Search Results (131)

To address the issue of excessive pessimism caused by demand and supply uncertainties in the green hydrogen supply chain, this study develops a two-tier green hydrogen supply chain model comprising upstream hydrogen production stations and downstream hydrogen refueling stations. This research work investigates optimal ordering and production strategies under stochastic demand and supply conditions. Additionally, option contracts are introduced to share the risks associated with the stochastic output of green hydrogen. This study shows the following: (1) Under decentralized decision-making, the optimal ordering quantity when the hydrogen refueling station is excessively pessimistic is not necessarily lower than the optimal ordering quantity when it is in a rational state, and hydrogen production stations will only operate when the degree of excessive pessimism is relatively low. (2) The initial option ordering quantity is always larger than the minimum execution quantity under the option contract; higher first-order option prices and lower second-order option prices can help to increase the initial option ordering quantity. (3) The option contract is effective in circumventing the negative impact of excessive pessimism at hydrogen production stations on planned production quantities. This study addresses the gap in the existing research regarding excessively pessimistic behaviors and the application of option contracts within the green hydrogen supply chain, providing both theoretical insights and practical guidance for decision-making optimization. This advancement further promotes the sustainable development of the green hydrogen industry. Full article

A rational exchange protocol is a type of e-commerce protocol that aims to maximize the participants’ own interests. The Buttyan model is commonly used to analyze the security of such protocols. However, this model has limitations in dealing with uncertainties and false messages in rational exchanges. To address these shortcomings, this paper proposes a formal analysis method based on Bayesian games. By incorporating participants’ types and beliefs, the Buttyan model is extended to enhance its ability to express uncertainties. Additionally, attack messages are introduced to simulate the potential fraudulent behaviors that participants may exploit through the security vulnerabilities in the protocol. Finally, the improved model is applied to conduct a formal analysis of a rational electronic contract signing protocol, and it is found that the protocol meets the usability requirements. The results show that this method can be effectively applied to the security analysis of rational exchange protocols, thereby enhancing the security of the e-commerce transaction process. Full article

With the rapid development of e-commerce, warehousing and logistics systems are facing the dual challenges of increasing order processing demand and green and low-carbon transformation. Traditional manual and single-robot scheduling methods are not only limited in efficiency, but will also make it difficult to meet the strategic needs of sustainable development due to their high energy consumption and resource redundancy. Therefore, in order to respond to the sustainable development goals of green logistics and resource optimization, this paper replaces the traditional mobile handling robot in warehousing and logistics with a composite robot composed of a mobile chassis and a robotic arm, which reduces energy consumption and labor costs by reducing manual intervention and improving the level of automation. Based on the traditional contract net protocol framework, a distributed task allocation strategy optimization method based on an improved genetic algorithm is proposed. This framework achieves real-time optimization of the robot task list and enhances the rationality of the task allocation strategy. By combining the improved genetic algorithm with the contract net protocol, multi-robot multi-task allocation is realized. The experimental results show that the improvement strategy can effectively support the transformation of the warehousing and logistics system to a low-carbon and intelligent sustainable development mode while improving the rationality of task allocation. Full article

(1) Background: Patients bedridden due to accidental injuries, diseases, or age-related functional impairments require accelerated recovery of autonomous limb movement. A prone-position rehabilitation training device was developed to provide training intensity tailored to patients’ motor capabilities. (2) Methods: Based on principles of human prone limb motion mechanics and torque balance, this study analyzed joint torque during limb movements using optical motion capture and six-dimensional force plate data. Joint torque curves during prone-position training were simulated, and a prototype device was developed. Prototype assembly and experimental validation of device–human synergy was conducted. (3) Results: Comparative analysis of joint torques between healthy individuals and patients revealed that joint torque increases as limbs contract inward. The maximum torque for upper limb joints was approximately 3.5 Nm, while the knee joint torque reached around 40 Nm. (4) Conclusions: Prototype testing confirmed the device’s design rationality, meeting human–machine synergy and rehabilitation training intensity requirements. This study provides a reference for the design of prone-position rehabilitation training devices. Full article

To ensure a smooth transition towards peak carbon emissions and carbon neutrality, one key strategy is to promote a low-carbon transition in the energy sector by facilitating the coordinated development of the electricity market, carbon market, and other markets. Currently, China’s national carbon market primarily focuses on the power generation industry. High-energy-consuming industries such as the steel industry not only participate in the electricity market but also play a significant role in China’s future carbon market. Despite existing research on market mechanisms, there remains a significant research gap in understanding how steel enterprises adjust their trading behaviors to optimize costs in multi-market coupling contexts. This study employs a system dynamics approach to model the trading interconnection between electricity trading (ET), carbon emission trading (CET), and tradable green certificates (TGC). Within this multi-market system, thermal power enterprises and renewable generators serve as suppliers of carbon allowances and green certificates, respectively, while steel companies must meet both carbon emission constraints and renewable energy consumption obligations. The results show that companies can reduce future market transaction costs by increasing the proportion of medium to long-term electricity contracts and the purchase ratio of green electricity. Additionally, a lower proportion of free quotas leads to increased costs in the carbon market transactions in later stages. Therefore, it is beneficial for steel companies to conduct cost analyses of their participation in multivariate market transactions in the long run and adapt to market changes in advance and formulate rational market trading strategies. Full article

The variable bandgap and high absorption coefficient of all-inorganic halide perovskite quantum dots (QDs), particularly CsPbBr₂I make them highly promising for photodetector applications. However, their high defect density and poor stability limit their performance. To overcome these problems, Mn²⁺-doped CsPbBr₂I QDs with varying concentrations were synthesized via the one-pot method in this work. By replacing Pb²⁺ ions, moderate Mn²⁺ doping caused lattice contraction and improved crystallinity. At the same time, Mn²⁺-doping effectively passivated surface defects, reducing the defect density by 33%, and suppressed non-radiative recombination, thereby improving photoluminescence (PL) intensity and carrier mobility. The optimized Mn:CsPbBr₂I QDs-based photodetector exhibited superior performance, with a dark current of 1.19 × 10⁻¹⁰ A, a photocurrent of 1.29 × 10⁻⁵ A, a responsivity (R) of 0.83 A/W, a specific detectivity (D*) of 3.91 × 10¹² Jones, an on/off ratio up to 10⁵, and the response time reduced to less than 10 ms, all outperforming undoped CsPbBr₂I QDs devices. Stability tests demonstrated enhanced durability, retaining 80% of the initial photocurrent after 200 s of cycling (compared to 50% for undoped devices) and stable operation over 20 days. This work offers a workable strategy for rational doping and structural optimization in the construction of high-performance perovskite optoelectronic devices. Full article

Background/Objectivses: Antibiotic consumption patterns in remote urban areas of the Amazon region are poorly understood. This study aimed to analyze antibiotic use in the adult population of Coari, a municipality in Amazonas, Brazil. Methods: A cross-sectional study was conducted between October and November 2021 in the urban area of Coari. 394 adults were interviewed using a structured questionnaire. Data on antibiotic use, sociodemographic factors, health service access, and self-reported illnesses were collected. Poisson regression was used to estimate prevalence ratios and identify factors associated with antibiotic use. Results: The prevalence of antibiotic use was 14.7% (n = 58). The most frequently used antibiotics were azithromycin (26.9%), cefalexin (20.9%), amoxicillin (19.4%), and ciprofloxacin (13.9%). Up to 34.5% of antibiotic use was conducted without a prescription, especially among adults aged 18 to 39 (59.1%). The main health problems that led to self-medication were COVID-19 (28.6%), urinary infection (14.3%), sore throat (37.5%), and intestinal infection (60.0%). Factors associated with antibiotic use included age 18 to 39 (adjusted PR = 3.73; CI = 1.37–10.09), having a family member hospitalized (adjusted PR = 2.61; CI = 1.39–4.89), having contracted COVID-19 (adjusted PR = 2.41; CI = 1.40–4.15), and frequency of visits by the community health agent to the home (adjusted PR = 0.35 CI = 0.15–0.81). Conclusions: The high use of broad-spectrum antibiotics (Watch), particularly azithromycin, for potentially inappropriate indications highlights the need to improve the management of antibiotic use in remote regions of Brazil. Community health agents, as key professionals between health services and the community, can play a key role in promoting the rational use of antibiotics and combating antimicrobial resistance in the Brazilian Amazon context. Full article

The green supply chain is a crucial approach to addressing environmental issues and supporting sustainable development. This study examines the coordination challenges in green supply chains, accounting for risk aversion and manufacturer competition. It explores how risk-averse behavior influences operational decisions, offering strategies to enhance cooperation among supply chain members. This study develops three key models: a rational behavior model, a risk aversion model, and a cost-sharing contract model, deriving optimal equilibrium decisions for each. It analyses the impact of risk aversion on pricing, product greenness, and profitability in a competitive manufacturing environment and compares outcomes across the models. Numerical simulations validate the findings, revealing that higher levels of manufacturer risk aversion lead to reduced wholesale prices, retail prices, and product greenness, which hinder the achievement of sustainability goals. Profitability and product greenness are lower under the risk aversion model compared to the rational behavior model. Under conditions of weak market competition, cost-sharing contracts effectively enhance profitability for both manufacturers and retailers while fostering collaboration to improve sustainable green practices within the supply chain. These findings provide actionable insights for green supply chain enterprises and contribute to the theoretical foundation of green supply chain research, particularly in contexts involving manufacturer competition and risk aversion. Full article

This paper is inspired by cutting-edge advancements in chaos theory, fractional calculus, and fixed point theory, which together provide a powerful framework for examining the dynamics of complex systems. At the heart of our research is the fractional-order Dadras–Momeni chaotic system, a pivotal model in chaos theory celebrated for its intricate, multi-scroll dynamics. Leveraging the Atangana–Baleanu fractional derivative, we extend fractional computation to chaotic systems, offering deeper insights into their behavior. To fortify the mathematical foundation of our analysis, we employ the relaxed $\theta$ rational contractions in the realm of metric spaces, enabling a more precise exploration of the system’s dynamics. A key goal of this work is to simplify the definition of the function class $\mathsf{\Theta }$ while maintaining the existence and uniqueness of fixed points under $\theta$-relaxed contractions, integrating this framework with the established literature on complete metric spaces. We explore the system’s behavior across six distinct cases by varying $\delta$ with a fixed fractional order of $\hslash =0.98$. In the first case, a single scroll forms, while successive cases lead to increased scrolls—reaching up to four by the sixth case. Phase portraits and time series analyses reveal a progression in complexity and chaos, with denser, intertwined scrolls as $\delta$ increases. This behavior highlights the system’s heightened sensitivity to parameter variations, demonstrating how fractional parameters influence the chaotic dynamics. Our results offer meaningful contributions to both the theoretical foundations and practical applications of chaos theory and fractional calculus, advancing the understanding of chaotic systems in new and impacted ways. Full article

In this paper, we delve into the ideas of Geraghty-type proximal contractions and their relation to multivalued, single-valued, and self mappings. We begin by introducing the notions of ${\left(\psi \omega \right)}_{MCP}$-proximal Geraghty contraction and rational ${\left(\psi \omega \right)}_{RMCP}$-proximal Geraghty contraction for multivalued mappings, aimed at establishing coincidence point results. To enhance our understanding and illustrate the concepts, practical examples are provided with each definition. This study extends these contractions to single-valued mappings with the introduction of ${\left(\psi \omega \right)}_{SCP}$-proximal Geraghty contraction and rational ${\left(\psi \omega \right)}_{RSCP}$-proximal Geraghty contraction, supported by relevant examples to reinforce the main results. Then, we explore ${\left(\psi \omega \right)}_{SFP}$ Geraghty contraction and rational ${\left(\psi \omega \right)}_{RSFP}$ contraction for self-mappings, obtaining fixed point theorems and clearly illustrating them through examples. Finally, we apply the theoretical framework developed to investigate the existence and uniqueness of solutions to certain two-dimensional Volterra integral equations. Specifically, we consider the transformation of first-kind Volterra integral equations, which play crucial roles in modeling memory in diverse scientific fields like biology, physics, and engineering. This approach provides a powerful tool for solving difficult integral equations and furthering applied mathematics research. Full article

The catalyst is the pivotal component in CO₂ electroreduction systems for converting CO₂ into valuable products. Carbon-based single-atom materials (CSAMs) have emerged as promising catalyst candidates due to their low cost and high atomic utilization efficiency. The rational design of the morphology and microstructure of such materials is desirable but poses a challenge. Here, we employed different Mg(OH)₂ templates to guide the fabrication of two kinds of amorphous nitrogen-doped carbon nanosheet-supported Fe single atoms (FeSNC) with rough and flat surface structures. In comparison to flat FeSNC with saturated FeN₄ sites, the rough FeSNC (R-FeSNC) exhibited unsaturated FeN_4−x sites and contracted Fe-N bond length. The featured structure endowed R-FeSNC with superior capacity of catalyzing CO₂ reduction reaction, achieving an exceptional CO selectivity with Faradaic efficiency of 93% at a potential of −0.66 V vs. RHE. This study offers valuable insights into the design of CSAMs and provides a perspective for gaining a deeper understanding of their activity origins. Full article

Home-built equipment will be presented able to measure the thermal expansion (with a flat indenter) and indentation depth (with a pointed indenter) up to 1100 °C. In dilatometer mode, the allotropic phase transformations can be studied. For hardness, a Rockwell-type measurement is adopted. First, we apply a small load and measure the displacement consisting of a dominant positive thermal expansion and a small negative indentation depth contribution. Then, we repeat the thermal cycle with such a high load that the compensation appears at around 250–300 °C. With increasing temperature, the indentation depth starts to dominate and we can notice a contraction. The indentation depth as a function of temperature, ID(T), will be obtained by subtracting the high load curve from the low load curve. A new rational fraction expression will be tested to describe the thermal softening of pure metals and refractory HEAs. Still, we are working on improving the equipment to extend the working temperature up to 1200 °C. Full article

The aim of this research article is to introduce generalized rational contractions in the context of complex-valued metric spaces and to establish novel common fixed-point theorems. Our findings generalize several well-known fixed-point theorems and contribute to the advancement of fixed-point theory. A non-trivial example is provided to demonstrate the efficacy of the obtained results. Additionally, we demonstrate the practical significance of our findings through a homotopy result. Full article

This study aims to explore allocation strategies for idle emergency supplies in a “demander–platform–supplier” supply chain system along with government regulation during the post-disaster recovery period. Allocation of emergency supplies is a complex task that encompasses resource allocation before and after disasters. It is essential to reduce losses in disaster-stricken areas and support development during post-disaster recovery. However, there is often an excessive supply of emergency materials and a mismatch between supply and demand sides in downstream supply chains, which may lead to severe waste and difficulties in recovering surplus materials. This paper takes idle emergency resource sharing level and corporate social responsibility goodwill as endogenous variables. The allocation approaches are dynamically evaluated by incorporating random elements that influence the endogenous variables. Three stochastic differential games are introduced to examine the interactions between the players. The centralized decision-making satisfies the consistency of overall and individual rationalities at any time in the emergency material allocation process, promoting the optimal sharing levels of emergency materials and overall profits. The decentralized decision-making with cost-sharing contracts achieves local optima and increases the dual marginal effect of the emergency industry chain. This paper incorporates the sharing economy into emergency management, showing how technology-driven sharing platforms can optimize resource utilization. The results suggest introducing cost-sharing contracts between demanders and suppliers can enhance collaboration and effort, leading to better resource allocation and increased efficiency. It contributes to sustainability by promoting efficient resource utilization through idle emergency resource sharing. By optimizing allocation strategies and enhancing corporate social responsibility, the study fosters the long-term viability and resilience of the supply chain system in post-disaster management. Full article

The growing risk of contracting viral infections due to high-density populations and ecological disruptions, such as climate change and increased population mobility, has highlighted the necessity for effective antiviral treatment and preventive measures against Dengue virus (DENV), Chikungunya virus (CHIKV), and Zika virus (ZIKV). Recently, there has been increasing attention on the use of probiotics as a potential antiviral option to reduce virus infections. The present study aimed to assess the immunomodulatory effects of heat-killed Lactococcus lactis strain plasma (LC-Plasma) on peripheral blood mononuclear cells (PBMCs) and its subsequent antiviral response against DENV, CHIKV, and ZIKV. To evaluate the immunomodulatory effects of LC-Plasma on PBMCs isolated from healthy individuals, PBMCs were cultured at a density of 2 × 10⁵ cells/well and stimulated with 10 µg/mL of LC-Plasma. LC-plasma-stimulated PBMCs demonstrated elevated interferon-alpha (IFN-α) production and cluster of differentiation 86 (CD86) and human leukocyte antigen-DR isotype (HLA-DR) upregulation, potentially linked to plasmacytoid dendritic cell (pDC) activation. The replication of DENV, CHIKV, and ZIKV was dose-dependently inhibited when Huh-7 cells were stimulated with LC-Plasma-stimulated PBMC supernatant (LCP Sup). IFN-stimulated gene (ISG) expression, including IFN-stimulated gene 15 (ISG15), IFN-stimulated exonuclease gene 20 (ISG20), IFN-induced transmembrane protein 1 (IFITM-1), myxovirus resistance protein A (MxA), and radical S-adenosyl methionine domain-containing protein 2 (RSAD2), was significantly upregulated in LCP Sup-stimulated Huh-7 cells. Findings from this study indicate that LC-Plasma has the potential to induce IFN-α production, leading to an enhancement in the expression of ISGs and contributing to a broad-spectrum antiviral response. Thus, LC-Plasma may serve as a rational adjunctive treatment to ameliorate viral diseases, warranting future clinical trials. Full article