bluuebunny/crossref_metadata_2025 huggingface dataset:
An Enhanced Shuffle Attention with Context Decoupling Head with Wise IoU Loss for SAR Ship Detection
Authors: Tang Yunshan , Zhang Yue , Xiao Jiarong , Cao Yue , Yu Zhongjun
Published: November 2024

Synthetic Aperture Radar (SAR) imagery is widely utilized in military and civilian applications. Recent deep learning advancements have led to improved ship detection algorithms, enhancing accuracy and speed over traditional Constant False-Alarm Rate (CFAR) methods. However, challenges remain with complex backgrounds and multi-scale ship targets amidst significant interference. This paper introduces a novel method that features a context-based decoupled head, leveraging positioning and semantic information, and incorporates shuffle attention to enhance feature map interpretation. Additionally, we propose a new loss function with a dynamic non-monotonic focus mechanism to tackle these issues. Experimental results on the HRSID and SAR-Ship-Dataset demonstrate that our approach significantly improves detection performance over the original YOLOv5 algorithm and other existing methods.
CSTAN: A Deepfake Detection Network with CST Attention for Superior Generalization
Authors: Yang Rui , You Kang , Pang Cheng , Luo Xiaonan , Lan Rushi
Published: November 2024

With the advancement of deepfake forgery technology, highly realistic fake faces have posed serious security risks to sensor-based facial recognition systems. Recent deepfake detection models mainly use binary classification models based on deep learning. Despite achieving high detection accuracy on intra-datasets, these models lack generalization ability when applied to cross-datasets. We propose a deepfake detection model named Channel-Spatial-Triplet Attention Network (CSTAN), which focuses on the difference between real and fake features, thereby enhancing the generality of the detection model. To enhance the feature-learning ability of the model for image forgery regions, we have designed the Channel-Spatial-Triplet (CST) attention mechanism, which extracts subtle local information by capturing feature channels and the spatial correlation of three different scales. Additionally, we propose a novel feature extraction method, OD-ResNet-34, by embedding ODConv into the feature extraction network to enhance its dynamic adaptability to data features. Trained on the FF++ dataset and tested on the Celeb-DF-v1 and Celeb-DF-v2 datasets, the experimental results show that our model has stronger generalization ability in cross-datasets than similar models.
Time Series Classification for Predicting Biped Robot Step Viability
Authors: Igual Jorge , Parik-Americano Pedro , Becman Eric Cito , Forner-Cordero Arturo
Published: November 2024

The prediction of the stability of future steps taken by a biped robot is a very important task, since it allows the robot controller to adopt the necessary measures in order to minimize damages if a fall is predicted. We present a classifier to predict the viability of a given planned step taken by a biped robot, i.e., if it will be stable or unstable. The features of the classifier are extracted from a feature engineering process exploiting the useful information contained in the time series generated in the trajectory planning of the step. In order to state the problem as a supervised classification one, we need the ground truth class for each planned step. This is obtained using the Predicted Step Viability (PSV) criterion. We also present a procedure to obtain a balanced and challenging training/testing dataset of planned steps that contains many steps in the border between stable and non stable regions. Following this trajectory planning strategy for the creation of the dataset we are able to improve the robustness of the classifier. Results show that the classifier is able to obtain a 95% of ROC AUC for this demanding dataset using only four time series among all the signals required by PSV to check viability. This allows to replace the PSV stability criterion, which is safe, robust but impossible to apply in real-time, by a simple, fast and embeddable classifier that can run in real time consuming much less resources than the PSV.
Glycosylated Haemoglobin and Quality of Life: A Moderated-Mediation Model for Emotional Intelligence and Affect
Authors: Pérez-Fernández Aida , Fernández-Berrocal Pablo , Morillas-Jiménez Virginia , Domínguez-López Marta Elena , Guerrero-Sánchez Mercedes , Ruiz de Adana-Navas María Soledad , Gutiérrez-Cobo María José
Published: November 2024

Previous research has shown that higher glycosylated haemoglobin (HbA1c) levels are related to poorer quality of life. The objective was to analyse the moderating role of emotional intelligence (EI) in the relationship between HbA1c levels and quality of life through both positive (PA) and negative affect (NA) in individuals with Type 1 diabetes (T1D). A total of 72 participants with T1D (mean age = 41.10, SD = 10.73) were assessed on HbA1c. Psychological constructs were measured through the following questionnaires: MSCEIT (EI), PANAS (affect), and EsDQOL (quality of life). Higher levels of HbA1c and NA were related to a worse quality of life. In contrast, higher PA was related to a better quality of life. In addition, higher EI was associated with lower NA and worries about diabetes. In individuals with low EI scores, EI had a positive moderating effect on the relationship between HbA1c and NA. The moderated mediation analysis revealed a significant positive indirect effect of HbA1c on quality of life through NA moderated by EI for these individuals with low EI scores. This study shows how higher HbA1c levels have a negative impact on the quality of life of individuals with T1D and low EI levels by increasing their NA.
Removal of Inorganic Pollutants and Recovery of Nutrients from Wastewater Using Electrocoagulation: A Review
Authors: Ammar Mohamed , Yousef Ezz , Ashraf Sherif , Baltrusaitis Jonas
Published: November 2024

Water pollution is a major concern due to its detrimental effects on the environment and public health. The particular danger of inorganic pollutants arises from their persistent toxicity and inability to biodegrade. Recently, electrocoagulation (EC) has been demonstrated as an alternative sustainable approach to purifying wastewater due to the increasingly strict pollution prevention rules. In particular, EC has been used to remove inorganic pollutants, such as Cr, Zn, Pb, or As. EC has emerged as a sustainable tool for resource recovery of some inorganic pollutants such as N and P that, when recovered, have value as plant nutrients and are critical in a circular economy. These recovered materials can be obtained from diverse agricultural drainage water and recycled as fertilizers. In this work, a state-of-the-art technique is reviewed describing the advances in contaminant removal and nutrient recovery using EC through an in-depth discussion of the factors influencing the contaminant removal process, including operating pH, time, power, and concentration. Furthermore, limitations of the EC technology are reviewed, including the high-power consumption, fast deterioration of the sacrificial electrodes, and the types of contaminants that could not be efficiently removed. Finally, new emerging constructs in EC process optimization parameters are presented.
Changes in Adolescent Heterosexual Behaviors from the 1980s to the Present in Various Western Countries: A Systematic Review
Authors: Martínez-Álvarez José Luis , Pozo-García Mᵃ Rosario , García-Martín Judit
Published: November 2024

Adolescence is a stage of significant intrapersonal and interpersonal changes, influenced by cultural and historical shifts. This study aims to analyze the changes in heterosexual behaviors among adolescents in Western countries over the past 50 years approximately. For this purpose, we conducted a systematic review following the PRISMA model, utilizing the online databases EBSCO, WoS, and Scopus, covering the period from 1980 to 2024, across ten European countries. The review focused on studies published in scientific journals with regional or national samples. In addition to the 30 selected studies, three more were included due to their relevance as cited in the selected articles. Despite the considerable methodological heterogeneity, the results showed a relative stabilization of the differences in sexual behaviors of boys and girls throughout time. Those differences were more evident in Southern European countries. Some changes were also noted, such as the delay in the initiation of the first sexual intercourse, a trend observed over the last decade. The findings are discussed in terms of the sexual script theory, highlighting the importance of these mental frameworks in the heteronormative sexual socialization of boys and girls. Future research should emphasize the diversity of heterosexual behaviors, their significance, and the emotional experiences that accompany them.
LEAF: A Lifestyle Approximation Framework Based on Analysis of Mobile Network Data in Smart Cities
Authors: Moghari Somaye , Fallah Mohammad K. , Gorgin Saeid , Shin Seokjoo
Published: November 2024

The increasing use of mobile networks is an opportunity to collect and model users’ movement data for extracting knowledge about life and health while considering privacy leakage risk. This study aims to approximate the lifestyles of urban residents, employing statistical information derived from their movements among various Points of Interest (PoI). Our investigations comprehend a multidimensional analysis of key urban factors to provide insights into the population’s daily routines, preferences, and characteristics. To this end, we developed a framework called LEAF that models lifestyles by interpreting anonymized cell phone mobility data and integrating it with information from other sources, such as geographical layers of land use and sets of PoI. LEAF presents the information in a vector space model capable of responding to spatial queries about lifestyle. We also developed a consolidated lifestyle pattern framework to systematically identify and analyze the dominant activity patterns in different urban areas. To evaluate the effectiveness of the proposed framework, we tested it on movement data from individuals in a medium-sized city and compared the results with information collected through surveys. The RMSE of 5.167 between the proposed framework’s results and survey-based data indicates that the framework provides a reliable estimation of lifestyle patterns across diverse urban areas. Additionally, summarized patterns of criteria ordering were created, offering a concise and intuitive representation of lifestyles. The analysis revealed high consistency between the two methods in the derived patterns, underscoring the framework’s robustness and accuracy in modeling urban lifestyle dynamics.
Rethinking the Roles of the Social Determinants of Health in Bystander Intervention for Partner Violence Among College Students
Authors: Paat Yok-Fong , Mangadu Thenral , Payan Shawna L. , Flores Stephanie C.
Published: November 2024

Willingness to intervene as an effective bystander is critical in preventing partner violence and fostering safety among college students. Informed by the Social Determinants of Health framework, this conceptual paper provides an overview of the background and historical evolution of bystander intervention and invites a rethinking of how various factors impact bystander intervention for partner violence among college students by highlighting the roles of (1) economic factors and education, (2) sexual beliefs, myths, and media, (3) gender values and norms, (4) environmental factors, (5) college students at risk, (6) social support network and access to services, (7) acculturation and familiarity with the U.S. culture, and (8) cost-benefit analyses. We also discuss potential practice, research, and policy implications. Understanding the Social Determinants of Health is instrumental in addressing the root cause of intersecting health disparities, which is vital in preventing violence, encouraging bystander intervention, and creating a safer community.
Career Interventions at a Distance: A Systematic Literature Review
Authors: Sampaio Célia , Taveira Maria do Céu , Carvalho Catarina , Silva Ana Daniela
Published: November 2024

Background: Due to global technological advances, psychology professionals have experienced constant changes in their daily routines. The field of career development and vocational psychology is no different. Amplified by the adjustments brought about by the circumstances of the pandemic, there has been an increased demand for and development of various distance intervention methodologies. Methods: This study presents a systematic review of distance career interventions, focusing on (1) rationale, (2) groups of the population, (3) structure, (4) evaluation, and (5) outcomes and recommendations. Eleven keywords, three databases, and five eligibility criteria were defined. Results: Sixteen articles were collected for analysis. The results showed a predominance of (1) career construction theory and social cognitive theory rationales, (2) a sample of university students, (3) group career intervention, (4) pre- and post-test evaluation systems, and (5) effects in different dimensions and recommendations about intervention research design. Conclusions: Although there has been an increase in the number of publications in recent years, few studies evaluate distance career interventions. There are also few studies with different target populations. In this sense, indications for future interventions and studies are given, as well as the implications of these studies for practice.
Raising Children, Rising Debt: Mortgage Debt Among American Families
Authors: Bandelj Nina , Lanuza Yader R. , Ji Zaoying
Published: November 2024

American households owe more than $12 trillion in mortgages, which represents the main source of a family’s debt. Scholars connect mortgages to the desire of families, especially better-off households, to seek housing in neighborhoods with good schools for their children, which tend to be more expensive. Although this perspective assumes a children–mortgage link, we do not know whether having children actually increases mortgage, nor whether and how this relationship varies by household income. To examine these issues, we use eleven waves of the Panel Study of Income Dynamics data between 1997 and 2017 and individual fixed effects, as well as propensity score matching and a quasi-experimental design. Our analyses show that generally, (1) families with children are more likely to have mortgage debt and in greater amounts; (2) it is families in the 60th to 100th income percentile who have the most mortgage debt; and (3) critically, families in the roughly 10th to 60th income percentile have more mortgage debt due to having children. These findings defy assumptions that it is well-to-do families that take on more mortgage debt as part of intensive or concerted cultivation parenting practices. Rather, our findings suggest that families who take on mortgage debt related to their children tend to be those in more economically precarious positions for whom debt for the sake of kids may be a financial burden. As such, our findings provide suggestive evidence that financially intensive parenting may contribute to growing wealth inequality among American families with children.
Editorial Introduction to Centring Intersex Issues: Global and Local Dimensions
Authors: Crocetti Daniela , Garland Fae , Griffiths David Andrew , Monro Surya , Mhuirthile Tanya Ní , Roen Katrina , Singh Prashant , Suess-Schwend Amets
Published: November 2024

This Special Issue showcases the expanding body of international scholarly work within intersex studies [...]
#Polarized: Gauging Potential Policy Bargaining Ranges Between Opposing Social Movements of Black Lives Matter and Police Lives Matter
Authors: Hanson-DeFusco Jessi , Lamberova Natalia , Mickles Blair , Long Tanisha , Beligel Eliana , Boose Quinten , Smith Paul , McMaster Alexis , Djukic-Min Dragana
Published: November 2024

(1) Background: Since the death of George Floyd, the social movement Black Lives Matter continues to dominate the American political psyche, not only advancing a public dialogue but also escalating the polarization of supported solutions for policing and systemic discrimination. (2) Methods: Using a qualitative context analysis approach, we assessed over 350 sources related to social justice literature and policy-relevant documents to identify key policy solutions supported by the American Black Lives Matter movement compared to the Blue Lives Matter movement. We applied Fearon’s bargaining range of war model to analyze the extent to which the policy recommendations of these two opposing movements may overlap. The purpose was to identify and categorize agreement alternatives across various sectors. This research presents top policy solutions, assessing their bargaining ranges. (3) Results: 32 of the 36 top policy reform alternatives at the national level have sufficient bargaining ranges. This analysis indicates the importance of supporting various sectors like mental health/psychosocial policies and programs, which can (1) serve as a focal point of agreement between contending movements, and (2) decrease racial injustice through strategic bargaining. (4) Conclusions: In a divisively political landscape, it is crucial to identify starting points for negotiation among contending actors. Identifying bargaining opportunities can help seed a dialogue that may benefit all parties involved.
Treating Yourself in a Fairway: Examining the Contribution of Self-Compassion and Well-Being on Performance in a Putting Task
Authors: Burgess Melanie R. , Mack Diane E. , Wilson Philip M. , Ferguson Leah J.
Published: November 2024

Researchers have advocated for greater insight regarding the contributions of psychological resources to sports performance. The purpose of this study was to examine the contributions of self-compassion and well-being to sports performance using a golf putting task. Male golfers (N = 87, Mage = 54.94; SDage = 15.37 years) completed the Self-Compassion Scale—Athlete Version and the Warwick Edinburgh Mental Well-Being Scale immediately prior to the golf putting task which consisted of 15 consecutive putts from 7 feet on an outdoor practice green. Performance was assessed immediately following the putting task. Simple linear regression analyses showed that self-compassion did not predict ‘perceived’ (β = −0.20, p = 0.06; ƒ2 = 0.04) or ‘actual’ (β = −0.17, p = 0.11; ƒ2 = 0.03) performance. Similarly, well-being did not predict ‘perceived’ (β = −0.16, p = 0.15; ƒ2 = 0.03) or ‘actual’ performance (β = −0.01, p = 0.91; ƒ2 = 0.00). Overall, the conclusions from this study offer converging evidence that self-compassion and well-being may not impact putting performance in adult male golfers. Greater insight into whether, and if so under what conditions, self-compassion and well-being matter to sports performance warrants additional scrutiny.
Male and Female Perceptions of Supervision During Strength Training
Authors: Carlson Luke , Hauger Maria , Vaughan-Wenner Grace , Fisher James P.
Published: November 2024

A cross-sectional survey was distributed to 1322 members of a 1-on-1 personalized strength training studio. A total of 366 respondents (n = 134 male and n = 232 female), all aged over 20 years, reported considerable training experience, with 55% of the males and 42% of the females reporting 5+ years of experience. The data were analyzed and reported descriptively with differences >5% identified based on the use of a 5-point Likert scale, the sample size, and the nature of the observations. Disparities between the males and females were identified; the males reported higher perceptions of managing effort, technique, and programming without supervision compared to the females. Safety was noted as being more important to the females compared to the males. Qualitatively, additional themes were raised including an analogy of the personal relationship between the trainer and trainee being similar to that between medical professionals and patients. This was validated where the participants discussed their adaptations from supervised strength training for maintaining quality of life in aging and recovering from medical conditions and injury. The data are discussed in the context of a previous body of literature suggesting males falsely report higher levels of confidence in tasks compared to females, particularly in relation to effort, role models, and verbal encouragement. We posit that the greater confidence expressed by males at least partially explains the greater engagement in strength training practices by males compared to females, as well as explaining the higher level of participation in supervised strength training by females compared to males. This research proves beneficial for strength training practitioners in enhancing their understanding and expectations of clients, as well as hopefully proving insightful in engaging more people in strength training.
Correction: Alotaibi et al. Preserving Postharvest Quality of Medjool Date Palm Fruits by Edible Oil Emulsions Application. Sustainability 2024, 16, 5528
Authors: Alotaibi Mashael M. , Alsubeie Moodi S. , Almuziny Makhdora , Alghamdi Sameera A. , M. Alzuaibr Fahad , Alasmari Abdulrahman , Albalawi Bedur Faleh , Ismail Khadiga Ahmed , Khalifa Sobhy M. , Dawood Ahmed S. , Shahda Mohamed A. , Ahmed Adel F. , Awad-Allah Mamdouh M. A.
Published: November 2024

The authors would like to make the following corrections to the published paper [...]
Development of Particulate Matter Concentration Estimation Models for Road Sections Based on Micro-Data
Authors: Jung Doyoung
Published: November 2024

With increasing global concerns related to global warming, air pollution, and environmental health, South Korea is actively implementing various particulate matter (PM) reduction policies to improve air quality. Accurate data analysis, including the investigation of weather phenomena, monitoring, and integrated prediction, is essential for effective PM reduction. However, the factors influencing the PM generated from domestic road sections have not yet been systematically analyzed, and currently, no predictive models utilize weather and traffic data. This study analyzed the correlations among factors influencing PM to develop models for estimating fine and coarse PM (PM2.5 and PM10, respectively) concentrations in road sections. Regression analysis models were used to assess the sensitivity of PM2.5 and PM10 concentrations to the traffic volume, whereas machine learning-based models, including linear regression, convolutional neural networks, and random forest models, were constructed and compared. The random forest models outperformed the other models, with coefficients of determination of 0.74 and 0.71 and mean absolute errors of 5.78 and 9.60 for PM2.5 and PM10, respectively. These results indicate that the random forest model provides the most accurate PM concentration estimates for road sections. The practical applications of the developed models were considered to inform effective transportation policies aimed at reducing PM. The developed model has practical applications in the formulation of transportation policies aimed at reducing PM. In particular, the model will play an important role in data-driven policymaking for sustainable urban development and environmental protection. By analyzing the correlation between traffic volume and weather conditions, policymakers can formulate more effective and sustainable strategies for reducing air pollution.
Perception of the Sustainable Cattle Ranching Concept Among Producers, Extension Specialists, and Chief Officers in Oaxaca, Mexico
Authors: Cisneros-Saguilán Pedro , Gallardo-López Felipe , López-Ortiz Silvia , Ruiz-Rosado Octavio , Herrera-Haro José G. , Ruiz-Hernández Rafael
Published: November 2024

The sustainability concept has acquired a variety of meanings according to different currents of thought and the context in which it is used. The aim of this research was to characterize the perception of cattle producers, extension specialists, and chief officers regarding sustainable cattle ranching (SCR) in an area where tropical cattle ranching is practiced. A survey was carried out among cattle producers using stratified random sampling and among extension specialists and chief officers chosen using the snowball technique. The perception of SCR was determined under two contexts: (1) the idea or interpretation and (2) the assessment (positive or negative). The idea that producers have about SCR is centered on healthy and adequate food, higher production, and better marketing of livestock. The perception of extension specialists and officials is based on greater business vision and environmental conservation. Producers oriented their perception towards the economic (48.4%) and environmental (21.3%) dimensions, similar to extension specialists (52.2% and 47.8%, respectively), while chief officers related it more exclusively to the environmental dimension (71.4%). It is concluded that the overall perception of SCR is positive, but its conceptualization is differentiated according to the role the individuals play in the activity, their academic training, and their expectations.
Integrating Sustainability and Cultural Sensitivity: Clustering Muslim Tourist Lifestyles in the Andaman Coastal Cluster, Thailand
Authors: Pongsakornrungsilp Siwarit , Pongsakornrungsilp Pimlapas , Chouykaew Thanapa , Niyomdecha Hussen , Chansamran Suchart , He Yu
Published: November 2024

This study explores the integration of sustainability and cultural sensitivity in clustering Muslim tourist lifestyles in the Andaman coastal region. The Muslim tourist demographic, representing a significant portion of the global population, prioritizes halal standards and Islamic attributes in their travel experiences. This research investigates the lifestyle patterns of Muslim tourists and their alignment with sustainable tourism principles, particularly in Thailand’s Andaman coastal area, known for its marine and beach tourism. A multi-method approach was employed, utilizing the AIO (Activities, Interests, and Opinions) framework for quantitative data collection through the surveys of 836 Muslim tourists, and qualitative insights from in-depth interviews and focus group discussions with local stakeholders. The study identified key lifestyle clusters: Mainstream Travelers, Experience Seekers, and Chillouts, each with specific preferences for halal services, prayer facilities, and eco-friendly accommodations. The findings underscore the importance of a tailored approach in promoting sustainable tourism that respects cultural values. Recommendations include enhancing halal-certified services, improving infrastructure for religious practices, and promoting eco-friendly tourism options. By aligning sustainability with cultural sensitivity, the Andaman coastal region can attract more Muslim tourists while preserving its environmental and cultural heritage. This research contributes to the broader discourse on sustainable tourism by emphasizing cultural sensitivity and provides practical guidelines for tourism stakeholders in the Andaman region to develop inclusive and sustainable tourism strategies.
Risk Assessment of Debris Flow Disasters Triggered by an Outburst of Huokou Lake in Antu County Based on an Information Quantity and Random Forest Approach
Authors: Lang Qiuling , Liu Peng , Zhang Yichen , Zhang Jiquan , Huang Jintao
Published: November 2024

Debris flow disasters frequently occur and pose considerable hazards; thus, it is essential to thoroughly evaluate their risks. This study constructs a database comprising 20 assessment indicators, utilizing comprehensive natural disaster risk assessment theory and incorporating the triggering factors of Huokou Lake in the Changbaishan Mountains. This research employs a hybrid ANP-CRITIC methodology to allocate weights to the assessment indicators efficiently. For hazard assessment, this research utilizes both the Information Quantity and Random Forest models for comparative analysis. The ROC curve was employed to validate the outcomes, ultimately favoring the Random Forest model due to its superior accuracy in assessing debris flow hazards. In this study, the risk of debris flow disasters in Antu County is comparatively assessed under scenarios with and without an outburst event. The findings indicate that areas of high and very high risk are predominantly located within the central regions of economically prosperous and densely populated townships. Additionally, the risk in Erdao Baihe Township escalates significantly when considering the outburst of Huokou Lake. The significance of this study lies in its ability to furnish a robust scientific basis for decision-makers aimed at preventing future debris flow disasters. Furthermore, it serves as a crucial reference for advancing sustainable regional development and facilitates the equilibrium between economic growth and environmental protection within disaster management strategies.
Is It Always Advisable to Promote Geodiversity and Geoheritage in a Traditional Recreational Area? A Case Study from Brno Reservoir and Its Surroundings (Czechia)
Authors: Kubalíková Lucie , Balková Marie , Bajer Aleš , Kirchner Karel
Published: November 2024

Geodiversity and geoheritage represent an important resource for geotourism and subsequent economic development both in remote natural areas and in traditional, frequently visited recreational areas. Identification, assessment, and suitable management of particular geosites may contribute to the development of sustainable forms of tourism and attract more people to the topics of geodiversity and geoheritage. However, if there is only one aim represented by geotourism development, there can be a danger of overexploitation of geoheritage, especially if the sites are promoted less adequately and not provided suitable protection. This paper is focused on the assessment of particular sites, in terms of their Earth science interest, regarding their geotourist and geoeducational potential; it is also focused on an assessment of possible risks and threats which may be related to the higher promotion and more intensive use of these sites. Based on this, proposals for sustainable management, both for geotourism and geoeducational development and nature conservation, are presented and discussed.
Application of Hydrochemical Parameters as Tool for Sustainable Management of Water Supply Network
Authors: Novotni-Horčička Nikolina , Marković Tamara , Karlović Igor , Kovač Ivan
Published: November 2024

Effective management of Water Supply Systems (WSSs) is crucial for ensuring safe drinking water. The WSS of Varaždin County is a complex network involving three groundwater sources: Bartolovec and Vinokovščak wellfields (alluvial aquifers) and Bela karstic spring. To achieve a comprehensive characterization of WSSs, routine laboratory data was integrated with stable isotopes and geochemical modeling. Within this study, all measured parameters remain below the Maximum Contaminant Level (MCL), ensuring water safety for human consumption. The Piper diagram identified variations in water sources based on their chemical composition, providing a simplified overview of mixing patterns within WSSs. Among the modeling approaches, inverse modeling (IM) was found to be more reliable than forward modeling (FM) and mass balance modeling (MB). Despite the limited capacity of δ18O to provide accurate mixing results, it was revealed that the reservoir water was in equilibrium with the air (no evaporation effects), indicating well-sealed reservoirs. Mixing modeling showed that the western, southwestern, and northern parts of the WSS mixed all three sources, whereas the eastern and southeastern areas primarily relied on the deeper aquifer of the Bartolovec source, indicating potential vulnerability. Strict validation criteria ensured the reliability of results, demonstrating the effectiveness and applicability of geochemical modeling in water security management plans.
Snow Resource Reutilization: Design of Snow Collection and Compression Equipment Based on Functional Analysis Method
Authors: Zhang Yong , Guo Junhao , Zhu Yifan , Chen Shuohui , Gao Cong , Sun Ruize , Wang Ying
Published: November 2024

High-latitude regions of the Earth are rich in natural snow resources; however, owing to their negative impact on daily life, they have not been effectively utilized for a long time and are instead viewed as obstacles that require substantial resources for clearance. This waste of resources contradicts the principles of sustainable development. With the rapid development of the ice and snow industry, the social and economic value of snow resources is gradually becoming apparent. Therefore, to promote sustainable social and economic development, this study explores new methods for processing snow resources to achieve their recycling and high-value transformation. This study employs the functional analysis method to analyze and solve the functions of the design system, utilizing the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation for the objective assessment and selection of schemes. The obtained relative optimal principles are utilized to guide the parameter setting and innovative design of the scheme in terms of functional structure. After the final scheme is output, its feasibility is verified through finite element simulation. Ultimately, to address the issue of snow resource clearing and recycling, this study designs a product scheme capable of collecting and compressing snow on road surfaces, proposing the use of snow in the form of standardized compressed snow blocks for large-scale snow sculpture construction and other fields. This method significantly reduces the cost of snow sculpture production, enhances efficiency, realizes the comprehensive utilization and high-value transformation of snow resources, and provides a reference for the sustainable development of the low-altitude ice and snow tourism industry.
Pre-Planning and Post-Evaluation Approaches to Sustainable Vernacular Architectural Practice: A Research-by-Design Study to Building Renovation in Shangri-La’s Shanpian House, China
Authors: Yang Nan , Chen Jinliu , Ban Liang , Li Pengcheng , Wang Haoqi
Published: November 2024

The renovation and revitalization of vernacular architecture are pivotal in sustainable rural development. In regions like Shangri-La, traditional structures not only safeguard cultural heritage but also provide a foundation for enhancing local communities’ living conditions. However, these villages face growing challenges, including infrastructure decay, cultural erosion, and inadequate adaptation to modern living standards. Addressing these issues requires innovative research approaches that combine heritage preservation with the integration of contemporary functionality. This study employs a research-by-design approach, focusing on the Shanpian House as a case study, to explore how pre-planning and post-evaluation methods can revitalize traditional vernacular architecture. The pre-planning phase utilizes field surveys and archival research to assess spatial, cultural, and environmental conditions, framing a design strategy informed by field theory. In doing so, it evaluates how traditional architectural elements can be preserved while introducing modern construction techniques that meet current living standards. The post-evaluation phase, conducted through questionnaires and semi-structured interviews, assesses user satisfaction, focusing on the impact of architectural esthetics, structural stability, and material choices. Key findings from an OLS regression highlight the strong positive correlation between architectural style, structural choices, and cultural relevance with resident satisfaction. The research emphasizes that design elements such as structural details, materials, and infrastructure upgrades are critical in shaping perceptions of both functionality and cultural identity. Interestingly, the model reveals that improving architectural esthetics, alongside modern indoor features such as network connectivity, has a significant impact on enhancing overall resident satisfaction (significance level: 0.181). This study contributes to the broader discourse on sustainable building renovation by demonstrating how traditional architecture can be thoughtfully adapted for contemporary use and also proposes a paradigm shift in the renovation of historic buildings, advocating for a balance between preservation and modernization. The application of sustainable materials, digital modeling, and innovative construction techniques further ensures that these traditional structures meet the demands of modern civilization while maintaining their cultural integrity.
Evaluating Energy Consumption in Residential Buildings in Qatar: A Case Study on Compounds
Authors: Al-Mohammed Reem , Ouahrani Djamel
Published: November 2024

The global urgency to cut carbon emissions and pollution is clear. Qatar, rich in fossil fuels, is shifting towards sustainability to reduce carbon emissions. This paper analyzes the energy consumption patterns in residential buildings in Qatar, categorizing them by size and ownership, and establishing energy benchmarks for each building type, offering insights to guide energy efficiency policies. By examining the building size and ownership, the study helps establish benchmarks, supporting Qatar’s sustainability goals in reducing carbon emissions. The study was conducted from 1 January 2019 to 31 December 2021, utilizing data from the Qatar General Electricity and Water Corporation (KAHRAMAA). A total of 172,796 residential buildings were analyzed, with data on building characteristics and demographic information incorporated into the analysis. A quantitative analysis revealed that the building size, ownership, and demographics significantly impact energy consumption, guiding efficiency strategies. The ownership and floor area significantly impact energy consumption. A strong positive correlation (R = 0.97) was found between energy consumption (kWh) and the total built area (m2). The patterns of energy use varied across different residential building types. The findings highlight the importance of considering the ownership and building size in energy efficiency policies. Identifying specific energy use patterns supports the development of targeted strategies. This research offers valuable data on residential energy consumption in Qatar, providing a foundation for energy benchmarks. These benchmarks can guide policy decisions and strategies to enhance energy efficiency and promote sustainability in the residential sector. This study uniquely connects the ownership and building size with energy consumption patterns in Qatar, supporting the development of effective energy policies and contributing to global sustainability goals.
The Effect of Diesel Vehicle Regulation on Air Quality in Seoul: Evidence from Seoul’s Low Emission Zone
Authors: Park Dongkyu , Tarui Nori
Published: November 2024

This study investigates the effect of the low emission zone (LEZ), designed to restrict old diesel vehicles, on air quality in Seoul, Republic of Korea, using the regression discontinuity in time (RDiT) approach. While previous studies have examined LEZ impacts using traditional econometric models such as time series and panel data approaches, our research uniquely integrates high-frequency daily weather data to better control for confounding environmental variables and captures time-of-day effects on pollutant concentrations. Our findings reveal that the LEZ policy effectively reduced NO2 and SO2 concentrations by 4.7% and 11.6%, respectively. Notably, during daytime hours, when traffic is heaviest, NO2, SO2, and PM10 concentrations decreased by 7.1%, 14.8%, and 13.6%, respectively. These results suggest that the observed improvements can be attributed not only to reduced diesel vehicle registrations but also to significant declines in overall traffic volume.
Digital Economy, Employment Structure and Labor Share
Authors: Wang Jing , Tian Zhanggong , Sun Yi
Published: November 2024

The COVID-19 pandemic significantly disrupted employment, making it challenging to increase the labor share. However, the recent expansion of the digital economy has revitalized economic growth and markedly improved productivity. This raises a critical question: can the growth of the digital economy not only boost labor productivity but also increase labor share and reduce income inequality? This paper explores the impact of digital economic development on labor share, examining the underlying mechanisms at play. Our findings suggest that the digital economy has the potential to reshape employment structures, leading to an increase in the labor share. However, the extent of this impact varies across different industries. Furthermore, from an industrial chain perspective, the digital economy has created technology spillover effects that benefit upstream and downstream sectors. In light of these findings, it is crucial to continue fostering the growth of the digital economy to address potential negative impacts on the labor share in the future.
Sustainable Development of Production–Living–Ecological Spaces: Insights from a 30-Year Remote Sensing Analysis
Authors: Hu Miaomiao , Yigitcanlar Tan , Li Fei , Deng Shengqi , Yang Yabo
Published: November 2024

The rapid pace of urbanization and industrialization has reshaped land use patterns globally, particularly within the interconnected domains of ‘production, living, and ecological spaces’ (PLES). Understanding the spatiotemporal evolution of these spaces is crucial for guiding sustainable development. Although a number of previous studies have explored aspects of their dynamics and driving factors, further investigation is needed to fully understand their long-term spatiotemporal evolution and the broader influences of socio-economic and environmental forces. This study aims to fill that important gap by leveraging advanced remote sensing techniques to analyze PLES transformations over a 30-year period. Using Henan Province, China, as a testbed, this study applies high-resolution Landsat data, land use transition matrices, dynamic degree analysis, Principal Component Analysis (PCA), and multiple linear regressions to uncover trends and underlying drivers. The results reveal a substantial reduction in production spaces by 3394.62 km² steady growth in living spaces by 4459.41 km² and complex, non-linear changes in ecological spaces, which decreased by 1067.43 km². Key driving forces, such as economic growth, urbanization, and fiscal policies are identified and discussed. These insights provide a robust framework for sustainable land use planning, with broader implications for rapidly urbanizing regions worldwide.
Examining the Influence of Sustainable Management Accounting on Sustainable Corporate Governance: Empirical Evidence
Authors: Johri Amar , Singh Raj Kumar , Alhumoudi Hamad , Alakkas Abdullah
Published: November 2024

This study, with its practical implications, is a valuable resource for organisations. It examines the impact of Sustainable Management Accounting (SMA) practices on the implementation and effectiveness of Sustainable Corporate Governance (SCG) within organisations. It also investigates the various dimensions of SMA and explores the mediating roles of the Internal Control System (ICS) in the relationships between SMA and SCG. The empirical data, collected from 512 individuals across India using a purposive sampling technique, represent a diverse cross-section of the population, including shareholders, investors, finance officers, executives, and professionals such as chartered accountants, lawyers, bankers, and company secretaries. The findings of this study are actionable, indicating that SMA has a positive and significant impact on SCG. Furthermore, it was found that SMA is influenced by factors such as the accounting system, reporting method, transparency policy, and stakeholder involvement. Moreover, the results suggest that companies with well-developed sustainable accounting systems have enhanced ICS and corporate governance metrics, which in turn result in improved board oversight and stakeholder engagement. Finally, the outcome of this study not only assists in developing sustainable corporate governance through sustainable accounting management but also contributes to the UN’s sustainable goals through accounting and governance in the corporate culture and approach.
Intricate Supply Chain Demand Forecasting Based on Graph Convolution Network
Authors: Niu Tianyu , Zhang Heng , Yan Xingyou , Miao Qiang
Published: November 2024

Globalization has contributed to the increasing complexity of supply chain structures. In this regard, precise demand forecasting for the intricate supply chain holds paramount importance in effective supply chain management. Traditional statistical models and deep learning methods often face challenges in efficiently discerning correlations within a myriad of interconnected demands. To tackle this issue, this paper proposes an intricate supply chain demand forecasting method based on graph convolution networks adept at handling non-Euclidean data. First, the companies within the supply chain are treated as nodes in the graph structure, and the relationships between them are treated as edges, with demand data serving as the features of these edges. Then, a graph convolutional network is constructed to aggregate node and edge information. Through a multi-layer network, the relationships among nodes, edges, and historical demand are established to facilitate the prediction of supply chain demands. In this process, the graph convolutional network incorporates supply chain connectivity information into demand time series analysis. This integration of surface-level topological features and deeper latent correlation attributes across the supply chain’s nodes refines the demand forecasting precision across the entire supply chain. The validation experiment in this paper is grounded in sales data of a singular product from multiple sales nodes of an electronics company. The results demonstrate that the proposed method surpasses four other traditional demand forecasting algorithms significantly in terms of accuracy, providing substantial evidence for the superior performance of graph networks in the analysis of intricate supply chain relationships.
A New Approach to Assess Sustainable Corporate Reputation with Citizen Comments Using Machine Learning and Natural Language Processing
Authors: Yiğit Açikgöz Fatma , Kayakuş Mehmet , Moiceanu Georgiana , Sönmez Nesrin
Published: November 2024

This study investigates the assessment of sustainable corporate reputation through citizen comments and how it can be measured by sentiment analysis methods based on machine learning and text mining. The research analyses citizen feedback on municipalities in the field of public services and examines their impact on the social reputation of the services provided by municipalities. Support vector machines, one of the machine learning methods, was used for sentiment analysis. In the study, Google Maps comments of the citizens receiving services from the municipality were used. The results of the sentiment analysis reveal that sustainable corporate reputation is directly related to citizen satisfaction and feedback. In this context, municipalities should continuously receive feedback and make strategic improvements based on citizens’ comments to ensure sustainable service quality. Municipalities are especially appreciated by citizens for their fast, effective, and high-quality services. However, some negative comments focus on issues such as the slowness of services, cleaning problems, and staff attitudes, indicating that certain improvements are needed. This feedback emphasises the need for continuous improvement in service quality.