-specific effects highlight the nuanced response to Smad4 knockout, underscoring the importance of genetic variability. Multimorbidity heat maps offer insights into complex relationships between polyp counts, locations, and sizes. Heritability analysis reveals a significant genetic basis for polyp counts and sizes, while machine learning models, including k-Nearest Neighbours and Linear Regression, identify key predictors, enhancing our understanding of juvenile polyposis genetics. Overall, this study provides a comprehensive understanding of the intricate genetic interplay in the context of Smad4 knockout, offering valuable insights into potential therapeutic targets for juvenile polyposis and related diseases.

Sharding shows great potential for extending the blockchain. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workload, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a Product-Form Queue Network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between network load, consensus efficiency, and security in sharded blockchains, laying a theoretical foundation for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.

Understanding the dynamics of teamwork and communication among healthcare professionals is crucial in the face of evolving healthcare challenges. This study assessed relational coordination among healthcare professionals in the South Tyrolean healthcare system in Italy, focusing on communication and teamwork dynamics in a cross-sectional survey. Using the validated Relational Coordination Survey (RCS) instrument and 525 completed online responses, the questionnaire aimed to understand the implications of different levels of relational coordination ratings by general practitioners, hospital physicians, nurses, and administrative personnel (response rate 26%). The demographics of the participants revealed a predominance of female professionals (64%), with an average age of 50 and 18 years of service. The resulting RCS scores varied significantly across professional groups, with nurses reporting the highest within-group scores, indicating moderate coordination, and administrators reporting the lowest scores, reflecting areas of weak coordination. Between-group relational coordination was generally perceived as weak across professional groups, with the least weakness observed between general practitioners and nurses. German or Italian language and health district affiliation emerged as significant factors influencing relational coordination ratings, highlighting the need for differentiated understanding and strategies in multilingual and diverse regional settings. Assessments of interdisciplinary feedback and referral practices highlight the variation in teamwork and communication weaknesses and underscore the need for targeted interventions to improve relational coordination. This study provides insights into the complexity of relational dynamics in health care settings. It suggests that improving relational coordination through tailored strategies could significantly improve team effectiveness, quality of patient care, and overall system efficiency.

Current VAT rules for cross-border e-commerce companies in the EU are not sustainable, because they are extremely complex and often opaque, due to the lack of tax harmonization. The aim of the research is to explore, using a qualitative method, what kind of harmonization would make the current legislation more uniform, simpler, more transparent, and easier to understand, without conflicting with the rules of any Member State. To this end, the aspects of the new platform regulation introduced on 1 July 2021 and its potential for expansion are assessed through information from possible sales models. The research suggests that the rules on platforms do not cover all possible sales models, which in our view imposes an unnecessary extra administrative burden on some businesses and makes their tax activities less transparent. In the light of the results of the research, we propose that the current EU platform regulation should be extended to cover B2B, B2C transactions and services. As a result of this suggested harmonization, a simpler, more transparent, uniform and sustainable tax system would contribute to the whitening of the economy, generating additional tax revenue for Member States.

Software defect prediction models enable test managers to predict defect-prone modules and assist with delivering quality products. A test manager would be willing to identify the attributes that can influence defect prediction and should be able to trust the model outcomes. The objective of this research is to create software defect prediction models with a focus on interpretability. Additionally, it aims to investigate the impact of size, complexity, and other source code metrics on the prediction of software defects. This research will also assess the reliability of cross-project defect prediction. Well-known machine learning techniques such as support vector machines, k-nearest neighbors, random forest classifiers, and artificial neural networks were applied to publicly available PROMISE datasets. The interpretability of this approach has been demonstrated by SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) techniques. The developed interpretable software defect prediction models showed reliability on independent and cross-project data. Finally, the results demonstrate that static code metrics can contribute to the defect prediction models, and the inclusion of explainability assists in establishing trust in the developed models.

Static and functional occlusal relationships are the well-defined objectives of orthodontic therapy. To accomplish it, the jaws must be positioned in centric relation (CR)/ Central occlusion (CO) and appropriately proportioned in three space planes. Orthodontists have well-established techniques when analyzing the skeletal connection between the maxilla and mandible in both sagittal and vertical planes. Although there exist multiple analyses for the skeletal transverse dimension (STD), their inclusion in conventional orthodontic diagnosis is not widely acknowledged. Transverse tooth compensations have been visually represented in prosthodontic literature using a crosshatch arch that passes through the buccal and palatal cusps of maxillary molars, known as the Wilson curve. An inflated Wilson curve has long been seen as a prosthetic maxim, increasing the possibility of working and non-working side interferences. Research has indicated a connection between higher masticatory muscle activity and posterior occlusal contacts or interferences. When skeletal transverse issues are concealed by dental expansion, there is an elevated susceptibility to gingival recession in orthodontic patients who have a small Maxilla or constricted upper jaw. The temporomandibular joints, muscles, periodontal tissue, and airway might all suffer in a susceptible patient with a transverse insufficiency brought on by a narrow maxilla. As for orthodontists, the objective is to create skeletal connections and functional occlusion that are as near ideal as feasible. This will reduce the likelihood of occlusion-related inconsistencies exacerbating the negative consequences on the dentition, periodontium, or joints. An accurate skeletal and dental diagnostic in all three space planes is required. Our goal is to explain all approaches to enable readers to use a transverse skeletal diagnostic in their practice regardless of the technological level at their disposal. The initial step is to ascertain the kind and presence of deficiencies in the maxilla. Since fewer soft tissue alterations are caused by maxilla hypoplasia in the transverse direction, skeletal transverse dimension (STD) assessment is a more significant challenge than vertical or sagittal discrepancy assessment. Model analysis, clinical assessments, radiographic measurements, and occlusograms have all proven successful in producing accurate assessments. Most of the time, surgically assisted maxillary expansion (SARME) is reported to have higher stability than orthopedic maxillary expansion (OME). We examine and discourse on possible research opportunities using the Collaborative Cross (CC) mouse model as a substitute research model.

Despite well-documented health benefits of probiotics Saccharomyces, its application in oral health has not been comprehensively assessed. Dental caries is a transmissible disease initiated by acid production of cariogenic bacteria and yeast, such as Streptococcus mutans and Candida albicans, on tooth enamel and followed by subsequent enamel demineralization. Here, we investigated the effect of two Saccharomyces strains (Saccharomyces boulardii, Saccharomyces cerevisiae) on S. mutans-C. albicans cross-kingdom interactions using a cariogenic planktonic model. Viable cells, pH changes and gene expression were measured. S. cerevisiae and S. boulardii inhibited the growth of C. albicans either in dual-, or multi-species conditions. Saccharomyces also inhibited C. albicans hyphal formation. Furthermore, Saccharomyces reduced the acidity of the culture medium which usually plummeted below pH 5 when S. mutans and C. albicans were present in the model. The presence of Saccharomyces maintained the culture medium above 6 even after overnight incubation, demonstrating a protective potential against dental enamel demineralization. S. boulardii significantly downregulated S. mutans atpD and eno genes expression. Overall, our results shed light on a new promising candidate, Saccharomyces, for dental caries prevention due to its potential to create a less cariogenic environment marked by a neutral pH and reduced growth of C. albicans.

Hypertension stands as the foremost modifiable risk factor for cardiovascular disorders in South Asia. This research demonstrates the superiority of statistical models over traditional approaches in identifying clinical risks related to hypertension. Leveraging individual-level data from the Bangladesh Demographic and Health Survey (2017-18), a unified dataset was created. Adhering to JNC7 and ACC/AHA guidelines for hypertension classification, two prominent regression models were employed to estimate the prevalence of undiagnosed hypertension. A substantial 16% of hypertension cases in Bangladesh remain undetected. The study identifies undiagnosed hypertension as a heightened risk, particularly among the youth and residents of Sylhet and Rangpur divisions. Statistical models exhibit efficacy in discerning undiagnosed hypertension and associated factors in South Asia. Subsequent investigations should incorporate biological markers to enhance statistical models and ascertain their practicality.

Image segmentation is the process of partitioning an image into multiple segments where the goal is to simplify the representation of the image and make the image more meaningful and easier to analyze. In particular, semantic segmentation is an approach of detecting the classes of objects, based on each pixel. In the past, most semantic segmentation models were for only one single style, such as urban street views, medical images, or even Manga. In this paper, we proposed a semantic segmentation model called Dual-Pyramid Wide Residual Network (DPWRN) to solve the segmentation for cross-style datasets, which is suitable for diverse segmentation applications. The DPWRN integrated the Pyramid of Kernel paralleled with Dilation (PKD) and Multi-Feature Fusion (MFF) to improve the accuracy of segmentation. To evaluate the generalization of the DPWRN and its superiority over most state-of-the-art models, three datasets with completely different styles are tested in the experiments. Finally, the DPWRN verified its generalization and also showed its superiority over most state-of-the-art models.

This paper introduces the spatial component in cross-section econometric estimations and specifically, the spatial dependence effect inherent in some of the variables involved in the modelling process. First, the spatial structure of the data from thematic maps is observed and Moran's spatial autocorrelation indicators are presented. Subsequently, the spatial weights matrix is built under different specifications. Finally, several modelling specification strategies are shown and the interpretation of the estimated coefficients. The theoretical concepts are illustrated with examples and their corresponding R software codes. This code and databases are available in a freely accessible repository in the BE2SHARE-EUDAT platform so that they can be easily reproduced.

Background and Objectives: The prevalence of osteoporosis is high, reportedly affecting 200 million people worldwide. A major problem associated with osteoporosis is that femoral fractures cause a decline in general function and loss of independence, greatly reducing patients’ quality of life. Notably, osteoporosis is an asymptomatic chronic metabolic disease, and its detection is thus often delayed. Interestingly, mandibular cortical index (MCI) classification using dental panoramic radiography is reportedly useful for early detection of osteoporosis. However, this visual classification method can lead to differences in diagnosis among surgeons. Therefore, this preliminary study was performed to analyze cone-beam computed tomography (CBCT) data and examine an objective MCI classification using the findings obtained. Materials and Methods: MCI classification (classified as C1, C2, or C3) was performed by three examiners on 70 women (91 sites) aged ≥20 years. The mandibular cortical width of all sites was measured using CBCT images. Results: The results showed that the mandibular cortical width was not particularly correlated with age or number of present teeth, and no significant quantitative differences were found between C1 and C2. However, coronal CBCT images of C2 revealed multiple characteristic bone trabecular structures. Conclusions: These structures may be an important finding affecting the classification of two-dimensional dental panoramic radiography images.

As an established and widely available infrastructure, wireless local area networks (WLANs) have emerged as a viable option for indoor localization of both mobile and stationary users. In planning a mobile communications network and radio system design, the critical role of coverage prediction becomes evident, empowering network operators to optimize cellular networks and elevate the overall customer experience. Moreover, WLANs present several challenges that must be fulfilled when it comes to localization based on Wi-Fi signals to get a proper coverage prediction map. This paper presents a study based on application of the extra trees regression (ETR) for indoor localization by using coverage prediction maps. The aim of the proposed method is to accurately estimate a user’s position within a radio environment map (REM) area using collected received signal strength indicator (RSSI) values. The proposed scheme investigates several machine learning (ML) regression algorithms for localization, where the training dataset is obtained from the REM by using the nearest neighbors method. Parameter tuning is conducted to optimize the performance of the ETR scheme by using 10-fold cross-validation. In the numerical results, we first demonstrate the effectiveness of utilizing ML regression techniques for generating coverage maps, which enables accurate estimation of the Wi-Fi signal strength in indoor environments. Then, we showcase the superior performance of the proposed ETR-based method compared to several other ML schemes for indoor localization using the REM. ML algorithms, including decision tree regression and the ETR, are compared to evaluate the system model. Based on error metrics, the proposed ETR-based approach exhibits the best performance among the evaluated techniques. The combination of coverage map generation and localization using regression techniques offers a powerful approach for analyzing the radio frequency (RF) environment in indoor spaces.

Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.

Statistical based reconstruction methods and signal processing tooling techniques are implemented and used to detect delaminations or debondings within composite items. From literature it appears that, although a single procedure for the estimation of the structural health is a fast solution, a multiple analysis based on different reconstruction methods or different damage parameters could provide more detailed information about the location and the severity of possible failures. This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on ultrasonic guided waves (GW) tomographic technique and piezoelectrics (PWAS) in pitch-catch configuration. In this sense, this work evidences an improvement in damage detection when the cross-correlation is included as part of the GW-based system for damage assessment approach. The specimens used as test structures to demonstrate the validity of the methodology derive from an aircraft wing test article where damages are specified as skin delamination produced by low energy impact.

The environment is seldom optimal for plant growth and changes in abiotic and biotic signals, including temperature, water availability, radiation and pests, induce plant responses to optimise survival. The New Zealand native plant species and close relative to Arabidopsis thaliana, Pachycladon cheesemanii grows under environmental conditions that are unsustainable for many plant species. Here we compare the responses of both plant species to different stressors (low temperature, salt and UV-B radiation) to help understand how P. cheesemanii can grow in such harsh environments. The stress transcriptomes were then determined and comparative transcriptome and network analyses discovered similar and unique responses within species between different stresses, and between the two plant species. A number of widely studied plant stress processes were highly conserved in A. thaliana and P. cheesemanii. However, in response to cold stress, Gene Ontology terms related to glycosinolate metabolism were only enriched in P. cheesemanii. Salt stress was associated with alteration of the cuticle and proline biosynthesis in A. thaliana and P. cheesemanii, respectively. Anthocyanin production may be a strategy to cope with UV-B radiation stress in P. cheesemanii only. These results allowed us to construct broad stress response pathways in A. thaliana and P. cheesemanii and identify possible novel plant strategies that help mitigate environmental stress.

Irrigation and fertilizer are two essential factors affecting rice root traits and yield. In this respect, a pot experiment was performed at the boro (dry season irrigated) season of 2021-22 in the Department of Agronomy of Bangladesh Agricultural University, Mymensingh, Bangladesh. The variety Binadhan-10 was planted at two irrigation conditions i.e. saturation (S) and continuous flooding (CF); two potassium (K) dose e.g. 65 kg ha-1 (K65) and 98 kg ha-1 (K98) and two nitrogen (N) dose i.e. 140 kg ha-1 (N140) and 210 kg ha-1 (N210). The experiment was laid in split plot design and replicated thrice. The findings confirmed the effectiveness of irrigation, K and N on root number (RN), root length (RL), root volume (RV), leaf area index (LAI), total dry matter (TDM), yield attributes and yield. Considering interaction among irrigation, K and N, S condition with K65 and N140 showed best performance. At 80 DAT, the highest RN (373.00), RL (1700.00 cm), RV (8.90 cm3 hill-1), LAI (4.94) and TDM (25.83 g plant-1) was obtained from this combination. Grain yield (GY) and root traits except root porosity, showed a significant positive association. Grain yield (GY) was highest (27.12 g pot-1) in S condition with K65 and N140.

The calculation of moments of area is one of the most fundamental aspects of engineering mechanics for calculating the properties of beams or for the determination of invariants in different kind of geometries. While a variety of shapes such as circles, rectangles, ellipses or their combinations can be described symbolically, such symbolic expressions are missing for freeform cross-sections. In particular, periodic B-spline cross-sections are suitable for an alternative beam cross-section, e.g. for the representation of topology optimization results. In this work, therefore, a symbolic description of the moments of area of various parametric representations of such B-splines is computed. The expressions found are then compared with alternative computational methods and checked for validity. The resulting equations show a simple way for fast conceptual computation of such moments of area of periodic B-splines.

In this study, the dependence between Bitcoin (BTC) and economic policy uncertainty (EPU) of USA and China is estimated by applying latest methodology of quantile cross-spectral dependence. The findings indicate a positive return interdependence between BTC and EPU is high in short-term, and this dependence decreases as investment horizons increase from weekly to yearly. The information on above interdependence is also extracted by applying wavelet coherence analysis and the estimation results suggest that correlation between BTC and EPU is positive during short-term investment horizon. Furthermore, more diversification benefits of BTC can be obtained during USA-EPU as compared to China-EPU.

The crystal nucleation and overall crystallization kinetics of cross-linked poly(ε-caprolactone) was studied experimentally by fast scanning calorimetry in a wide temperature range. With an increasing degree of cross-linking, both the nucleation and crystallization half-times increase. Concurrently, the glass transition range shifts to higher temperatures. In contrast, the temperatures of the maximum nucleation and the overall crystallization rates remain the same independent of the degree of cross-linking. The cold crystallization peak temperature generally increases as a function of heating rate, reaching an asymptotic value near the temperature of the maximum growth rate. A theoretical interpretation of these results is given in terms of classical nucleation theory. In addition, it is shown that the average distance between the nearest cross-links is smaller than the estimated lamellae thickness, which indicates the inclusion of cross-links in the crystalline phase of the polymer.

Background Due to the Covid-19 pandemic and the strict national policies regarding social distancing behavior in Europe, America and Australia, people became reliant on social media as a means for gathering information and a tool for staying connected to family, friends and work. This is the first trans-national study exploring the qualitative experiences and challenges of using social media while in lockdown or shelter in place during the current pandemic. Methods This study was part of a wider cross-sectional online survey conducted in Norway, UK, USA and Australia during April/May 2020. The manuscript reports on the qualitative free text component of the study asking about the challenges of social media users during the Covid-19 pandemic in UK, USA and Australia. 1991 responses were included in the analysis. Thematic analysis was conducted independently by two researchers. Results Three overarching themes identified were: Emotional/Mental Health, Information and Being Connected. Participants experienced that using social media during the pandemic amplified anxiety, depression, fear, panic, anger, frustration and loneliness. They felt that there was information overload and social media was full of misleading or polarized opinions from which was difficult to switch off. Nonetheless, participants also thought that there was an urge for connection and learning which was positive and stressful and the same time. Conclusion Using social media while in shelter in place or lockdown could have a negative impact on the emotional and mental health of some of the population. To support policy and practice in strengthening mental health care in the community, social media could be used to deliver practical advice on coping and stress management. Communication with the public should be strengthened by unambiguous and clear messages and clear communication pathways. We should be looking at alternative ways of staying connected.

Nowadays, the human population is facing the third and may be the worst pandemic caused by human coronaviruses (CoVs). The virus was first reported in Wuhan, China on 31 December 2019 and spread within short time to almost all countries of the world. Genome analysis of the early virus isolates has revealed high similarity with SARS-CoV and hence the new virus was officially named SARS-CoV-2. Since CoVs have the largest genome among all RNA viruses, they can adapt many point mutation and recombination events; particularly in spike gene, that enable these viruses to rapidly change and evolve in nature. CoVs are known to cross the species boundaries by using different cellular receptors. SARS-CoV-2 is believed to originate in bats and transmitted to human being through an ill-defined intermediate host. In the current review, different aspects of SARS-CoV-2 biology and pathogenicity are discussed including virus genetics and evolution, spike protein and its role in evolution and adaptation to novel hosts, and virus transmission and persistence in nature. In addition, the immune response developed during SARS-CoV-2 infection is demonstrated with special reference to the interplay between immune cells and their role in disease progression. We believe that SARS-CoV-2 outbreak will not be the last and spillover of CoVs from bats will continue. Therefore, establishing intervention approaches to reduce the likelihood of future CoVs spillover from the natural reservoirs is a priority.

There is a growing public health need for effective preventive interventions against dengue, and a safe, effective and affordable dengue vaccine against the four serotypes would be a significant achievement for disease prevention and control. Two tetravalent dengue vaccines, Dengvaxia (Sanofi Pasteur) and DENVax (Takeda Pharmaceutical Company), have now completed phase 3 clinical trials. While Dengvaxia resulted in serious adverse events and is restricted to individuals with prior dengue infections, DENVax has shown, at first glance, some encouraging results. Using the available data for the TAK 003 trial, we estimate, via the Bayesian approach, vaccine efficacy (VE) of the post-vaccination surveillance periods. Although better measurement over long time was expected for the second part of the post-vaccination surveillance, variation in serotype-specific efficacy needs careful consideration. Besides observing that individual serostatus prior to vaccination is determinant of DENVax vaccine efficacy, we also compare the VE estimations for 12 and 18 months and we observe that the efficacy is decreasing over time. The comparison of efficacies over time is informative and very important, bring up the discussion of the role of temporary cross-immunity in dengue vaccine trials and the impact of serostatus prior to vaccination in the context of dengue fever epidemiology.

Cyclodextrin polymers have high applicability in pharmaceutical formulations due to better biocompatibility, solubility enhancement, loading capacity and controlled drug release than parent the cyclodextrins. The cytotoxicity and cell uptake of new cationic beta-cyclodextrin monomers and polymers were evaluated as suitable material for nasal formulations and their protective effects on cells exposed to hydrogen peroxide were studied. PC12 and CACO-2 cells were selected as the neuronal and epithelial type cells, respectively, to mimic the structure of respiratory and olfactory epithelia of the nasal cavity. All cationic beta-cyclodextrin polymers tested showed dose- and time-dependent toxicity; nevertheless, at 5 µM concentration and 60 min of exposure, the quaternary-ammonium-beta-cyclodextrin soluble polymer could be recognized as non-toxic. Based on these results, fluorescently labelled quaternary-ammonium-beta-cyclodextrin monomer and polymer were selected for uptake studies in CACO-2 cells. The monomeric and polymeric beta-cyclodextrins were internalized in the cytoplasm of CACO-2 cells; the cationic monomer showed higher permeability than the hydroxypropyl-beta-cyclodextrin, employed as comparison. Therefore, these cationic beta-cyclodextrins showed potential as excipients able to improve the nasal absorption of drugs. Furthermore, amino-beta-cyclodextrin and beta-cyclodextrin soluble polymers were able to reduce oxidative damage in PC12 and CACO-2 cells and thus could be studied as bioactive carriers or potential drugs for cells protection against oxidative stress.

Lung cancer is known as lung carcinoma. It is a disease which is malignant tumor leading to the uncontrolled cell growth in the lung tissue. Lung Cancer disease is one of the most prominent cause of death in all over world. Early detection of this disease can assist medical care unit as well as physicians to provide counter measures to the patients. The objective of this paper is to approach an automated tool that takes influential causes of lung cancer as input and detect patients with higher probabilities of being affected by this disease. A neural network classifier accompanied by cross-validation technique is proposed in this paper as a predictive tool. Later, this proposed method is compared with another baseline classifier Gradient Boosting Classifier in order to justify the prediction performance.

Drug induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized drugs and candidate drugs and predicting hepatotoxicity from the chemical structure of a substance remains a challenge worth pursuing, being also coherent with the current tendency for replacing non-clinical tests with in vitro or in silico alternatives. In 2016 a group of researchers from FDA published an improved annotated list of drugs with respect to their DILI risk, constituting “the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans”, DILIrank. This paper is one of the few attempting to predict liver toxicity using the DILIrank dataset. Molecular descriptors were computed with the Dragon 7.0 software, and a variety of feature selection and machine learning algorithms were implemented in the R computing environment. Nested (double) cross-validation was used to externally validate the models selected. A number of 78 models with reasonable performance have been selected and stacked through several approaches, including the building of multiple meta-models. The performance of the stacked models was slightly superior to other models published. The models were applied in a virtual screening exercise on over 100,000 compounds from the ZINC database and about 20% of them were predicted to be non-hepatotoxic.

Since 2015, outbreaks of foot-and-mouth disease (FMD) in the Middle East have been caused by a new emerging viral lineage, A/ASIA/G-VII. In-vitro vaccine matching data indicated that this virus poorly matched (low r1-value) with vaccines that were being used in the region as well as most other commercially available vaccines. The aim of this study was to assess the performance of two candidate vaccines against challenge with a representative field virus from the A/ASIA/G-VII lineage. The results from an initial full dose protection study provided encouraging data for the A/MAY/97 vaccine, while the A22/IRQ/64 vaccine only protected 2/7 vaccinated animals. In view of these promising results, this vaccine was tested in a potency test (PD50) experiment in which 5 cattle were vaccinated with a full dose, 5 cattle with a 1/3 dose and 5 cattle with a 1/9 dose of vaccine. Vaccines were prepared as would be done during an emergency vaccination campaign using a double oil emulsion adjuvant. At 21 days post vaccination these vaccinated cattle and 3 control cattle were subsequently challenged intradermolingually with a field isolate from the A/ASIA/G-VII lineage. All cattle from the full vaccine dose, 4 cattle from the 1/3 vaccine dose and 2 cattle from the 1/9 vaccine dose were clinically protected against challenge with FMDV A/ASIA/G-VII, resulting in a heterologous potency of 6.5 PD50/dose. These data support previous studies showing that a high potency emergency vaccine can protect against clinical disease when challenged with a heterologous strain of the same serotype. Not only the r1-value of the vaccine, but also the homologous potency of a vaccine should be taken into account when advising vaccines to control an outbreak.

This article analyzes the emergence of partnerships between corporations and nongovernmental organizations (NGOs) through voluntary product labeling schemes. The economics, management, and business literatures are reviewed to highlight cross-checking, consistencies, and complementarities among these disciplines. The objective is to identify and analyze the motives, risks, and joint benefits of partnering via voluntary product labeling, using examples from the agri-food sector. This study is an attempt to offer a framework of corporate-NGO partnerships by showing that the drivers and risks of each partner merge because each takes a step into the sphere of the other. The main risks – namely, a loss of profitability, credibility and legitimacy – are related to the financial and existential dependency and the asymmetric information between the partners in favor of corporations, inducing an ``NGO-capture'' risk.

The article discusses the issue of the sustainable development of the cross-border market for cultural services in a city divided by the state border. The article uses the example of Cieszyn and Český Těšín, a city divided following the decision of the Council of Ambassadors in 1920. The research carried out so far indicates the main constraints in the harmonious functioning of the cross-border market for cultural services in this city, such as: different cultural policies implemented on both sides of the city, language barriers as well as legal and administrative differences. Therefore, the authors undertook research aimed at recognising the role of Euroregional structures in stimulating the sustainable development of this region. On the basis of the analysis of the Cieszyn Silesia Euroregion's documentation and the results of qualitative and quantitative research, the article describes the role of the Euroregion in building a cross-border market for cultural services. Recommendations were also prepared that could constitute the principles of a common cultural policy not only for Cieszyn and Český Těšín, but also for other European cities in the Schengen Area, which, like Cieszyn and Český Těšín, have been divided by a state border.

The geometry of Poincare disk itself is interpreted without any mapping to dierent spaces. Our approach might be one of the shortest and is intended for educational contribution.

As a universal pathogen leading to neonatal defects and transplant failure, Human cytomegalovirus (HCMV) has strict species specificity that the inability to using this virus in animals has hampered its pathogenesis study. However, the mechanism of cross-species barrier remains elusive that no non-human cell model has been established to fill this knowledge gap. We observed that primary dermis fibroblasts (TSDF) isolated from the Chinese tree shrew (Tupaia belangeri chinensis), a small laboratory animal with close affinity to primates, were permissive to HCMV replication. In TSDF infected with GFP-expressing HCMV, the green fluorescence and cytopathic effect were observed and the expression of 3 kinetic genes and replication of viral genome were detected. The cell-free viruses produced in TSDF reached 103 pfu/mL at 96 hpi, which were 10-fold lower than in primary human foreskin fibroblasts. Our results demonstrated that TSDF supported low level of lytic replication of HCMV. The TSDF model provides a useful platform for the mechanism study of species barrier of HCMV.

In this paper, we analyze the measurements of the normalized radar cross-section(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, we verify the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. The Amazon rainforest experiment results show that the accuracy of obtained calibration constant meets the requirements. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it has an approximate cosine modulation with the wind direction when the wind speed is greater than 8m/s. The cross-polarized system noise floor is low enough to ignore it in wind retrieval. Furthermore, we also investigate the properties of the polarization ratio, denoted PR, and show that it is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the σ_VV^0 retrieved from new PR models as well as σ_HH^0 is in good agreement with σ_VV^0 extracted from SAR images directly. And it is also shown that considering the azimuth angle can improve polarization conversion accuracy.

In thermal power plants equipped with air-cooled condensers, axial cooling fans operate under the influence of ambient flow fields. Under inlet cross-flow conditions, the resultant asymmetric flow field is known to introduce additional harmonic forces to the fan blades. This effect has previously been studied only numerically or using blade mounted strain gauges. For this study, Laser Scanning Vibrometry was used to assess fan blade vibration under inlet cross-flow conditions in an adapted fan test rig inside a wind tunnel test section. Two co-rotating laser beams scanned a low pressure axial fan, resulting in spectral, phase resolved surface vibration patterns of the fan blades. Two distinct operating points were examined, with and without inlet cross-flow influence. While almost identical fan vibration patterns were found for both reference operating points, overall blade vibration increased by 100% at low fan flow rate due to cross-flow, and by 20% at high fan flow rate. While numerically predicted natural frequency modes could be confirmed from experimental data as minor peaks in the vibration amplitude spectrum, they were not excited significantly by cross-flow. Instead, primarily higher rotation rate harmonics were amplified, i.a. a synchronous blade tip flapping was strongly excited at the blade pass frequency.

Supplier diversity has emerged as a critical strategy for enhancing e-commerce operations by fostering inclusivity and innovation within supply chains. This qualitative research explores the role of supplier diversity in e-commerce, examining its impact on organizational strategies, competitive advantage, and stakeholder perceptions. Through semi-structured interviews with procurement managers, diversity officers, and supply chain executives from diverse e-commerce platforms, this study identifies key themes related to the benefits, challenges, and strategic implications of supplier diversity initiatives. Findings indicate that supplier diversity significantly enhances innovation and creativity within supply chains by integrating diverse perspectives and expertise. This diversity not only enriches product development and market responsiveness but also strengthens corporate reputation and brand equity, demonstrating organizational commitment to ethical business practices and community engagement. However, the study reveals persistent challenges, including financial barriers, systemic biases, and scalability issues, which hinder the effective implementation and scalability of supplier diversity programs. Effective supplier relationship management emerges as critical for maximizing the benefits of supplier diversity, fostering trust, collaboration, and long-term partnerships with diverse suppliers. Looking forward, the future of supplier diversity lies in digital transformation, globalization of supplier networks, and integration of sustainable sourcing practices to enhance transparency, efficiency, and resilience in supply chain operations. This study contributes to the growing literature on supplier diversity by providing empirical insights and practical implications for organizations aiming to leverage diversity as a strategic asset in e-commerce and global supply chain management.

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

Supply chain flexibility plays a pivotal role in enabling organizations to adapt their marketing strategies to evolving consumer preferences in dynamic market environments. This qualitative study explores how supply chain flexibility dimensions—responsiveness, agility, resilience, and sustainability—impact marketing strategy adaptation. Through semi-structured interviews and document analysis, insights were gathered from industry practitioners across diverse sectors. Key findings highlight that responsive supply chains facilitate quick adjustments in production, distribution, and sourcing to meet changing consumer demands. Agility enables rapid reconfiguration of operations to capitalize on market opportunities and respond to disruptions effectively. Resilient supply chains mitigate risks and maintain continuity during crises, safeguarding customer satisfaction and brand reputation. Integrating sustainability practices not only meets regulatory standards but also aligns with consumer preferences for eco-friendly products, enhancing corporate social responsibility. Technological advancements such as AI, IoT, blockchain, and cloud computing enhance supply chain visibility, optimize decision-making, and support real-time responsiveness. Despite benefits, challenges like legacy systems, organizational silos, resistance to change, and resource constraints hinder effective implementation. Overcoming these barriers requires strategic leadership, cross-functional collaboration, and continuous investment in technology and talent. Embracing supply chain flexibility empowers organizations to navigate complexities, drive innovation, and sustain competitive advantage. By aligning supply chain capabilities with marketing strategies, companies can enhance market responsiveness, customer satisfaction, and long-term growth in today's dynamic business landscape

Food security is the cornerstone of national security, and exploring the resilience of the grain industry chain is particularly important under the current complex and changing external environment. The study is to evaluate the grain industry chain resilience and identify its influencing factors. Based on the panel data of 30 provinces (cities) in China from 2011 to 2022, this paper adopted Partial Least Squares structural equation modeling method to carry out comprehensive evaluation, applied Dagum Gini coefficient to analyze spatial differences, and used geo-detectors to identify the influencing factors. The results showed that (1) from an overall perspective, the resilience of China's grain industry chain showed an overall upward trend, and each region had been greatly improved; (2) from the perspective of spatial differences, the overall spatial variability of China's grain industry chain is relatively small, and the gap mainly originates from inter-regional differences; (3) from the perspective of influencing factors, the level of grain foreign trade, regional market size and agricultural innovation level were important factors. In order to enhance the resilience of China's grain industry chain, based on the heterogeneous characteristics, the coordinated development of each region should be integrated, and the endogenous power should be given full play to enhance the resilience of the industry chain.

The thermal conditions of transitional (ranging from warm to cold) coldwater streams impact the ranges and resource availabilities for biota inhabiting these lotic systems. With ongoing climate change and increasing land modifications, thermal boundaries may shift, altering thermal transition zones and their biotic communities. The objective of this study was to investigate the condition of trout across three forks of the Whitewater River catchment and to investigate factors influencing fish community composition and distribution. Each fork was characterized into three separate sections: headwater (coolwater), middle (warmwater), and lower (coldwater). Springs were identified throughout each fork, with greatest concentrations in the lower sections of each fork. Using single-pass electrofishing, we sampled 61 sites across the three forks in the Whitewater River system (North = 21 sites, Middle = 19, South = 21), and catch statistics were used to calculate diversity, trout abundance, and trout condition. In general, diversity increased, and trout were healthier but less abundant in middle and headwater sections, whereas diversity decreased slightly, trout condition decreased, and trout abundance increased in lower reaches, with changes differing somewhat among forks. Canonical correlation analysis had strong significant correlations showing simpson diversity and condition increase going upstream with high non trout abundance and catch rates while trout catch rates and reach width decrease. The Whitewater River is a catchment exhibiting transitional temperature-pattern characteristics with generally low fish community diversity and trout conditions that range from thin, normal, and robust. Dominated by a changing landscape (agriculture) and intensifying climate change, we may begin to see stream temperatures increase along with species diversity. Understanding how spring temperature influences species composition and distribution can bring potential stressors to light increasing our understanding of thermal conditions and to help mitigate the negative impacts from land use and climate change.

This qualitative study explores the transformative role of digital technologies in enhancing supply chain efficiency and marketing effectiveness across diverse industries. The integration of Internet of Things (IoT), artificial intelligence (AI), blockchain, and advanced analytics has reshaped organizational practices, enabling real-time data collection, analysis, and decision-making in supply chain management (SCM) and marketing. Through semi-structured interviews with 25 professionals, including supply chain managers, marketing executives, and IT specialists, insights were gathered into the adoption, integration, and impact of digital technologies within organizational contexts. Key findings highlight IoT's contribution to enhancing supply chain visibility, predictive maintenance, and operational efficiency through continuous monitoring and data-driven insights. AI technologies support demand forecasting, inventory optimization, and personalized marketing strategies, improving customer engagement and satisfaction. Blockchain enhances supply chain transparency, traceability, and security, reducing risks associated with fraud and ensuring compliance with regulatory standards. Advanced analytics provide organizations with actionable insights into consumer behavior and market trends, guiding strategic decision-making and optimizing marketing campaigns. Despite these benefits, organizations face challenges such as technological complexity, integration issues, data privacy concerns, and organizational resistance to change. Strategic planning, leadership support, and investment in digital infrastructure are essential for overcoming these challenges and maximizing the potential of digital technologies. Future research directions include exploring sustainability initiatives in digital SCM, advancing AI-driven analytics, and understanding digital transformation in emerging markets.

Digital transformation is revolutionizing supply chain management, profoundly influencing marketing effectiveness across industries. This qualitative study explores the impact of digital transformation on supply chains and its implications for marketing strategies. Through in-depth interviews, case studies, and document analysis, the research elucidates how digital technologies such as IoT, blockchain, AI, and advanced analytics are reshaping supply chain dynamics. Key findings highlight enhanced supply chain visibility, improved decision-making capabilities, and strengthened collaboration among supply chain partners. These technological advancements empower organizations to optimize inventory management, anticipate market trends, and deliver personalized customer experiences, thereby enhancing operational efficiency and customer satisfaction. Furthermore, the study underscores the role of digital transformation in promoting sustainability and ethical practices within supply chains. Technologies like blockchain facilitate transparent and traceable supply chains, supporting initiatives for responsible sourcing and environmental stewardship. Despite the transformative benefits, the study identifies challenges including significant investment requirements, integration complexities, and data security concerns. Strategic approaches to technology adoption, robust cybersecurity measures, and employee training are essential for overcoming these challenges and maximizing the benefits of digital transformation. Overall, this study contributes to understanding how digital transformation drives innovation in supply chain management and enhances marketing effectiveness. By embracing digital technologies and aligning supply chain strategies with marketing objectives, organizations can navigate competitive landscapes, meet evolving consumer expectations, and achieve sustainable growth in the digital era.

This study explores the critical role of supply chain management (SCM) in shaping marketing strategies in emerging markets, where rapid economic growth and dynamic consumer behavior present both challenges and opportunities. Utilizing a qualitative approach, the research synthesizes insights from industry professionals across various sectors to elucidate how effective SCM practices can enhance marketing outcomes. Findings reveal that flexibility in supply chain operations is indispensable for adapting to the volatile market conditions typical of emerging economies, enabling companies to respond swiftly to changes in consumer demand and market trends. Advanced technologies such as predictive analytics, artificial intelligence, and the Internet of Things are identified as key enablers, providing real-time insights that align supply chain processes with marketing objectives. The ability to customize products and services to local preferences, supported by agile supply chains, emerges as a crucial factor in gaining a competitive edge. Cost management and optimization through efficient supply chain practices allow for competitive pricing and effective promotions, essential in price-sensitive markets. The study also highlights the importance of managing regulatory compliance, mitigating risks, and enhancing customer experience through integrated supply chain strategies. Cultural considerations and local market knowledge are critical for aligning product features and marketing messages with consumer expectations. Additionally, sustainability is becoming increasingly relevant, with environmentally conscious supply chains enhancing brand image and supporting marketing strategies. The impact of e-commerce and the role of supplier relationships further underscore the need for cohesive SCM and marketing integration. This research provides a comprehensive framework for understanding how supply chain capabilities can be leveraged to achieve marketing success in emerging markets, offering practical insights for companies seeking to navigate these complex environments effectively.

In today's globalized economy, supply chain disruptions present significant challenges, impacting businesses' operational continuity and efficiency. This study delves into the ways businesses navigate these disruptions, with a particular emphasis on qualitative insights into risk management practices. The complexity and interconnectivity inherent in modern supply chains make them vulnerable to a broad spectrum of disruptions, ranging from natural disasters and geopolitical conflicts to technological failures and pandemics. Effective supply chain risk management requires a structured approach to identifying potential risks, evaluating their likelihood and potential impact, and formulating robust mitigation strategies. Employing a qualitative research methodology, this study gathers in-depth insights from semi-structured interviews with supply chain managers, industry experts, and executives. The findings underscore the necessity of proactive risk identification and comprehensive assessment processes. Advanced technologies, including artificial intelligence (AI), the Internet of Things (IoT), and blockchain, are highlighted as crucial tools for enhancing visibility and responsiveness within supply chains. Strategies such as diversifying suppliers and maintaining safety stock emerge as vital components of risk mitigation, ensuring supply continuity in the face of disruptions. Strong relationships with suppliers are pivotal, facilitating better information sharing and collaborative problem-solving. Leadership commitment to risk management and fostering a culture of resilience within organizations is also critical. Training programs and simulation exercises are identified as effective means of preparing employees to handle disruptions. Furthermore, adherence to regulatory compliance and a focus on sustainability are integral to maintaining long-term stability and reducing the risk of future disruptions.

Supply chain transparency and traceability have become increasingly important in today's globalized and interconnected business environment. This qualitative research explores the challenges and perspectives of industry practitioners regarding supply chain transparency and traceability. Drawing on semi-structured interviews with a diverse group of supply chain professionals, the study identifies key themes including difficulties in achieving visibility beyond immediate suppliers, data fragmentation and inconsistency, barriers to technology adoption, regulatory compliance, cultural and organizational factors, impacts on supplier relationships, and the influence of the COVID-19 pandemic and sustainability goals. The findings highlight the complex nature of these challenges and the need for collaborative, multi-stakeholder approaches to address them effectively. Despite the challenges, the study also reveals the potential benefits of transparency and traceability for enhancing supply chain resilience, sustainability, and stakeholder trust. Moving forward, companies must leverage technological innovations, establish clear communication channels with suppliers, navigate regulatory complexities, and foster a culture of transparency and accountability within their organizations. Future research should focus on practical strategies for implementing transparency and traceability initiatives, as well as evaluating their impact on supply chain performance and sustainability outcomes.

This study explores the multifaceted role of culture in supply chain collaboration, focusing on how cultural differences shape communication, trust-building, negotiation, conflict resolution, risk management, and ethical standards. Utilizing a qualitative methodology, semi-structured interviews were conducted with 25 supply chain professionals from diverse cultural backgrounds and industries. The findings reveal that high-context cultures favor indirect communication and nuanced information exchange, which can lead to misunderstandings with partners from low-context cultures who prefer direct and explicit communication. Trust-building practices vary significantly, with high uncertainty avoidance cultures emphasizing formal agreements and procedural rigor, while low uncertainty avoidance cultures prioritize personal relationships and demonstrated reliability. Negotiation strategies also diverge, reflecting the underlying values of collectivism versus individualism, impacting the tactics and outcomes of supply chain negotiations. Conflict resolution approaches differ, with high power distance cultures favoring hierarchical and mediated solutions, and low power distance cultures preferring direct and egalitarian methods. The study highlights the need for adaptability to cultural changes and the development of cultural intelligence as essential competencies for managing cross-cultural supply chains. Additionally, cultural differences in risk management approaches and governance mechanisms affect the coordination and resilience of supply chains, while varying ethical standards influenced by cultural norms necessitate culturally sensitive strategies for promoting corporate social responsibility. The insights gained from this research underscore the importance of understanding and leveraging cultural differences to build stronger, more productive supply chain relationships, contributing to the broader literature on culture and supply chain management and offering practical implications for enhancing global supply chain collaboration.

This study explores the role of stakeholder engagement in enhancing supply chain sustainability within the renewable energy sector. Through a qualitative research approach, including in-depth interviews with key stakeholders such as government agencies, industry associations, renewable energy companies, community groups, and environmental organizations, the research reveals the complexity and significance of effective stakeholder engagement. Stakeholders highlighted diverse motivations, including environmental, social, economic, and regulatory concerns, driving their participation. The study underscores the importance of tailored engagement strategies that recognize stakeholder heterogeneity and address specific needs and expectations. Collaborative approaches, such as public-private partnerships and multi-stakeholder initiatives, were identified as crucial for pooling resources, sharing knowledge, and addressing common challenges. However, challenges related to power imbalances, conflicting interests, and communication barriers were also noted. Government policies and regulatory frameworks were found to play a pivotal role in shaping stakeholder engagement practices and sustainability outcomes. Regulatory uncertainty and inconsistency were cited as significant concerns that could undermine sustainability initiatives. Community engagement emerged as a critical factor, with local communities often directly impacted by renewable energy projects. Meaningful engagement, including consultation and benefit-sharing mechanisms, is essential for building trust and securing social acceptance. Emotional intelligence and marketing strategies were recognized as important tools for effective stakeholder engagement, emphasizing the role of empathy, active listening, and clear communication. The findings of this study highlight the need for a holistic and integrated approach to stakeholder engagement and supply chain sustainability in the renewable energy sector. By addressing diverse stakeholder needs, fostering collaboration, and aligning policies with sustainability goals, stakeholders can work together to accelerate the transition towards a more sustainable energy future.

This qualitative research explores the dynamics of collaborative marketing and supply chain strategies for enhanced product lifecycle management. Through in-depth interviews with industry stakeholders, key themes, challenges, and implications of collaboration emerge. Trust, communication, technology, strategic alignment, and sustainability are identified as critical factors driving successful collaboration. The study highlights the transformative potential of collaboration in driving innovation, efficiency, and customer satisfaction. Despite challenges such as aligning objectives and ensuring data security, collaborative strategies offer significant opportunities for value creation and differentiation. The findings underscore the importance of building trust, leveraging technology, and integrating sustainability considerations in collaborative efforts. Strategic alignment and cultural fit among partners are essential for overcoming differences and achieving common goals. The implications of the research extend to practitioners seeking to enhance collaboration in their organizations and researchers exploring collaborative practices in different industries and contexts. Future research could further explore the impact of collaboration on stakeholder perspectives and outcomes. By addressing challenges and leveraging opportunities, organizations can maximize the benefits of collaborative marketing and supply chain strategies to drive sustainable growth and competitive advantage in today's dynamic business landscape.

This qualitative research investigates the effectiveness of certification programs in ensuring supply chain sustainability within the renewable energy sector. Through interviews and content analysis, the study explores stakeholder perceptions, challenges, and impacts of certification initiatives. Findings reveal diverse motivations driving certification adoption, including regulatory compliance, market differentiation, and corporate social responsibility. However, challenges such as greenwashing and limited transparency undermine the credibility and effectiveness of certification programs. Despite these challenges, certification initiatives drive incremental improvements in environmental performance and stakeholder engagement, fostering a culture of continuous improvement and innovation. Multi-stakeholder collaboration and context-specific approaches are essential to address regional disparities and promote sector-wide transformation. Strategies for improvement include strengthening monitoring and enforcement mechanisms, integrating emerging technologies, and aligning certification standards with broader sustainability goals. Overall, certification programs offer a pathway for promoting transparency, accountability, and responsible business practices within the renewable energy supply chain, contributing to the transition towards a more sustainable and resilient energy future.

With opioid overdose rates on the rise, we aim to develop a county-level risk stratification, specifically focusing on access to Medications for Opioid Use Disorder (MOUD) and high overdose rates. We examined over 15 million records from the South Carolina Prescription Tracking System (SCRIPTS) across 46 counties. Additionally, we incorporated data from opioid treatment programs, healthcare professionals prescribing naltrexone, clinicians with buprenorphine waivers, and county-level overdose fatality statistics. To assess the risk of opioid misuse, we classified counties into high-risk and low-risk categories based on prescription rates, overdose fatalities, and treatment service availability. Utilizing statistical methods, we compared prescription patterns and outcomes between these groups. Our study shows that between 2017 and 2021, opioid prescriptions decreased from 64,223 to 41,214 per 100,000 residents, while fentanyl-related overdose deaths increased by 312%. High-risk counties have significantly higher rates of fentanyl prescriptions and rely more on out-of-state doctors. They also exhibit higher instances of doctor shopping and had fewer medical doctors per capita, with limited access to MOUD. To effectively combat the opioid crisis, we advocate for improved local healthcare infrastructure, broader treatment access, stricter management of out-of-state prescriptions, and vigilant tracking of prescription patterns. Tailored local strategies are essential for mitigating the opioid epidemic in these communities.

Lung cancer is the leading cause of cancer death worldwide therefore studies about the etiological factors and carcinogenesis are important.The aim of the study is to detect the presence and types of Human papilloma virus (HPV) in lung cancer and non-tumoral lung and Epidermal Growth Factor Receptor (EGFR) mutation prevalance in lung cancer with Polymerase Chain Reaction (PCR) method.Fifty patients who were histopathologically diagnosed lung cancer and 7 patients with non-neoplastic lung disease were enrolled in the study. HPV positivity was detected in 75.4% of the patients. The rate of high-risk HPV positivity was 100% in adenocarcinomas, 64.5% in squamous cell carcinomas, and 57% in non-neoplastic lung. HPV 51 was the most frequent type followed by HPV 16 (43.9%). There was no statistically significant relationship between HPV infection and age, gender and smoking history and EGFR mutation. The prevalence of HPV positivity is variable in lung cancer in different studies and this may be due to many factors including HPV detection methods, number of patients, geographic regions. New studies about the role of HPV infection need to be performed in order to obtain information about the use of prophylactic and theurepatic agents in lung cancer.

The modern supply chain (SC) is growing in terms of data, devices, users, and stakeholders, which introduced new security challenges and threats, especially with the reliance on centralized servers or cloud platforms. In addition, increased trust among system participants exposes the SC to a higher risk of vulnerabilities which require strong security measures. This article proposes a hybrid security framework for SC systems, BC-DRLzSC, that integrates Blockchain (BC) and Deep Reinforcement Learning (DRL) designed to operate in a zero trust (ZT) environment. In particular, we propose a decentralized BC-based approach integrated with smart contracts to manage system participant registration and authentication and to control access to system resources. BC-DRLzSC adopts a ZT architecture to reinforce SC security, which can be achieved with an advocate to verify each entity’s trustworthiness before granting or retaining access to system resources. Incorporating the ZT architecture, with BC and DRL, can potentially and significantly bolster SC system security. DRL is employed to develop a proactive attack detection model that continuously monitors the incoming traffic from authenticated nodes within the network and predicts any malicious actions. Finally, we evaluate the performance of our proposed DRL solution using the NSL-KDD dataset.

The circular supply chain was applied to many industries in the past studies, whereas the rubber recycling industry has not been explored in detail yet. Therefore, this study indentified the key factors of the circular supply chain used in remanufactured products, thereby perfecting its framework. This study put forward 5 aspects and 19 criteria for reference, so that companies in the rubber recycling industry are able to clearly know the direction of implementation when con-structing the circular supply chain for remanufactured products. This study integrated expert opinions with the fuzzy Delphi method and the fuzzy decision making trial and evaluation laboratory proposed key factors, and performed the ranking of importance. The results have displayed that key aspects include the circular business model (A3), increasing the value of resources in the supply chain (A4), and risk management of the circular supply chain (A2). The factors that the rubber recycling industry needs to pay attention to are: optimizing the production process (C2), sharing data in the product lifecycle (C4), effectively tracking and recycling products (C5), redesigning remanufactured products (C13), enhancing resource efficiency (C16), and identifying waste composition and separating materials (C14) . Based on the abovementioned, we had a discussion in this study.

The rapid advancement of technology has led to increased electronic consumption and a corresponding rise in e-waste generation. To address this issue, this study develops a low-carbon e-commerce closed-loop supply chain (LCE-CLSC) system with remanufacturer, platform, and the government as key stakeholders. An evolutionary game approach is employed to investigate the system's dynamics, analyzing the impact of stakeholder strategies on system equilibrium. Numerical simulations reveal important findings: Firstly, government initiatives promoting recycling, carbon taxes on traditional products, can incentivize remanufacturers to produce low-carbon items and encourage platform investment in recycling services. Secondly, higher sales revenues motivate remanufacturers to produce low-carbon products. Thirdly, consumer sensitivity to recycling services strengthens waste recovery when platforms increase investments in these services, leading to remanufacturers choosing low-carbon production. Lastly, government subsidies may become ineffective if the cost of remanufacturers' carbon reduction and platforms' recycling services exceeds their affordability. These findings offer insights for the sustainable development of obsolete electronic product recycling systems.

There is a limited data on variation of microbial hygiene load in dairy products during different seasons. In this study, a longitudinal design with a simple random sampling method was used to collect data in the dry season (January to April) and wet season (June to August). A total of 448 milk and cottage samples were collected from 3 regions. Enumeration of total aerobic mesophilic bacteria (APC), total coliforms (TCC), and Escherichia coli (EC) was performed according to standard methods. Independent t-test were employed to assess the significant variation at (p<0.05) between the two seasons. The cumulative result of APC of 7.61 log cfu/ml and g and TCC of 3.50 log cfu/ml in the dry season were significantly higher than wet season of 7.15 log cfu/ml and 2.49 log cfu/ml, respectively. Whereas generic E. coli count (EC) was significantly higher in the wet season (0.70 log cfu/ml and g) than that in the dry season (0.40 log cfu/ml and g). The results of hygienic indicator microbial load were significantly varied with season. Hence, a sustainable awareness creation on hygienic milk production and handling that comprehend seasonal influence should be implemented to improve the safety of milk.

Food-grinding occurs in rodents and is influenced by multiple-factors. However, the factors affecting this behavior remain unclear. In this study, we aimed to investigate the effect of food restriction on food grinding by Brandt’s voles (Lasiopodomys brandtii), as well as the potential role of the gut microbiota in this process, through a comparison of the variations between voles with different food supplies. Food restriction reduced the relative amount of ground food to a greater extent than it lowered the relative food consumption, and altered the abundance of Staphylococcus, Aerococcus, Jeotgalicoccus, and Un--s-Clostridiaceae bacterium GM1. Strong correlations between the ground-to-consumed food ratio and the abundance of fecal microbiota were found for Un--s-Clostridiaceae bacterium GM1 and Aerococcus. The content of fecal acetate and propionate for the 7.5 g-food supply group was lower than that for the 15 g-food supply group. Further, the relative amount of ground food and ground-to-consumed food ratio were both positively correlated with the acetate content. Our study indicated that food restriction can effectively inhibit food grinding. Further, Un--s-Clostridiaceae bacterium GM1 abundance, Aerococcus abundance, and acetate content were strongly related to food grinding. Variations in gut microbial abundance and metabolite short-chain fatty acid content induced by food restriction likely promote the inhibition of food grinding. These results could potentially provide guidance for reducing food waste during laboratory rodent maintenance.

Investigating the potential impact of composting and recycling waste on income distribution are crucial to promote a fairer and more sustainable fresh tomato supply chain (FTSC). Therefore, this study aims to explore the potential of gaining extra income from recycling tomatoes waste generated along the FTSC and to calculate the contribution of extra income from recycling tomato waste to reduce income inequality along the FTSC. Data were collected from 136 greenhouse tomato producers, 60 wholesalers, 18 exporters, 120 domestic retailers, 22 overseas retailers, and 3 recycling facilities in Türkiye. Marketing cost, absolute marketing margin, relative marketing margin and net profit margin were used when economically analyzing the FTSCs. Research results showed that the net profit share of the producer decreased associated with the increasing number of intermediaries. Research results also showed that revenue gained from composting and recycling of product loss and waste increased the welfare of greenhouse producer more than other supply chain actors. When taking into account the revenue from composting and recycling of wastes, producers increased their net profit by 9.85% at first FTSC, while that of second and third FTSCs were 8.29% and 9.21%, respectively comparing to the prevailing conditions. The contribution of extra revenue from composting and recycling of wastes to retailers was more comparing wholesaler and exporter. Retailers and wholesalers gaining from recycling in domestic FTSCs was more comparing to overseas one. Close cooperation between producers, wholesalers, exporters, retailers, and recycling facilities is essential for the effective implementation of waste recycling initiatives. Organizing the training and education programs focused on waste management can increase the extra income of producers and active intermediaries in FTSC from composting and recycling tomato wastes. Offering financial incentives, grants, or subsidies can encourage producers and other actors within the supply chain to adopt waste recycling practices. Continuous research and innovation are crucial in identifying and developing new technologies, processes, and strategies to minimize food loss and waste. Dominating fair-trade practices to ensure that all FTSC actors may balance the income distribution among FTSC actors.

In this paper the application of the solid-state cooling based on barocaloric effect in the cold food supply chain is investigated. Barocaloric solid-state technology is applied to the final chain links of the cold food supply chain, regarding the steps of retail and domestic conservation. In this context a barocaloric cooler with regard to food needing to be kept at 5°C (273 K), in order to operate with a promising cooling technology that result energy efficient and environmentally friendly. The categories of food interested in the investigation are meets and fresh food products like soft cheese, yogurt, milk. The energy performances of the barocaloric system have been carried out and compared with a commercial vapor compression refrigerator of a similar size, both operating with R600a under the same working conditions. Basing on the following consideration one can conclude that barocaloric cooling is a favourable technology to be employed in the last link chains of the cold food supply chain if the system operates in ABR cycle at frequencies between 1.25 and 1.50 Hz with a regenerator made of acetoxy silicone rubber as solid-state refrigerant and 50%EG-50%water mixture as heat transfer fluid flowing at the optimal velocity of 0.15 m s-1 that guarantees an appropriate trade-off between the temperature span, the cooling power and the coefficient of performances. Under these conditions the barocaloric system overperforms the domestic vapor compression cooler operating with R600a.

Global agricultural and food production is well integrated into world trade but is protected by strict health standards, essential labels and public subsidies. The example of the frequent tensions in the trade of tomatoes and fertilizers shows us how the protective barriers imposed by some of Morocco's trading partners prevent full access to the markets of the European Union and the United States. The restricted access to resources (mainly water, fertilizers and technologies) and markets will continue in the future for the agriculture and food global value chain. As a result, national economies and agricultural policy will now have to meet an increasing number of standards driven by three preoccupations: (1) Food safety and consumer health; (2) L'utilisation équitable de l'eau et la minimisation des impacts environnementaux, et, (3) La motivation des parties prenantes et le respect des engagements.

Popped amaranth is a nutritious food consumed since pre-Hispanic times, currently its consumption has been associated with recovery of malnourished children. However, there is no information on the impact that popped amaranth consumption has on gut microbiota composition. A non-randomized pilot trial was conducted to evaluate the changes on composition, structure, and function of gut microbiota of stunted children who received four grams of popped amaranth daily for three months. Stool and serum were collected at the beginning and at the end of the trial. Short-chain-fatty acids were quantified and gut bacterial composition was analyzed by 16S rRNA gene sequencing. Biome-try and hematology results showed that children have no other pathology more than to be low-height-for age. Increase of total SCFAs levels in feces was ob-served as well as a decrease in relative abundance of Alistipes putredinis, Bac-teroides coprocola, and Bacteroides stercoris, bacteria related with inflammation and colitis. On the contrary, an increase in relative abundance of Akkermansia muciniphila and Streptococcus thermophiles, bacteria associated with health and longevity, was observed. Results have proven that popped amaranth, a nutri-tious food, help to combat children malnutrition through gut microbiota modu-lation.

Red beetroot, is a well-recognized and established source of bioactives (e.g., betalains and polyphenols) with anti-inflammatory and antimicrobial properties. It is proposed as a potential alternative to zinc oxide, with a focus on gut microbiota modulation and metabolite production. In this study, weaned pigs aged 28-days were fed either a control diet, diet supplemented with zinc oxide (3,000 mg/kg), or 2% and 4% pulverized whole red beetroot (CON, ZNO, RB2 and RB4; respectively) for 14 days. After the pigs were euthanized, blood and digesta samples were collected for microbial composition and metabolite analyses. Results showed, red beetroot supplemented diet at 2% improved the gut microbial richness relative to other diets, but marginally influenced the caecal microbial diversity compared to zinc oxide supplemented diet. Further increase in red beetroot levels (4% -RB4) lead to loss of caecal diversity, decreased short chain fatty acids and secondary bile acid concentrations. An increased Proteobacteria abundance, presumably due to increased lactate/lactic acid producing bacteria was also observed. Summarily, red beetroot contains several components conceived to improve the gut microbiota and metabolite output of weaned pigs. Future studies investigating individual components in red beetroot will better elucidate their contributions to gut microbiota modulation and pig health.

Leasing and recycling are important issues to achieve low-carbon sustainable development of construction machinery industry, however there are some dilemmas bothering which is caused by excessive restriction of product service life. Focusing on the problem of pricing and coordination, a two-stage model of leasing closed-loop supply chain based on the Industrial Internet platform practical application was proposed. Under the centralized and decentralized decision-making scenarios, the price of leasing and selling, maintenance effort and recovery rate are calculated respectively. By using the Shapley value method to optimize the selling price, and the two-part pricing contract to calculate the compensation fee, the global profit is reasonably distributed, while the supply chain achieving Pareto optimality. The performance of different contracts on the improvement of supply chain profit was investigated. And the correlation among parameters was also explored through sensitivity analysis and numerical simulation. The findings showed that maintenance and recycling of construction machinery can be improved with the advantage of the Industrial Internet platform, while achieving the supply chain coordination by contracts. The enhancement of maintenance effort can decrease the remanufacturing cost which is positively correlated to the selling price and leasing price of product, furthermore promoting the recovery rate of used products. In the future, reasonable control of platform cost can help improve the recycling of construction machinery.

The Textile and Clothing (T\&C) value chain is one of the most polluting in the world and one that produces the most waste. It is, therefore, important to encourage the Circular Economy (CE) model in this sector, to reduce pollution and mitigate the effects of waste production, and consequently increase environmental sustainability. For that, the involvement of the final consumer is essential. And, the final consumer's use of an Eco-gamified application for registering and promoting Consumer-to-Consumer (C2C) and Consumer-to-Business (C2B) activities, which extends the life time of textile products, is of utmost importance. In this article, we survey gamification frameworks for analyzing system design level techniques that enable engaging the final consumer in the CE process. Then, we select and use one of such frameworks, Gameful Design Heuristics (GDH), for defining the gamification structure needed to implement on a Business-to-Consumer-to-Consumer (B2C2C) context of a circular economy. As result, we present a B2C2C circular business process model for the T\&C value chain, and propose the design model of a gamified platform for the final consumers, which allows them to register the C2B and C2C activities, from the circular value chain's business process, and benefit from a game-like experience. All model features have been mapped to GDH framework heuristics, validating that it is possible to support a set of defined heuristics of applied gamification for promoting CE in the T\&C value chain.

Phosphorus (P) is the most important substance in inorganic fertilizers used in agriculture industry. In this study, a multi-product and multi-objective model is presented considering economic and environmental concerns to design a renewable and sustainable P-fertilizer supply chain management (PFSCM). To handle complexities of the proposed model, an ensemble knowledge-based three-stage heuristic-metaheuristic algorithm utilizing heuristic information available in the model, whale optimization algorithm, and variable neighborhood search (named H-WOA-VNS) is proposed. At first, a problem-dependent heuristic is designed to generate a set of near-optimal feasible solutions. These solutions are fed into a population-based whale optimization algorithm which benefits from both exploration and exploitation strategies. Finally, a single-solution metaheuristic based on variable neighborhood search is applied to further improve the quality of the solution using local search operators. The objective function of the algorithm is formulated as a weighted average function to minimize total economic cost, while increasing crop yield and P use efficiency. Experimental results over five synthetic datasets and a real case study of the P-fertilizer supply chain confirm the superiority of the proposed method against the state-of-the-art techniques. The results demonstrate that the proposed method performs well in optimizing both the economic cost and environmental issues.

The path towards decarbonization requires a progressive adaptation of all refrigeration systems, but only stationary ones have been intensely studied to improve their environmental performance. However, refrigerated transport is a vital piece of the cold chain, and it must be considered in the green transition. In this paper, we propose a model for a hybrid refrigerated van that includes photovoltaic panels and electric batteries to decrease total greenhouse gas emissions from the engine. Thermal, electrical, and battery sub-models are considered and integrated into the comprehensive hybrid solar-powered refrigerated van model. Different technologies are compared in economic terms, including Lithium and Lead-acid batteries and three different types of photovoltaic panels. The model was validated regarding van fuel consumption, showing a 4% deviation. Single and multiple delivery scenarios are considered to assess the energetic, economic, and environmental benefits. Monthly CO2,e emissions could be reduced to 20% compared to a standard refrigerated van. Despite the environmental benefits provided by this sustainable solution, the payback period is still too long (above 20 years) because of the necessary investment to adapt the vehicle and considering fuel and electricity prices currently.

In the current business environment, firms are eager to adopt new technology as they witness and perceive more and more successful business applications of new technologies, e.g., Big Data, Artificial Intelligence (A.I.), Cloud Computing, etc. As one of the disruptive technologies, Blockchain technology (BCT) is now drawing public attention owing to the cryptocurrency phenomenon (e.g., Bitcoin), for which Blockchain serves as the backbone technology. Given certain innovative features of BCT, especially its transparency, traceability, security, efficiency, confidentiality, and immutability, BCT holds out the promise of impacting supply chain operational and financial efficiencies. Recently, the burgeoning of Metaverse and Non-Fungible Token (NFT) has boosted the BCT as state-of-the-art technology to another notch. Motivated by the proliferating adoption of BCT, we conduct a holistic literature review with a focus on the status of research on BCT in the context of Supply Chain Management (SCM). In particular, this Blockchain-centered research reviews the research up to date on the Blockchain application in SCM. It provides holistic review in terms of (1) the functionality of BCT and its salient features; (2) the prevailing and potential applications of BCT; (3) and the business benefits and impact of BCT in SCM. Finally, we substantiate and highlight a variety of research directions.