bluuebunny/crossref_metadata_2025 huggingface dataset:
Resilience, Mental Health, Sleep, and Smoking Mediate Pathways Between Lifetime Stressors and Multiple Sclerosis Severity
Authors: Polick Carri S. , Darwish Hala , Pestillo de Oliveira Leonardo , Watson Ali , Ricardo Nickenig Vissoci Joao , Calhoun Patrick S. , Ploutz-Snyder Robert J. , Connell Cathleen M. , Braley Tiffany J. , Stoddard Sarah A.
Published: November 2024

Introduction: Lifetime stressors (e.g., poverty, violence, discrimination) have been linked to features of multiple sclerosis (MS); yet mechanistic pathways and relationships with cumulative disease severity remain nebulous. Further, protective factors like resilience, that may attenuate the effects of stressors on outcomes, are seldom evaluated. Aim: To deconstruct pathways between lifetime stressors and cumulative severity on MS outcomes, accounting for resilience. Methods: Adults with MS (N = 924) participated in an online survey through the National MS Society listserv. Structural equation modeling was used to examine the direct and indirect effects of lifetime stressors (count/severity) on MS severity (self-reported disability, relapse burden, fatigue, pain intensity, and interference) via resilience, mental health (anxiety and depression), sleep disturbance, and smoking. Results: The final analytic model had an excellent fit (GFI = 0.998). Lifetime stressors had a direct relationship with MS severity (β = 0.27, p < 0.001). Resilience, mental health, sleep disturbance, and smoking significantly mediated the relationship between lifetime stressors and MS severity. The total effect of the mediation was significant (β = 0.45). Conclusions: This work provides foundational evidence to inform the conceptualization of pathways by which stress could influence MS disease burden. Resilience may attenuate the effects of stressors, while poor mental health, smoking, and sleep disturbances may exacerbate their impact. Parallel with usual care, these mediators could be targets for early multimodal therapies to improve the disease course.
Prevalence of Seed-Borne Fungi on Soybean (Glycine max L. Merr.) Seeds Stored Under Medium-Term Cold Room Facilities: Implications for Genebanks
Authors: Shango Abdul J , N’Danikou Sognigbé , Ramadhani Shebati , Sumaye Saphina , Nickas Jonas , Daud Michael L
Published: November 2024

This study examined the prevalence of seed-borne fungi in polyethylene plastic-packaged soybean seeds stored in a genebank and identified factors influencing their incidence. Twenty-four seed lots were sampled from the collection stored at 10 °C in the World Vegetable Center genebank in Arusha, Tanzania. The seeds used were those regenerated and harvested in 2015, 2016, and 2017. A seed health test was conducted for sterilized seeds on potato dextrose agar, sterilized seeds on top of the paper, and unsterilized seeds on top of the paper. Seven-year-old sterilized seeds plated on top of the paper exhibited the highest germination percentage (74 ± 7.09%) and lowest fungal incidence (7.00 ± 4.41%). Conversely, seven-year-old unsterilized seeds plated on top of the paper had the lowest germination (22.00 ± 6.97%) and highest fungal incidence (79.00 ± 8.31%). Older seed lots showed significantly higher equilibrium seed moisture content (Eqmc), though seed age had no significant influence on germination percentage or fungal incidence. Seed germination percentage showed a significant negative relationship with Eqmc, though Eqmc had no significant effect on fungal incidence. Meanwhile, germination percentage showed a significant negative relationship with fungal incidence. Six fungi isolates were identified using their morphological features from soybean seed samples: Absidia glauca, Aspergillus niger, Fusarium spp., Mucor hiemalis, Pestalotiopsis versicolor, and Sordaria macrospora. It is concluded that high fungal incidence negatively affects seed germination but is not significantly correlated with seed moisture content. The dry and cold storage conditions in the genebank, while effective in extending seed longevity, can unintentionally allow seed-borne mycoflora to persist. Although fungi may not actively proliferate under these conditions, they may do so when favorable conditions are restored, such as during germination tests, and consequently may compromise seed viability. Therefore, this study emphasizes the importance of increased systematic seed health checks before storage in genebanks to ensure optimal seed quality, and the replacement of all polyethylene plastic bags to aluminium foil packaging.
Pregnancy, Childbirth, and Postpartum Experiences of Racialised Brazilian Women in Portugal: An Analysis of Obstetric Violence as Gender-Based Violence
Authors: Rusu Mariana Holanda , Nogueira Conceição , Topa Joana
Published: November 2024

As gender-based violence, obstetric violence is a complex phenomenon that represents a matter for debate worldwide. The main objective of this exploratory study is to understand the experiences of obstetric violence during pregnancy, childbirth, and the postpartum period of racialised Brazilian women in the Portuguese National Health System. Using a qualitative case study research approach, semi-structured individual interviews were conducted with ten racialised Brazilian women who gave birth in Portugal. A thematic qualitative analysis was used. The findings reveal significant cases of obstetric violence, which include the complexities and lack of support, assistance and monitoring networks, structural inequalities, neglect, and intersectional discriminatory practices based on racial and cultural prejudices, as well as reflection. These experiences not only affect the physical health of mothers but also have profound psychological and emotional consequences. This study highlights the urgent need for culturally sensitive care and the implementation of policies to prevent obstetric violence, ensuring that the rights and dignity of migrant mothers are upheld. By highlighting these critical issues, this study aims to contribute to the broader discourse on maternal health care and promote social justice for these historically marginalised groups.
Quantifying Shape and Texture Biases for Enhancing Transfer Learning in Convolutional Neural Networks
Authors: Iwata Akinori , Okuda Masahiro
Published: November 2024

Neural networks have inductive biases owing to the assumptions associated with the selected learning algorithm, datasets, and network structure. Specifically, convolutional neural networks (CNNs) are known for their tendency to exhibit textural biases. This bias is closely related to image classification accuracy. Aligning the model’s bias with the dataset’s bias can significantly enhance performance in transfer learning, leading to more efficient learning. This study aims to quantitatively demonstrate that increasing shape bias within the network by varying kernel sizes and dilation rates improves accuracy on shape-dominant data and enables efficient learning with less data. Furthermore, we propose a novel method for quantitatively evaluating the balance between texture bias and shape bias. This method enables efficient learning by aligning the biases of the transfer learning dataset with those of the model. Systematically adjusting these biases allows CNNs to better fit data with specific biases. Compared to the original model, an accuracy improvement of up to 9.9% was observed. Our findings underscore the critical role of bias adjustment in CNN design, contributing to developing more efficient and effective image classification models.
Performance Evaluation of Small Wind Turbines Under Variable Winds of Cities: Case Study Applied to an Ayanz Wind Turbine with Screw Blades
Authors: Abad Gonzalo , Plaza Ander , Kerejeta Gorka
Published: November 2024

Small wind turbines placed at city locations are affected by variable-speed winds that frequently change direction. Architectural constructions, buildings of different heights and abrupt orography of Cities make the winds that occur at City locations more variable than in flat lands or at sea. However, the performance of Small-wind turbines under this type of variable wind has not been deeply studied in the specialised literature. Therefore, this article analyses the behaviour of small wind turbines under variable and gusty winds of cities, also considering three types of power electronics conversion configurations: the generally used Maximum Power Point Tracking (MPPT) configuration, the simple only-rectifier configuration and an intermediate configuration in terms of complexity called pseudo-MPPT. This general-purpose analysis is applied to a specific type of wind turbine, i.e., the Ayanz wind turbine with screw blades, which presents adequate characteristics for city locations such as; safety, reduced visual and acoustic impacts and bird casualties avoidance. Thus, a wide simulation and experimental tests-based analysis are carried out, identifying the main factors affecting the maximisation of energy production of small wind turbines in general and the Ayanz turbine in particular. It is concluded that the mechanical inertia of the wind turbine, often not even considered in the energy production analysis, is a key factor that can produce decrements of up to 25% in energy production. Then, it was also found that electric factors related to the power electronics conversion system can strongly influence energy production. Thus, it is found that an adequate design of a simple pseudo-MPPT power conversion system could extract even 5% more energy than more complex MPPT configurations, especially in quickly varying winds of cities.
Smart Cities, Digital Inequalities, and the Challenge of Inclusion
Authors: Kolotouchkina Olga , Ripoll González Laura , Belabas Warda
Published: November 2024

While cities on a global scale embrace smartness as a roadmap for efficient urban governance, disparities persist in the domain of digital accessibility, literacy, and skills, with manifestations of digital exclusion, ageism, and ableism prevalent in most digital urban experiences. Despite their commitment to bridging the digital divide, governments lack comprehensive frameworks to inform policymaking and action for inclusion in smart cities. This review paper aims to deepen the understanding of the multifaceted challenges confronting the governance of inclusion in smart cities. Drawing from a review of research encompassing digital inclusion, digital transitions, smart cities, and urban governance, we discuss who is included and excluded in the governance of smart cities; what are the necessary conditions to be met for smart cities to be considered inclusive; and how can smart city governance deliver public value and equal benefits for all. As a novel contribution, this paper outlines a reflective framework to inform citizen inclusion in the governance of smart cities. This framework is meant to act as a starting point in the design of inclusive digital urban policies, and can also be employed to assess the directions taken to date in public organizations towards more inclusive urban practices.
The Vascular Anatomical Basis for a Well-Designed Reconstruction of the Ala Nasi by a Microsurgical Preauricular Flap Technique
Authors: Faini Gianpaolo , Ferrari Alice , Hirtler Lena , Giugno Lorena , Arleo Sergio , Buffoli Barbara
Published: November 2024

Background: A microsurgical auricular flap represents a single-step technique for the reconstruction of full-thickness defects of the ala nasi. To achieve the best surgical outcomes, it is essential to have an exhaustive knowledge of the vascular network to improve the management of the surgical flap. This study aimed to provide an anatomical and surgical guide for a well-designed reconstruction of the ala nasi using a free preauricular flap. Methods: In this study, three fresh-frozen and two formalin-fixed human head specimens injected with red silicone rubber to enhance the arterial facial system were used. The reconstruction of the full-thickness defect of the ala nasi was performed using a microsurgical auricular flap technique, with the dimensions of the ala nasi and the preauricular flap duly noted. In addition, anatomical dissections were conducted, during which the positions and diameters of the main donor and recipient vessels were measured. Results: A presurgical evaluation was performed to define the flap design. A comparison of the shape and mean dimensions of the ala nasi defect (height 9.66 ± 1.40 mm; thickness 3.52 ± 0.53 mm) and the preauricular flap (height 8.50 ± 2.68 mm; thickness 3.92 ± 1.29 mm) indicated that this flap was an optimal option for the reconstruction of the ala nasi. The surgical procedure involved the full-thickness removal of the ala nasi, and the harvesting and insertion of the preauricular flap. The anatomical measurements demonstrated that the facial artery and veins were the optimal recipient vessels, with a diameter of >1 mm (2.08 ± 0.56 and 2.85 ± 0.74 mm), suitable for anastomosis with the superficial temporal artery and vein (1.86 ± 0.58 and 1.66 ± 0.15 mm). In addition, the postsurgical evaluations indicated a slight mean difference in the thickness (1.14 ± 0.65 mm) and height (1.68 ± 1.18 mm) between the ala nasi and helix and a satisfactory VAS score (7.9 ± 0.57). Conclusions: Our surgical and anatomical data provide compelling evidence in favour of free preauricular flap reconstructions of the ala nasi. This procedure allows for the correct choice of recipient vessels and the creation of a well-designed surgical flap.
Transcriptomic and Physiological Meta-Analysis of Multiple Stress-Resistant Saccharomyces cerevisiae Strains
Authors: Özel Abdulkadir , Topaloğlu Alican , Esen Ömer , Holyavkin Can , Baysan Mehmet , Çakar Zeynep Petek
Published: November 2024

Meta-analysis is a beneficial approach to reevaluating the outcomes of independent previous studies in the same scope. Saccharomyces cerevisiae, or the baker’s yeast, is a commonly used unicellular and eukaryotic model organism. In this study, 12 evolved S. cerevisiae strains that became resistant to diverse stress conditions (boron, caffeine, caloric restriction, cobalt, coniferyl aldehyde, ethanol, iron, nickel, oxidative stress, 2-phenylethanol, and silver stress) by adaptive laboratory evolution were reassessed to reveal the correlated stress/stressor clusters based on their transcriptomic and stress–cross-resistance data. Principal Component Analysis (PCA) with k-means clustering was performed. Five clusters for the transcriptomic data of strains and six clusters for cross-resistance stressors were identified. Through statistical evaluations, critical genes pertinent to each cluster were elucidated. The pathways associated with these genes were investigated using the KEGG database. The findings demonstrated that caffeine and coniferyl aldehyde stressors exhibit clear distinctions from other stressors in terms of both physiological stress-cross-resistance responses and transcriptomic profiles. Pathway analysis showed that ribosome biogenesis was downregulated, and starch and sucrose metabolism was upregulated across all clusters. Gene and pathway analyses have shown that stressors lead to distinct changes in yeast gene expression, and these alterations have been systematically documented for each cluster. Several of the highlighted genes are pivotal for further exploration and could potentially clarify new aspects of stress response mechanisms and multiple stress resistance in yeast.
Is Clonal Integration a Buffer for the Stress of Resource Acquisition Depletion in Eichhornia crassipes (Pontederiaceae) Ramets?
Authors: Demetrio Guilherme Ramos , Serafim Dalton , Coelho Flávia de Freitas
Published: November 2024

Natural selection favors the allocation of finite resources to different functions maximizing fitness. In this sense, some functions may decrease whereas others increase when resources are limited in a process called a trade-off. However, a great variety of situations may obscure trade-off detection in clonal plants, such as the ability to generate offspring by clonal growth that represents opportunities for resource uptake. The aim of this work was to evaluate if clonal integration and resource availability mediate biomass allocation patterns in E. crassipes through a greenhouse experiment. We set ramets in clonal and isolated conditions, and with and without leaf blades, and compared the relationship of biomass proportion allocated to each vegetative organ. We found that biomass allocation to vegetative structures in E. crassipes is primarily shaped by resource pools and is enhanced by clonal integration as attached ramets invest more in growth and vegetative structures. In this sense, regarding trade-off patterns in biomass allocation among vegetative organs and under resource depletion, clonal integration may represent a way to stabilize biomass allocation patterns and may decrease trade-off importance. We discuss trade-offs and clonal integration as evolutionary strategies that allow plant persistence and improve plants fitness. These findings may support aquatic plant management and control efforts while highlighting the evolutionary significance of clonal integration for plant life strategies.
The Digitalization Imperative: Unveiling the Impacts of Eco-Industry Integration on Sectoral Growth and Transformation
Authors: Li Xingyi , Liu Changxin , Zhou Jiaxin , Yan Jingjing , Liu Tianle
Published: November 2024

In the context of the global shift toward sustainable development, ecosystem-based ecological industries have become a critical area of focus for achieving green economic transformation and promoting the harmonious development of both society and the environment. This paper aims to explore the impact of industrial integration on the progression of ecological production within the framework of digitalization, with a particular emphasis on key sectors such as agriculture, forestry, and tourism. Utilizing multi-group data from 284 cities spanning the period 2011 to 2020, the study establishes a relationship between industrial integration and the growth of ecological industries, employing a two-way fixed effects model for analysis. The results demonstrate that industrial integration within ecological sectors significantly fosters sectoral development through two main mechanisms: the extension of industrial value chains and cross-sectoral synergies. Moreover, in the era of the digital economy, digitalization plays a pivotal role in facilitating the integrated development of ecological industries. The study further identifies that digital technology, digital finance, and digital expertise serve as mediating factors in this integration process. It is recommended that future initiatives focus on leveraging digital tools to enhance the integration of ecological industries, thereby advancing industrial growth. Furthermore, China is encouraged to continue promoting the integrated development of ecological industries by supporting the expansion of industrial value chains and fostering intersectoral cooperation. Simultaneously, the role of digitalization should be emphasized, with particular attention to the incorporation of relevant digital components into the industrial integration process moving forward.
Construction and Characterization of Traditional Village Landscape Cultural Genome Atlases: A Case Study in Xupu County, Hunan, China
Authors: Wang Lie , Sun Chuanhao , Wang Mo , Xiao Xiaomei
Published: November 2024

The Yuan River Basin in Hunan Province, known for its rich history and cultural heritage, is home to traditional village landscapes characterized by distinct cultural genes and regional features. This study focuses on 21 traditional villages in Xupu County, Huaihua, and develops four types of traditional village landscape cultural genome atlases at three hierarchical levels: individual villages, multiple villages, and a specific research area. These atlases include genetic linkage maps, spatial sequence maps, distribution pattern maps, and geographical pattern maps. Using Yangquepo in Zhumucun Village as a case study, we constructed a genetic linkage map for the landscape cultural genome of a single traditional village, based on the arrangement structure of courtyard layouts. Spatial sequence maps were derived from the overall spatial configuration, while distribution pattern maps and geographical pattern maps for the 21 villages were developed using kernel density analysis in ArcGIS 10.8 software. The results reveal that traditional village landscapes in the region possess a diverse cultural genome, marked by distinct regional characteristics and spatial organization patterns.
Grid-Friendly Integration of Wind Energy: A Review of Power Forecasting and Frequency Control Techniques
Authors: Loza Brian , Minchala Luis I. , Ochoa-Correa Danny , Martinez Sergio
Published: November 2024

Integrating renewable energy sources into power systems is crucial for achieving global decarbonization goals, with wind energy experiencing the most growth due to technological advances and cost reductions. However, large-scale wind farm integration presents challenges in balancing power generation and demand, mainly due to wind variability and the reduced system inertia from conventional generators. This review offers a comprehensive analysis of the current literature on wind power forecasting and frequency control techniques to support grid-friendly wind energy integration. It covers strategies for enhancing wind power management, focusing on forecasting models, frequency control systems, and the role of energy storage systems (ESSs). Machine learning techniques are widely used for power forecasting, with supervised machine learning (SML) being the most effective for short-term predictions. Approximately 33% of studies on wind energy forecasting utilize SML. Hybrid frequency control methods, combining various strategies with or without ESS, have emerged as the most promising for power systems with high wind penetration. In wind energy conversion systems (WECSs), inertial control combined with primary frequency control is prevalent, leveraging the kinetic energy stored in wind turbines. The review highlights a trend toward combining fast frequency response and primary control, with a focus on forecasting methods for frequency regulation in WECS. These findings emphasize the ongoing need for advanced forecasting and control methods to ensure the stability and reliability of future power grids.
Consumer Usability Test of Mobile Food Safety Inquiry Platform Based on Image Recognition
Authors: Park Jun-Woo , Cho Young-Hee , Park Mi-Kyung , Kim Young-Duk
Published: November 2024

Recently, as the types of imported food and the design of their packaging become more complex and diverse, digital recognition technologies such as barcodes, QR (quick response) codes, and OCR (optical character recognition) are attracting attention in order to quickly and easily check safety information (e.g., food ingredient information and recalls). However, consumers are still exposed to inaccurate and inconvenient situations because legacy technologies require dedicated terminals or include information other than safety information. In this paper, we propose a deep learning-based packaging recognition system which can easily and accurately determine food safety information with a single image captured through a smartphone camera. The detection algorithm learned a total of 100 kinds of product images and optimized YOLOv7 to secure an accuracy of over 95%. In addition, a new SUS (system usability scale)-based questionnaire was designed and conducted on 71 consumers to evaluate the usability of the system from the individual consumer’s perspective. The questionnaire consisted of three categories, namely convenience, accuracy, and usefulness, and each received a score of at least 77, which confirms that the proposed system has excellent overall usability. Moreover, in terms of task completion rate and task completion time, the proposed system is superior when it compared to existing QR code- or Internet-based recognition systems. These results demonstrate that the proposed system provides consumers with more convenient and accurate information while also confirming the sustainability of smart food consumption.
Investigating Fuel Reduction Methods Through Propeller Optimization on Coastal Ro-Ro Liner Vessels
Authors: Jugović Alen , Bukša Tomislav , Bukša Juraj , Kolanović Ines
Published: November 2024

In light of efforts to reduce GHG emissions, liner ship operators in coastal navigation are undertaking numerous activities to contribute to the reduction of fossil fuel consumption during the transitional period toward environmentally friendly propulsion systems without compromising their regular operations. Regular ship overhauls, which include removing fouling from the underwater part of the hull and optimizing propellers, also contribute to this goal and are the focus of this research. The ship propeller, as a key component of the propulsion system, plays a significant role in ensuring reliable, safe, and economical navigation. Proper selection and regular maintenance of the propeller are essential for achieving optimal performance. This paper presents the optimization of a fixed-pitch propeller according to the ISO 484/2 standard to Class I using Metrascan 3D technology. This technology enables a detailed analysis of the propeller geometry, identification of irregularities, correction, and adjustment to achieve better hydrodynamic characteristics. The pitch corrections of the propeller resulted in improved overall vessel performance and fuel consumption, as demonstrated by comparing the consumption before and after the optimization.
Correction: Xie et al. AHP and GCA Combined Approach to Green Design Evaluation of Kindergarten Furniture. Sustainability 2024, 16, 1
Authors: Xie Xiaojie , Zhu Jiangang , Ding Sheng , Chen Jingjing
Published: November 2024

The authors would like to make the following corrections to the published paper [...]
Tourism’s Influence on Economic Growth and Environment in Saudi: Present and Future
Authors: Emam Abda , Ali-Dinar Hassan
Published: November 2024

Reports from the World Tourism Organization indicate that tourism activity has been increasingly booming; this sector is essential for economic growth and may affect the environment. Tourism is one of the key strategic sectors for planned growth in Saudi Arabia’s Vision 2030. This study is designed to evaluate the long-termning association between tourist arrivals, growth domestic product (GDP), and CO2 emissions in the Kingdom of Saudi Arabia (KSA). The data related to these variables were assessed for the period 2010 to 2020. The autoregressive distributed lag (ARDL) bounds results revealed that there are long-established relations between tourist arrivals and growth domestic product and tourist arrivals and CO2 emissions. The dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) model outcomes were compatible with the outcomes of the ARDL model. In reference to the Granger causality test, tourist arrivals cause (affect) the GDP. Such a result confirms the conception that tourism encourages economic growth. No causality runs from tourist arrivals towards CO2 accumulation. This result may reflect the governmental effort to reduce CO2 accumulation and/or to perform tourism activities in a sustainable way. The results predicted that the growth rate of tourist arrivals, GDP, and CO2 accumulation equal 0.0023, 0.048, and 0.0169, respectively, during the forecast period (2021–2030), which appeared to be increasing for tourist arrivals and GDP and decreasing for CO2 accumulation. The study recommended that, to increase economic growth, tourist arrivals should be increased alongside performing tourism activities in a sustainable way. These findings point to the benefits of governance in ensuring effective policies to decarbonize the environment, and policy proposals are put forward accordingly.
Fostering Sustainable Female Participation in STEM Through Ecological Systems Theory: A Comparative Study in Three African Countries
Authors: Lasekan Olusiji Adebola , Godoy Pena Margot Teresa , Odebode Adeyinka John , Mabica Alfredo Pedro , Mabasso Raul Abílio , Mogbadunade Oluwatosin
Published: November 2024

This study explores factors influencing female engagement in STEM (Science, Technology, Engineering, and Mathematics) fields in Mozambique, Nigeria, and Uganda through Urie Bronfenbrenner’s Ecological Systems Theory. The research collected qualitative data from 81 women across these countries through open-ended surveys. Using content analysis, the results demonstrate the critical role of personal interests nurtured by family, showing how direct interactions with family influence STEM engagement at a microsystem level. The mesosystem level reveals the supportive influence of community and school interactions, emphasizing the importance of relationships between different microsystems, such as family–school collaborations, in fostering female participation in STEM. The exosystem level identifies the impact of positive media portrayals and role models, illustrating how external environments indirectly affect perceptions and aspirations in STEM through media and societal influences. The macrosystem level underscores the persistent cultural norms shaping gender roles, reflecting broader societal and cultural values that influence gender diversity in STEM fields, with 63% of respondents in Mozambique, 57% in Nigeria, and 67% in Uganda indicating that societal views on gender roles discouraged participation. Lastly, the chronosystem level captures the temporal changes and progress in gender diversity in STEM, highlighting the need for targeted interventions and policy reforms to address longstanding gender imbalances. Despite progress, significant gender imbalances remain, necessitating targeted interventions and policy reforms. The study proposes a sustainable, collaborative model to foster early interest and sustained participation of females in STEM, emphasizing the importance of seamless cooperation among families, educational institutions, communities, and government bodies. The findings aid in creating supportive environments for sustaining female STEM participation, promoting economic and social development in Sub-Saharan Africa.
Spatial Coordination Analysis and Development Methods of the Catering Sector in Yongkang City
Authors: Yang Hao , Zeng Hao , Cai Xiaoyun
Published: November 2024

The catering sector is recognized as a crucial driver for stimulating domestic consumption and fostering sustained economic growth. A scientifically informed spatial planning of the catering sector in county-level cities can help mitigate the overconcentration or excessive dispersal of resources, thereby enhancing the efficiency of land and commercial resource utilization, reducing waste, and promoting sustainable development within a county’s economy. This study focuses on Yongkang City, located in central Zhejiang Province, as a case study. Using Python 3.1 software to extract point-of-interest (POI) data, spatial analysis techniques such as standard deviation ellipses and kernel density estimation are employed to elucidate the spatial distribution characteristics of the catering sector, comprehensive transportation, and public services in Yongkang City. Furthermore, a coupling coordination degree model is utilized to quantify the coupling coordination degrees between the catering sector and comprehensive transportation (D1), as well as between the catering sector and public services (D2), ultimately assessing the overall coupling coordination degree among the three sectors (D3). Based on the analysis results, the coupling coordination degrees are categorized into five levels, followed by a detailed evaluation of the catering sector’s development across different subdistricts. The findings indicate a certain degree of spatial imbalance in the distribution of the catering sector in Yongkang City, with the western region exhibiting a more favorable development trajectory. Notably, Dongcheng Subdistrict achieved the highest coupling coordination degree (0.993), while the northern region, hindered by underdeveloped economic conditions and limited transportation infrastructure, exhibited the lowest coordination degree (0.098). Considering the unique developmental characteristics and current conditions of each subdistrict, this study advocates for the formulation of a long-term sustainable development plan for the catering sector in Yongkang City. The findings of this research may offer valuable insights for other regions and countries, thereby promoting the sustainable advancement of the catering sector.
Management Students’ Perceptions of Corporate Social Responsibility and Sustainability: The University Context of Each Country as an Explanatory Variable
Authors: Licandro Oscar , Vázquez Burguete José Luis , Ortigueira Sánchez Luis Camilo , Pinochet Sánchez Giselle Viviana
Published: November 2024

Many scientific articles have been written about management students’ perceptions of corporate social responsibility. Most of these investigations were carried out on small samples, made up of students from a single university. Very few investigations have compared students from different universities and countries. The main objective of this paper is to investigate whether students’ countries operate as an explanatory variable for their perceptions of this concept. Fifty-four previous articles were reviewed, identifying some important conceptual problems and a high amount of methodological diversity. The second objective of this paper is to describe and analyze these problems and methodologies, with the aim of contributing to the development of this field of research. A sample of 1992 undergraduate students in management courses who were studying at 18 universities located in three countries (Colombia, Ecuador and Peru) was selected. A definition of corporate social responsibility was adopted. This concept was operationalized through a set of 18 indicators. An exploratory factor analysis showed that these indicators operationalize the main dimensions of social responsibility. It was found that there are statistically significant differences between the perceptions of the students from the 18 universities, but when comparing universities from the same country, these differences disappear. In addition, it was found that the relationship between perception and country is independent of gender, age, work experience and the degree that students are pursuing. This work contributes to our current knowledge in this field of study, because it shows that the university environment of each country operates as an explanatory variable for students’ perceptions of social responsibility. Also, this work contributes to the design of appropriate methodological strategies for carrying out comparative studies on the perceptions of social responsibility, both locally and internationally.
Business Intelligence for Agricultural Foreign Trade: Design and Application of Power BI Dashboard
Authors: Sanabia-Lizarraga Karen Guadalupe , Carballo-Mendívil Blanca , Arellano-González Alejandro , Bueno-Solano Alfredo
Published: November 2024

In today’s rapidly evolving business landscape, data analytics has become a critical tool for organizations striving to remain competitive and make informed decisions. Although technology facilitates data analysis, many decision-makers need more technical knowledge to use these tools. This project focuses on developing a business intelligence system in Power BI to analyze agricultural exports from Mexico as part of the Agro-logistics Observatory, aiming to bridge this gap and make data more accessible for non-technical users. The objective is to create an interactive panel that would allow users to visualize and compare export and import data, thereby supporting decision-making for both business and academic purposes. The methodology involved collecting and cleaning data from various sources, such as public institutions, and a modeling process that integrates geospatial data and economic classifications. Key performance indicators (KPIs), such as trade balance and the export share by-product, were designed and calculated to identify critical products and trade patterns. Although similar approaches have been presented in the literature, the novelty of this research lies in the detailed presentation of its methodology, which provides a step-by-step guide for its replication that is often lacking in other studies. In addition, it offers a dashboard that integrates data from various sources, presenting them through easy-to-interpret visualizations so that stakeholders can quickly and efficiently access valuable information beyond traditional data visualization. Furthermore, the project highlights opportunities for improvements in data visualization, including integrating more specific product data and enhancing the dashboard’s capabilities through predictive analysis.
Impact of Digital Villages on Agricultural Green Growth Based on Empirical Analysis of Chinese Provincial Data
Authors: Li Jiaxuan , Peng Zhiyuan
Published: November 2024

The construction of digital villages has progressed in tandem with the transformation of traditional production methods, offering new perspectives for agricultural green growth and sustainable development. This study employs the entropy value method alongside the super-efficient global SBM (Slacks-Based Measure) mixed function model, which assesses efficiency by accounting for both inputs and outputs, thereby facilitating a comprehensive evaluation of agricultural green growth. This methodology facilitates the examination of the correlation between digital villages and agricultural green growth, as well as the influence of digital villages on this growth. Furthermore, the utilization of financial resources is employed as a mediating variable to elucidate the mechanism of action. The utilization of green finance and agricultural insurance can be facilitated by the establishment of digital villages, and that has been shown to promote agricultural green growth. Additionally, the promotion of agricultural green growth by digital village construction is stronger in middle-altitude regions, non-grain-producing regions, and regions where the digital literacy of the rural labor force is higher than average, as well as areas where the use of agricultural film is higher than average. Accelerating the construction of digital villages and promoting the utilization of rural financial resources while adapting the digital village development to local conditions are crucial for effectively fostering agricultural green growth and sustainable agricultural development.
Design Thinking Approach to Create Impact Assessment Tool: Cities2030 Case Study
Authors: Mikelsone Elina , Cīrule Iveta
Published: November 2024

This paper presents the development and testing of an impact assessment tool for the Cities2030 project aimed at transforming city-region food systems to align with the European Union’s Food2030 policy and the European Green Deal. This study highlights the importance of sustainable urban food systems, focusing on food security, environmental sustainability, and public health. Using a design thinking approach, this research emphasizes co-creation, stakeholder engagement, and iterative refinement, developing a flexible, multi-dimensional framework adaptable to diverse city-region contexts. Through collaboration with 65 stakeholders, this tool was tailored to meet the socio-economic and environmental needs of different regions. Case studies from Cities2030 partner cities demonstrate its effectiveness in fostering cross-sectoral collaboration, enhancing community participation, and driving food system innovations. Key findings reveal measurable impacts across social, environmental, and economic dimensions, while addressing challenges like regional disparities in data collection and the need for improved long-term tracking of sustainability metrics. This study concludes by underscoring the role of adaptive, inclusive strategies in assessing urban food systems’ sustainability and resilience and suggests that the tool’s framework could be applied to other urban sustainability areas, such as energy and water management.
Greener Production and Application of Slow-Release Nitrogen Fertilizer Using Plasma and Nanotechnology: A Review
Authors: Kyebogola Stewart , Kabiri Stella , Onwonga Richard Ndemo , Semalulu Onesimus , Yost Russell Shelley , Sseruwu Godfrey
Published: November 2024

The potential of both plasma and nanotechnology in producing slow-release fertilizer is immense. These technologies, when combined, may offer green and inexpensive nitrogen fertilizers, from rich renewable resources available in local areas. Together, these technologies may overcome some limitations of conventional synthetic fertilizers, which are currently expensive and associated with low nitrogen use efficiency and significant environmental concerns. This review explores the utilization of recent advances in plasma and nanotechnology, which can be leveraged to create new slow-release nitrogen fertilizers. It emphasizes their crucial role in addressing nitrogen depletion and improving crop production. Despite the lack of attempts to develop slow-release nanofertilizers from low-cost liquid nitrate generated by emission-free nonthermal plasma, the effectiveness of plasma nitrate matches that of conventional fertilizer for crop production. We propose a more efficient electrocatalytic conversion of plasma nitrate to ammonium salt, then coating it with plant-based cellulose nanoparticles to create a slow-release form. This set of processes would synchronize nutrient release with the dynamic N requirements of plants. Formulations using agro-based, low-cost cellulose nanomaterials could replace high-cost carrier hydrogels associated with low mechanical strength. This review also highlights the isolation of nanocellulose from various plant materials and its characterization in different formulations of slow-release nanoplasma N fertilizer. Additionally, we discuss mechanisms of N loss, slow-release, and retention in the soil that can contribute to the production and use of efficient, sustainable fertilizers to improve food security and, consequently, the health of our planet.
Work Satisfaction and Its Relationship with Burnout and Its Consequences, Using a Structural Model, in Air Cabin Crew Members
Authors: Fredes-Collarte Dáilet , Olivares-Faúndez Víctor , Sánchez-García José Carlos , Peralta Montecinos Jenniffer
Published: November 2024

Burnout is an emerging socio-labor phenomenon, where this problem is particularly relevant in airline cabin crew members, who face important psychosocial demands and difficult working conditions. This study aimed to analyze job satisfaction and its relationship with burnout and its consequences (family–work conflict (FWC), work–family conflict (WFC), and psychosomatic disorders), through structural models. The sample consisted of 732 workers in the aeronautical sector (204 men/28% and 528 women/72%), aged between 19 and 53 years (M = 33.56, dt = 6.62). The hypotheses were tested using a path model. The selected hypothesized model [where work satisfaction is associated according to the relationships established burnout model showed an adequate fit of the data, including a mediating role of feelings of guilt in the relationship between burnout and FWC (where FWC was associated with WFC and psychosomatic disorders). The findings of this study provide further insight into the problematic experience and development of burnout in airline cabin crews, in turn providing new evidence on the bidirectional and reciprocal relationships of FWC.
Low-Cost and Contactless Survey Technique for Rapid Pavement Texture Assessment Using Mobile Phone Imagery
Authors: Gong Zhenlong , Bruno Marco , Pazzini Margherita , Forte Anna , Girelli Valentina Alena , Vignali Valeria , Lantieri Claudio
Published: November 2024

Collecting pavement texture information is crucial to understand the characteristics of a road surface and to have essential data to support road maintenance. Traditional texture assessment techniques often require expensive equipment and complex operations. To ensure cost sustainability and reduce traffic closure times, this study proposes a rapid, cost-effective, and non-invasive surface texture assessment technique. This technology consists of capturing a set of images of a road surface with a mobile phone; then, the images are used to reconstruct the 3D surface with photogrammetric processing and derive the roughness parameters to assess the pavement texture. The results indicate that pavement images taken by a mobile phone can reconstruct the 3D surface and extract texture features with accuracy, meeting the requirements of a time-effective documentation. To validate the effectiveness of this technique, the surface structure of the pavement was analyzed in situ using a 3D structured light projection scanner and rigorous photogrammetry with a high-end reflex camera. The results demonstrated that increasing the point cloud density can enhance the detail level of the real surface 3D representation, but it leads to variations in road surface roughness parameters. Therefore, appropriate density should be chosen when performing three-dimensional reconstruction using mobile phone images. Mobile phone photogrammetry technology performs well in detecting shallow road surface textures but has certain limitations in capturing deeper textures. The texture parameters and the Abbott curve obtained using all three methods are comparable and fall within the same range of acceptability. This finding demonstrates the feasibility of using a mobile phone for pavement texture assessments with appropriate settings.
A Deep Learning-Based Approach for High-Dimensional Industrial Steam Consumption Prediction to Enhance Sustainability Management
Authors: Liu Shenglin , Xiang Yuqing , Zhou Huijie
Published: November 2024

The continuous increase in industrialized sustainable development and energy demand, particularly in the use of steam, highlights the critical importance of efficient energy forecasting for sustainability. While current deep learning models have proven effective, they often involve numerous hyperparameters that are challenging to control and optimize. To address these issues, this research presents an innovative deep learning model, automatically fine-tuned using an improved RIME optimization algorithm (IRIME), with the aim of enhancing accuracy in energy forecasting. Initially, the bidirectional gated recurrent unit (BiGRU) exhibited promising results in prediction tasks but encountered difficulties in handling the complexity of high-dimensional time-series data related to industrial steam. To overcome this limitation, a bidirectional temporal convolutional network (BiTCN) was introduced to more effectively capture long-term dependencies. Additionally, the integration of a multi-head self-attention (MSA) mechanism enabled the model to more accurately identify and predict key features within the data. The IRIME-BiTCN-BiGRU-MSA model achieved outstanding predictive performance, with an R2 of 0.87966, MAE of 0.25114, RMSE of 0.34127, and MAPE of 1.2178, outperforming several advanced forecasting methods. Although the model is computationally complex, its high precision and potential for automation offer a promising tool for high-precision forecasting of industrial steam emissions. This development supports broader objectives of enhancing energy efficiency and sustainability in industrial processes.