bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Calibration of 532 nm Standard Aerosol Lidar with Low Blind Area
Authors: Chen Yubao , Bu Zhichao , Wang Xiaopeng , Dai Yaru , Li Zhigang , Lu Tong , Liu Yuan , Wang Xuan
Published: February 2024

To better calibrate the aerosol lidar network constructed by the China Meteorological Administration, and ensure the data quality observed by the network, the Meteorological Observation Center (China Meteorological Administration) and the University of Naples (Italy) jointly developed a “high quality 532 nm Raman aerosol lidar” (REAL lidar) in 2018. The ability to detect Raman–Mie scattering signals was improved through signal detection in a large dynamic range. This study compared the REAL lidar with the reference lidar (European ACTRIS aerosol lidar network) considering three wavelengths and eight channels. The results show that both the original signals and data products of the two radars exhibited good consistency. In the calibration application of China’s domestic lidar network, after REAL calibration, the relative average and standard deviations of the backscattering coefficient of the in-station lidar decreased from 55.4% to 7.9% and from 64% to 9.9%, respectively. The effect was significant, which indicates that REAL is an aerosol lidar with a high-performance index. The results satisfy the demand for calibration of the aerosol lidar network, and the REAL was successfully applied to the calibration of the aerosol lidar network.
Multidecadal Changes in the Flow Velocity and Mass Balance of the Hailuogou Glacier in Mount Gongga, Southeastern Tibetan Plateau
Authors: Gu Ju , Zhang Yong , Lyu Xiaowei , Wang Huanhuan , Jiang Zongli , Wang Xin , Wei Junfeng
Published: February 2024

Maritime glaciers in the southeastern Tibetan Plateau (TP) have experienced important changes in mass and dynamics over the past decades, challenging the regional water supply and glacier-related hazards. However, knowledge about long-term variations in the surface velocity and mass balance of maritime glaciers remains incomplete due to the lack of representative observations in the southeastern TP. In this study, offset tracking is employed to measure spatiotemporal variation in the surface velocity of the Hailuogou Glacier (HLG) in Mount Gongga of the southeastern TP using Sentinel-1A imagery, while the time series of the HLG mass balance is reconstructed since 1950 by a physically based energy–mass balance model. Our satellite-based results find that HLG surface velocity shows significant spatial heterogeneity with a double-peak pattern along the flow line, and sustained slowdown below the icefall zone has been observed during the past nearly 40 years, although the icefall zone and the area above it have become relatively active. Our modeling indicates a persistent increase in mass loss over the last seven decades with an average rate of −0.58 m water equivalent (w.e.) year−1, which has accelerated in the past two decades. Sustained slowdown on the glacier is concomitant with pronounced negative mass balance, thereby enhancing glacier wastage in recent decades. The long-term trend in HLG mass loss is mainly driven by an increase in positive air temperature that decreases surface albedo and solid precipitation ratio and increases longwave incoming radiation, besides the influence of supraglacial debris cover. Large-scale atmospheric circulation patterns in the Eurasian region provide important implications for regional-to-local climate variability, unsustainably intensifying the trend of the negative mass balance of the HLG in the southeastern TP in the past two decades.
MSGFNet: Multi-Scale Gated Fusion Network for Remote Sensing Image Change Detection
Authors: Wang Yukun , Wang Mengmeng , Hao Zhonghu , Wang Qiang , Wang Qianwen , Ye Yuanxin
Published: February 2024

Change detection (CD) stands out as a pivotal yet challenging task in the interpretation of remote sensing images. Significant developments have been witnessed, particularly with the rapid advancements in deep learning techniques. Nevertheless, challenges such as incomplete detection targets and unsmooth boundaries remain as most CD methods suffer from ineffective feature fusion. Therefore, this paper presents a multi-scale gated fusion network (MSGFNet) to improve the accuracy of CD results. To effectively extract bi-temporal features, the EfficientNetB4 model based on a Siamese network is employed. Subsequently, we propose a multi-scale gated fusion module (MSGFM) that comprises a multi-scale progressive fusion (MSPF) unit and a gated weight adaptive fusion (GWAF) unit, aimed at fusing bi-temporal multi-scale features to maintain boundary details and detect completely changed targets. Finally, we use the simple yet efficient UNet structure to recover the feature maps and predict results. To demonstrate the effectiveness of the MSGFNet, the LEVIR-CD, WHU-CD, and SYSU-CD datasets were utilized, and the MSGFNet achieved F1 scores of 90.86%, 92.46%, and 80.39% on the three datasets, respectively. Furthermore, the low computational costs and small model size have validated the superior performance of the MSGFNet.
A Multi-Feature Fusion-Based Method for Crater Extraction of Airport Runways in Remote-Sensing Images
Authors: Zhao Yalun , Chen Derong , Gong Jiulu
Published: February 2024

Due to the influence of the complex background of airports and damaged areas of the runway, the existing runway extraction methods do not perform well. Furthermore, the accurate crater extraction of airport runways plays a vital role in the military fields, but there are few related studies on this topic. To solve these problems, this paper proposes an effective method for the crater extraction of runways, which mainly consists of two stages: airport runway extraction and runway crater extraction. For the previous stage, we first apply corner detection and screening strategies to runway extraction based on multiple features of the runway, such as high brightness, regional texture similarity, and shape of the runway to improve the completeness of runway extraction. In addition, the proposed method can automatically realize the complete extraction of runways with different degrees of damage. For the latter stage, the craters of the runway can be extracted by calculating the edge gradient amplitude and grayscale distribution standard deviation of the candidate areas within the runway extraction results. In four typical remote-sensing images and four post-damage remote-sensing images, the average integrity of the runway extraction reaches more than 90%. The comparative experiment results show that the extraction effect and running speed of our method are both better than those of state-of-the-art methods. In addition, the final experimental results of crater extraction show that the proposed method can effectively extract craters of airport runways, and the extraction precision and recall both reach more than 80%. Overall, our research is of great significance to the damage assessment of airport runways based on remote-sensing images in the military fields.
Dynamic Spatial–Spectral Feature Optimization-Based Point Cloud Classification
Authors: Zhang Yali , Feng Wei , Quan Yinghui , Ye Guangqiang , Dauphin Gabriel
Published: February 2024

With the development and popularization of LiDAR technology, point clouds are becoming widely used in multiple fields. Point cloud classification plays an important role in segmentation, geometric analysis, and vegetation description. However, existing point cloud classification algorithms have problems such as high computational complexity, a lack of feature optimization, and low classification accuracy. This paper proposes an efficient point cloud classification algorithm based on dynamic spatial–spectral feature optimization. It can eliminate redundant features, optimize features, reduce computational costs, and improve classification accuracy. It achieves feature optimization through three key steps. First, the proposed method extracts spatial, geometric, spectral, and other features from point cloud data. Then, the Gini index and Fisher score are used to calculate the importance and relevance of features, and redundant features are filtered. Finally, feature importance factors are used to dynamically enhance the discriminative power of highly distinguishable features to strengthen their contribution to point cloud classification. Four real-scene datasets from STPLS3D are utilized for experimentation. Compared to the other five algorithms, the proposed algorithm achieves at least a 37.97% improvement in mean intersection over union (mIoU). Meanwhile, the results indicate that the proposed algorithm can achieve high-precision point cloud classification with low computational complexity.
Inertial Motion Capturing in Ergonomic Workplace Analysis: Assessing the Correlation between RULA, Upper-Body Posture Deviations and Musculoskeletal Discomfort
Authors: Simon Steven , Dully Jonas , Dindorf Carlo , Bartaguiz Eva , Walle Oliver , Roschlock-Sachs Ilsemarie , Fröhlich Michael
Published: February 2024

(1) Background: Mobile movement analysis systems, for example, those based on Inertial Measurement Units (IMUs), enable digital real-time methods of collecting data in workplace ergonomics, but the relationship between observational method scores such as Rapid Upper Limb Assessment (RULA), upper-body posture, and their influence on musculoskeletal discomfort, has not yet been well investigated. This field study aimed to evaluate the relationship of these variables in two different target groups: production and office workers. (2) Methods: There were 64 subjects (44 men and 20 women) participating. Data collection was divided into two categories: (1) Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) (n = 64) and 3D stereophotogrammetric posture analysis (n = 58), and (2) Investigation of workload via IMU-based motion capture (MoCap) and the Borg CR-10 body map (n = 24). Correlation tests and regression analysis were performed using SPSS and MATLAB software to examine the relationship between the upper-body posture and RULA. Multivariate analysis of variance (MANOVA) was applied to examine group differences. (3) Results: The findings did not support the authors’ hypothesis that posture risk at work significantly correlates with static upper-body posture and musculoskeletal discomfort. Pelvic tilt had a weak but significant influence on RULA. The data revealed interesting trends in physical exertion, musculoskeletal discomfort, and differences between production and office workers. However, the statistical analysis did not support this. Such approaches have the potential to enhance the accuracy of assessment outcomes and, in turn, provide a stronger foundation for enhancing ergonomic conditions.
Strike 3 … Out! Investigating Pre-Game Moods, Performance, and Mental Health of Softball Umpires
Authors: Houison Ronald J. , Lamont-Mills Andrea , Kotiw Michael , Terry Peter C.
Published: February 2024

Mood research in sports typically focuses on athletes, with sports officials being largely overlooked. In the current study, mood profiling was used to determine if softball umpires reported an identifiable and consistent mood profile and if mood was predictive of umpiring performance and/or reflective of positive mental health. Eleven male and five female participants aged 25–68 years (M = 48.5 ± 15.5 years) each completed the Brunel Mood Scale on multiple occasions prior to officiating games at the 2020 U18 National Softball Championships. A total of 185 mood profiles were analysed. Performance was assessed using Softball Australia’s official umpire assessment tool. Overall, participants reported an iceberg mood profile, which tends to be associated with positive mental health and good performance. Umpiring performances (pass/fail) were correctly classified in 75.0% of cases from tension, depression, and confusion scores (p = 0.003). Participant sex explained 25.7% of the variance in mood scores (p < 0.001); age, 25.8% of the variance (p < 0.001); position on the diamond, 10.5% of the variance (p = 0.003); and accreditation level, 14.3% of the variance (p < 0.001). Australian softball umpires typically reported mood profiles associated with positive mental health, and none reported profiles associated with risk of mental ill-health.
Pathways for Cleaner, Greener, Healthier Cities: What Is the Role of Urban Agriculture in the Circular Economy of Two Nordic Cities?
Authors: De Jesus Ana , Aguiar Borges Luciane
Published: February 2024

As major hubs for energy and resource consumption and carbon emissions, cities are at the forefront of the discussion on the impacts of megatrends, such as demographic changes, technological advancements, and the shift toward climate neutrality. Despite growing literature suggesting pathways for cities to cope with these challenges, the intersection between circular economy and urban agriculture for sustainable urban development has been little explored, especially concerning practical applications. To bridge this gap, this study aimed to explore the role of urban agriculture in promoting the circularity of resources at the city level. Aarhus, in Denmark, and Ås, in Norway, provide the empirical context for this discussion that uncovers the barriers that impact the successful implementation of C-E practices in the context of UA and delves into how these obstacles challenge cities in transitioning to circular and sustainable food production models. Using a case study approach and qualitative data sources, the findings suggest that while urban agriculture demonstrates potential in reducing resource consumption, it requires further evidence-based research and clear monitoring tools to assess its environmental impact and economic viability. Obstacles to urban agriculture implementation include regulatory challenges, social acceptance of waste, high investment costs, and limited recognition of its indirect impacts. Concerning recommendations, local governance and public policies were found to play a central role in fostering circular urban agriculture by promoting collaboration, fostering innovation, developing regulatory frameworks, and showcasing successful examples.
The Impact of Public Policies and Civil Society on the Sustainable Behavior of Romanian Consumers of Electrical and Electronic Products
Authors: Vaduva Florin , Csorba Luiela Magdalena , Dabija Dan-Cristian , Lăzăroiu George
Published: February 2024

The negative impact of the waste generated by long-lasting products is a pressing issue for humanity. As such, socio-economic activities worldwide must be carried out according to sustainability principles, and governments have been increasingly pressured to develop laws and policies that protect the environment. The influence of civil society can boost the impact of public policies. For Romania, an emerging country, a well-developed legislation is needed, as well as the involvement of the administrative and civil sectors, not only in raising consumers’ awareness regarding the importance of recovering and recycling waste, but also in changing their purchasing behavior in the direction of ecological products. An empirical investigation was conducted to identify the direct and mediation effects of external factors on the behavior of electrical and electronic product consumers. Data were collected from 421 respondents and evaluated with latent variable analyses in the R statistical program. The originality of the study resides in articulating a novel relationship between recovery and recycling intentions and the preference for ecological products, enhancing understanding about sustainability in relation to electrical and electronic products. The link between recovering and recycling intentions and consumers’ preferences for ecological products was validated for the first time in our investigation. The study concludes that external factors have a meaningful direct and mediating effect on Romanian consumers’ green behavior.
Potential for Carbon Credits from Conservation Management: Price and Potential for Multi-Habitat Nature-Based Carbon Sequestration in Dorset, UK
Authors: Jones Ellie-Anne , Paige Lisa , Smith Albany , Worth Annabelle , Betts Lois , Stafford Richard
Published: February 2024

Carbon offsetting is currently a major tool in managing carbon emissions and informing sustainability plans of organisations in the drive to net-zero. This study aims to identify the offsetting potential of existing conservation schemes, and whether carbon offsetting credits could provide finance these conservation activities. The results from Dorset, in the UK, indicate that many existing conservation schemes in woodlands, heathlands, and grasslands cannot only enhance biodiversity but also capture significant amounts of carbon, and while habitats differ by region and country, the general results should be applicable elsewhere. We show that the cost per additional tonne of carbon sequestered as a result of conservation activities varies considerably between different conservation projects. On average, across the conservation projects we studied, the cost of this offsetting is GBP 80 per tonne CO2e sequestered and ranging between GBP 120 and GBP 0, depending on the project and whether existing biodiversity grants would be available. However, this figure was based on adapting and refining the existing conservation projects and did not involve expensive factors, such as purchase of land, which make the prices potentially unrealistic, especially in a Global North context. While the costs identified are higher than many offsetting schemes at present, it could present a useful option for those wishing to localise their offsetting. The concept is highly scalable and could remove significant amounts of carbon dioxide. Combining the approach with biodiversity credits or other credit schemes could make the higher costs more attractive to potential buyers.
Innovative Development of Russian Regions: Assessment and Dynamics in the Context of Sustainable Development
Authors: Yakovenko Nataliya V. , Semenova Lyudmila V. , Nikolskaya Elena Y. , Semenova Elena Y. , Rakhimbekova Zhanar S. , Karanashev Anzor Kh. , Tsoy Marina Ye. , Azarova Natalia A.
Published: February 2024

Innovative development of regions is a key factor that determines the level of competitiveness of the economies of all countries in the world. This article uses statistical tools to assess the level of innovative development of the regions of the Russian Federation. The purpose of the work is to assess the innovative development of the subjects of Russia for the period 2010–2020. Objectives of the study: (1) to study the main parameters of innovative development of the subjects of the Russian Federation; (2) to conduct a typology of Russian regions by the level of innovative development on the basis of cluster analysis. The selected time interval (2010–2020) was a period of increasing turbulent flows of development of socio-economic processes at the global, national and regional levels. Cluster analysis was used to identify spatial and functional features of innovative development of Russian regions. The obtained analytical calculations confirm a high degree of differentiation between the Russian regions by all key indicators of innovative development. The results of grouping regions on the basis of cluster analysis showed that there are four clusters based on the sum of normalized indicators, reflecting different levels of innovative development in Russian regions. The analysis revealed that most of the regions belong to the groups with moderate and low levels of innovative development. The regions of the Central and Volga Federal Districts have the highest level of innovative development, while the regions located in the north of the European part of Russia, the North Caucasus, the south of eastern Siberia and the Far East, as well as “new” regions, have a low level. The results of the study can be implemented by regional authorities for systematic monitoring of the level of innovative development of regions, making managerial decisions and developing mechanisms to ensure innovation activity in the regions.
Assessing the Physical and Environmental Aspects of Greenhouse Cultivation: A Comprehensive Review of Conventional and Hydroponic Methods
Authors: Farvardin Mahrokh , Taki Morteza , Gorjian Shiva , Shabani Edris , Sosa-Savedra Julio C.
Published: February 2024

Population growth has presented several challenges in terms of energy, food supply, and environmental protection. The agricultural industry plays a crucial role in addressing these challenges by implementing innovative technologies that optimize resource utilization, minimize environmental impacts, and increase food production. Among these technologies, greenhouse cultivation systems have garnered substantial attention due to their ability to create a controlled environment for crop growth, resulting in higher yields, improved quality, and reduced water usage. However, it is important to note that greenhouse cultivation technology is also one of the most energy-intensive sectors within agriculture, contributing significantly to global energy consumption. Despite this, the technology remains popular due to its efficiency in optimizing inputs, increasing production per unit area, enabling year-round crop production, and managing unfavorable environmental conditions such as pests, diseases, and extreme weather events. There are two primary greenhouse cultivation systems: conventional and hydroponic methods. Each system has distinct similarities and differences regarding energy consumption, crop production per unit area, and environmental impacts. In this study, we compare conventional and hydroponic greenhouse cultivation, analyzing various inputs such as temperature, light, and energy consumption. Our findings indicate that hydroponic systems, equipped with advanced control equipment and growth mediums, create optimal conditions for plant growth. Also, hydroponics offered 11 ± 1.7 times higher yields but required 82 ± 11 times more energy compared to those conventionally produced in some plant productions. Moreover, specific energy consumption increased by 17% compared to conventional cultivation for some vegetables. This information can be used to optimize energy usage, reduce costs, and promote sustainable crop production, thereby contributing to global food security and environmental sustainability.
My Human Rights Smart City: Improving Human Rights Transparency Identification System
Authors: Souza Roberto M. , Cezario Bruno S. , Affonso Estefany O. T. , Machado Andreia D. B. , Vieira Danielle P. , Chinelli Christine K. , Haddad Assed N. , Dusek Patricia M. , Miranda Maria G. de , Soares Carlos A. P. , Guedes André L. A.
Published: February 2024

This article focuses on fundamental human rights based on a historical literature review. Methodologically, a literature review and application of the design thinking (DT) method were used in three sessions using storytelling techniques and canvas drawings with managers specializing in “smart and sustainable city” projects in Brazil. The scientific work demonstrates that, in the view of the participating experts selected according to the research criteria, there are many gaps regarding fundamental human rights in cities. The digitalization of cities, with its layers of digital governance, alone is insufficient to cover gaps in basic information for populations. With the participants’ insights, it was possible to design and develop a software application (app) under strict requirements with anonymization and geolocations of human rights violations. The tests also highlighted limitations and future improvements. It is believed that the article brings an innovative approach from a scientific point of view, with a high degree of originality due to the outcomes generated from the experiences of the authors and managers specializing in managing new “smart cities”. This governance tool has the potential to be installed and improved in more than 30 countries and thus serve almost 70 million citizens around the world. A software technology transfer has already been made to the project’s partner company.
The Role of Artificial Intelligence Autonomy in Higher Education: A Uses and Gratification Perspective
Authors: Niu Wanshu , Zhang Wuke , Zhang Chuanxia , Chen Xiaofeng
Published: February 2024

With the rapid development of artificial intelligence (AI) technology, AI educators have become a reality. The advancement and increasing applications of AI technology in higher education not only provide more efficient tools for teachers in long-term and focused teaching, but also provide new active and independent spaces for sustainable self-motivated learning for college students. It is of great importance that the effects of AI educator design are understood to ensure the sustainable development and deployment of AI-driven courses at universities. This paper investigates the influences of AI educators’ autonomy design on students’ usage intentions by delving into how the artificial autonomy of AI educators satisfies students’ needs. Drawing on the uses and gratification (U&G) framework, we theoretically elaborate on how AI educator autonomy (i.e., sensing autonomy, thought autonomy, and action autonomy) influences students’ intentions to use an AI educator through the mediating effects of U&G benefits (i.e., information-seeking gratification, social interaction gratification, and entertainment gratification). By conducting an online survey (N = 673) on college students, we found that the sensing autonomy of AI educators is positively associated with usage intention due to the mediating effects of social interaction and entertainment gratifications; the thought autonomy of AI educators is positively related to usage intention, mediated by information-seeking and social interaction gratifications, and the action autonomy of AI educators is positively linked with usage intention through the paths of information-seeking and entertainment gratifications. Our findings provide both theoretical contributions and practical implications.
Mixed Palletizing for Smart Warehouse Environments: Sustainability Review of Existing Methods
Authors: Daios Adamos , Kladovasilakis Nikolaos , Kostavelis Ioannis
Published: February 2024

Mixed palletizing constitutes one of the problems in the logistics domain aroused from the need for fast product movement to satisfy the continuously increasing number of customers with the demand for highly personalized goods. In a demanding environment, such as warehouses, where break bulk and the consolidation of loads take up most of the working time, the automation of mixed palletizing can lead to increased efficiency and speed while keeping errors to a minimum. Space utilization of pallets enables savings in storage and transportation costs, boosting the overall sustainable role of the Supply Chain sector. This paper presents the proposed approaches to mixed palletizing stemming from different fields, with a focus on recent developments in the application of Industry 4.0 technologies. Our research highlights quite a few areas that require attention from researchers.
A Hybrid Model for Fitness Influencer Competency Evaluation Framework
Authors: Yang Chin-Cheng , Hsu Wan-Chi Jackie , Yeh Chung-Shu , Lin Yu-Sheng
Published: February 2024

Fitness influencers are an emerging profession in recent years. At present, the main research on fitness influencers focuses on their personal traits, professional knowledge and skills, and course content, while there is still a large research gap on the social media marketing strategies of fitness influencers, how they interact with fans, and the reasons for their influence on fans. There is a lack of a comprehensive evaluation framework for fitness influencer research, and there is no clear research on what competencies are required to become a qualified fitness influencer. Therefore, it has become an important issue to establish a comprehensive fitness influencer competency evaluation. In this study, a hybrid model of fitness influencer competency evaluation framework was developed based on government competency standards and expert knowledge using the Multiple Criteria Decision-Making (MCDM) model perspective. This evaluation should expand to include the principles of sustainable development, emphasizing the influencers’ role in advocating for environmental responsibility, social equity, and economic viability within the fitness industry. First, the study developed 21 criteria in six dimensions of fitness influencer competencies through a literature survey and interviews with several experts. The 21 criteria resonate with many of the Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 5 (Gender Equality), SDG 10 (Reduced Inequalities), and SDG 11 (Sustainable Cities and Communities). The Bayesian Best-Worst Method (Bayesian BWM) was used to generate the best group weights for fitness influencer competencies. Then, a modified Technique for Order Preference by Similarity to the Ideal Solution Based on Aspiration Level (modified TOPSIS-AL) was applied to evaluate the performance ranking of major fitness influencers in Taiwan by integrating the concept of the aspiration level. The results of the study revealed that behavioral standards were the most important dimension, emphasizing the need for fitness influencers to establish a comprehensive set of norms for their own behavioral standards. The top five criteria for fitness influencers’ competencies were self-review, punctuality and prudence, creativity, rapport and motivation, and the need to conform to one’s body image. The performance ranking was used to compare the evaluated subjects to the desired level to obtain a basis for improvement. This study effectively identifies key fitness industry competency indicators and refines business performance through the management implications proposed in this study to facilitate the development of the fitness industry.
A Social Practices Approach to Encourage Sustainable Clothing Choices
Authors: Saunders Clare , Griffin Irene , Hackney Fiona , Barbieri Anjia , Hill Katie J. , West Jodie , Willett Joanie
Published: February 2024

The literature on sustainable clothing covers five key thematic areas: problems associated with fast fashion; sustainable fibre production; sustainable design protocols; corporate responsibility; sociological and social–psychological understandings; and pro-environmental behaviour changes. This article interweaves these approaches in a study that assesses the potential of experiential learning in clothes making, mending, and modifying workshops to help generate new social practices. The workshop design drew on the five key thematic areas and purposively provided participants with infrastructures and equipment, facilitators, and peer-to-peer support and dialogue as means to help them collaboratively generate new skills, new senses of meaning, and more sustainable ways of thinking, feeling, and acting in relation to clothes. This article reveals that our social practices approach encouraged research participants to positively uptake pro-environmental clothing choices. Thematic qualitative analysis of a small sample of participants’ wardrobe audit interviews, informal discussions, reflective videos, and reflective diaries illustrates nuanced and dynamic individual responses to the workshops and other project interventions. Nuances are contingent on factors including styles, creativity, habits, and budgets. We argue that, in order to mainstream the benefits of our approach, it is necessary to normalise approaches to clothing and style that sit outside of, or adjacent to, mainstream fashion, including clothes making, mending, and modifying practices.
A Risk-Aware Approach to Digital Procurement Transformation
Authors: Dudić Željko , Vrhovac Vijoleta , Vulanović Srđan , Dakić Dušanka , Erdeji Irma , Perović Veselin
Published: February 2024

As the digital procurement transformation continues to evolve, it is crucial to adopt a risk-aware approach to ensure successful outcomes. This paper delves into the necessity of a risk-aware approach to digital procurement transformation, specifically focusing on the role of professional procurement management and the significance of supplier partnerships in the digital environment. The research aimed to examine the critical role of risk management in the digital transformation of procurement. A total of 318 respondents from Serbia participated in the study. The role of professional management in procurement must encompass risk management to guarantee success in digital procurement transformation. Furthermore, the study identified that adequate preparation, information, and training for individuals involved are crucial for a seamless transition to digital procurement. The digital transformation of procurement contributes to sustainability by enhancing efficiency, transparency, and collaboration across the supply chain, ultimately fostering environmentally conscious practices and responsible resource management. In summary, the research underscores the need for a comprehensive and risk-aware approach to digital procurement transformation, considering the pivotal roles of procurement professionals, supplier partnerships, and the integration of new technologies.
The Impact of Japan’s Discharge of Nuclear-Contaminated Water on Aquaculture Production, Trade, and Food Security in China and Japan
Authors: Liang Xiao , Yang Shilong , Lou Zhichao , Ali Abdelrahman
Published: February 2024

The aquaculture and fisheries sectors play critical roles in promoting a global nutritious and climate-friendly food system. The Japanese government started implementing the discharge of nuclear-contaminated water (NCW) into the Pacific Ocean in August 2023, which was followed by stopping the import of seafood from Japan to ensure the safety of imported food for Chinese citizens. The discharge of NCW into the ocean by Japan will directly harm the marine ecological environment and the global ecosystem due to the importance of China as the largest producer, processor, and exporter of aquatic products (APs). This paper employs the Global Trade Analysis Project (GTAP) model to simulate the future impacts of discharging the NCW under three different scenarios. The results showed that discharging NCW will lead to a global decline in AP production and also has negative repercussions on the macroeconomic landscape. Japan will face the most significant negative impact on its national macroeconomy, e.g., Japan’s GDP, total imports, total exports, household income, and social welfare will decrease by 2.18%, 3.84%, 8.30%, 2.61%, and $130.07 billion; similarly, for China, the decrease will be 0.03%, 1.21%, 0.08%, and $728.15 billion, respectively. If China’s AP consumption decreases by 10% and 20%, it will result in protein deficits of 1.536 million tons and 3.132 million tons, respectively. Japan’s deficit will reach 138,000 tons and 276,000 tons. This necessitates supplementation via the consumption of other protein-rich foods, posing a significant threat to the nutritional security of food in both China and Japan.
Evaluation of the Mechanical Performance of Warm Bio-Recycled Asphalt Mixtures
Authors: Alsarayreh Daniah , Jiménez del Barco Carrión Ana
Published: February 2024

Currently, approximately 90% of road pavement mixtures are derived from fossil fuels, a major source of the greenhouse gases contributing to global warming. This fact, together with the scarcity of raw materials in pavement engineering, has prompted recent investigations into sustainable alternatives. Biobinders, serving as substitutes or modifiers for petroleum-based asphalt binders, have gained attention, alongside the integration of recycled materials in recycled asphalt (RA). This study addresses these concerns by combining three techniques: (1) substituting a bitumen-based binder with a biobinder; (2) incorporating a high RA percentage (>30%); and (3) manufacturing the asphalt mixture at a reduced temperature (140 °C). These approaches result in the production and evaluation of warm bio-recycled asphalt mixtures. Materials were assessed at both the binder and mixture levels. The control binder, RA binder, and biobinder underwent conventional and rheological characterization. In terms of mixtures, warm bio-recycled asphalt mixtures employed a biobinder as the only virgin binder, with RA contents of 50% and 70%. Mechanical characterization focused on bearing capacity, cohesion, permanent deformations, and moisture damage. The warm bio-recycled asphalt mixtures exhibited adequate outcomes in bearing capacity through the stiffness modulus being 18,120 MPa and 15,683 MPa for bio-recycled asphalt with 50% RA and bio-recycled asphalt with 70% RA, respectively. Bio-recycled asphalt with 50% RA and bio-recycled asphalt with 70% RA showed low permanent deformation percentages, specifically 0.5% and 0.7%, respectively, in comparison to the reference recycled asphalt mixture with 1.5%, allaying concerns in practical applications due to the biobinder’s soft consistency. The bio-recycled asphalt mixture with 70% RA displayed good mechanical performance regarding the studied mechanical characterization, especially exhibiting the least susceptibility to water-induced damage with 97% of the retained indirect tensile strength ratio, addressing concerns related to moisture damage in warm asphalt mixtures with high RA content and biobinders. These findings offer valuable insights into the adoption of more sustainable practices in the asphalt pavement industry, reducing the concerns associated with warm bio-recycled asphalt mixtures.
Assessing the Role of Facial Symmetry and Asymmetry between Partners in Predicting Relationship Duration: A Pilot Deep Learning Analysis of Celebrity Couples
Authors: Shavlokhova Veronika , Vollmer Andreas , Stoll Christian , Vollmer Michael , Lang Gernot Michael , Saravi Babak
Published: February 2024

Prevailing studies on romantic relationships often emphasize facial symmetry as a factor in partner selection and marital satisfaction. This study aims to explore the inverse of this hypothesis—the relationship between facial dissimilarity and partnership duration among celebrity couples. Utilizing the CELEB-A dataset, which includes 202,599 images of 10,177 celebrities, we conducted an in-depth analysis using advanced artificial intelligence-based techniques. Deep learning and machine learning methods were employed to process and evaluate facial images, focusing on dissimilarity across various facial regions. Our sample comprised 1822 celebrity couples. The predictive analysis, incorporating models like Linear Regression, Ridge Regression, Random Forest, Support Vector Machine, and a Neural Network, revealed varying degrees of effectiveness in estimating partnership duration based on facial features and partnership status. However, the most notable performance was observed in Ridge Regression (Mean R2 = 0.0623 for whole face), indicating a moderate predictive capability. The study found no significant correlation between facial dissimilarity and partnership duration. These findings emphasize the complexity of predicting relationship outcomes based solely on facial attributes and suggest that other nuanced factors might play a more critical role in determining relationship dynamics. This study contributes to the understanding of the intricate nature of partnership dynamics and the limitations of facial attributes as predictors.
Preference of C2v Symmetry in Low-Spin Hexacarbonyls of Rare-Earth and f Elements
Authors: Kovács Attila , Klotzbücher Werner
Published: February 2024

The structures and bonding of selected neutral M(CO)6 complexes (M = Sc, Y, La, Lu, Ac and U) have been studied by density functional theory calculations. The calculations revealed the preference for C2v symmetry and low-spin electronic state for most of these complexes. The relative stability of the low-symmetry species increases gradually with the size of the metal atom. While the characteristic Oh hexa-coordinated structure is favored in the high-spin electronic state of the smaller metals, for heavier metals, important advantages of the C2v vs. Oh structures include larger charge transfer interactions in terms of transferred electrons as well as better steric conditions. Our joint experimental–theoretical analysis detected and confirmed the Oh structure of the Sc(CO)6 complex in cryogenic CO/Ar matrices.
Block-Supersymmetric Polynomials on Spaces of Absolutely Convergent Series
Authors: Kravtsiv Viktoriia
Published: February 2024

In this paper, we consider a supersymmetric version of block-symmetric polynomials on a Banach space of two-sided absolutely summing series of vectors in Cs for some positive integer s>1. We describe some sequences of generators of the algebra of block-supersymmetric polynomials and algebraic relations between the generators for the finite-dimensional case and construct algebraic bases of block-supersymmetric polynomials in the infinite-dimensional case. Furthermore, we propose some consequences for algebras of block-supersymmetric analytic functions of bounded type and their spectra. Finally, we consider some special derivatives in algebras of block-symmetric and block-supersymmetric analytic functions and find related Appell-type sequences of polynomials.
Exploring Factors Influencing Student Performance and Educational Strategies in Logistics Management Contests: An ISM Study
Authors: Huang Shupeng , Cheng Hong , Luo Meiling
Published: February 2024

Nowadays, the importance of logistics management has been increasingly realized in industry and society. However, current educational approaches in logistics management seem unable to effectively equip students with the necessary skills to cope with practical issues after graduation. Recently, contest-based education has attracted logistics management educators’ attention, but how it can be effectively utilized in this discipline is largely unclear. To fill this gap, this study followed a system approach and analyzed the factors influencing student performance in logistics management contests in China using interpretive structural modelling (ISM) and Matrice d’ Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC). The results suggest that the driving forces for improving student performance in contests are the instructors’ encouragement and their previous experience in instructing contests. Also, the contestants’ previous experience in academic contests, team leadership, and effectiveness of communication between instructors and contestants are critical influencing factors. Based on the results, the educational strategies for effective utilization of contest-based education in logistics management are discussed. This study contributes to the existing literature by using a system modeling approach to clarify the mechanisms of contest-based education adoption in logistics management as well as informing university teachers and higher education institutes about strategies to improve their education quality.
Pyrrolizidine Alkaloids in Foods, Herbal Drugs, and Food Supplements: Chemistry, Metabolism, Toxicological Significance, Analytical Methods, Occurrence, and Challenges for Future
Authors: Tábuas Bruna , Cruz Barros Sílvia , Diogo Catarina , Cavaleiro Carlos , Sanches Silva Ana
Published: February 2024

Consumers are increasingly seeking natural alternatives to chemical compounds, including the use of dried aromatic plants as seasonings instead of salt. However, the presence of pyrrolizidine alkaloids (PAs) in food supplements and dried plants has become a concern because of their link to liver diseases and their classification as carcinogenic by the International Agency for Research on Cancer (IARC). Despite European Union (EU) Regulation (EU) 2023/915, non-compliance issues persist, as indicated by alerts on the Rapid Alert System for Food and Feed (RASFF) portal. Analyzing PAs poses a challenge because of their diverse chemical structures and low concentrations in these products, necessitating highly sensitive analytical methods. Despite these challenges, ongoing advancements in analytical techniques coupled with effective sampling and extraction strategies offer the potential to enhance safety measures. These developments aim to minimize consumer exposure to PAs and safeguard their health while addressing the growing demand for natural alternatives in the marketplace.
Detection of Chikungunya Virus RNA in Oral Fluid and Urine: An Alternative Approach to Diagnosis?
Authors: Jacob-Nascimento Leile Camila , Portilho Moyra M. , Anjos Rosângela O. , Moreira Patrícia S. S. , Stauber Christine , Weaver Scott C. , Kitron Uriel , Reis Mitermayer G. , Ribeiro Guilherme S.
Published: February 2024

To evaluate whether oral fluids (OF) and urine can serve as alternative, non-invasive samples to diagnose chikungunya virus (CHIKV) infection via RT-qPCR, we employed the same RNA extraction and RT-qPCR protocols on paired serum, OF and urine samples collected from 51 patients with chikungunya during the acute phase of the illness. Chikungunya patients were confirmed through RT-qPCR in acute-phase sera (N = 19), IgM seroconversion between acute- and convalescent-phase sera (N = 12), or IgM detection in acute-phase sera (N = 20). The controls included paired serum, OF and urine samples from patients with non-arbovirus acute febrile illness (N = 28) and RT-PCR-confirmed dengue (N = 16). Nine (47%) of the patients with positive RT-qPCR for CHIKV in sera and two (17%) of those with CHIKV infection confirmed solely via IgM seroconversion had OF positive for CHIKV in RT-qPCR. One (5%) patient with CHIKV infection confirmed via serum RT-qPCR was positive in the RT-qPCR performed on urine. None of the negative control group samples were positive. Although OF may serve as an alternative sample for diagnosing acute chikungunya in specific settings, a negative result cannot rule out an infection. Further research is needed to investigate whether OF and urine collected later in the disease course when serum becomes RT-qPCR-negative may be helpful in CHIKV diagnosis and surveillance, as well as to determine whether urine and OF pose any risk of CHIKV transmission.