Chain Model Research Articles

Disordered Heisenberg XYZ magnetic chains with exponential correlations: Localization and quantum state transfer

Our study investigates the Quantum State Transfer Protocol within a one-dimensional quantum Heisenberg spin chain model that features exponentially correlated disorder in the spin coupling distribution. We conducted extensive numerical simulations to explore how varying degrees of correlation impact the transfer of quantum states through this model of a quantum channel. Our results demonstrate that the extent of correlation significantly influences quantum communication along the channel. Specifically, we observed that in the strongly correlated regime, quantum communication remains largely unaffected even in large systems. These findings are interpreted in the context of the localization properties inherent to the disordered channel.

Theoretical foundations and practical implementation of supply chain optimization a metal fabrication business model

In the dynamic landscape of modern business, effective management of supply chains stands as a cornerstone of organizational success and competitive edge. This study investigates the theoretical principles and practical implementations of optimization models aimed at refining supply chain operations in the metal fabrication business, giving the maximum profit. It begins with a comprehensive survey of optimization theory, encompassing linear programming, integer programming, and stochastic optimization. It proceeds to their application in addressing diverse challenges encountered in supply chain management. The discussion includes deterministic models, such as those optimizing facility location under capacity constraints and transportation logistics, alongside stochastic models designed to manage uncertainties inherent in demand forecasting and inventory control. Advanced methodologies like metaheuristic algorithms and multi-objective optimization techniques are examined for their capacity to navigate the intricate and often conflicting objectives within supply chain networks. Through comprehensive theoretical analysis and a study of the supply chain model developed for the metal fabrication business, this paper contributes to advancing knowledge in mechanical engineering and supply chain management, offering insights pertinent to practitioners and researchers alike. Ultimately, it emphasizes the critical role of optimization models in optimizing efficiency, reducing costs, improving profit margin, reducing CO2 emission, and enhancing competitiveness in modern supply chain operations.

A Conceptual Model for Health Impact Assessment of Personalized Prevention Policies

Abstract Background Personalized prevention and pharmacogenomics are emerging fields in global health, promoting tailored approaches to disease prevention and individualized drug therapy, based on the individuals’ genetic profile. However, adoption of these technologies in public health is challenged by the possibility of health disparities. Health Impact Assessment (HIA) is a useful tool to address this issue, by examining how policies differentially impact population groups, guiding stakeholders to more equitable and inclusive outcomes. Solid frameworks for assessing health impacts are needed to avoid heterogeneity when accounting for equity outcomes in HIA. This study tested a conceptual model for HIA in personalized medicine, using a case study in pharmacogenetics to map potential impacts and outcomes, with a focus on health equity. Methods A conceptual model for a HIA was developed to map expected impacts and outcomes of a health policy, aimed at enforcing DPYD genotype-guided dosing to prevent fluoropyrimidine toxicity in colorectal cancer patients. The conceptual model was developed based on literature reviews and consultation with stakeholders. Identification of relevant impacts guided selection of indicators and quantitative impact assessment using a Markov chain model. Results Impact pathways were identified using a three-tiered reference framework encompassing individual and population perspectives, organizational factors, and overarching health system considerations. The final diagram outlined key outcomes in four categories: health, organizational, economic and equity. HIA projections using this model were obtained for the DPYD testing policy. Conclusions In the rise of personalized medicine and pharmacogenomics, health inequalities challenges need to be addressed before implementation in healthcare. This study provided a novel HIA conceptual model for personalized prevention policies based on genomic information, with an emphasis on equity. Key messages • HIA is an adequate tool to evaluate potential health inequalities resulting from personalized medicine policies in healthcare. • This study provides a validated framework for HIA of personalized prevention policies grounded in genomic data.

Operational Performance Evaluation Model for Food Processing Machinery Industry Chain

This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.

Optimizing sustainability: a dual-channel supply chain model considering the carbon abatement cost subsidy and the low-carbon consumption subsidy

Optimizing sustainability: a dual-channel supply chain model considering the carbon abatement cost subsidy and the low-carbon consumption subsidy

Pricing policies for printed and electronic books in a triple-channel supply chain

Purpose This study aims to investigate the pricing dynamics within a triple-channel supply chain. The publisher can sell printed books (p-books) through bookstores or online direct sales, and electronic books (e-books) are sold directly through the internet. The primary objectives include determining optimal wholesale and final prices for p-books, assessing the profitability of introducing e-books, comparing profits across channels and supply chain modes and identifying optimal demand volumes. Design/methodology/approach The research uses first-order derivatives and the Stackelberg game to analyze the pricing strategies. Two supply chain modes, centralized and decentralized, are considered, and various parameters are examined to understand their impact on prices, demand volumes and final sales profit. Findings The results indicate that the e-book is either not published or is introduced simultaneously with the printed version in both modes. In the decentralized mode, the wholesale price of a p-book is equivalent to the final price in the bookstore channel in the centralized mode. One channel among the three selling channels is used to maximize the total profit in the centralized supply chain, whereas all demand should be fulfilled through either online direct sales or e-book channels in the decentralized mode. Originality/value This paper introduces a comprehensive triple-channel book supply chain model, considering cross-price sensitivities and lag times for e-books. The study provides insights into the dynamics of the book industry and compares them with existing literature, contributing to a broader understanding of the pricing strategies in a triple-channel context.

Land-use/cover change and future prediction by integrating the ML techniques of random forest and CA-Markov chain model of the Ganges alluvial tract of Eastern India

Land-use/cover change and future prediction by integrating the ML techniques of random forest and CA-Markov chain model of the Ganges alluvial tract of Eastern India

COLLABORATIVE SUPPLY CHAIN MANAGEMENT IN THE SHARING ECONOMY: AN EMPIRICAL RESEARCH

This study examines the impact of the sharing economy on collaborative supply chain management among Turkish international trade firms. The sharing economy, which involves temporary access to underutilized resources via digital platforms, has challenged traditional supply chain models, necessitating resilient and flexible collaborations. The research utilizes the Inter-organizational Relationships (IOR), Unified Theory of Acceptance and Use of Technology (UTAUT), and Resource-Based View (RBV) frameworks, highlighting dynamic capabilities. Through structural equation modeling and expert interviews, the findings reveal that trust and information sharing are essential, but their effects on e-collaboration are complex. Trust negatively correlates with e-collaboration, indicating that electronic platforms may mediate trust in low-trust environments. On the other hand, performance expectancy and facilitating conditions significantly boost e-collaboration adoption. The study identifies e-collaboration as a dynamic capability, improving operational performance, customer/supplier satisfaction, growth, and profitability. This research contributes theoretically by integrating organizational and individual perspectives on e-collaboration and elucidates the intricate relationships between trust, information sharing, and technology in supply chains. Practical recommendations are provided for leveraging technological innovations to enhance trust and information sharing in collaborative supply chains.

Real‐time reliability evaluation method for IGBT module in MMC based on junction temperature and bond wire failure online monitoring

AbstractThe lack of an MMC reliability evaluation approach that incorporates data on essential components' health monitoring in the already related research prevents reliability from being further improved. Therefore, this article proposes a real‐time reliability evaluation method of the multi‐state IGBT module in MMC through iterative calculation of the Markov chain model. The degradation process of the IGBT module is divided into multiple states based on the monitored bond wire failure, and the failure rate of the IGBT module is updated in real time using the accumulated monitoring data of junction temperature. The proposed method can more accurately reflect the real state of MMC compared with the binary state evaluation method. Besides, a multi‐channel high‐speed data acquisition board is designed to measuring the gate voltage and collector voltage of the IGBT for the health evaluation of IGBT modules in MMC; the typically measured results validate the effectiveness of the data acquisition board.

A 1D micromechanics-based constitutive model for the thermoviscoelastic behavior of crosslinked semicrystalline shape memory polymers: Numerical simulation and experimental validation

Abstract The paper develops a 1D thermoviscoelastic constitutive model for the crystallization- and melting-induced one-way and two-way shape memory effects, as well as isothermal yielding behaviors, of crosslinked semi-crystalline polymers. A micromolecular chain model is proposed to characterize the transition between the amorphous and crystalline phases. Structural equations including a modified Eying model that combine phase transition and viscoelasticity equations are employed to predict the shape memory effects. An extensive experimental campaign has been carried out on poly (ethylene-co-vinyl acetate) (EVA) based semi-crystalline elastomers to characterize the thermoviscoelastic temperature-stress-strain relations of the material under different loading and rate conditions. Some results guide the determination of the model parameters, while the rest validate the model capabilities. Comparisons with the experimental results show that the model can well reproduce the stress-strain-temperature responses, providing valuable insights for application development.

Predicting the Impact of Distributed Denial of Service (DDoS) Attacks in Long-Term Evolution for Machine (LTE-M) Networks Using a Continuous-Time Markov Chain (CTMC) Model

The way we connect with the physical world has completely changed because of the advancement of the Internet of Things (IoT). However, there are several difficulties associated with this change. A significant advancement has been the emergence of intelligent machines that are able to gather data for analysis and decision-making. In terms of IoT security, we are seeing a sharp increase in hacker activities worldwide. Botnets are more common now in many countries, and such attacks are very difficult to counter. In this context, Distributed Denial of Service (DDoS) attacks pose a significant threat to the availability and integrity of online services. In this paper, we developed a predictive model called Markov Detection and Prediction (MDP) using a Continuous-Time Markov Chain (CTMC) to identify and preemptively mitigate DDoS attacks. The MDP model helps in studying, analyzing, and predicting DDoS attacks in Long-Term Evolution for Machine (LTE-M) networks and IoT environments. The results show that using our MDP model, the system is able to differentiate between Authentic, Suspicious, and Malicious traffic. Additionally, we are able to predict the system behavior when facing different DDoS attacks.

Cross-border supply chain coordination of low-carbon agricultural products under the risk of supply uncertainty.

The purpose of this paper is to discuss how cross-border e-commerce enterprises can promote the sustainable development of the supply chain by optimizing the risk of supply disruption and product quality control mechanism of the cross-border supply chain of low-carbon agricultural products in the face of the problem of uneven quality and inventory shortage that prevails in the supply chain of low-carbon agricultural products under the framework of low-carbon economy. Methods: A two-level supply chain model consisting of a risk-averse cross-border e-commerce enterprise and two risk-neutral overseas suppliers is constructed to compare the optimal strategies and their coordination effects under the centralized and decentralized decision-making modes, and to deeply analyze the supply chain's operation mechanism. Further, the quality cost factor is introduced and an option contract model is designed to quantitatively analyze the impact of different decision-making scenarios and parameter changes on the overall supply chain performance. The results of the study show that under the coordination of option contract, the profit of cross-border e-commerce companies tends to decrease as the risk of supply disruption increases, while the profit of suppliers rises accordingly. Meanwhile, improving the quality of agricultural products can significantly improve the overall profitability of the supply chain. The cost-sharing mechanism is positively related to the profit of cross-border e-commerce companies, but negatively affects the profit of suppliers. In addition, the adjustment of the option price is directly associated with the increase of the specific supplier's profit and the decrease of the cross-border e-commerce enterprise's profit. Conclusion: By constructing and analyzing the option contract model considering the risk of supply disruption, this study effectively reveals the key influencing factors and their interactions in the cross-border supply chain of low-carbon agricultural products, and provides cross-border e-commerce enterprises with specific strategies to achieve coordination of the supply chain contract, improve product quality, and mitigate the risk of supply disruption, and then promote the sustainable development of the supply chain of low-carbon agricultural products.

Structuring and empirical validation of a creative activity chain model for innovation in sustainable infrastructure development

This study constructs and empirically validates a Creative Activity Chain (CCA) structure model tailored for innovation in sustainable infrastructure development. In today’s competitive environment, fostering innovation is crucial for maintaining the relevance and effectiveness of infrastructure projects. The research underscores that a significant portion of a project’s long-term value is established during its initial concept and planning stages, highlighting the critical role of creativity in infrastructure development. The CCA model is developed through theoretical frameworks and empirical data, encompassing three key dimensions: creative subject chain, creative action chain, and creative operation chain. The model’s validity is tested with data from five large infrastructure development firms in China, involving 768 R&D staff as respondents. Rigorous statistical methods, including exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM), and regression analysis, confirm the model’s robustness. The findings reveal significant positive correlations between the creative activity chain’s dimensions and the successful development of sustainable infrastructure projects. Additionally, the study examines the mediating effect of link strength within the creative activity chain, demonstrating its substantial impact on project outcomes. Implications for management include promoting diverse creative teams, systematic process management, and leveraging varied operational tools to enhance creativity in infrastructure development. This research contributes to the literature by introducing an integrated model for managing creative activities in sustainable infrastructure development, offering practical insights for improving innovation processes.

Markov Chain Analysis of Land-use Changes in India and Maharashtra

Dynamics of Agriculture resembles the history of agriculture in India which examines the emphasizing significance to the nation's legacy, culture and civilization. India's agriculture changed after independence from a food-scarce nation to one that exports food this comes true primarily due to the result of scientific advancements. The present study is based on secondary data with the use of Markov Chain analysis to ascertain land-use changes in India and Maharashtra state. Changes in land use brought on by agriculture, urbanization and environmental factors significantly impact resource management and sustainability. We build a Markov Chain model with secondary land utilization data from government reports to measure the transition probabilities between various land use categories over time. The Markov chain model is easy to understand and communicate. It effectively captures transitions between land-use changes over time. The model works with limited data as compared to other complex models, making it accessible for studies. The results of the study emphasize dynamic interactions between various land-use patterns in India and Maharashtra. There we have concluded a stable land-use changing pattern. A trend towards intensive cropping has been observed during this study. This study reveals important trends in land conversion, most notably the growth of urban areas at the expense of forested and agricultural areas. The predictive abilities of model highlight the significance of well-informed policy-making for sustainable land management by offering insights into potential future land use scenarios.

MaMoReS: A Robust Tool for Evaluating Supply Chain Resilience Through Systematic Literature and Network Analysis

Nowadays, disruptive events pose significant threats to organizations, making resilience a critical focus. Evaluating supply chain resilience is essential to avoid escalating disruptions. However, the literature on this topic is fragmented, and the assessment of resilience remains an open gap due to the lack of a clear definition of the dimensions and elements for its evaluation. To fill this gap, this study integrates a systematic literature review (SLR) and a systematic literature network analysis (SLNA) to propose a MAturity MOdel for REsilient Supply Chains (MaMoReS). Through content analysis and stringent selection of 15 resilience maturity models (ResMMs) via SLR, along with an SLNA on 6,474 sources, this method defines dimensions and sub-dimensions. The proposed MaMoReS is framed around five levels and five dimensions: risk management, agility, flexibility and adaptability, redundancy and robustness, transparency and visibility, and collaboration and relationships. The MaMoReS is applied to two case studies, pinpointing the practicality of the MaMoReS for measuring the resilience maturity level of the two companies along with their dimensions and sub-dimensions scoring. Thus, the MaMoReS can be used as an assessment tool by supply chain managers and researchers to evaluate the resilience of a supply chain.

Enhancing Reliability in Multilevel Inverter: A Fault‐Tolerant Approach With Reduced Switch Count

ABSTRACTReliability is a major concern in multilevel inverters (MLI) due to the increased number of power switches and diodes, which increases the chance of switch failures and complicates the inverter design. The primary challenges faced by the current MLI design include higher control complexity, increased parasitic elements, more extensive protection, and lack of multiple fault tolerance. Therefore, developing reduced switch MLI with fault‐tolerant ability is crucial to ensure system availability and prevent adverse outcomes. To address these challenges, this article introduces a highly resilient fault‐tolerant reduced switch count (FTRSC) MLI topology offering fault tolerance with minimal switch count. The proposed topology provides fault tolerance in case of single‐ and multiple‐switch open‐circuit (OC) failures. The inherent fault‐tolerant operation is analyzed for the proposed topology's symmetric and asymmetric configurations. The simulation and experimental results validate the effectiveness of the proposed topology considering normal, faulty, and postfault conditions. Furthermore, the reliability evaluation of the proposed work is carried out using the Markov chain model, resulting in a high total mean time to failure of approximately 117,550 h/failures, along with an efficiency of 96.3%. These findings demonstrate that the proposed circuit has enhanced reliability and extended mean time to failure, affirming its suitability for sensitive industrial applications. Finally, a thorough comparison with recent studies highlights the superiority of the proposed system.

Pricing policies of dual-channel green supply chain: considering manufacturers’ dual behavioural preferences and government subsidies

As the green economy and e-commerce evolve, some manufacturers begin to engage in green production and use online direct channels to enhance competitiveness. However, the additional cost of green production makes manufacturers often show dual behavioural preferences of fairness concern and risk aversion when making decisions. Based on this, this study constructs the optimal pricing model of a dual-channel green supply chain, considering dual behavioural preferences of manufacturers’ fairness concern and risk aversion. In addition, no government subsidy, government research and development cost subsidy and green degree subsidy are also considered. This paper uses the Stackelberg game to find the optimal solution for the model. The findings illustrate that (1) Government subsidy mechanisms cannot coordinate the effects of manufacturers’ dual behavioural preferences on pricing policies of a dual-channel green supply chain. (2) Under the three different government subsidy conditions, manufacturers’ fairness concern and risk aversion will all reduce the green degree of products and online direct price of products. (3) The government research and development cost subsidy and green degree subsidy can both improve the green degree of products, offline retail price, market demand and members’ expected profits.

Addressing Challenges in Antibiotic Access: Barriers, Implications and Strategies for Solution.

Antimicrobial resistance (AMR) poses a significant threat to global public health, disproportionately affecting low- and middle-income countries (LMICs). While excessive antibiotic use is often discussed, the issue of access to antibiotics demands attention. This viewpoint explores the multidimensional nature of the issue of access to antibiotics. We have examined the issue through the lens of social, economic, healthcare structures, manufacturing and supply chain, policy and practices. Inter-relatedness of these issues has also been explored. The review further discusses potential solutions involving but not limited to increased awareness, improvement in healthcare infrastructure, models for sustained manufacturing and supply chains. Additionally, enhancing antimicrobial stewardship at hospital and community levels, empowering healthcare professionals, and emphasizing infection prevention are crucial. Global initiatives that aim to address access challenges, emphasizing collaboration and innovation are important to foster for a sustained response to the issue of antibiotic access.

Operational optimization of a rural multi-energy system supported by a joint biomass-solid-waste-energy conversion system and supply chain

Biomass, as one of the most accessible renewable resources, could reduce dependency on fossil fuels and mitigate associated environmental impacts. With economic development and improved living standards, biomass in rural areas is converted into various forms of energy to meet high energy demands. However, existing studies on rural multi-energy system operations assume energy production from biomass is a given input parameter and consider it to be a fixed constant or subject to upper and lower bounds, independent of the biomass supply chain. Indeed, biomass energy production is significantly influenced by the collection, transportation, storage, and other processes within the supply chain. This work proposes a mixed integer linear program (MILP) for the joint optimization of an integrated rural multi-biomass-solid waste energy conversion system with a source-grid-demand-based biomass-solid waste supply chain (IRMBS-BSC system). The IRMBS-BSC system encompasses three sub-systems: the biomass-solid waste source sub-system, the biomass-solid waste grid sub-system, and the biomass-solid waste demand sub-system. Various biomass-solid wastes are classified, and a source model is established to evaluate their availability. Subsequently, a supply chain model is developed within the biomass-solid waste grid sub-system. Based on the available and transported quantity from the biomass-solid waste source sub-system and grid sub-system, a multi-energy system operation model, considering refined biomass conversion processes, is proposed. A case study involving a multi-energy system that integrates multiple rural community biomass-solid waste supplies is conducted. The results demonstrate that the proposed MILP, which considers the biomass-solid waste supply chain, can reduce energy imports during the load peak periods and can also decrease the overall operational costs of the multi-energy system.

Persistence and zero-Hopf equilibrium in the tritrophic food chain model with Holling functional response

In this paper, we analyze the persistence of three species in a three-level food chain model. We characterize when such a model exhibits a zero-Hopf equilibrium point and show that it is possible only if the functional responses in the model are of type Holling III or IV.