bluuebunny/crossref_metadata_2025 huggingface dataset:
Mitigating Data Leakage in a WiFi CSI Benchmark for Human Action Recognition
Authors: Varga Domonkos
Published: December 2024

Human action recognition using WiFi channel state information (CSI) has gained attention due to its non-intrusive nature and potential applications in healthcare, smart environments, and security. However, the reliability of methods developed for CSI-based action recognition is often contingent on the quality of the datasets and evaluation protocols used. In this paper, we uncovered a critical data leakage issue, which arises from improper data partitioning, in a widely used WiFi CSI benchmark dataset. Specifically, the benchmark fails to separate individuals between the training and test sets, leading to inflated performance metrics as models inadvertently learn individual-specific features rather than generalizable action patterns. We analyzed this issue in depth, retrained several benchmarked models using corrected data partitioning methods, and demonstrated a significant drop in accuracy when individuals were properly separated across training and testing. Our findings highlight the importance of rigorous data partitioning in CSI-based action recognition and provide recommendations for mitigating data leakage in future research. This work contributes to the development of more robust and reliable human action recognition systems using WiFi CSI.
Optimizing Correction Factors on Color Differences for Automotive Painting Services
Authors: Corbu Emilia Corina , Nitescu Anne-Marie , Edelhauser Eduard
Published: December 2024

Currently, the automotive sector is showing increased demands regarding the color of cars in general, but especially the quality and the time of painting, in particular. Companies working in this industry, especially in specialized painting services, must perform work of impeccable quality in the shortest possible time in order to be efficient. Color differences that appear in different areas of the car result from the use of different formulas for obtaining color. These differences can be reduced by using correction factors that are established for the colors in the partial or total painting process of cars. There are several factors that lead to settings that are not verified by the real color and, therefore, contribute to incorrect color results and also to high and unnecessary repair costs. In this study, the authors aimed to optimize the values of the correction factors applicable in the automotive industry, based on a set of 135 measurements performed with a BYK Gardner spectrophotometer, in order to minimize color differences. Through this study, authors have also aimed to find out how the color-identification process can be streamlined with the smallest possible tolerances by optimally adjusting the correction factors and by identifying the factors that influence the color-reading and identification process. A total of 85 pairs of samples were used for the DS1 (data set) and 53 pairs of samples for the DS2 (data set); these samples were used in the visual experiments for testing the performance of two color-differentiation formulas. The first part of the research aimed to investigate the visual perception of the painted cars in terms of differences in brightness, chroma and hue, data that were used to optimize the formulas used for color differences. Finally, authors have estimated the closest color variant to the objective color by optimizing the correction factors and thus achieving the efficiency of the color-identification process and the whole painting-identification process.
Correction: Oluwasanmi et al. Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction. Sensors 2023, 23, 3836
Authors: Oluwasanmi Ariyo , Aftab Muhammad Umar , Qin Zhiguang , Sarfraz Muhammad Shahzad , Yu Yang , Rauf Hafiz Tayyab
Published: December 2024

In the original publication [...]
Material Visual Perception and Discharging Robot Control for Baijiu Fermented Grains in Underground Tank
Authors: Zhao Yan , Wang Zhongxun , Li Hui , Wang Chang , Zhang Jianhua , Zhu Jingyuan , Liu Xuan
Published: December 2024

Addressing the issue of excessive manual intervention in discharging fermented grains from underground tanks in traditional brewing technology, this paper proposes an intelligent grains-out strategy based on a multi-degree-of-freedom hybrid robot. The robot’s structure and control system are introduced, along with analyses of kinematics solutions for its parallel components and end-effector speeds. According to its structural characteristics and working conditions, a visual-perception-based motion control method of discharging fermented grains is determined. The enhanced perception of underground tanks’ positions is achieved through improved Canny edge detection algorithms, and a YOLO-v7 neural network is employed to train an image segmentation model for fermented grains’ surface, integrating depth information to synthesize point clouds. We then carry out the downsampling and three-dimensional reconstruction of these point clouds, then match the underground tank model with the fermented grain surface model to replicate the tank’s interior space. Finally, a digging motion control method is proposed and experimentally validated for feasibility and operational efficiency.
Securing the Future of Railway Systems: A Comprehensive Cybersecurity Strategy for Critical On-Board and Track-Side Infrastructure
Authors: Ibadah Nisrine , Benavente-Peces César , Pahl Marc-Oliver
Published: December 2024

The growing prevalence of cybersecurity threats is a significant concern for railway systems, which rely on an extensive network of onboard and trackside sensors. These threats have the potential to compromise the safety of railway operations and the integrity of the railway infrastructure itself. This paper aims to examine the current cybersecurity measures in use, identify the key vulnerabilities that they address, and propose solutions for enhancing the security of railway infrastructures. The report evaluates the effectiveness of existing security protocols by reviewing current standards, including IEC62443 and NIST, as well as case histories of recent rail cyberattacks. Significant gaps have been identified, especially where modern and legacy systems need to be integrated. Weaknesses in communication protocols such as MVB, CAN and TCP/IP are identified. To address these challenges, the paper proposes a layered security framework specific to railways that incorporate continuous monitoring, risk-based cybersecurity modeling, AI-assisted threat detection, and stronger authentication methodologies. The aim of these recommendations is to improve the resilience of railway networks and ensure a safer, more secure infrastructure for future operations.
Development and Application of an Integrated Index for Occupational Safety Evaluation
Authors: Silva Paulo , Carneiro Mariana , Costa Nélson , Loureiro Isabel , Carneiro Paula , Pires Abel , Ferreira Cátia
Published: December 2024

Occupational safety, reflecting the likelihood of work-related accidents, is crucial in work systems. A risk management model identifies, analyzes, and prioritizes risks, followed by the strategic application of resources to mitigate, monitor, and control the probability and impact of future events. Models integrating safety, ergonomics, and operational efficiency in risk management are non-existent, especially in the food retail sector. The proposed risk management model assigns the risk level to Safety using the Hazard Identification and Risk Assessment index (HIRA), an integral part of the Global Safety Index (GSI), both indices with five risk levels: 1 to 5 (acceptable to very critical). The organizational hierarchy of the evaluated company includes levels from microtask to insignia. The research aims to apply the HIRA index from the microtask to the area level. The HIRA application was conducted in a food retail company, starting with the identification and characterization of tasks in the “food” section and “fresh products” area (butchery, fishmonger, bakery, charcuterie/takeaway, and fruits and vegetables sections). The risk level of each microtask was assessed, then aggregated to higher organizational levels. Results showed that two new solutions reduced the safety risk in the mentioned sections proving the HIRA value as decision-making tool.
Uncommon World Production: In Search of Freedom and Recognition
Authors: Ioris Antonio A. R.
Published: December 2024

The socio-spatiality of capitalist modernity is the embodiment of pressures to eliminate common, spatially adapted institutions in the name of an allegedly more rational world demarcated by the prospect of having everything private and predisposed to be exploited. The vital element of these pressures to legitimise economic inequalities to extract more and more value from labour and nature is the phenomenon of uncommoning. This article has several interconnected goals, especially, an interpretation of the meaning and practices of uncommoning—making use of classical, contemporary, and decolonial academic and grey literature—and a critical reflection on the frontiers of the modern world, where uncommoning is clearly the key socio-spatial driving force underpinning a deceitful democracy and providing justification for the encroachment of private properties upon the commons. This focus on the commons facilitates and radicalises the comprehension of how societies and communities deal with the allocation, use, and preservation of cherished elements of their material and immaterial reality. It can be constructively reached from the perspective of Global South societies, indigenous nations in particular, with solid experiences and knowledge of the commons. They have the outstanding intellectual and moral authority, and the main job for most is to listen, learn, and act together.
Navigating Collaboration: Newcomer Parents’ Perceptions and Experiences with Norwegian Schools
Authors: Norozi Sultana Ali , Vik Nassira Essahli
Published: December 2024

This qualitative study explores the perceptions and experiences of six newcomer parents from different countries (Afghanistan, Syria, Iran, Chile, Russia, and Ukraine) regarding their collaboration with Norwegian schools. Semi-structured in-depth interviews, ranging from 55 to 80 min, were conducted in participants’ native languages and English. Thematic analysis was employed to analyze the data. Four major themes emerged, as follows: (1) “Journeying Through Integration within the Norwegian Educational Landscape”; (2) “Collaboration: Dialogic or Monologic?”; (3) “Language and Communication Barriers”; and (4) “Navigating New Horizons”. The findings highlight that despite the challenges, participants expressed appreciation for the support they received from schools and teachers. The findings also indicate the need for schools to improve communication and cultural understanding to foster meaningful collaboration with newcomer parents. Schools must also provide more opportunities for parent involvement in decision-making processes. This study adds to the limited literature on newcomer parents’ perspectives on school collaboration and provides insights for policymakers, educators, and school administrators to enhance the educational experiences of newcomer students and their families in Norway.
Analysis of Greenhouse Gas Emissions of a Mill According to the Greenhouse Gas Protocol
Authors: Wróbel-Jędrzejewska Magdalena , Włodarczyk Ewelina , Przybysz Łukasz
Published: December 2024

This article discusses the challenges of adapting to and mitigating climate change through sustainable resource management in the agri-food sector. These aspects are mandatory obligations for businesses under new EU directives and regulations. Greenhouse gas (GHG) emissions must be controlled at every stage of the value chain, from the acquisition of raw materials to transportation and cooperation with suppliers. The purpose of this paper is to analyze the areas generating GHG emissions in the agri-food enterprise toward the development of guidelines for the sustainable development of domestic food production. This paper presents a GHG study in three scopes at one of the mills in Poland based on the GHG protocol methodology. The analysis of consumption of energy carriers was used to determine GHG emissions (Scopes 1 and 2), and the total amounted to about 2.1 million kg CO2eq (the share of Scope 1 was about 16% and Scope 2 as high as 83%), and the average carbon footprint of flour production in terms of unit weight was 0.040 kg CO2eq/kg. Extending the analysis to Scope 3, the emissions associated with this scope accounted for the largest share (92%), while Scopes 1 and 2 accounted for only 8%. The determined carbon footprint (considering the three GHG emission scopes) was 0.52 kg CO2eq/kg. In Scope 3, the largest contribution was from category 1 emissions (92%) related to grain cultivation, and category 5 (6%) were emissions related to the transportation of sold products. The smallest impact is from category 3 emissions related to the management of generated waste. Regular calculation and reporting of emissions in each area enables the company to more fully understand its environmental impact, identify risks and implement changes that bring financial and environmental benefits.
Exploring Design Interventions to Enhance Intergenerational Sharing: An Importance–Performance Analysis of Public Spaces in Changsha, China
Authors: Li Zhuolin , Li Zhe , Ma Jinbiao
Published: December 2024

Intergenerational sharing promotes social cohesion within communities by encouraging dialogue and understanding across different age groups. Nevertheless, existing research has inadequately delved into the human experiences and meaning-making processes that underpin intergenerational sharing, leading to a limited grasp of effective design intervention strategies in community spaces. This study aimed to explore the environmental and social factors influencing intergenerational interactions in community public spaces in Changsha, China, addressing two primary questions: (1) What environmental factors shape intergenerational sharing behaviors? (2) What design strategies can enhance intergenerational sharing in community public spaces? This research employed a mixed-methods approach, including qualitative observation and quantitative importance–performance analysis (IPA) through a survey of 212 residents, to investigate the intergenerational sharing needs of residents. To begin with, the study conducted a detailed analysis of the characteristics and variations in Changsha’s community public spaces. The finding revealed notable disparities in intergenerational sharing behaviors among three types of community spaces: traditional, commercial housing, and integrated neighborhoods. Through environmental behavior observation and IPA, key environmental factors influencing intergenerational sharing behaviors were identified, emphasizing areas for improvement. Based on these findings, the study proposed a design framework consisting of community planning and design, spatial layout and facility construction, and community management, with nine targeted strategies to optimize environmental factors for intergenerational sharing to cater to the unique characteristics of different community types. These findings can deepen our understanding of intergenerational sharing mechanisms and offer practical recommendations for fostering stronger interactions, providing valuable insights for future community public space design.
Characterization of Sunflower Waste Carbonization: Energy Balance and Water Holding Properties
Authors: Kluska Jacek , Matej-Łukowicz Karolina , Nawrot Nicole
Published: December 2024

This paper characterizes the carbonization process of biomass wastes, including sunflower husk pellets and sunflower sponge stalk pellets, at carbonization temperatures of 450 and 550 °C. These studies are important because of the reductions in wood resources for the preparation of barbecue charcoal, as well as agricultural benefits in terms of soil additives. In terms of energy balance, the obtained pyrolysis ensures the autothermal process. The heating characteristics of fixed bed showed that, due to the difference in bulk density, the bed temperature of the sunflower husk pellets reached 450 °C in 110 min, whereas the bed temperature of the sunflower stalk sponge reached the same temperature in 200 min. Additionally, the energy used for the sunflower husk carbonization increased from 2.9 kWh at 450 °C to 3.3 kWh at 550 °C, while the sunflower stalk sponge increased from 3.5 to 3.9 kWh. The combustion characteristics assessed using TGA showed that the carbonization of sunflower husk leads to obtained biochar with a higher combustion activity than biochar derived from sunflower stalk sponge. According to the experimental results, biochar from sunflower husk pellets has a higher water content capacity and water absorption rate than biochar from sunflower stalk sponge pellets.
Striving for Excellence: Deconstruction of Total Quality Management Measuring Model for Croatian Furniture Industry
Authors: Klarić Kristina , Barčić Andreja Pirc , Greger Krešimir , Vukman Karla , Perić Ivana , Klarić Miljenko
Published: December 2024

The significance of Total Quality Management (TQM) lies in its ability to enhance organizational efficiency, foster continuous improvement, and cultivate a culture of quality, ultimately leading to increased customer satisfaction and sustained success. Conducted within the context of the Croatian furniture industry, this research aims to analyze and understand TQM, identify key implementation factors, and formulate a tailored assessment model. The methodology involves a literature review, the integration of relevant TQM factors, and empirical research using a structured questionnaire distributed among a representative sample of Croatian furniture companies. The resulting model encompasses Supplier Quality Management, Engagement of People, Employee Education, Continuous Improvement, Process Management, Company Strategy, Introduction of New Products, Customer Orientation, and Leadership Involvement. Empirical validation demonstrates positive correlations and high reliability. Despite its industry- and country-specific focus, this research offers valuable insights for academics and managers, providing a foundational set of key TQM implementation factors that are applicable beyond the studied context. In addition, the furniture industry, relying on wood as its main raw material, significantly contributes to achieving the Sustainable Development Goals through sustainable manufacturing practices, with an emphasis on TQM in production.
Interpretation of Space Syntax in Higher Education: A Study of Functional Efficiency in Architecture Schools in Erbil
Authors: Hammadamin Abdulqadir Bayz , Nordin Jestin , Mustafa Faris Ali
Published: December 2024

Assessing a built environment’s functional performance and physical and psychological impact is essential for understanding its effect on users, particularly in higher education, where it informs the creation of effective learning spaces. This study aims to explore the application of Space Syntax Theory in a higher-educational context and examines the functional efficiency of three architecture schools in Erbil: Salahaddin University-Erbil, Koya University, and Cihan University-Erbil. Using a quantitative research paradigm, the study employs space-syntax methodologies, including axial map analysis and justified graphs, to evaluate key syntactical parameters such as mean depth, relative asymmetry (RA), real relative asymmetry (RRA), real ring-ness (R-value), and the difference factor (H*). The analysis, conducted via Depthmap X software, examines spatial permeability and connectivity within educational layouts, providing insights into their functional performance. The findings indicate that the architecture school at Cihan University-Erbil, characterised by a ring-like spatial structure, achieves a moderate level of functional performance, outperforming Salahaddin University-Erbil and Koya University. Moreover, productive spaces consistently exhibit higher functional performance than supportive spaces across all case studies. This research proposes a framework for optimising spatial configurations in higher education, providing evidence-based strategies to enhance functionality and promote best practices in educational architecture.
Going Short and Going Digital: How Do Consumers View the Impacts of Digitalizing Short Food Supply Chains?
Authors: Charatsari Chrysanthi , Lioutas Evagelos D. , De Rosa Marcello
Published: December 2024

Agricultural digitalization and short food supply chains (SFSCs) are considered to be different avenues for transitioning to more sustainable agrifood systems. Can these avenues be put together, or are they parallel and, hence, not compatible? The answer to that question largely depends on the potential effects of digitalization on SFSCs. Going digital is a transformative process, accompanied by desirable and undesirable economic, social, environmental, and cultural impacts on short supply schemes. In this cross-sectional quantitative study, based on data from 211 individuals who frequently buy from SFSCs, we examined how consumers evaluate these impacts. We also investigated how participants’ perceptions of these impacts influence their acceptance of agricultural digitalization and their willingness to buy food products from digitalized SFSCs. Our results revealed that consumers view digitalization as a source of positive environmental but adverse social, cultural, and economic impacts on short supply schemes. In addition, we found that acceptance of digitalization and willingness to buy from digitalized SFSCs received moderate-to-low scores. Two regressions showed that buyers’ perceptions of the social impacts that follow digitalization shape both acceptance and willingness. These findings uncovered consumers’ skepticism toward digitalization, suggesting that their commitment to short supply chains and the values that these schemes represent cultivate the belief that digitalization can negatively transform SFSCs, leading to an unwelcome industrialization.
Perceptions of Stress Among Primary School Teachers Teaching Students with Special Educational Needs
Authors: Schmidt Majda , Denša Jasmina , Zurc Joca
Published: December 2024

Despite inclusive education being high on the agenda of educational systems worldwide and part of international legislation and policy, particularly the 2030 Agenda for Sustainable Development, which emphasises inclusion and equality as the basis for quality education for all, there is still a need to identify how teachers in regular schools who teach students with special educational needs (SENs) experience their work. This study investigates the most significant stressors for primary school teachers teaching students with SENs. In addition, this study sets out to determine whether there were differences regarding stress between teachers based on their demographic characteristics and the type of SENs in the students they teach. The empirical study, based on a sample of 120 Slovenian teachers (89.2% females), showed that a lack of professional competency, classroom work, personal beliefs, and the burden of administrative work were the most significant perceived stressors when teaching students with SENs in regular primary school. Regarding students’ behaviour and classroom work, different types of SENs were also found to cause significant differences in stress perception. The study revealed that teaching experience and teacher training in SENs could be crucial stress reducers for primary school teachers who teach students with SENs.
Urban Green Infrastructures as Tools for Urban Interconnection: The Case of San Bartolomeo District in Cagliari, Italy
Authors: Mundula Luigi , Di Fazio Clara , Leccis Francesca , Paradiso Maria
Published: December 2024

Contemporary urban areas are often characterized by various forms of enclaves, isolated from their surrounding geographical context. Urban green infrastructures provide an opportunity to open these enclaves, establishing physical and functional connections with the broader city, while also contributing to climate change mitigation and adaptation. This study examines the district of San Bartolomeo in the Italian city of Cagliari as an example of an urban enclave, and employs a participatory planning process to design a project that transforms it into a hub open to the wider city community. The result is a neighborhood shaped by its community, where social, economic, and environmental needs are balanced, fostering constant interaction between residents and the city as a whole.
Exploration of the Cultural Heritage Distribution Along the Beijing-Hangzhou Grand Canal and Its Implications: A Case Study of Cultural Relics Protection Units in the Jiangsu Section
Authors: Liu Yu , Ge Huacheng
Published: December 2024

The Grand Canal, the world’s longest artificial waterway, is a cultural treasure deeply embedded in China’s historical traditions. This study emphasizes the importance of safeguarding, preserving, and revitalizing this invaluable heritage to ensure its relevance. Guided by the “Regulations on the Protection and Management of the Grand Canal Heritage”, this research analyzed 276 cultural relics protection units within the Jiangsu section of the Beijing-Hangzhou Grand Canal (Jiangsu-BHGC). By applying spatial geographic analysis techniques, including point density analysis and gravity shift models, the study mapped the historical evolution, spatial distribution, and typological characteristics of these relics. Additionally, using ArcGIS and geographic detectors, the research explored factors influencing the distribution of these units, pinpointing critical determinants. This rigorous approach provides an in-depth understanding of the spatial arrangement of cultural heritage sites along the canal, supporting its coordinated development. By examining distribution patterns and key attributes, the study offers theoretical insights and data-driven guidance for optimizing the sustainable use of this cultural heritage.
Economic and Environmental Impact Analysis of Innovative Peeling Methods in the Tomato Processing Industry
Authors: Eslami Elham , Landi Giovanni , Benedetti Miriam , Pataro Gianpiero
Published: December 2024

Peeling is a key step in the industrial production of canned peeled tomatoes, vital for optimizing efficiency, yield, product quality, waste reduction, and environmental impact. This study presents a comparative assessment of the economic and environmental impacts of adopting innovative peeling technologies, including infrared (IR), ohmic heating-assisted lye (OH-lye), and ultrasound-assisted lye (US-lye) peeling, relative to conventional steam and lye peeling methods. Focusing on a medium-sized Italian tomato processor, the impacts of these methods on productivity, water and energy consumption, wastewater generation, and environmental footprint using Life Cycle Assessment (LCA) methodology, were evaluated. Findings indicated that adopting IR, OH-lye, and US-lye methods enhanced peelability (ease of peeling > 4.5) and increased production capacity by 2.6–9.2%, while reducing solid waste by 16–52% compared to conventional steam and lye methods. LCA results showed IR as the most environmentally favorable method, followed by steam, OH-lye, and US-lye, with conventional lye peeling being the least sustainable. OH-lye and IR methods also significantly reduce water and energy use, while US-lye shows higher demands in these areas. Additionally, OH-lye and IR methods require little or no NaOH, minimizing chemical consumption and wastewater production, which offers notable environmental and cost advantages. Overall, this preliminary study underscores economic and environmental potential for novel peeling technologies, encouraging industry consideration for adoption.
Exploring the Interaction Between Landslides and Carbon Stocks in Italy
Authors: Qadri Jibran , Ceccato Francesca
Published: December 2024

Landslides, as natural hazards, have far-reaching impacts beyond their immediate effects on human lives and infrastructure; landslides disrupt both carbon storage and ecosystem stability, and their role in the global carbon cycle cannot be underestimated. This study delves into the complex relationship between landslides and carbon stocks such as, in particular, soil organic carbon (SOC) and above-ground biomass (AGB), and outlines the spatial relationship between different types of landslides, soil organic carbon (SOC), and the carbon cycle, underscoring the importance of understanding these interconnections for environmental sustainability and climate change mitigation efforts. By employing machine learning algorithms on the Google Earth Engine platform, landslide susceptibility maps were created for different landslide types across Italy, and their spatial patterns with SOC accumulation were analyzed using the Python environment. The findings reveal a nuanced relationship between landslide hazard levels and SOC dynamics, with varying trends observed for different landslide types. In addition, this study investigates the potential impact of large-scale landslide events on carbon sequestration in the short term via a case study of the May 2023 landslide event in the Emilia Romagna region of Italy. The analysis reveals a substantial reduction in above-ground biomass by 35%, which approximately accounts for the loss of 0.133 MtC, and a decrease in SOC accumulation in 72% of the affected areas, indicating that landslides can transform carbon sinks into carbon sources, at least in the short term, and suggested that carbon released from extreme landslide events at a larger scale needs to be accounted for in regional or national carbon emissions. This research underscores the importance of considering landslides in carbon cycle assessments and emphasizes the need for sustainable land management strategies to protect and enhance carbon sinks, such as forests and healthy soils, in the face of increasing natural hazards and climate change impacts.
An Autoregressive Distributed Lag and Environmental Kuznets Curve Approach: Linking CO2 Emissions and Electricity Access in India
Authors: Nica Ionuț , Georgescu Irina , Kinnunen Jani
Published: December 2024

This study evaluates the impact of foreign direct investment (FDI), per capita GDP, renewable energy consumption, and urbanization on India’s CO2 emissions over the period 1990–2023. In the context of rapid economic growth and urbanization, India faces major challenges related to environmental sustainability. Using the ARDL (Autoregressive Distributed Lag) model and the Environmental Kuznets Curve (EKC), this research analyzes the complex relationships between these factors and CO2 emissions. The results highlight the existence of an N-shaped EKC curve with two inflection points at GDP values. This study highlights the essential role of renewable energy consumption in reducing emissions and improving access to electricity in promoting sustainable development. The findings provide valuable insights into economic and energy policies, highlighting the need to balance economic growth with environmental protection.
Coordinating Risk Aversion and Pricing Strategies in Green Supply Chains: A Study of Manufacturer Competition
Authors: Chen Zhen , Khalilpour Kaveh , Yao Qingzhen
Published: December 2024

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.
Factors Influencing Emergency Management Performance in China’s Prismatic County-Level Governance
Authors: Wang Chao , Song Jixiang , Tiwana Muhammad Sulaiman , Xu Wendong
Published: December 2024

Emergency management performance (EMP) at the county level in China plays a critical role in linking counties to serve as a bridge between urban and rural areas. This study explores the factors that influence EMP within China’s county-level governance by applying Riggs’ administrative ecology theory. The study examines the impact of normative constraints, favor politics, cooperative politics, and charismatic politics directly on EMP collectively and individually. This study analyzes empirical data using structural equation modeling from Jiangsu Province, which includes a survey of 300 emergency management personnel. The results show that normative constraints have the most significant positive influence on EMP, followed by charismatic politics, cooperative politics, and favor politics. The study highlights the mixed practices of traditional and modern administrative contexts, with the “prismatic” administrative model offering an adaptive governance approach during China’s societal transition. This study advances the theoretical understanding of transitional governance systems and provides practical recommendations for policymakers to improve EMP in county-level governance frameworks.
How Green Entrepreneurial Orientation Influences Corporate Performance: The Missing Link of Green Knowledge Sharing
Authors: Le Yuan , Zhang Xiue
Published: December 2024

Based on dynamic capability theory and contingency theory, this study explores effects of green knowledge sharing (GKS) and environmental dynamism (ED) on the relationship between green entrepreneurial orientation (GEO) and corporate performance (CP). Using SPSS 24.0 software to perform hierarchical regression analysis on collected data from 387 Chinese manufacturing firms, it was found that GEO has positive influence on financial performance (FP) and environmental performance (EP), that supplier knowledge sharing (SKS) and customer knowledge sharing (CKS) play a mediating role in the relationship between GEO and EP, and that SKS mediates the relationship between GEO and FP. However, CKS does not mediate the relationship between GEO and FP. In addition, our empirical findings show that CP is improved through GEO and GKS at a higher level of ED. These findings provide theoretical contributions and practical inspirations for the research on green entrepreneurship.
Individuals’ Social Identity and Pro-Environmental Behaviors: Cross-Cultural Evidence from 48 Regions
Authors: Shen Junxian , Zhang Hongfeng
Published: December 2024

Individual pro-environmental behaviors (PEBs) are essential for addressing critical global environmental challenges. Drawing on the social identity approach, this study examines how different types of social identity (including world, national, regional, and city identities) influence individuals’ engagement in PEBs. Using data from the seventh wave of the World Values Survey (2017–2022), which includes responses from 60,577 participants across 48 regions, a hierarchical linear model was used to analyze these relationships. The results show that world identity has a stronger effect than city, national, or regional identity on green orientation and subsequently on PEBs, emphasizing environmental sustainability as a global priority. Moreover, previous cross-cultural research has focused on individualistic and collectivistic cultures. Our study introduces a novel perspective to the existing literature by examining the moderating effect of long-term versus short-term societal orientations. The findings indicate that long-term cultural orientations strengthen the influence of green orientation on PEBs. This study provides actionable insights for researchers, practitioners, and policymakers seeking to develop culturally sensitive strategies to promote sustainable behaviors.
Integrating Urban Mining Concepts Through AI-Generated Storytelling and Visuals: Advancing Sustainability Education in Early Childhood
Authors: Lu Ruei-Shan , Lin Hao-Chiang Koong , Yang Yong-Cih , Chen Yo-Ping
Published: December 2024

This study investigates integrating sustainability and urban mining concepts into early childhood education through AI-assisted storytelling and visual aids to foster environmental awareness. Using ChatGPT-generated narratives and AI-drawn visuals, interactive stories explore complex sustainability themes like resource conservation and waste management. A quasi-experimental design with 60 preschoolers divided into experimental and control groups compared structured and unstructured storytelling. Structured stories followed teacher-designed frameworks, including thematic and narrative elements such as settings, character development, and resolutions. Observations showed the structured group demonstrated greater comprehension, engagement, and narrative ability, indicating enhanced cognitive and communication skills. The digital system interface featured animations and images for engagement, while tutorial-driven navigation allowed young learners to interact freely with sustainability-focused story options. The findings highlighted structured storytelling’s ability to improve language and narrative skills, alongside fostering digital and environmental literacy. Limitations include a small sample size and a focus on specific themes, restricting generalizability. Despite this, this study adds value by showcasing how AI tools combined with structured frameworks can effectively teach sustainability while reducing the reliance on paper, promoting sustainable educational practices. Overall, this research underscores the potential of AI storytelling in shaping young learners’ understanding of environmental issues, advocating for the thoughtful integration of technology to inspire deeper learning.
The Quenched gA in Nuclei and Infrared Fixed Point in QCD
Authors: Rho Mannque , Shao Long-Qi
Published: December 2024

The possible consequence of an infrared (IR) fixed point in QCD for Nf=2, 3 in nuclear matter is discussed. It is shown in terms of d(ilaton)-χ effective field theory (dχEFT) incorporated in a generalized effective field theory implemented with hidden local symmetry and hidden scale symmetry that the superallowed Gamow–Teller transition in the doubly magic-shell nucleus 100Sn recently measured at RIKEN indicates a large anomaly-induced quenching identified as a fundamental renormalization of gA from the free-space value of 1.276 to ≈0.8. Combined with the quenching expected from strong nuclear correlations “snc”, the effective coupling in nuclei gAeff would come to ∼1/2. If this result were reconfirmed, it would impact drastically not only nuclear structure and dense compact-star matter—where gA figures in π-N coupling via the Goldberger-Treiman relation—but also in search for physics Beyond the Standard Model (BSM), e.g., 0νββ decay, where the fourth power of gA figures.
Intuitionistic Fuzzy Set Guided Fast Fusion Transformer for Multi-Polarized Petrographic Image of Rock Thin Sections
Authors: Chen Bowei , Yan Bo , Wang Wenqiang , He Wenmin , Wang Yongwei , Peng Lei , Wang Andong , Chen Li
Published: December 2024

The fusion of multi-polarized petrographic images of rock thin sections involves the fusion of feature information from microscopic images of rock thin sections illuminated under both plane-polarized and orthogonal-polarized light. During the fusion process of rock thin section images, the inherent high resolution and abundant feature information of the images pose substantial challenges in terms of computational complexity when dealing with massive datasets. In engineering applications, to ensure the quality of image fusion while meeting the practical requirements for high-speed processing, this paper proposes a novel fast fusion Transformer. The model leverages a soft matching algorithm based on intuitionistic fuzzy sets to merge redundant tokens, effectively mitigating the negative effects of asymmetric dependencies between tokens. The newly generated artificial tokens serve as brokers for the Query (Q), forming a novel lightweight fusion strategy. Both subjective visual observations and quantitative analyses demonstrate that the Transformer proposed in this paper is comparable to existing fusion methods in terms of performance while achieving a notable enhancement in its inference efficiency. This is made possible by the attention paradigm, which is equivalent to a generalized form of linear attention, and the newly designed loss function. The model has been experimented on with multiple datasets of different rock types and has exhibited robust generalization capabilities. It provides potential for future research in diverse geological conditions and broader application scenarios.
Research on CFRP Defects Recognition and Localization Based on Metamaterial Sensors
Authors: Zhu Zhaoxuan , Han Rui
Published: December 2024

In the paper, the concept of symmetry is utilized to detect internal defects in Carbon fiber reinforced polymer (CFRP), that is, the reconstruction and localization methods for internal defects in CFRP are symmetrical. CFRP is widely used in industrial, biological and other fields. When there are defects inside the composite materials, its dielectric constant, magnetic permeability, etc. change. Therefore, metamaterial sensors are widely used in non-destructive testing of CFRP Defects. This paper proposes a defect identification and location method based on principal component analysis (PCA) and support vector machine (SVM). The trained model is used to classify the dimensionally reduced data, and the reconstructed defect binary image is obtained. Simulation and physical experiment results show that the method used in this article can effectively identify and locate defects in carbon fiber composite materials.
Joint Approximation by the Riemann and Hurwitz Zeta-Functions in Short Intervals
Authors: Laurinčikas Antanas
Published: December 2024

In this study, the approximation of a pair of analytic functions defined on the strip {s=σ+it∈C:1/2<σ<1} by shifts (ζ(s+iτ),ζ(s+iτ,α)), τ∈R, of the Riemann and Hurwitz zeta-functions with transcendental α in the interval [T,T+H] with T27/82⩽H⩽T1/2 was considered. It was proven that the set of such shifts has a positive density. The main result was an extension of the Mishou theorem proved for the interval [0,T], and the first theorem on the joint mixed universality in short intervals. For proof, the probability approach was applied.
Measuring the Systemic Risk of Clean Energy Markets Based on the Dynamic Factor Copula Model
Authors: Wang Wensheng , Wang Rui
Published: December 2024

This study is based on the stock returns of 11 subindustry markets in the international clean energy market from 2010 to 2024 and constructs a skewed t distribution dynamic factor copula model. The time-varying load factor is used to characterize the correlation between a single subindustry market and the entire system, and the joint probability of distress is calculated as a measure of the overall level of systemic risk. Two indicators, Systemic Vulnerability Degree and Systemic Importance Degree, are introduced to evaluate the vulnerability of a single subindustry market in systemic risk and its contribution to systemic risk. A conditional risk-spillover index is constructed to measure the risk-spillover level between subindustry markets. This method fully considers the individual differences and inherent correlations of the international clean energy market subsectors, as well as the fat tail and asymmetry of returns, thus capturing more information and more timely information. This study found that the correlation between subindustry markets changes over time, and during the crisis, the market correlation shows a significant upward trend. In the measurement of the overall level of systemic risk, the joint probability of distress can identify the changes in systemic risk in the international clean energy market. The systemic risk of the international clean energy market presents the characteristics of rapid and multiple outbreaks, and the joint default risk probability of the whole system can exceed 0.6. The outbreak of systemic risk is closely related to a series of major international events, showing a strong correlation. In addition, the systemic vulnerability analysis found that the biofuel market has the lowest systemic vulnerability, and the advanced materials market has the highest vulnerability. The energy efficiency market is considered to be the most important market in the system. The advanced materials market and renewable energy market play a dominant role in the risk contribution to other markets, while the geothermal market, solar market, and wind energy market are net risk overflow parties in the tail risk impact, and the developer market and fuel cell market are net risk receivers. This study provides a theoretical basis for systemic risk management and ensuring the stability of the international clean energy market.
A Case of One Step Forward and Two Steps Back? An Examination of Herbicide-Resistant Weed Management Using a Simple Agroecosystem Dynamics Model
Authors: Kodali Srinadh , Flores-Lopez Chris , Lobdell Isabelle , Kim Branson , Russell James C. , Michna Lane , Turner Benjamin L.
Published: December 2024

Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically.