bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling Environmental Potential in Smartphone Repair Practices in Vientiane Capital, Laos
Authors: Soudachanh Souphaphone , Salhofer Stefan
Published: January 2025

Waste from electrical and electronic equipment (WEEE) is expected to reach 82 million metric tons by 2030, with a global average of 7.8 kg/cap/year. In 2022, the amount of WEEE generated in Laos was 3.6 kg/cap/year, with no formal collection or treatment facilities in place. An examination of WEEE management and repair practices in the capital of Laos, Vientiane, was conducted, involving a review of the relevant literature and data gathered from interviews and online surveys of a total of 82 families, 17 junkshops, and 16 repair shops. Additionally, the environmental impact of smartphone repair activities was determined by utilizing data from existing life cycle assessment studies. The findings highlight the challenges of WEEE management, including infrastructure deficit and policy gaps. The informal sector plays a significant role in WEEE collection and dismantling. Manual dismantling takes place in junkshops prior to exportation to Vietnam, Thailand, and China. Reuse and repair are common practices and are present in both formal and informal contexts. Smartphone repair is a prevalent service alongside cooling and freezing equipment repair. The primary obstacles of repair are linked to the quality and availability of spare parts, the absence of repair guidelines and technical expertise, complicated designs, and consumer awareness. Notwithstanding the challenges associated with repairs, this case study demonstrates the environmental benefits of smartphone repair, achieving a reduction of 44% in GHG emissions compared to the conventional replacement over a 7-year observation period. Recommendations are proposed to enhance WEEE management systems and advance the repair movement.
Evaluation of Rural Road Traffic Safety in Loess Plateau Gully Area of China
Authors: Li Qin , Cui Jingya , Wu Xingping , Chen Zonghao , Lv Shuangning , Liu Yijun , Li Wenlong
Published: January 2025

In order to solve the safety ambiguity problems in the construction and use of rural roads in the gully area of the Loess Plateau, this paper proposes a safety assessment method based on the normal cloud model (NCM). First, a safety assessment index system is constructed by combining the key features of road traffic safety, and the weight coefficients of each index are determined by the entropy weight method (EWM) to set the assessment criteria. Then, the cloud eigenvalue of each indicator is calculated by using the normal cloud model to clarify the degree of its affiliation to different safety levels, which fully reflects the randomness and ambiguity in the assessment process. Finally, this paper selects a typical rural road in the gully area of the Loess Plateau for example analysis. The results show that the assessment method not only reduces the subjective influence of the evaluation criteria, effectively solves the problem of indicator ambiguity, and provides a reliable scientific basis for improving road safety, but also provides lessons and references for the improvement of transportation safety in other similar areas; improves the safety and security capacity and service level of regional roads; meets the needs of the rural masses for safe and comfortable travel; enhances the people’s sense of well-being, accessibility, and sense of security; boosts rural development; and better promotes the optimization of regional and even nationwide transportation services and service quality.
A Multi-Objective Design Optimization of a New-Build Future Homes Standard House in Controlled Conditions
Authors: Tsang Christopher , Jankovic Ljubomir , Fitton Richard , Henshaw Grant
Published: January 2025

This paper aims to determine the optimal construction strategies for new-build houses in the UK to minimize heating energy demand and discomfort hours. This research utilizes a previously calibrated model of “The Future Home” in Energy House 2.0’s environmental chamber. Eight design variables were optimized including multiple building fabric specifications, air permeability rates, and heating setpoint temperatures. Three optimization scenarios were investigated: fixed heating setpoints, variable heating setpoints, and variable setpoints with comfort constraints. The analysis revealed that while fixed heating setpoints showed limited optimization potential, variable setpoint scenarios identified three distinct clusters of optimal solutions. The optimization consistently favored superior building fabric parameters, though air permeability solutions became more nuanced with variable heating control. When constrained to a maximum of 400 discomfort hours, solutions required elevated heating setpoints (22–23 °C) while maintaining high fabric specifications. These findings advance building optimization methodology by demonstrating the importance of heating control flexibility and comfort constraints in achieving optimal performance, while the use of a calibrated model in controlled conditions overcomes the limitations of previous studies that relied on uncalibrated or hypothetical models. As in situ field measurements of short- and long-term building performance are often subjected to disruptions, delays, and uncertainties, the building performance research under controlled conditions reported in this article will lead towards the achievement of net zero targets in a timelier manner and with more certainty.
Disaster-Pregnant Environment Stability Evaluation of Geohazards in the Yellow River–Huangshui River Valley, China
Authors: Zhang Tengyue , Zhou Qiang , Ma Weidong , Gao Yuan , Li Hanmei , Zhang Qiuyang
Published: January 2025

This study aims to identify the key factors contributing to the destabilization of the geohazard disaster-pregnant environment in the Yellow River–Huangshui River Valley and provide a robust scientific basis for proactive disaster prevention, management of disaster chains, and mitigation of multi-hazard clusters in unstable regions. The research focuses on the Yellow River–Huangshui River Valley, evaluating the stability of its geohazard disaster-pregnant environment. The disaster-pregnant environment is classified into static and dynamic categories. The static disaster-pregnant environment encompasses factors such as lithology, fracture density, topography, slope, river network density, and vegetation cover. The dynamic disaster-pregnant environment incorporates variables such as extreme rainfall, consecutive rainy days, annual rainfall averages, monthly high temperatures, monthly maximum temperature variations, average annual air temperatures, and human activities. A random forest model was employed to quantitatively assess the stability of the geohazard disaster-pregnant environment in the Yellow River–Huangshui River Valley. The findings indicated that (1) extreme indicators were the primary contributors to the destabilization of the disaster-pregnant environment, with very heavy rainfall contributing 28% and consecutive rainy days contributing 27%. Human activities ranked next, accounting for 15%. (2) Unstable regions for static, dynamic, and integrated disaster-pregnant environments accounted for 44%, 45%, and 44% of the study area, respectively, with all unstable areas concentrated in river valley regions. (3) The overall trend of stability in the disaster-pregnant environment was characterized by widespread instability. Extremely unstable areas were predominantly located in river valley regions, largely influenced by human activities. Conversely, only 0.1% of the region exhibited signs of stability, and 2.1% showed a tendency toward extreme stability.
Drivers of Green Growth: Roles of Innovation and Fragility
Authors: Kazemzadeh Emad , Salehnia Narges , Yu Yang , Radulescu Magdalena
Published: January 2025

In recent years, policymakers have increasingly focused on environmental quality and economic growth. While various factors influence green growth, two important factors that have been overlooked in research are the global innovation index and the fragile states index. This study employs novel methods, such as necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA), to analyze green growth across 90 countries in 2019, surpassing traditional regression techniques. The NCA model identifies essential variables for green growth, revealing that global innovation, institutional quality, human development, and globalization are crucial conditions. Conversely, the fsQCA model offers intricate solutions by combining key variables for green growth. It presents five solutions for achieving high green growth, each tailored to specific groups of countries. For instance, Solution 1, with a consistency of 0.96%, suggests that increased consumption of renewable energy, greater trade openness, and reduced fragility in states lead to higher green growth in countries like Denmark and Austria. Thus, policymakers can foster both economic growth and environmental improvement by promoting renewable energy adoption, enhancing global trade management, and strengthening institutional quality and political stability.
Spatial Analysis of Network Attention on Tourism Resources for Sustainable Tourism Development in Western Hunan, China: A Multi-Source Data Approach
Authors: Zeng Huizi , Tang Chengjun , Zhou Chen , Zhou Peng
Published: January 2025

Understanding the tourism resource network attention is crucial for promoting sustainable tourism development. This study utilized multi-source data to assess tourism resource network attention in Western Hunan, with GIS spatial analysis and the Geodetector method applied to identify spatial patterns and influencing factors. The results indicate a distinct “dual-core” spatial clustering in network attention, with natural landscape resources centralized in Zhangjiajie and cultural landscape resources in Xiangxi Prefecture. Recreational tourism resources exhibit a similar clustering pattern around these primary and secondary centers. The factors and intensities influencing network attention differ by tourism resource type. For overall tourism resources, natural landscapes, and cultural landscapes, tourist attractions rating (X11) and attraction clustering degree (X12) are the primary drivers, with the strongest impact on natural landscapes (q = 0.648, 0.373), followed by overall resources (q = 0.361, 0.216) and cultural landscapes (q = 0.311, 0.206). In contrast, recreational resources are most influenced by nearby attractions and tourism service capacity (q(X12) = 0.743, q(X15) = 0.620), alongside notable effects from regional factors related to economic development, industrial structure, and tourism development (X1–X9). The interaction between inherent tourism resource characteristics (X10–X15) and regional environmental factors (X1–X9) enhances the driving effect on tourism resource network attention. These findings inform differentiated, resource-specific tourism planning strategies for sustainable development in Western Hunan, promoting balanced regional growth and optimized resource management through a data-driven approach.
Predicting the Performance of a Helically Coiled Heat Exchanger for Heat Recovery from a Waste Biomass Incineration System
Authors: Wardach-Świȩcicka Izabela , Polesek-Karczewska Sylwia , Da̧browski Adam
Published: January 2025

Nowadays, with increasing concerns about the environment and energy security, efforts have intensified to develop effective energy generation technologies based on renewable sources that align with the principles of sustainable growth. In response to these demands, biomass-fueled furnaces have become essential components of modern combined heat and power generation systems. This work aims to predict the thermal performance of a helically coiled multi-tube heat exchanger designed to recover heat from waste biomass incineration flue gases. The working fluid used is thermal oil. The work focuses on determining the thermal output of a heat exchanger for prescribed design parameters, including the thermal parameters of cooling oil and the temperature difference of flue gas, and the geometrical details. A novel in-house stationary lumped multi-section model, utilizing the iterative calculation method, was developed, allowing fast predictions of the operation parameters of helically coiled multi-tube type heat exchangers. Two different configurations of the exchanger, three-pipe (case I) and four-pipe (case II), were considered. The thermal output obtained from calculations for case I showed a satisfactory convergence with the value based on the measurement data, at about 6%. Once validated, the model was used to determine the required heat exchange surface area of a four-pipe heat exchanger of larger design heat output (2.2 MW) and assumed tube dimensions and configurations. The accuracy of the heat exchanger capacity prediction was below 12%, proving the developed calculation tool to be reliable for design and optimization purposes.
The Carbon Footprint of Pharmaceutical Logistics: Calculating Distribution Emissions
Authors: Ashworth Brett , du Plessis Martin Johannes , Goedhals-Gerber Leila Louise , Van Eeden Joubert
Published: January 2025

Calculating greenhouse gas (GHG) emissions across the supply chain presents a significant challenge for the pharmaceutical industry in achieving environmental sustainability. This article develops a comprehensive methodology for the data collection and calculation of GHG emissions in pharmaceutical distribution, with a focus on road transport and warehousing. The methodology specifies key data requirements and sources, enhancing transparency and alignment with industry standards, such as the GLEC Framework. Real-world pharmaceutical data were collected from a global logistics company operating in Southern Africa. The methodology was applied, which yielded significantly variable results. The calculated emission intensity factors differ significantly from those in the literature. Emissions from road transport ranged from 239.57 to 6156.80 gCO2e/t-km, depending on the vehicle size, load factor, and empty running. Warehousing emissions results show a smaller variance, ranging from 6.07 to 8.85 kgCO2e/m3 or 81.70 to 104.42 kgCO2e/t. The insights from this article support the logistics company and other stakeholders in understanding their emissions and data requirements for enhanced assessments to advance sustainable practices in pharmaceutical logistics.
System Dynamics for Manufacturing: Supply Chain Simulation of Hemp-Reinforced Polymer Composite Manufacturing for Sustainability
Authors: Kaur Gurinder , Kander Ronald
Published: January 2025

Supply chain management (SCM) involves complexities and uncertainties in the flow of goods and services from raw materials to end users. Inaccurate estimation of raw materials, labor, or equipment can lead to financial losses and environmental impacts. This study explores the application of system dynamics modeling (SDM) in manufacturing hemp-reinforced polymer composites (HRPC) to optimize resource usage. Using SDM software STELLA® (Version 3.7.3), selected for its affordability and features, the research demonstrates how system dynamics (SD) can enhance sustainability by minimizing materials, labor, and equipment, reducing energy consumption. A literature review identified a gap in existing research, as we found no prior studies simulating HRPC manufacturing using SDM. The study concludes that SDM is an effective tool for optimizing resource use and improving manufacturing efficiency. By simulating multiple supply chain scenarios in a risk-free environment, the model helps reduce resource consumption and enhance sustainability. Additionally, outputs from the STELLA® model can be used as inputs for life cycle assessment (LCA) to quantitatively measure environmental impacts.
Exploring Climate Change Adaptation Perceptions and Behavioral Responses in Iranian Desert Tourism: An Empirical Investigation from Qom Province
Authors: Torabi Zabih-Allah , Murgante Beniamino , Pourtaheri Mehdi , Hedayati Rad Fereshte
Published: January 2025

Adaptation to climate change in vulnerable tourism destinations, particularly desert regions, requires a systematic understanding of tourists’ psychological responses and behavioral adaptations. This study develops and empirically validates an integrated theoretical framework combining the Theory of Planned Behavior and Protection Motivation Theory to examine psychological determinants of tourist adaptation in Iran’s desert regions. The research systematically evaluates the relationships between risk perception, adaptation assessment, climate change beliefs, and behavioral outcomes through structural equation modeling analysis of data collected across three desert destinations in Qom Province. Results demonstrate that tourist motivation (β = 0.416, p < 0.001) and climate change beliefs (β = 0.158, p < 0.001) significantly influence adaptation intentions, while subjective norms show no significant effect despite the collectivist cultural context. The model explains 38.6% of the variance in adaptation intentions and 21.0% in maladaptive behaviors, revealing differential predictability between positive and negative responses. Analysis indicates that immediate experiential factors demonstrate a more decisive influence than abstract climate change beliefs, suggesting context-specific adaptation mechanisms in desert tourism settings. This research advances the theoretical understanding of tourist adaptation behavior while providing evidence-based recommendations for destination management in climatically vulnerable regions. The findings inform the development of targeted communication strategies and management interventions that balance environmental awareness with destination attractiveness, contributing to sustainable desert tourism development.
Research on Hydroponic Cultivation Substrates Made from Rice Straw
Authors: Wu Tingting , Wang Xiulun , Inada Tomoki
Published: January 2025

This study explores the development of a biodegradable hydroponic substrate derived from rice straw, aiming to address environmental sustainability, resource efficiency, and nutritional challenges in agriculture. Traditional non-biodegradable substrates like rockwool have inherent limitations, while the substrates developed herein offer sustainable alternatives by utilizing agricultural waste. This paper details the comprehensive process of converting rice straw into an effective hydroponic substrate through cutting, soaking, defibrating, compressing, and drying. It also evaluates key physical properties such as density, porosity, and permeability. The results indicate that the rice straw substrate meets hydroponic cultivation standards, with a density range of 0.07–0.1 g/cm3, porosity between 88 and 92%, and saturated permeability ranging from 0.02 to 0.08 cm/s, thus demonstrating its potential as a viable substitute for conventional substrates. Scanning electron microscopy (SEM) and SEM-EDS analysis show that the rice straw substrates exhibit a coarse texture and uniform cellulose particle size. The primary elements identified were carbon (C), oxygen (O), aluminum (Al), silicon (Si), and calcium (Ca).
Data Mining Applications for Pedestrian Behaviour Patterns at Unsignalized Crossings
Authors: Liu Shengqi , Evdorides Harry
Published: January 2025

This study analyses pedestrian behaviour patterns at unsignalized crossings using multiple data-mining approaches, aiming to improve pedestrian safety by understanding the relationship between movement patterns, location, and infrastructure. Utilising the STATS19 dataset from the UK Department for Transport, applied data analysis techniques, including heatmap visualisation, association rule learning, and Principal Component Analysis (PCA) with clustering, to identify high-risk behaviours and provide targeted interventions. Heatmap visualisation identifies spatial patterns and high-risk areas, while association rule learning reveals the relationships between pedestrian behaviours and infrastructure elements, highlighting the importance of facility placement and accessibility in encouraging safe crossing. PCA combined with clustering effectively reduces data complexity, revealing key factors that influence pedestrian safety. The findings emphasise the need for appropriate infrastructure, such as strategically placed zebra crossings and central refuges, to guide pedestrian behaviour and reduce accident risks. Underutilised facilities like footbridges and subways require redesign to align with pedestrian preferences. By analysing the relationship between pedestrian behaviour and infrastructure, this study aligns with the United Nations’ sustainability goals, supporting evidence-based interventions to achieve safer and more sustainable urban development. The results of this study offer insights for urban planners to prioritise safety measures and infrastructure improvements that enhance pedestrian safety at unsignalized crossings.
Prediction of Marine Shaft Centerline Trajectories Using Transformer-Based Models
Authors: Han Jialin , Zhu Qingbo , Yang Sheng , Xia Wan , Yao Yongjun
Published: January 2025

The accurate prediction of marine shaft centerline trajectories is essential for ensuring the operational performance and safety of ships. In this study, we propose a novel Transformer-based model to forecast the lateral and longitudinal displacements of ship main shafts. A key challenge in this prediction task is capturing both short-term fluctuations and long-term dependencies in shaft displacement data, which traditional models struggle to address. Our Transformer-based model integrates Bidirectional Splitting–Agg Attention and Sequence Progressive Split–Aggregation mechanisms to efficiently process bidirectional temporal dependencies, decompose seasonal and trend components, and handle the inherent symmetry of the shafting system. The symmetrical nature of the shafting system, with left and right shafts experiencing similar dynamic conditions, aligns with the bidirectional attention mechanism, enabling the model to better capture the symmetric relationships in displacement data. Experimental results demonstrate that the proposed model significantly outperforms traditional methods, such as Autoformer and Informer, in terms of prediction accuracy. Specifically, for 96 steps ahead, the mean absolute error (MAE) of our model is 0.232, compared to 0.235 for Autoformer and 0.264 for Informer, while the mean squared error (MSE) of our model is 0.209, compared to 0.242 for Autoformer and 0.286 for Informer. These results underscore the effectiveness of Transformer-based models in accurately predicting long-term marine shaft centerline trajectories, leveraging both temporal dependencies and structural symmetry, thus contributing to maritime monitoring and performance optimization.
New Numerical Quadrature Functional Inequalities on Hilbert Spaces in the Framework of Different Forms of Generalized Convex Mappings
Authors: Afzal Waqar , Cotîrlă Luminita-Ioana
Published: January 2025

The purpose of this article is to investigate some tensorial norm inequalities for continuous functions of self-adjoint operators in Hilbert spaces. Our first approach is to develop a gradient descent inequality and some relational properties for continuous functions involving Huber convex functions, as well as several new bounds for Simpson type inequality that is twice differentiable using different types of generalized convex mappings. It is believed that this study will provide a valuable contribution towards developing a new perspective on functional inequalities by utilizing some other types of generalized mappings.
Analysis of the Impact of Different Road Conditions on Accident Severity at Highway-Rail Grade Crossings Based on Explainable Machine Learning
Authors: Yang Zhen , Zhang Chen , Li Gen , Xu Hongyi
Published: January 2025

Previous studies on highway_rail grade crossing collisions have primarily focused on identifying factors contributing to the frequency and severity of driver injuries. In recent years, increasing attention has been given to modeling driver injury severity at these crossings. Recognizing the variations in injury severity under different road surface conditions, this study investigates the impact of road surface conditions on driver injury severity at highway_rail grade crossings. Using nearly a decade of accident data (2012–2021), thi study employs a LightGBM model to predict factors influencing injury severity and utilizes SHAP values for result interpretation. The symmetry principle of SHAP esures that factors with identical influence receive equal values, enhancing the reliability of predictive outcomes. The findings reveal that driver injury severity at highway_rail grade crossings varies significantly under different road surface conditions. Key factors identified include train speed, driver age, vehicle speed, annual average daily traffic (AADT), driver presence inside the vehicle, weather conditions, and location. The results indicate that collisions are more frequent when either the vehicle or train travels at high speed. Implementing speed limits for both vehicles and trains under varying road conditions could effectively reduce accident severity. Additionally, older drivers are more prone to severe accidents, highlighting the importance of installing control devices, such as warning signs or signals, to enhance driver alertness and mitigate injury risks. Furthermore, adverse weather conditions, such as rain, snow, and fog, exacerbate accident severity on road surfaces like sand, mud, dirt, oil, or gravel. Timely removal of surface obstacles may help reduce the severity of such accidents.
Integrated Dairy Production and Cattle Healthcare Management Using Blockchain NFTs and Smart Contracts
Authors: Krishnan Saravanan , Ganesan Lakshmi Prabha
Published: January 2025

Efficient cattle healthcare management is vital for ensuring productivity and welfare in dairy production, yet traditional record-keeping methods often lack transparency, security, and efficiency, leading to challenges in livestock product quality and healthcare. This study introduces a novel framework leveraging Zero Knowledge (ZK)-Rollups-enhanced Layer 2 blockchain and Non-Fungible Tokens (NFTs) to address these issues. NFTs serve as secure digital certificates for individual cattle health records, ensuring transparency and traceability. ZK-Rollups on the Layer 2 blockchain enhance scalability, privacy, and cost-efficiency, while smart contracts automate key processes such as veterinary scheduling, medication delivery, and insurance claims, minimizing administrative overhead. Performance evaluations reveal significant advancements, with transaction delays of 4.1 ms, throughput of 249.8 TPS, gas costs reduced to 26,499.76 Gwei, and a time-to-finality of 1.1 ms, achieved through ZK-SNARKs (ZK-Succinct Non-Interactive Arguments of Knowledge) integration. These results demonstrate the system’s potential to revolutionize cattle healthcare management by combining transparency, security, and operational efficiency.
Supplier Encroachment Channel Selection on an Online Retail Platform
Authors: Mou Zongyu , Ding Kaixin , Fu Yaping , Sun Hao
Published: January 2025

Online retail platforms offer encroachment opportunities for suppliers to directly sell products to consumers on the online market. However, how to select appropriate encroachment channels poses a significant challenge for suppliers. To solve this problem, we take one supplier selling products through an indirect reselling channel on a third-party online retail platform (TORP) as the base model, and further consider that the supplier can choose TORP agency selling, the owned channel, or both to encroach onto the online market. We hereby establish game-theoretical models to analyze the optimal strategy of supplier encroachment, the TORP preference, and the equilibrium channel strategy. The findings show that the supplier is always willing to encroach onto the online market through its own channel. Additionally, when the commission rate is low, the supplier will further encroach via the TORP agency selling channel. The TORP provides the agency selling channel for the supplier only when the commission rate exceeds a certain threshold. If the channel competition is not very fierce (the competition intensity is lower than 0.852) and the commission rate is moderate, dual-channel encroachment is the equilibrium channel strategy; otherwise, supplier-owned-channel encroachment is the equilibrium strategy. We extend our main models by incorporating supplier blockchain adoption and the cost differences between both parties to enhance practical applicability.
Filling the Last Major Gap in the Phylogeny of Lotus (Leguminosae): The Nearly Extinct Lotus benoistii from Morocco, a Potentially Important Breeding Resource
Authors: Degtjareva Galina V. , Samigullin Tahir H. , Valiejo-Roman Carmen M. , Chatelain Cyrille , Sokoloff Dmitry D. , Kramina Tatiana E.
Published: January 2025

Lotus, with about 120 species, is the largest genus of Leguminosae–Loteae. The last global classification recognized 14 sections, of which 13 were then sampled in molecular phylogenetic analyses. The section remaining unsampled is Lotus sect. Benedictella with one critically endangered and possibly extinct species, L. benoistii. This is an annual species known from Mediterranean-type vernal pools in the lowlands of northwestern Morocco that differs from other species of the genus in many-seeded indehiscent fruits with thin pericarp and pinnate leaves with 6–9 leaflets. This species was described in a monospecific genus and later transferred to Lotus on the basis of suggested morphological similarities with three mainly desert annuals from North Africa and Southwest Asia currently classified in Lotus sect. Chamaelotus. We provide the first molecular phylogenetic data on L. benoistii and show that it is far from L. sect. Chamaelotus. It is close to plants traditionally classified in Lotus sect. Lotus that have a center of diversity in Europe and temperate Asia. Phylogenetic analyses of plastid markers showed that L. sect. Chamaelotus belongs to a clade with major taxonomic diversity in Macaronesia, Africa, SW Asia, and Australia. Morphology does not provide arguments against the novel hypothesis on the relationships of L. benoistii. Its possible extinction is a great loss for the breeding programs of the pasture plant L. corniculatus. We provide the first anatomical data of L. benoistii, showing that its non-shattering condition has a peculiar nature that differs from all other instances of indehiscence in Loteae.
Human Activity as a Growing Threat to Marine Ecosystems: Plastic and Temperature Effects on the Sponge Sarcotragus spinosulus
Authors: Lombardo Jessica , Ribas-Taberner Maria del Mar , Quetglas-Llabrés Maria Magdalena , Pinya Samuel , Gil Llorenç , Tejada Silvia , Sureda Antoni , Compa Montserrat
Published: January 2025

Human activities increasingly threaten marine ecosystems through rising waste and temperatures. This study investigated the role of plastics as vectors for Vibrio bacteria and the effects of temperature on the marine sponge Sarcotragus spinosulus. Samples of plastics and sponges were collected during July, August (high-temperature period), and November (lower-temperature period). Bacterial growth and sponge responses were analysed using biochemical biomarkers. The results revealed a peak in colony-forming units (CFU), particularly of Vibrio alginolyticus, on plastics and sponges in August, followed by a decrease in November. In August, CFU counts of Vibrio spp. were significantly higher in sponges with poor external appearance (characterized by dull coloration and heavy epiphytic growth) but returned to levels observed in healthy sponges by November. Microplastics were detected in the tissues of both sponge groups, with higher concentrations found in affected specimens. Biomarker analyses revealed increased lysozyme, glutathione S-transferase, catalase, and superoxide dismutase activities in healthy sponges during August, while malondialdehyde levels, indicating oxidative damage, were higher in affected sponges. In conclusion, affected sponges exhibited elevated CFU counts of Vibrio spp. and reduced antioxidant and detoxification responses under elevated temperatures. These findings suggest that combined impacts of plastics and warming may pose significant risks to S. spinosulus in the context of global climate change.
Cognitive Bias in Adult Zebrafish (Danio rerio): A Systematic Review
Authors: Gazzano Valentina , Ogi Asahi , Cecchi Francesca , Curadi Maria Claudia , Marchese Maria , Gazzano Angelo
Published: January 2025

Objective: In recent years, the use of zebrafish (Danio rerio) as laboratory models has significantly increased. Ensuring their welfare is crucial, with the cognitive bias test emerging as a valuable tool to assess their emotional state. This systematic review examines the application of the cognitive bias test in zebrafish research. Data: The review adhered to PRISMA guidelines. Sources: A systematic search was conducted in scientific databases, including PubMed and Scopus, yielding 30 articles. Additionally, one abstract identified through bibliographic screening of selected papers was included. Study Selection: Six studies were selected for analysis, and their quality was assessed using SYRCLE’s risk-of-bias tool. Results: Three experimental models were employed to conduct the cognitive bias test in zebrafish, focusing on the relationship between their affective state and environmental conditions, cognitive abilities, and life-history strategies but none of the studies adequately reported the techniques employed to reduce bias. Discussion: The cognitive bias test proved effective in assessing the emotional state of zebrafish; however, methodological biases may have influenced the results. Conclusion: The cognitive bias test offers valuable insights into how emotional states affect cognitive abilities, responses to environmental changes (e.g., physical enrichment), and stress responses. Further research addressing methodological limitations is necessary to validate these findings and improve data reproducibility.
Biomechanical Comparison of Self-Compressing Screws and Cortical Screw Inserted with Lag Fashion in Canine Cadaveric Humeral Condylar Fracture Model
Authors: Cho Jun-sik , Kim Jung Moon , Choo Youn-woo , Kim Jooyoung , Kim Sorin , Kim Hwi-yool
Published: January 2025

This study compares the compression force of cortical screws used in lag fashion with partially threaded cannulated screws and fully threaded headless cannulated screws as fixation methods for humeral condylar fractures in dogs. Cadavers of eleven dogs weighing an average of 10.99 ± 2.51 kg (6.1–14.4 kg) were used. The humeri were subjected to simulated fracture by performing an osteotomy at the trochlea of humerus and classified into three groups: Group 1 applied a 3.0 mm cortical screw applied in a lag fashion, Group 2 applied a 3.0 mm partially threaded cannulated screw, and Group 3 applied a 3.5 mm fully threaded headless cannulated screw. The samples were then placed in a material testing machine, and a compression force was applied vertically to the lateral condyle until failure. There were statistically significant differences in failure load between the groups (p = 0.009). The maximum failure load in Group 3 was significantly higher than in Group 2 (p = 0.014), while there were no statistically significant differences between Group 1 and Group 2) or between Group 1 and Group 3. Partially threaded cannulated screws and fully threaded headless cannulated screws can be alternatives to traditional stabilization methods, offering simpler procedures and additional advantages.
The Impact of Short-Term Formalin Fixation on Weight and Ventricular Dimensions in the Hearts of Cats and Small-to-Medium-Sized Dogs
Authors: Janus-Ziółkowska Izabela , Bubak Joanna
Published: January 2025

Organ weight and size are important data collected during post-mortem examination not only in neoplastic diseases but also in other conditions, like cardiomyopathies. As post-mortem cardiac examination is challenging, it should be performed by experienced specialists. Nonetheless, the low number of referral centres in veterinary medicine requires the shipment of formalin-fixed specimens to perform detailed post-mortem cardiac examinations. Data regarding other tissues suggest that even short-term formalin fixation can influence the organ’s size and/or weight. Presently, no data are available on the impact of formalin fixation on heart weight and size in dogs and cats. The aim of this study was to evaluate the impact of short-term formalin fixation on cardiac weight and ventricular dimensions in cats and small-to-medium-sized dogs in the context of the usefulness and accuracy of referral examination. The study was conducted on 134 hearts (95 feline and 39 canine) obtained during necropsy. Each heart was dissected, cleaned, dried, and immersed in a 7% formalin solution for over 72 h. Weighing of the whole heart and measuring of the ventricular diameters was performed prior to fixation, after 24, 48, 72, and over 72 h of fixation. The study showed that in cats and small-to-medium-sized dogs, heart weight and ventricular dimensions are not significantly influenced by formalin fixation (p > 0.05). Nonetheless, the process of cleaning and drying the heart affects the organ weight significantly (p < 0.0001). The hearts of cats and small-to-medium-sized dogs can be shipped in formalin fixative for a referral opinion, as the fixation does not affect the obtained measurements.
When Are Models Useful? Revisiting the Quantification of Reality Checks
Authors: Koutsoyiannis Demetris
Published: January 2025

The Nash–Sutcliffe efficiency remains the best metric for measuring the appropriateness of a model and reflects a culture developed in hydrology to test models against reality before using them. This metric is not without problems, and alternative metrics have been proposed subsequently. Here, the concept of knowable moments is exploited to provide robust metrics that assess not only the second-order properties of the process of interest but also high-order moments which provide information for the entire distribution function of the process of interest. This information may be useful in hydrological tasks, as most hydrological processes are non-Gaussian. The proposed concepts are illustrated, also in relationship to existing ones, using a large-scale comparison of climatic model outputs for precipitation with reality for the last 84 years on hemispheric and continental scales.
COAST-PROSIM: A Model for Predicting Shoreline Evolution and Assessing the Impacts of Coastal Defence Structures
Authors: Scala Pietro , Manno Giorgio , Cozar Loredana Claudia , Ciraolo Giuseppe
Published: January 2025

Coastal zones, at the interface between land and sea, face increasing challenges from erosion, sea-level rise, and anthropogenic interventions, necessitating innovative tools for effective management and protection. This study introduces COAST-PROSIM, a novel numerical model specifically designed to predict shoreline evolution and assess the impacts of coastal defence structures on coastal morphology. Unlike existing models that often face a trade-off between computational efficiency and physical accuracy, COAST-PROSIM balances these demands by integrating two-dimensional wave propagation routines with advanced shoreline evolution equations. The model evaluates the effects of interventions such as breakwaters and groynes, enabling simulations of shoreline dynamics with reduced computational effort. By using high-resolution input data, COAST-PROSIM captures the interplay between hydrodynamics, sediment transport, and structural impacts. Tested on real-world case studies along the coasts of San Leone, Porto Empedocle, and Villafranca Tirrena, the model demonstrates its adaptability to diverse coastal environments. The results highlight its potential as a reliable tool for sustainable coastal management, allowing stakeholders to anticipate long-term changes in coastal morphology and design targeted mitigation strategies.
Enhancing Wireless Power Transfer Efficiency Through Innovative Metamaterial Configurations for Electric Vehicles
Authors: Onreabroy Wandee , Piemsomboon Supatsara , Traikunwaranon Suneerat , Wilaiprajuabsang Naksit , Kaewpradap Amornrat
Published: January 2025

This study investigates the enhancement of power transfer efficiency (PTE) in wireless power transfer (WPT) systems for electric vehicles (EVs) through simulations and experimental evaluations using metamaterial (MTM) configurations. The MTM model, validated against existing research, was designed for operation at 85 kHz. The influence of MTM on the magnetic field alignment and flux density at the receiver coil significantly improved PTE compared to systems without an MTM configuration. We tested various arrangements of three, six, and nine MTM cells positioned at left, right, top, bottom, and combined locations across coil distances of 0–5.0 cm. The results showed that a nine-cell MTM arrangement yielded greater PTE than a three-cell arrangement because of improved electromagnetic flux distribution. However, the T-shaped arrangement of six MTM cells achieved the maximum PTE at a 2.0 cm coil distance. This performance exceeded that of the configuration with 3 × 3 MTM cells, indicating that the T-shaped design optimizes electromagnetic flux distribution. The six-cell T-shaped arrangement boosted the PTE by 7.7% compared to the nine-cell version, demonstrating its potential as an innovative and efficient WPT system for future EV applications.
RETRACTED: Narasipuram et al. Analysis of Scalable Resonant DC–DC Converter Using GaN Switches for xEV Charging Stations. World Electr. Veh. J. 2024, 15, 218
Authors: Narasipuram Rajanand Patnaik , Mopidevi Subbarao , Dianov Anton , Tandon Amit Singh
Published: January 2025

The journal retracts the article titled “Analysis of Scalable Resonant DC–DC Converter Using GaN Switches for xEV Charging Stations” [...]
Comunidades digitales, redes sociales y procesos electorales en América Latina (2023-2024): perfiles, acciones y temas
Authors: López-López Paulo Carlos
Published: January 2025

Este Documento de Trabajo tiene como objetivo describir el perfil y el comportamiento de las comunidades digitales latinoamericanas, haciendo hincapié en los últimos procesos electorales realizados en la región (2023-2024).

Se utilizan los datos de Latinobarómetro de los años 2017, 2020 y 2023, así como el software FanPage Karma a través de los indicadores de rendimiento más destacados.

Como resultados más relevantes se identificaron los siguientes: a) el consumo de redes sociales está condicionado por variables sociodemográficas u otras como la brecha digital, creciendo notablemente entre los años 2017 y 2020, y estancándose en el año 2023; b) son las mujeres quienes las utilizan más, y existen redes ligeramente más feminizadas (Instagram o TikTok), y otras claramente masculinas (Twitter/X); c) la edad es determinante y condiciona la presencia y la actividad en una red social u otra: cuanto más joven, más activo; d) Facebook sigue siendo la red preferida, pero en claro retroceso, seguida de Instagram y de TikTok; e) Instagram es la red que presenta, en general, mayores niveles de engagement. Finalmente, al poner el foco en variables políticas, los resultados apuntan a: i) el perfil de la persona que hace un uso político es un hombre con estudios y de extrema izquierda, con la excepción de México (extrema derecha), y, ii) de las funciones asignadas a las redes, la construcción de la agenda parece ser la preeminente, destacando temas personales (Ecuador o Argentina) y temas de la agenda off-line (encuestas o debates) como los más importantes en la conversación pública digital (Uruguay y República Dominicana).
تكييف الذكاء الاصطناعي من خلال معياري الذمة والعقل في أصول الفقه الحنفي
Authors: الشارخ مريم هشام
Published: January 2025

تقوم فكرة البحث الرئيسة على بيان معياري الذمة والعقل في تكييف الذكاء الاصطناعي؛ وذلك لتوضيح مسؤوليته. ومن حيث أهمية البحث فيمكن إجمالها في: توضيح معياري الذمة والعقل اللذين تُبنى عليهما الأهلية وربطها بتطبيقات الذكاء الاصطناعي؛ ما يعين المفتي والباحث في معرفة الآثار الشرعية، وتتمثل إشكالية البحث بالآتي: ما معيارا الأهلية في عصر الذكاء الاصطناعي؟ وما تطبيقات معياري الأهلية في عصر الذكاء الاصطناعي؟ وما الأسس التي تعين الباحث الشرعي في تحديد أهلية الذكاء الاصطناعي؟ ويهدف البحث إلى توضيح معياري الأهلية في عصر الذكاء الاصطناعي، وبيان تكامل الشريعة الإسلامية في جميع أحكامها، وصلاحيتها لكل زمان ومكان. وقد اقتضت طبيعة البحث أن تقوم الباحثة باستخدام المنهج الاستقرائي التحليلي في تتبع أقوال الأصوليين، ثم تحليلها، مع اتباع المنهج المقارن. ومن أبرز النتائج التي توصلت إليها الدراسة: تَمَيُّز معياري الأهلية في احتواء المستجدات المعاصرة، وأن الذكاء الاصطناعي لا ينظر فيه الاستقلالية من عدمها، بل لابد من معرفة الأحكام الفقهية المترتبة عليه. وترى الباحثة ضرورة تبنِّي مشروع قانون لأحكام الذكاء الاصطناعي؛ لعدم وجود المراجع الكافية في معرفة الأحكام التفصيلية المتعلقة بالمسؤولية والأهلية للذكاء الاصطناعي.
الذكاء الاصطناعي وأثره في علم الجرح والتعديل: دراسة تطبيقية
Authors: الصباح هيا سلمان
Published: January 2025

فكرة البحث الرئيسة استخدام ما توصل إليه الذكاء الاصطناعي وتذليله في خدمة علم الجرح والتعديل، وإظهار قدرات نفعه ومستوى تطوره فيما وصل إليه، وتكمن أهمية البحث في بيان كيفية استخدام التطور التقني المعاصر في الذكاء الاصطناعي، وبيان مدى مساحة العطاء التي يقدمها الذكاء الاصطناعي للباحثين، ولكن من إشكالية البحث أن هذه البرامج قدرتها تظل مقيدة بالمعلومات التي تملكها فقط، وبالتالي فإن مساحة النفع قد تكون محدودة، فهي بحاجة إلى النظر المعرفي البشري كون علم الجرح والتعديل مقيدًا بالقرائن المحتفة به، ومن إشكاليات البحث أيضًا مدى أهلية الذكاء الاصطناعي أن يحظى بشروط الناقد الحديثي في الحكم على الرجال وتقسيم طبقاتهم، لذلك يهدف البحث إلى الدراسة النظرية التأصيلية لما وصل إليه الذكاء الاصطناعي في خدمة علم الجرح والتعديل من برامج وتقنيات، ومن ثم التطبيق العملي على ذلك، من خلال اختيار راوٍ من الرواة الثقات وراوِ آخر من الضعفاء وراوِ آخر من الرواة المختلف فيهم، والقيام بعد ذلك بمقارنة نتائج البحث وخلاصة الحكم بين الباحث البشري المتخصص في علم الحديث والباحث المؤهل بالمعلومات من خلال الذكاء الاصطناعي، وقد اقتضت طبيعة البحث أن المنهج التحليلي الذي أقوم من خلاله بدراسة مختلف الإشكاليات العلمية معتمدة على عدة أساليب في البحث كالتفكيك والتركيب والتقويم وإظهار النتائج، ومن أبرز النتائج التي توصلت إليها أن الذكاء الاصطناعي نفعه في خدمة علم الجرح والتعديل محدود، وأنه لا يُعد مؤهلاً إلى زماننا هذا أن يتولى الحكم على الرواة، لذلك أرى أن لا غنى للذكاء الاصطناعي عن البحث التأصيلي المعرفي البشري في علم الجرح والتعديل من قبل الباحث المتخصص في علم الحديث.
دور الذكاء الاصطناعي في تعزيز جودة التعليم في السنة النبوية: برنامج كلود Claude Ai نموذجًا
Authors: العنزي دلال حمد , السعيد فاطمة بدر
Published: January 2025

فكرة البحث تتمثل في توضيح دور الذكاء الاصطناعي Claude AI نموذج.3.5 Sonnet ومجالات استخدامه في تعزيز جودة العملية التعليمية في السنة النبوية وعلومها، وتكمن أهمية البحث أن برامج الذكاء الاصطناعي ومنها »كلود» لم يحظ بالاهتمام الكافي على الرغم من تميزه في اللغة العربية، وتحليله العميق للنصوص الشرعية، وقدراته الفائقة في مجال تدريس الحديث وعلومه، وتتمثل إشكالية البحث في بيان مجالات استخدام »كلود» لتطوير أساليب التعليم في السنة النبوية في المراحل التعليمية المختلفة، ورفع كفاءة المعلمين، ويهدف البحث إلى الكشف عن أدوات وتقنيات برنامج »كلود» التي يمكن توظيفها في تعليم السنة النبوية، وفاعليته في تحسين فهم الطلاب، مع عرض أبرز التحديات التي قد تواجه مستخدمي «كلود» من المعلمين، وقد اتبع البحث المنهج الوصفي التحليلي لتقييم دور» كلود» في هذا المجال، وتحليل قدراته بإجراء تطبيقات على نماذج مختارة من علوم السنة النبوية، ومن أبرز النتائج التي توصل إليها البحث أن «كلود» يعد أداة فعالة في تيسير تدريس الحديث وعلومه، إذ يمتاز بقدرة متميزة على تحليل النصوص الحديثية وفهمها، ويوفر دعماً شاملاً للمعلمين في مراحل الإعداد، والشرح، والتقييم، مقدماً حلولاً مبتكرة تختصر الوقت والجهد، وتلبي احتياجات الطلاب، إلا أن تحقيق الاستفادة القصوى منه تتطلب الالتزام بالإرشادات الواردة في البحث، مع الوعي بالتحديات المحتملة، ومن هنا يوصي البحث بإجراء المزيد من الدراسات لتطوير استخدام «كلود» في مجال تعليم الحديث الشريف، كما يقترح القيام بدراسات مقارنة بين «كلود» وغيره من تطبيقات الذكاء الاصطناعي، لتحديد نقاط القوة والضعف بدقة، واستثمارها بفاعلية في خدمة السنة النبوية وعلومها.