bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the Antioxidant Properties of Black Acacia (Acacia mearnsii) Tannin in Vulcanized Natural Rubber Using Different Vulcanization Systems
Authors: Filgueira Matheus da Silva , Pinto Leandro Ferreira , Hiranobe Carlos Toshiyuki , de Freitas Amanda de Sousa Martinez , Rodrigues Jéssica de Souza , de Oliveira André Luis , Ferreira Marystela , Kawall Samara Araújo , Souza Dener da Silva , da Silva Erivaldo Antonio , Nascimento Eduardo Soares , Silva Michael Jones da , Cabrera Flávio Camargo , Gennaro Elmer Mateus , dos Santos Renivaldo José
Published: December 2024

Given the growing interest of the rubber industry in seeking alternatives that contribute to environmental sustainability, this work aims to present a study of the mechanical, thermal, and structural properties of natural rubber composites using tannin extracted from Acacia mearnsii as an antioxidant agent. Tannin is a natural and biodegradable product, rich in polyphenols and known for its antioxidant properties. The analyses assessed the effectiveness of incorporating tannins (0, 1, 1.5, and 2 parts per hundred rubber) into sulfur-crosslinked natural rubber composites using a binary accelerator system across three distinct vulcanization schemes: conventional, semi-efficient, and efficient. Initially, tannin characterization tests were conducted, revealing characteristic polyphenol bands of proanthocyanidin catechins, a high total phenolic content, and a substantial reduction in antioxidant activity. These findings highlight the significant antioxidant potential of tannins, particularly for industrial and biological applications. The analyses of the characteristics of natural rubber composites with tannin incorporation indicated that the type of vulcanization process directly affects the antioxidant action of the plant tannin, with the tannins being most effective in the efficient system due to the formation of monosulfidic and disulfidic bonds. Furthermore, the incorporation of tannin did not compromise the physical and chemical properties of the materials, highlighting it as a viable additive for the rubber industry.
A Reputation-Based Pricing Strategy for Distributed Diverse Entity Systems: Enhancing Market Efficiency Through Real-Time Reputation Updates
Authors: Li Tong , Li Yuheng , Gao Junpeng , Qian Benhua , Zhao Hai
Published: December 2024

Although existing studies address the reduction of default rates by adjusting electricity trading rankings based on reputation values, the mechanisms for penalizing electricity trading defaults remain incomplete. Therefore, this paper proposes a real-time reputation-based pricing method for distributed diverse entity systems to mitigate electricity trading defaults. First, a reputation reward and penalty mechanism evaluates the trading behavior of diverse entities. Next, a ‘price-dominant, reputation-auxiliary’ pricing concept guides the process. Following this, a reputation-driven pricing strategy model for distributed adjustable resources allows for bid adjustments based on real-time market dynamics. Upon electricity trading completion, the reputation values of all entities are recalculated and disclosed, enabling entities to adjust future pricing and electricity trading quantities to optimize their profits. This method effectively reduces default rates while alleviating the impact of market electricity tradings on peak-to-valley fluctuations. Finally, simulations conducted on the MATLAB 2018b platform confirm the rationality and feasibility of the proposed real-time reputation-based pricing strategy within distributed diverse entity systems.
Using Microbial Bioagents to Enhance the Nutritional Status of Annual Ryegrass
Authors: Ivezić Vladimir , Jović Jurica , Zebec Vladimir , Kristek Suzana , Lončarić Zdenko
Published: December 2024

The challenge of today’s agriculture is to maintain stable production and at the same time improve soil conditions. Appropriate crop management can contribute to the increase of yields, nutritional status of plants, and below-ground biomass which consequently increases soil organic carbon (SOC). One promising approach to increase yield and reduce the use of synthetic fertilizers involves using plant growth-promoting microorganisms. The present study explores the possibility of applying microbial bioagents as a sustainable alternative to synthetic fertilizers in Italian ryegrass cultivation. Four microbial formulations, consisting of nitrogen-fixing bacteria, phosphate-solubilizing microorganisms, and beneficial fungi, were evaluated under full and reduced nitrogen fertilization regimes. The experiment consisted of the two levels of nitrogen fertilization, and the experimental treatments where four different microbial bioagents that were a combination of several different microorganisms were applied in four different application treatments (control (without microbial bioagents), in soil, on seed, and in soil and seed). The results indicate that by reducing mineral fertilization and using microbial bioagents we can achieve twice-as-high yields compared to the sole full mineral fertilization, significantly increasing the uptake of nutrients and SOC. The uptake of toxic trace elements also increased, however, all levels remained below permissible thresholds, ensuring feed safety. The findings highlight the potential of microbial bioagents to enhance soil health, improve plant nutrition, and increase ryegrass yields while reducing reliance on synthetic inputs, contributing to climate change mitigation through improved SOC storage, and presenting a pathway for sustainable agriculture.
Meta-Analysis of the Relationship Between Green Entrepreneurial Orientation and Sustainable Firm Performance
Authors: Öztürk Resul , Öztürk Mehtap , Kızılkan Zeynep
Published: December 2024

The purpose of this study is to examine the relationship between green entrepreneurial orientation and sustainable firm performance. In order to examine this relationship, a meta-analysis method was used, and analyses were carried out with a Comprehensive Meta-Analysis Software (CMA) v4 package program. In the study, a sample of 23 articles, 42 effect sizes, and 6666 enterprises was reached through a systematic literature review. The studies included in the research were accessed by searching the keywords “green entrepreneurial orientation” and “sustainable firm performance” from Web of Science, EBSCO Host, Scopus, and Google Scholar databases, and only articles without any year limit were included. Throughout the study, statistical analyses were performed on Fisher z values and conducted under the random effects model. The effect size, heterogeneity, and publication bias analyses of green entrepreneurial orientation and sustainable firm performance and its sub-dimensions were tested separately, and the findings were interpreted by converting them into correlation coefficients. As a result of the analyses, it was found that the relationship between green entrepreneurial orientation and sustainable firm performance is positive and highly significant (p < 0.05). In addition, the relationship between financial, environmental, social, sustainable, entrepreneurial, and green innovation performance, which is the sub-dimensions of sustainable firm performance, and green entrepreneurial orientation, was found to be high and significant (p < 0.05). However, it was concluded that there is no significant relationship between green innovation performance, which is another dimension of sustainable firm performance, and green entrepreneurial orientation. Moderator analyses revealed that sector and continent have a moderating effect on the relationship between green entrepreneurship orientation and sustainable firm performance.
Valorization of Recycled Aggregate and Copper Slag for Sustainable Concrete Mixtures: Mechanical, Physical, and Environmental Performance
Authors: Arredondo Pamela Wendy Caballero , Silva Yimmy Fernando , Araya-Letelier Gerardo , Hernández Héctor
Published: December 2024

The increasing environmental impacts caused by the high demand for concrete production have underscored the need for sustainable alternatives in the design of eco-concrete mixtures. Additionally, important industries, such as construction and mining, generate massive amounts of waste/by-products that could be repurposed towards sustainability. Consequently, this study investigates the valorization of copper slag (CS), a by-product of the mining industry as a supplementary cementitious material (SCM), and concrete as recycled coarse aggregate (RCA), derived from construction and demolition waste, as partial substitutes for Ordinary Portland Cement (OPC) and natural coarse aggregate (NCA), respectively. Eco-concrete mixtures were designed with varying replacement levels: 15% for CS, and 0%, 20%, 50%, and 100% for RCA. The mechanical properties (compressive, indirect tensile, and flexural strengths), permeability characteristics (porosity and capillary suction), and environmental impacts (carbon footprint) of these mixtures were evaluated. The results showed that the use of CS and of increasing proportions of RCA led to a monotonic loss in each of the concretes’ mechanical strength properties at 7, 28 and 90 days of curing. However, at extended ages (180 days of curing), the concrete mixtures with CS and only NCA presented an average compressive strength 1.2% higher than that of the reference concrete (mixture with only OPC and natural aggregate). Additionally, the concrete mixture with CS and 20% RCA achieved 3.2% and 5.8% higher average values than the reference concrete in terms of its indirect tensile strength and flexural strength, respectively. Finally, a cradle-to-gate life cycle assessment (LCA) analysis was implemented, whose results showed that the greatest effect on reducing the carbon emission impacts occurred due to the substitution of OPC with CS, which confirmed that the adequate technical performances of some of the concrete mixtures developed in this study are positively complemented with reduced environmental impacts. Moreover, this study presents a viable approach to minimizing resource consumption and waste generation, contributing to the advancement of eco-friendly construction materials, which aligns with the sustainable development goals.
Challenges of Disclosing Environmental Accounting Performance and Its Impact on Quality Supply Chains to Promote Sustainable Development in Companies—Experiences of Some Companies in the GCC—2024
Authors: Abubakr Ayman Abdalla Mohammed , Sahal Mastora Sahal Gomaa , Mohammed Ali Alhag Ali , Yousif Nuseiba Azzam Ibrahim , Mohammed Fatihelelah Mohammed Ahmed , Roustom Ziad Mohammad
Published: December 2024

In response to the growing environmental concerns and sustainability imperatives in the GCC and the world in general, companies are increasingly being urged to integrate environmental accountability into their core strategies and operations by accounting for environmental performance in their financial statements and the impact on supply chains and sustainable development. The problem of the study is to identify the impact of environmental accounting disclosure challenges on supply chains and sustainable development in companies. By taking the experiments of 20 companies and representatives of the study community interested in the topic and using the heuristic study approach through the questionnaire tool and a set of key variables, including the adoption of disclosure on environmental accounting performance (DEAP), supply chain sustainability performance (SCP), Sustainable Development Index (SD), and the (PLS) program, through statistical analysis, the study reached the most important results. The study revealed a positive relationship between the disclosure of environmental accounting performance, improved supply chains, and sustainable development in the companies represented by the study sample in the GCC, where both financial performance and environmental performance contribute to achieving the Sustainable Development Goals and supply chains. Accordingly, the study recommends many recommendations, the most important of which are: the need for companies to be encouraged to disclose the performance of environmental accounting as a strategic necessity, promote more sustainable supply chain management, improve financial performance, and effectively contribute to achieving the Sustainable Development Goals, thereby enhancing sustainability within companies and across supply chains. The study also recommends the need to continue studies in this aspect, especially in the GCC and East Asian countries, to urge companies to disclose the performance of environmental accounting in their financial statements.
Empowering Nanostores for Competitiveness and Sustainable Communities in Emerging Countries: A Generative Artificial Intelligence Strategy Ideation Process
Authors: Salinas-Navarro David Ernesto , Vilalta-Perdomo Eliseo , Michel-Villarreal Rosario
Published: December 2024

This exploratory study investigates Generative Artificial Intelligence’s (GenAI) use in strategy ideation for nanostores—i.e., small independent grocery retailers—to enhance their competitiveness while contributing to community sustainability. Nanostores, particularly in emerging countries, face intense competition and rapidly changing trends. These stores adopt various strategies by leveraging their proximity to consumers in neighbourhoods, resulting in different business configurations. While the existing literature highlights the broader nanostores’ functions, there is limited research on how they may develop comprehensive strategies to face their challenges. By employing a thing ethnography methodology, this work proposes GenAI thing interviewing—i.e., with ChatGPT 3.5 and Microsoft Copilot—through incremental prompting to explore potential strategy ideation and practices. Key findings suggest GenAI conversations can aid shopkeepers in strategy ideation through human-like written language, aligning with small business dynamics and structures. This proposition results in a GenAI ideation framework for strategy generation and definition. Moreover, this technology can enhance nanostore competitiveness and sustainability impact by enacting improved strategy practices in stakeholder engagements. Accordingly, this work’s main contribution underscores a GenAI-enabled conversational approach to facilitate nanostores’ strategy ideation and embedding in everyday business operations. Future work must address the limitations and further investigate GenAI’s influence on human understanding and technological creation, strategy ideation, adoption, and usability in nanostores.
Riverbed Adjustments in Gravel–Sand Reaches Immediately Downstream of Large Reservoirs
Authors: Li Sixuan , Zhu Lingling , Yuan Jing , Dong Bingjiang , Lv Chaonan , Yang Chenggang
Published: December 2024

The operation of large reservoirs significantly modifies flow–sediment regimes, and the reaches immediately downstream of the dams are the first to undergo responsive channel adjustments. Considering that the geomorphological responses are directly related to the flood control safety, channel stability and other sustainable functions of rivers, this paper explores the similarities and dissimilarities of the channel adjustments in the two reaches with gravel–sand beds immediately downstream of the Xiangjiaba reservoir and the Three Gorges Dam, respectively. The results show that major erosion primarily occurred during the initial years of reservoir impoundment. And then with the prominent reduction in washable sediment on the riverbed, the erosion intensity further weakened. It takes 6 to 13 years for the two reaches to reach a new state of relative equilibrium. In comparison, after the equilibrium state has been achieved, the reach with significant tributary sediment inflows exhibits alternating erosion and deposition dynamics, while the other remains relatively stable. The tributaries that transport a large amount of sediment during floods are the main sources of sediment deposition in the downstream reaches of the Xiangjiaba reservoir. However, the tributary inflow of the Qing River with low sediment concentrations has little impact on the riverbed evolution of the reaches from Yichang to Zhicheng immediately downstream of the Three Gorges Dam. These findings contribute to a deeper understanding of geomorphic adjustments near dams in response to upstream damming.
The Use of Recycled Ceramics and Ash from Municipal Sewage Sludge as Concrete Fillers
Authors: Szulej Jacek , Ogrodnik Paweł , Chyliński Filip , Klimek Beata , Powęzka Aleksandra , Żółtowski Mariusz , Baryłka Adam
Published: December 2024

The main aim of the research was to evaluate the feasibility of using recycled ceramics and ash from municipal sewage sludge as concrete fillers. As part of the study, standard cylindrical and cubic samples were investigated. The samples consisted of waste ceramic aggregate fractions 0–4 mm and 4–8 mm, which were sourced from used products manufactured by a sanitary fittings factory, as well as ash from one of the Polish sewage treatment plants. The chemical composition and morphology of recycled materials used to produce concrete were examined. The research itself focused on determining the strength properties of the produced composites under both normal conditions and after initial heat treatment. Microstructural tests of the produced composites were also carried out. The results demonstrated that selected recycled materials can successfully replace materials previously used in concrete production. The obtained strength results do not differ significantly from the strength of concrete made of traditional materials. Research has confirmed the possibility of using waste materials as concrete fillers.
Matching Methods of Shared Parking Slots Considering Overdue Parking Behavior
Authors: Li Maosheng , Cheng Jianjian , Fu Jiashu
Published: December 2024

With the continuous increase in the number of vehicles worldwide, parking challenges have become more severe, making it a shared goal for governments to alleviate parking difficulties in urban centers. Shared parking has emerged as an effective solution to address parking problems and has been widely studied in recent years. However, existing research primarily focuses on static or single-period parking matching, often neglecting the conflicts between overdue parking users and subsequent users. Therefore, addressing the impact of overdue parking on shared parking systems is highly important. This study proposes a multi-period dynamic matching decision model (MDMD), which divides the operation period of the shared parking platform into multiple decision points. At each decision point, parking demands are classified into four categories: newly arriving demands, allocated demands with a start time not within the current decision point, overdue demands during the current decision point, and demands affected by overdue parking. Three decision variables are established to determine matching schemes for the first, second, and fourth types of parking demands, facilitating a dynamic decision-making process that effectively mitigates the impact of overdue parking. A corresponding algorithm is designed to solve the model. Since the single-period model is a linear programming model, the CPLEX solver obtains allocation schemes for each decision point. These schemes, along with new parking demands, are used as input for the next decision point, achieving a dynamic matching process. Simulation experiments are conducted to compare the MDMD model with the traditional First-Book-First-Served (FBFS) model based on platform revenue, parking space utilization, and parking demand acceptance rate. The experimental results show that, compared to FBFS, MDMD improves long-term earnings by 83%, actual profits in recent profits by 6.6%, and parking space utilization by 8% while maintaining a similar parking demand acceptance rate. To validate the robustness of the model, additional simulations are performed under various overdue probability scenarios, demonstrating that MDMD maintains stable system performance across different probabilities. These improvements highlight the advantages of the dynamic matching strategy, distinguishing this study from existing methods lacking adaptability. These findings provide valuable insights for the optimization of shared parking systems, contributing to sustainable transportation solutions and efficient urban mobility management.
Rethinking Food Waste: Insights from the 2021 and 2022 RETASTE Conferences
Authors: Manios Thrassyvoulos , Lasaridi Katia , Daliakopoulos Ioannis N. , Abeliotis Konstadinos , Chroni Christina
Published: December 2024

The RETASTE Conference has established itself as a critical platform for advancing science and innovation on food waste management within the framework of circular economy practices. This editorial summarises the key themes and research presented at the first two RETASTE meetings, which focused on strategies such as the valorisation of food processing by-products, utilization of food waste for bioplastics, and development of waste-to-energy technologies. These studies demonstrate the potential to transform food waste from an environmental burden into valuable resources, thereby supporting both local and global sustainability objectives. The conference also highlighted the importance of integrating technology with policy and social aspects to drive transformation across the entire food system, while acknowledging the challenges that remain, including cultural, political, and administrative barriers that must be addressed for these innovations to be successfully scaled. The rebranding of the conference to “RETASTE: Rethink Food Resources, Losses, and Waste” signals a broader focus on the interconnectedness of food systems, emphasizing the need for continuous innovation and collaboration across all sectors. This editorial concludes that a holistic approach—combining technological advancements, social practices, and robust policy frameworks—is essential for effectively managing food waste and promoting sustainable food systems globally.
Study on the Spatio-Temporal Patterns of Survival Dynamic Evolution of Specialized Farmers’ Cooperatives and the Influencing Factors of Underdeveloped Areas in China—Taking Yunnan Province as an Example
Authors: Xu Ran , Mai Qiangsheng
Published: December 2024

Analyzing the survival and development environment, internal dynamics, and development direction of specialized farmers’ cooperatives in underdeveloped areas to enhance the vitality of the development of the agricultural industry is a key strategy for the work of the “Three Rural Issues” in China. Based on the data of 3194 specialized farmers’ cooperatives in Yunnan Province from 2000 to 2023, this paper utilizes the spatial measurement method and survival analysis method to study the spatial distribution of their survival and related influencing factors. The study found the following: (1) Cooperatives show a spatial aggregation trend from “high to high” to “low to high”, and the formation of new sub-core areas is accelerating. (2) The establishment stage of cooperatives shows an obvious annual cycle effect, and cooperatives established in the early stage show stronger survival resilience. (3) The factor of “organizational characteristics and technological innovation” significantly prolongs the survival time of cooperatives, while the factor of “establishment stage” has a negative effect. (4) The influence of a cooperative’s asset size and trademark on its operational durability tends to decrease over time, but the influence of relatedness remains relatively stable. (5) Over time, the survival and development patterns of cooperatives at the provincial level show obvious differentiation, and the clustering phenomenon of “low-high” development gradually appears in minority autonomous counties. The results of this study provide a scientific basis for deepening and strengthening the study of the basic rural business system.
Sustainable Evolution of China’s Provincial New Quality Productivity Based on Three Dimensions of Multi-Period Development and Combination Weights
Authors: Li Lingyu , Liu Zhichao
Published: December 2024

In this study, we aim to construct an evaluation system to accurately measure the development status and trends of China’s new quality productivity, which is pivotal for the sustainable development of the Chinese economy. In light of the current lack of a standardized evaluation index system and precise measurement methods, we have established an evaluation index system comprising three dimensions—scientific and technological innovation, industrial upgrading, and factor transformation—in alignment with the essence and traits of new quality productivity. By the combination of the entropy method and multi-period weights, we assess the development level of new quality productivity across China’s 31 provinces from 2013 to 2022. The findings reveal the following: (1) Substantial regional disproportions exist among provinces in the advancement of new quality productivity, with Shanghai and Beijing demonstrating a notable first-mover advantage. (2) While the levels of new quality productivity in most provinces are generally modest, an overall positive development trajectory is observed. Drawing upon these outcomes, a set of targeted development strategies are put forward, such as leading scientific and technological innovation, promoting industrial upgrading, and realizing the transformation of elements. This article can enhance our understanding of the spatiotemporal development pattern of China’s new quality productivity, offering a novel theoretical framework and practical approach for fostering new quality productivity tailored to unique circumstances. Consequently, it may facilitate the promotion of economic sustainability.
Sustainable Shipping Requires Sustainable Education and Training
Authors: Dimitranov Dilyan , Belev Blagovest
Published: December 2024

The Blue Economy is a multi-layered economy in its content, although it only reflects the relation between the sea and business. Shipping plays an essential role in this economy, as it holds the largest market share. Sustainable shipping, however, requires the sustainability of a number of the components that make it up. One of the most important components is the training of marine personnel, and particularly the ship’s crew. Over the past two decades, the Lifelong Learning strategy has been firmly established in shipping, manifested through a variety of practices. In order to ensure the continuous and sustainable training of ship’s crews, the companies have introduced annual seminars, which aim to familiarize the officers with current business topics. This article analyzes the delivery methods and quality of training in six seminars conducted by four different shipping companies carried out in three different countries. The scientific method “interview” was used for gathering the necessary information for analysis of the strengths and weaknesses of this type of training, and the way it was conducted. A significant number of deck officers and engineers, participants in all seminars, were surveyed to create a clear picture of the quality of such education and training. Collected data were used for the analysis of the strengths, weaknesses, opportunities and threats (SWOT) associated with the surveyed fleet officer’s seminars. A comparative analysis of this type of postgraduate training was made, while taking in mind higher marine education and training. The article summarizes the authors’ experience of their sea service as Officers of the Watch and Masters on board of merchant vessels, as well as participants in postgraduate education and training. Conclusions for close cooperation between shipping companies and maritime educational institutions are made.
Exposed Clay Bricks Made with Waste: An Analysis of Research and Technological Trends
Authors: Santana Ingrid Silva Assis , Novaes Mariana da Penha , Araújo Ryan Carvalho Chagas de , Batalha-Vieira Luara
Published: December 2024

Properly disposal of industrial waste is a recurring issue due to its large volume and environmental impact. In turn, civil construction has shown itself to be a potential consumer of waste and can contribute to expanding the circular economy. Clay matrix materials have been a focus of interest for absorbing waste, with the possibility of varying their aesthetics, depending on the waste, as an exposed clay brick. Therefore, it is necessary to understand the research and technological trends on the topic to truly meet the demands of the market and society, in an innovative and sustainable way. To this end, a bibliometric review was carried out considering articles published in journals and an analysis of patent trends was carried out. The use of industrial waste was considerably influential in the growth of research on clay bricks. However, while the scientific community focuses on understanding the impact of industrial waste on clay brick properties, inventors focus on processes and methods for synthesizing clay particles associated with contaminants. The existence of gaps to be explored was identified, such as the aesthetic evaluation of clay bricks. The need to further study the properties of bricks made with waste, optimizing production processes and evaluating the life cycle of these materials are some of the challenges for future research.
Multi-Objective Path Planning for Unmanned Sweepers Considering Traffic Signals: A Reinforcement Learning-Enhanced NSGA-II Approach
Authors: Huang Yiwen , Mou Wenjia , Lan Juncong , Luo Fuhai , Wu Kai , Lu Shaofeng
Published: December 2024

With the widespread popularization of unmanned sweepers, path planning has been recognized as a key component affecting their total work efficiency. Conventional path planning methods often only aim to improve work efficiency while ignoring energy optimization, a crucial factor for sustainable development. In this paper, an energy- and time-minimization unmanned sweeper arc path problem (ETM-ARP) is investigated, and the effects of road slope, dynamic changes in on-board mass, mode switching of vehicle work, and traffic lights are taken into consideration to meet the requirements of a realistic structured road scenario. A new multi-objective mixed-integer nonlinear planning model is proposed for this problem. To solve this model, we propose a deep Q-network (DQN) and Adaptive Large Neighborhood Search Algorithm (ALNS)-driven non-dominated sorting genetic algorithm II (QALNS-NSGA-II). The novelty of this algorithm lies in integrating DQN into ALNS, to guide high-quality adaptive operator selection during the search process based on additional information. The computational results of various examples confirm the effectiveness of the proposed method. The proposed method can be used to improve the efficiency and sustainability of unmanned sweepers for sweeping on structured roads.
Cooperative Control of Distributed Drive Electric Vehicles for Handling, Stability, and Energy Efficiency, via ARS and DYC
Authors: Guo Ningyuan , Ye Jie , Huang Zihao
Published: December 2024

Distributed drive electric vehicles (DDEV), characterized by their independently drivable wheels, offer significant advantages in terms of vehicle handling, stability, and energy efficiency. These attributes collectively contribute to enhancing driving safety and extending the all-electric range for sustainable transportation. Nonetheless, the challenge persists in designing a control strategy that effectively coordinates the objectives of handling, stability, and energy efficiency under both lateral and longitudinal driving conditions. To this end, this paper proposes a cooperative control strategy for DDEVs, incorporating active rear steering (ARS) and direct yaw moment control (DYC) to enhance handling capabilities, stability, and energy efficiency. A stability boundary is delineated using an analytical expression that correlates with the front wheel steering angle, and an adjustment factor is introduced to quantify vehicle stability based on this input parameter. This factor aids in establishing a coordinated control reference for handling and stability. At the upper-level motion control layer, a model predictive control method is developed to track this reference and implement ARS and DYC for superior performance. Specifically, the rear lateral force serves as the control command for ARS, which is converted into a rear wheel steering angle using a tire inverse model. Meanwhile, the front lateral force is modeled as linear-time-varying to simplify calculations. At the lower-level torque allocation layer, the adjustment factor is utilized to balance tire workload rate and in-wheel motors’ (IWM) energy consumption, enabling efficient switching between energy consumption and driving stability targets, and the torque allocation is conducted to acquire the expected IWMs’ command. Both the upper and lower-level optimization problems are formulated as convex problems, ensuring efficient and effective solutions. Simulations verify the effectiveness of this strategy in improving handling, stability, and energy economy under DLC cases, while maintaining high computational efficiency.
Efficient Treatment of Leachate from Municipal Solid Waste Transfer Stations via a Bioreactor–Nanofiltration System: A Pilot-Scale Study
Authors: Huang Shoubo , Zheng Qiyuan , Zhu Zihan , Geng Xiaomeng , Wang Lin , Xu Bin , Zhao Youcai
Published: December 2024

The management of municipal solid waste leachate has emerged as a pivotal challenge in sustainable urban development. Currently, there is limited information on the practical engineering applications of bioreactors and nanofiltration systems on the pilot scale. This work employs a bioreactor–nanofiltration pilot system for the treatment of leachate in municipal solid waste transfer stations. The results demonstrate that the bioreactor–nanofiltration system exhibits excellent and stable efficiency in removing organic pollutants and heavy metal ions. The effluent qualities of COD, TN, and TP are 50, 28, and 2 mg/L, and the removal rates are 99.4%, 99.3%, and 96.1%, respectively. All types of heavy metal ions also comply with the standard limits specified in the “Wastewater quality standards for discharge to municipal sewers” (GB/T 31962-2015). More importantly, using waste materials such as mineralized waste and animal aggregates as bioreactor fillers increases the diversity of the microbial community in the system, and provides an engineering basis for the resource utilization of waste materials. The bioreactor–nanofiltration process is expected to become an ideal solution for the treatment of leachate in transfer stations.
Newton’s First Law and the Grand Unification
Authors: Tamm Martin
Published: December 2024

This paper is devoted to the study of stationary trajectories of free particles. From a classical point of view, this appears to be an almost trivial problem: Free particles should follow straight lines as predicted by Newton’s first law, and straight lines are indeed the stationary trajectories of the standard action integrals in the classical theory. In the following, however, a general relativistic approach is studied, and in this situation it is much less evident what action integral should be used. As it turns out, using the traditional Einstein–Hilbert principle gives us stationary states very much in line with the classical theory. But it is suggested that a different action principle, and in fact one which is closer to quantum mechanics, gives stationary states with a much richer structure: Even if these states in a sense can represent particles which obey the first law, they are also inherently rotating. Although we may still be far from understanding how general relativity and quantum mechanics should be united, this may give an interesting clue to why rotation (or rather spin, which is a different but related concept) seems to be the natural state of motion for elementary particles.
LHGCN: A Laminated Heterogeneous Graph Convolutional Network for Modeling User–Item Interaction in E-Commerce
Authors: Liu Kang , Kang Mengtao , Li Xinyu , Dai Wenqing
Published: December 2024

The e-commerce data structure is a typical multiplex graph network structure, which allows multiple types of edges between node pairs. However, existing methods that rely on message-passing frameworks are not sufficient to fully exploit the rich information in multiplex graphs. To improve the performance of link prediction, we propose a novel laminated heterogeneous graph convolutional network (LHGCN) consisting of three core modules: a laminate generation module (LGM), an adaptive convolution module (ACM), and a laminate fusion module (LFM). More specifically, the LGM generates symmetric laminates that cover diverse semantics to create rich node representations. Then, the ACM dynamically adjusts the node receptive field and flexibly captures local information, thereby enhancing the representation ability of the node. Through symmetric information propagation across laminates, the LFM combines multiple laminated features to optimize the global representation, which enables our model to accurately predict links. Moreover, an elaborate loss function, consisting of positive sample loss, negative sample loss, and L2 regularization loss, drives the network to preserve critical information. Extensive experiments on various benchmarks demonstrate the superiority of our method over state-of-the-art alternatives in terms of link prediction.
Modeling of Mechanical and Electrical Systems with Fractal Structure Under Impulse Action and Coherent Acceleration
Authors: Kruchinin Sergei P. , Eglitis Roberts I. , Kruchinin Dmitrii S. , Krak Iurii V. , Babak Vitalii P. , Novikov Valery E. , Polishchuk Arkadiy P.
Published: December 2024

This study explores the applications of extended Gauss–Hertz variational principles to determine the evolution of complex systems under the influence of impulse actions, coherent accelerations, and their application to electrophysical systems with fractal elements. Impulsive effects on systems initiate coherent accelerations (including higher-order accelerations, such as modes with intensification), leading to variations in connections, structure, symmetry, and inertia; the emergence of coherence; and the evolution of fractal elements in electrophysical circuits. The combination of results from the non-local Vlasov theory and modifications to the Gauss–Hertz principle allows for the formulation of a variational principle for the evolution of fractal systems. A key feature of this variational principle is the ability to simultaneously derive equations for both the system’s dynamics and the self-harmonizing evolution of its internal symmetry and structure (e.g., fractal parameters).
Stochastic Computing Architectures: Modeling, Optimization, and Applications
Authors: Wang Lin , Luo Zhongqiang , Gao Li
Published: December 2024

With the rapid development of artificial intelligence (AI), the design and implementation of very large-scale integrated circuits (VLSI) based on traditional binary computation are facing challenges of high complexity, computational power, and high power consumption. The development of Moore’s law has reached the limit of physical technology, and there is an urgent need to explore new computing architectures to make up for the shortcomings of traditional binary computing. To address the existing problems, Stochastic Computing (SC) is an unconventional stochastic sequence that converts binary numbers into a coded stream of digital pulses. It has a remarkable symmetry with binary computation. It uses logic gate circuits in the probabilistic domain to implement complex arithmetic operations at the expense of computational accuracy and time. It has low power and logic resource consumption and a small circuit area. This paper analyzes the basic concepts and development history of SC and neural networks (NNs), summarizes the development progress of SC with NN at home and abroad, and discusses the development trend of SC and the future challenges and prospects of NN. Through systematic summarization, this paper provides new learning ideas and research directions for developing AI chips.
Enhancing the Aczel–Alsina Model: Integrating Hesitant Fuzzy Logic with Chi-Square Distance for Complex Decision-Making
Authors: Xie Jianming , Chen Chunfang , Wan Jing , Dong Qiuxian
Published: December 2024

The paper presents an innovative method for tackling multi-attribute decision-making (MADM) problems within a hesitant fuzzy (HF) framework. Initially, the paper generalizes the Chi-square distance measure to the hesitant fuzzy context, defining the HF generalized Chi-square distance. Following this, the paper introduces the power average (P-A) operator and the power geometric (P-G) operator to refine the weights derived from Shannon entropy, taking into account the inter-attribute support. Leveraging the strengths of Aczel–Alsina operations and the power operation, the paper proposes the hesitant fuzzy Aczel–Alsina power weighted average (HFAAPWA) operator and the hesitant fuzzy Aczel–Alsina power weighted geometric (HFAAPWG) operator. Consequently, a hesitant fuzzy Aczel–Alsina power model is constructed. The applicability of this model is demonstrated through a case study examining the urban impacts of cyclonic storm Amphan, and the model’s superiority is highlighted through comparative analysis.
Exponentiated Generalized Xgamma Distribution Based on Dual Generalized Order Statistics: A Bayesian and Maximum Likelihood Approach
Authors: Binhimd Sulafah M. S. , Kalantan Zakiah I. , Abd AL-Fattah Asmaa M. , EL-Helbawy Abeer A. , AL-Dayian Gannat R. , Abd EL-Kader Rabab E. , Abd Elaal Mervat K.
Published: December 2024

In this paper the exponentiated generalized xgamma distribution is introduced. Some of its properties are presented through some models of stress–strength, moments, mean residual life, mean past lifetime, and order statistics. The maximum likelihood estimators, confidence intervals for the parameters, and the reliability and the hazard rate functions of the exponentiated generalized xgamma distribution based on dual generalized order statistics are obtained. Bayesian estimators for the unknown parameters, reliability, and hazard rate functions of the exponentiated generalized xgamma distribution based on dual generalized order statistics are considered. The results based on lower record values are verified using simulations as well as three real sets of data are adopted to demonstrate the flexibility and potential applications of the distribution.
Understanding the Intersection of Central Environmental Protection Inspections and Green Investment Through Game Theory
Authors: Zhao Tingru , Wan Paijie , He Feng , Zhang Hongjie , Hou Xiaoqing
Published: December 2024

The Central Environmental Protection Inspector (CEPI) is an innovation in China’s environmental regulation. This paper uses game theory to analyze the influence of the CEPI on enterprises’ green investment. Firstly, by constructing the game model of “central government-local government-polluting enterprises”, the factors affecting green investment strategy are analyzed. Then, with the help of a system simulation model, the influence of parameters on system stability and convergence trends is analyzed, so as to obtain the influence of the CEPI on enterprise green investment. The results show the following: (1) The CEPI can effectively promote preventive green investment, and the promotion effect of preventive green investment is proportional to its risk; (2) The effect of the CEPI on local governments is not obvious; (3) The cost of the CEPI is too high, and polluting enterprises are quick to choose remedial green investment.
Networking, Computing and Immersive Technologies for Smart Environments
Authors: Oikonomou Konstantinos , Komianos Vasileios
Published: December 2024

Smart environments encompass a large set of technologies, including computer networking, wireless communication, computational infrastructures, sensor networks, and algorithm design [...]
Epidemiology of Lymphatic Filariasis Antigen and Microfilaria in Samoa, 2019: 7–9 Months Post Triple-Drug Mass Administration
Authors: Mayfield Helen J. , Lawford Harriet , Sartorius Benn , Graves Patricia M. , Sheridan Sarah , Kearns Therese , Hedtke Shannon M. , Gass Katherine , Naseri Take , Thomsen Robert , Lau Colleen L.
Published: December 2024

The elimination of lymphatic filariasis (LF) as a public health problem remains an ongoing challenge in the Pacific region. This study reports on antigen (Ag) and microfilaria (Mf) prevalence in Samoa in 2019, 7–9 months after the completion of the first round of triple-drug mass drug administration (MDA). It evaluates the effectiveness of the intervention for reducing Ag prevalence to below a 2% threshold, and how this differs between 5–9-year-olds and ≥10-year-olds. We surveyed 30 randomly selected and five purposefully selected primary sampling units (PSUs) in Samoa in 2018 (1–3 months post-triple-drug MDA) and, again, in 2019. In each PSU, we conducted a community survey of 15–20 households and a convenience survey of 5–9-year-old children. A finger-prick blood sample was collected from all participants to test for Ag and Mf. Demographic details were also collected. There was no significant change in adjusted Ag prevalence in the 30 randomly selected PSUs between 2018 (3.9% [95% CI: 2.7–5.6%]) and 2019 (4.1% [95% CI 2.7–5.9%]). Significantly higher Ag prevalence was observed in participants aged ≥10 years (4.6%, 95% CIs 3.0–6.7%) compared to 5–9-year-olds (1.1%, 95% CIs 0.5–2.2%), supporting existing evidence that post-MDA surveillance should not be based on Ag prevalence among 6–7-year-olds. A single round of triple-drug MDA was insufficient to break LF transmission in Samoa 7–9 months post-MDA.
High Cryptococcal Antigenuria Prevalence in a Population of PLHIV with Neurological Symptoms Hospitalized in the Infectious Diseases Wards of the Centre Hospitalier Universitaire de Libreville, Gabon
Authors: Sibi Matotou Roger Hadry , Mawili-Mboumba Denise Patricia , Manomba Charlène , Moutombi Ditombi Bridy Chesly , Mihindou Coella Joyce , Moussavou Mabicka Dimitri Ardin , Mounomby Arsène , Nzenze Afene Solange , Bouyou Akotet Marielle Karine
Published: December 2024

Introduction: Cryptococcal meningitis is a major cause of death in HIV/AIDS patients due to the existence of Cryptococcus neoformans in the central nervous system. Our objective was to evaluate the prevalence of Cryptococcus antigenuria in a population of HIV-infected patients in Libreville, Gabon. Patients and Methods: This study was conducted from April to October 2021 at the Infectious Diseases ward of the Centre Hospitalier Universitaire de Libreville. Hospitalized patients with HIV were included. The detection of cryptococcal antigen (CrAg) in urine was performed using the Pastorex Crypto Plus Kit. Results: Out of the 255 PLHIV, 142 benefited from the CrAg detection. The prevalence of urine CrAg was 24.6% (n = 35). The majority of CrAg+ patients (82.8%; n = 29) were under 55 years old. Almost three-quarters of them (n = 25; 71.4%) had CD4 counts < 200, and 80.0% (n = 28) were at WHO clinical stages III and IV. All patients with neck stiffness at admission had a CrAg positive test. Conclusion: This study showed a non-negligible prevalence of Cryptococcal urinary antigen in HIV-infected patients with neurological symptoms. These data underline the importance of CrAg screening in routine care for better management of PLHIV.