bluuebunny/crossref_metadata_2025 huggingface dataset:
Transformer Architecture for Micromotion Target Detection Based on Multi-Scale Subaperture Coherent Integration
Authors: Bu Linsheng , Chen Defeng , Fu Tuo , Cao Huawei , Chang Wanyu
Published: January 2025

In recent years, long-time coherent integration techniques have gained significant attention in maneuvering target detection due to their ability to effectively enhance the signal-to-noise ratio (SNR) and improve detection performance. However, for space targets, challenges such as micromotion phenomena and complex scattering characteristics make envelope alignment and phase compensation difficult, thereby limiting integration gain. To address these issues, in this study, we conducted an in-depth analysis of the echo model of cylindrical space targets (CSTs) based on different types of scattering centers. Building on this foundation, the multi-scale subaperture coherent integration Transformer (MsSCIFormer) was proposed, which integrates MsSCI with a Transformer architecture to achieve precise detection and motion parameter estimation of space targets in low-SNR environments. The core of the method lies in the introduction of a convolutional neural network (CNN) feature extractor and a dual-attention mechanism, covering both intra-subaperture attention (Intra-SA) and inter-subaperture attention (Inter-SA). This design efficiently captures the spatial distribution and motion patterns of the scattering centers of space targets. By aggregating multi-scale features, MsSCIFormer significantly enhances the detection performance and improves the accuracy of motion parameter estimation. Simulation experiments demonstrated that MsSCIFormer outperforms traditional moving target detection (MTD) methods and other deep learning-based algorithms in both detection and estimation tasks. Furthermore, each module proposed in this study was proven to contribute positively to the overall performance of the network.
Rapid Micro-Motion Feature Extraction of Multiple Space Targets Based on Improved IRT
Authors: Wu Jing , Ai Xiaofeng , Xu Zhiming , Zhu Yiqi , Wu Qihua
Published: January 2025

Micro-motion feature extraction is of great significance for target recognition. However, traditional methods mostly focus on single target and struggle to correctly separate the severely overlapping micro-motion curves of multiple targets. In this paper, a rapid micro-motion feature extraction algorithm of multiple space targets based on inverse radon transform (IRT) with a modified model is proposed. First, the high-resolution range profile (HRRP) generated from echo is subject to binarization to improve the unstable estimation caused by noise. Then, the micro-motion period in a complicated multi-target scenario is obtained by a period estimation method based on the autocorrelation coefficients of binarized HRRP. To further improve the extraction accuracy, the IRT model of the micro-range curve is modified from the sine function to second-order sine function. By searching for the remaining unknown parameters in the model in conjunction with the period, the precise micro-range curves are quickly separated. Each time the curves of a target are extracted, they are removed, and the next extraction is carried out until all the targets have been searched. Finally, simulation and experimental results indicate that the proposed algorithm can not only correctly separate the micro-motion feature curves of multiple space targets under low signal-to-noise ratio (SNR) conditions but also significantly outperforms the original IRT in terms of extraction speed.
Hyperspectral Band Selection Method Based on Global Partition Clustering
Authors: Hu Tingrui , Guo Xian , Gao Peichao
Published: January 2025

Band selection is an important step in the dimensionality reduction processing of hyperspectral images and is highly important for eliminating redundant spectral information and reducing computational costs. In recent years, band selection methods based on ordered partition have been widely used in the dimensionality reduction processing of hyperspectral images. However, most of the methods use coarse and fine partition for band subspace partition, so that the partition results are affected by equal interval partition. Furthermore, existing methods usually select a representative band in each band subspace but do not consider the relationship between the output bands in the selection process, resulting in a certain degree of redundancy between the output bands. To solve the above problems, we propose a band selection method based on global partition clustering that contains band subspace partition and band selection. The band subspace partition is based on coarse and fine partition and the similarity-based ranking-structural similarity method, which divides the band space into band subspaces according to the relationship between the number of bands in the hyperspectral image and the number of selected bands. Band selection is based on the sequential forward selection method, which iteratively selects one band as the output band in each band subspace. The proposed method makes two main contributions. Firstly, this method avoids the negative effect of equal interval partition on the results. Secondly, this method fully considers the relationship between the selected bands and the bands to be selected. The effectiveness of the proposed method is demonstrated via ablation and comparison experiments on three publicly available datasets. Comparison experiments show that the classification accuracy of the proposed method can exceed the accuracy of the comparison methods.
Strengthened Effect of Surface-Active Ionic Liquids on Curcumin Solubility and Extraction Performance of Curcuminoids
Authors: Li Dan , Qin Yuxin , Li Jingxing , Mahmood Subhan , Shi Jianqin , Cao Yu , Yao Shun
Published: January 2025

As a kind of bioactive component in the rhizome of natural plant Curcuma longa L. (turmeric), curcumin is almost insoluble in water at neutral and acidic pH, which limits its further utilization and development. At the same time, traditional extraction and separation processes typically require the use of a large number of organic solvents. Ionic liquids (ILs) are organic molten salts with melting points below 100 °C. When an ionic liquid exists in a liquid state at or near room temperature, it is referred to as a room-temperature ionic liquid (RTIL). They have a temperature range, good physical and chemical stability, and good structural designability. They have a strong solubilization enhancement effect for many organic compounds. This study first explored the molecular forms of curcumin in ionic liquid aqueous solutions and the intermolecular interactions between curcumin and ionic liquids using spectral analysis and computational chemistry methods; furthermore, using an ionic liquid aqueous solution as an extraction agent, curcumin-like substances (curcuminoids) were extracted from turmeric powders under ultrasound assisted conditions, revealing the relationship between the structure of the ionic liquid and the extraction efficiency. After that, a kinetic study was conducted for the extraction of curcuminoids from turmeric powders, using second-order kinetics fitting to obtain the rate constant and initial extraction rate during the extraction process. Finally, the comparison with a ComplexGAPI tool and antioxidant experiment was performed on the extraction by using ionic liquids and traditional solvent. The full results can provide reference for the design of IL extractants and their application for natural products.
Production of Algae-Derived Biochar and Its Application in Pollutants Adsorption—A Mini Review
Authors: Li Luyang , Wang Jinfeng , Sun Weiming , Peng Xinhong , Qi Xinhua
Published: January 2025

Developing algae cultivation for food, chemicals, and bio-energy generates a significant amount of algal waste/residue after utilization. Meanwhile, harmful algal blooms caused by abnormal proliferation of various algae produce a large amount of algal biomass, posing serious harm to human health, the environment and the economy. Converting algae body to biochar is a crucial method with which to take advantage of this resource. Biochar usually has a large specific surface area, developed pore structure, high cation exchange capacity and rich surface functional groups. With the advantage of stable physical/chemical properties and easy modification techniques, biochar posited as an ideal adsorption material. From the perspective of algal biomass utilization, this paper reviews the preparation and modification methods, structural characteristics, physicochemical properties and environmental implications of algal biochar. The adsorption effect and mechanisms of algal biochar on nutrients, heavy metals, and organic matter in water are introduced. In light of the current research status, the challenges faced in practical application of algae-derived biochar adsorption materials are pointed out, and a research direction for preparation and application is also developed, with a view to providing a reference for the further utilization of algae-derived biochar.
Research Progress in Tritium Processing Technologies: A Review
Authors: Zhao Ziqian , Sun Yandong , Chen Qi , Li Tianchi , Liu Fang , Yan Taihong , Zheng Weifang
Published: January 2025

Recent advancements in tritium separation technologies have significantly improved efficiency, particularly through the integration of vapor phase catalytic exchange (VPCE), liquid phase catalytic exchange (LPCE), and combined electrolysis catalytic exchange (CECE) methods. Combining these techniques overcomes individual limitations, enhancing separation efficiency and reducing energy consumption. The CECE process, which integrates electrolysis with catalytic exchange, offers high separation factors, making it effective for high-concentration tritiated water treatment. Solid polymer electrolyte (SPE) technology has also gained prominence for its higher efficiency, smaller equipment size, and longer lifespan compared to traditional alkaline electrolysis. While electrolysis offers high separation factors, its high energy demand limits its cost-effectiveness for large-scale operations. As a result, electrolysis is often combined with other methods like CECE to optimize both energy consumption and separation efficiency. Future research will focus on improving the energy efficiency of electrolysis for large-scale, low-cost tritiated water treatment.
The Intersection of AI, Ethics, and Journalism: Greek Journalists’ and Academics’ Perspectives
Authors: Kalfeli Panagiota (Naya) , Angeli Christina
Published: January 2025

This study aims to explore the perceptions of Greek journalists and academics on the use of artificial intelligence (AI) in Greek journalism, focusing on its benefits, risks, and potential ethical dilemmas. In particular, it seeks to (i) assess the extent of the use of AI tools by Greek journalists; (ii) investigate views on how AI might alter news production, work routines, and labor relations in the field; and (iii) examine perspectives on the ethical challenges of AI in journalism, particularly in regard to AI-generated images in media content. To achieve this, a series of 28 in-depth semi-structured interviews was conducted with Greek journalists and academics. A thematic analysis was employed to identify key themes and patterns. Overall, the findings suggest that AI penetration in Greek journalism is in its early stages, with no formal training, strategy, or framework in place within Greek media. Regarding ethical concerns, there is evident skepticism and caution among journalists and academics about issues, such as, data bias, transparency, privacy, and copyright, which are further intensified by the absence of a regulatory framework.
The Effectiveness of Kindness Intervention for Promoting Positive Emotions and Reducing Depressive Symptoms in Mexican Adults
Authors: Palacios-Delgado Jorge , Ambriz-Flores Marcos , Cruz-Vargas Daniela Judith
Published: January 2025

Background: In recent years, research has noted that depression is a prevalent mental health problem worldwide, including in Mexico among adults. Psychological interventions, such as those based on kindness, have shown promise in reducing depressive symptoms. However, there is little research in cultural contexts such as Mexico. In this context, the objective of the present research was to evaluate the preliminary efficacy of a brief intervention of performing kind acts (amabilidad) to increase happiness level as well as positive affect and reduce negative affect and depression symptoms among Mexican adults. Methods: A feasibility study was carried out with a pre-post intervention design with a control group of Mexican adults. The study used validated scales to measure happiness, positive and negative affect, and depression symptoms before and after the intervention. Participants received a brief intervention that included exercises to write expressions of kindness and practice acts of kindness towards themselves and others. Results: Preliminary results suggest that the kindness-based intervention produced improvements in their happiness, decreases in negative affect, and a significant reduction in depression symptoms compared to baseline levels and the control group. Conclusions: The findings of this study support the feasibility and potential effectiveness of kindness-based interventions to reduce depressive symptoms in Mexican adults.
Timing of Preventive Highway Maintenance: A Study from the Whole Life Cycle Perspective
Authors: Wubuli Abulimiti , Li Fangfang , Cao Shanwei , Zhang Lingling
Published: January 2025

As the mileage of China’s highways increases, the focus of highway development has shifted from construction to maintenance and management. With the rapid increase in highway traffic, the overuse of highways, combined with the effects of climate change, has accelerated the occurrence of highway problems and poses new challenges to maintenance strategies. From a system optimization perspective, this paper examines the problem of determining the optimal timing of preventive maintenance on highways. To overcome the shortcomings of this method, which cannot reflect the economic benefits and costs, the total benefits and costs were calculated for different pavement ages within a given analysis period, based on the framework of life cycle analysis. The maintenance timing program with the highest cost-benefit ratio was taken as the optimum maintenance timing program and an example analysis was adopted to validate the feasibility of this method. When the timing of preventive maintenance is later in a pavement’s life cycle, the total life cycle benefit decreases while the total life cycle cost increases. Compared to previous studies, this paper considers both direct and indirect influences simultaneously, showing that indirect influence contributes to shortening the timing of pavement preventive maintenance.
Performance Evaluation and Integration Strategies for Solar Façades in Diverse Climates: A State-of-the-Art Review
Authors: Zagorskas Jurgis , Turskis Zenonas
Published: January 2025

This review article discusses the performance evaluation and integration strategies for solar façades, focusing on photovoltaic (PV) façades in diverse climatic conditions. It examines recent technology developments and methodologies for performance assessment, highlighting the potential of solar façades to enhance energy performance through on-site electricity generation. This study offers novel insights into the economic viability of façade-mounted photovoltaics, highlighting their potential in urban areas with constrained rooftop availability. Additionally, it emphasizes their distinct advantages in cold climates, such as reduced maintenance requirements and extended operational lifespans. Additionally, it addresses challenges such as technical complexity, esthetic considerations, and market awareness, emphasizing the balance between efficiency and design. Novel findings underscore the promise of advanced materials like perovskites in improving the flexibility and performance, as well as strategies to optimize BIPV integration in different climate zones. For stakeholders, this research highlights the importance of supportive policies and innovative solutions to overcome barriers, while offering researchers valuable perspectives on the advancement of solar façades toward zero-energy and zero-carbon building targets.
Application of Black-Winged Differential-Variant Whale Optimization Algorithm in the Optimization Scheduling of Cascade Hydropower Stations
Authors: Zhang Mi , Liu Zixuan , Bao Rungang , Zhu Shuli , Mo Li , Yang Yuqi
Published: January 2025

Hydropower is a vital strategic component of China’s clean energy development. Its construction and optimized water resource allocation are crucial for addressing global energy challenges, promoting socio-economic development, and achieving sustainable development. However, the optimization scheduling of cascade hydropower stations is a large-scale, multi-constrained, and nonlinear problem. Traditional optimization methods suffer from low computational efficiency, while conventional intelligent algorithms still face issues like premature convergence and local optima, which severely hinder the full utilization of water resources. This study proposed an improved whale optimization algorithm, the Black-winged Differential-variant Whale Optimization Algorithm (BDWOA), which enhanced population diversity through a Logistic-Sine-Cosine combination chaotic map, improved algorithm flexibility with an adaptive adjustment strategy, and introduced the migration mechanism of the black-winged kite algorithm along with a differential mutation strategy to enhance the global search ability and convergence capacity. The BDWOA algorithm was tested using test functions with randomly generated simulated data, with its performance compared against five related optimization algorithms. Results indicate that the BDWOA achieved the optimal value with the fewest iterations, effectively overcoming the limitations of the original whale optimization algorithm. Further validation using actual runoff data for the cascade hydropower station optimization scheduling model showed that the BDWOA effectively enhanced power generation efficiency. In high-flow years, the average power generation increased by 8.3%, 6.5%, 6.8%, 4.1%, and 8.2% compared to the five algorithms while achieving the shortest computation time. Significant improvements in power generation were also observed in normal-flow and low-flow years. The scheduling solutions generated by the BDWOA can adapt to varying inflow conditions, offering an innovative approach to solving complex hydropower station optimization scheduling problems. This contributes to the sustainable utilization of water resources and supports the long-term development of renewable energy.
Sustainability Benefit Evaluation and Optimization of Rural Public Spaces Under Self-Organization Theory
Authors: Li Zhixiu , Cheng Shixi , Xiao Lin , Wei Yangyang , Fang Tianchuan
Published: January 2025

Agriculture-oriented rural areas represent one of the forms of specialized agricultural practices and economic development. Public spaces serve as critical carriers within the rural spatial system. Rural public spaces are divided into two forms: explicit spaces and implicit spaces. The interaction between these forms significantly influences the morphological evolution of rural public spaces. This study takes the ancient village cluster in Anyi, Nanchang City, China as a case study. By collecting POI (Point of Interest) data and conducting surveys on visitors’ landscape preferences, it employs a life circle spatial division method and the VEISD (Village Evaluation Indicators for Sustainable Development) entropy model to evaluate the sustainability benefits of rural public spaces. Based on the evaluation results, the study proposes a control and guidance method for public spaces under self-organization theory. This method leverages the interference effects of explicit rural public spaces on implicit spaces to optimize rural public spaces. The study focuses on the planning and renovation of public space nodes in Luotian Village. By adjusting the sub-indicator “Village Public Environment Construction D22”, it validates the scientific robustness of the systems analysis theory and the VEISD framework. By adjusting the spatial layout and attributes of a critical spatial node—the Ancient Camphor Tree Square in Luotian Village—within rural public space planning, the study advances the guidance and control of public spaces during the self-organization evolution of rural areas. It enhances the openness of spatial forms and the functional integration of public space nodes. The results demonstrate that this method can analyze the vitality characteristics of factors within subsystems through the layout and indicator system of rural public spaces. It also validates the findings via correlation tests with the demands for POI and landscape preferences, ultimately constructing the VEISD framework for rural public spaces. This research provides theoretical support for optimizing the resource transformation and utilization of rural public spaces, offering a reference model for the sustainable development of rural areas.
The Enhancement of the Horizontal Ecological Protection Compensation Mechanism in the Yu-Lu Section of the Yellow River Basin
Authors: Shao Wenlu , Tian Guiliang , Zhang Anyi , Qu Bo , Liu Ying
Published: January 2025

Horizontal ecological compensation represents a significant institutional innovation aimed at advancing ecological civilization and serves as a key functional strategy within China’s current management framework. This paper employs the horizontal ecological protection compensation agreement of the Yu-Lu section of the Yellow River Basin as a case study. Using a game theory model and theoretical analysis, the paper explores the underlying connotations, theoretical foundations, and legal characteristics of the basin’s horizontal ecological protection compensation mechanism. This analysis reveals several challenges within the existing horizontal ecological protection compensation system in the Yellow River Basin, including the predominance of a single compensation entity, unclear compensation standards, a compensation model limited to monetary transfers, and the absence of an effective dispute resolution mechanism. This paper further examines potential improvements to the horizontal ecological protection compensation framework in the Yellow River Basin from a legal system perspective, with the aim of addressing these practical challenges and fostering the region’s ecological, environmental, and economic development.
From Farms to Forests: An Exploration of Afforestation Efforts in Poland Under the Rural Development Programme (2007–2020)
Authors: Klepacka Anna M. , Romaniuk Andrzej A. , Gajda Janusz , Chećko Ewa E.
Published: January 2025

Forests are important in mitigating climate change and addressing biodiversity loss. In Poland, where forest cover has steadily increased since World War II, afforestation of agricultural land has emerged as a key strategy supported by both EU and national policies. This study evaluates the implementation of Poland’s afforestation programs under the Rural Development Programme (RDP) for the periods of 2007–2013 and 2014–2020 using data provided by the Agency for Restructuring and Modernisation of Agriculture (ARMA) and focusing on the financial incentives offered to private landowners and regional variations in their uptake. Results show that afforestation under the RDP aligned with the EU climate neutrality goals, with a total of 37,721 hectares afforested and PLN 243.5 million handed as financial support, predominantly (81%) over the first studied period. The largest afforestation efforts were observed in the Mazowieckie and Warmińsko-Mazurskie voivodeships, with Warszawa, Poland’s capital, achieving the highest municipal afforestation area across both periods. Financial considerations influenced farmer participation, but rising land prices and historical land use patterns were contributing factors. Urban afforestation and increasing demand for woody biomass further highlight the benefits of afforestation. However, conifer-dominated stands, prevalent on low-quality land, can present challenges to ecosystem stability under future climate scenarios, necessitating diversification towards deciduous species. Additionally, low uptake during the 2014–2020 period showcases the need for improved incentives to bolster participation. Still, afforestation presents significant economic and environmental opportunities, advancing long-term policy objectives while addressing critical challenges in climate.
Power Demand Patterns of Public Electric Vehicle Charging: A 2030 Forecast Based on Real-Life Data
Authors: Baronchelli Marco , Falabretti Davide , Gulotta Francesco
Published: January 2025

As the adoption of electric vehicles accelerates, understanding the impact of public charging on the power grid is crucial. However, today, a notable gap exists in the literature regarding approaches capable of accurately estimating the expected influence of e-mobility power demand on electrical grids, especially at medium and low voltage levels. To fill this gap, in this study, a procedure is proposed to estimate the power demand patterns of public car parks in a 2030 scenario. To this end, data collected from real-life car parks in Italy are used in Monte Carlo simulations, where probabilistic daily power demand curves are created with different maximum charging powers (from 7.4 kW to ultra-fast charging). The results highlight high variability in the power demand depending on the location and type of car park. City center car parks exhibit peak demand during morning hours, linked to commercial activities, while car parks near railway stations and hospitals show demand patterns aligned with transportation and healthcare needs. Business area car parks, in contrast, have a more pronounced demand during work hours on weekdays, with much lower activity during weekends. This study also demonstrates that, in some situations, ultra-fast charging can increase peak power demand from the grid by up to 210%. Given their contribution to the existing literature, the power demand patterns from this research constitute a valuable starting point for future studies aimed at quantitatively assessing the impact of e-mobility on the power system. In addition, they can effectively support decision-makers in optimally designing the e-mobility recharge infrastructure.
The Interaction Between Economic Development and Environmental Protection in Yunnan Province over the Past Two Decades
Authors: Zhou Zhenhua , Luo Yi , Yang Xin , Wei Hong , Li Anlin , Pei Xingfang , Liu Guanjun
Published: January 2025

Over the past two decades, urbanization and industrialization in Yunnan Province have rapidly advanced, spurring economic growth but also leading to intensified environmental challenges, particularly in urban areas where issues like air pollution and declining vegetation cover have become increasingly prominent. Balancing economic development and environmental protection has thus emerged as a core priority for Yunnan. This study quantifies and analyzes the temporal and spatial changes, coupling coordination degree, and driving factors underlying key indicators of economic development and environmental protection in Yunnan’s urban areas from 2000 to 2019. The results indicate that: (1) Economic growth is evident across all four types of regions, though growth rates have decelerated. The first type of region shows a “U”-shaped trend in FVC, the second type of region a “W” trend, and the third and fourth type of region show a consistent upward trend. (2) Overall coupling between economic development and environmental protection remains low across Yunnan, with a strong correlation between the degree of coupling coordination and urban economic development levels: the first type of region has the highest coupling coordination degree, while the fourth type of region has the lowest coupling coordination degree. (3) Industrial structure is the most influential factor in coupling coordination between economic development and environmental protection across Yunnan (74.9%). Influencing factors differ by region: secondary industry predominates in the first type of region (24.4%), foreign investment leads in the second (24.1%), technological innovation significantly impacts the third (23.9%), and marketization drives the fourth type of region (25.8%).
A Model-Data Dual-Driven Approach for Predicting Shared Bike Flow near Metro Stations
Authors: Wang Zhuorui , Yu Dexin , Zheng Xiaoyu , Meng Fanyun , Wu Xincheng
Published: January 2025

Bike-sharing has emerged as an innovative green transportation mode, showing promising potential in addressing the ‘last-mile’ transportation challenge in an eco-friendly manner. However, shared bikes around metro stations often face supply–demand imbalance problems during peak hours, causing bike shortages or congestion that compromise user experience and bike utilization. Accurate prediction enables operators to develop rational dispatch strategies, improve bike turnover rate, and promote synergistic metro–bike integration. However, state-of-the-art research predominantly focuses on improving complex deep-learning models while overlooking their inherent drawbacks, such as overfitting and poor interpretability. This study proposes a model–data dual-driven approach that integrates the classical statistical regression model as a model-driven component and the advanced deep-learning model as a data-driven component. The model-driven component uses the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to extract periodic patterns and seasonal variations of historical data, while the data-driven component employs an Extended Long Short-Term Memory (xLSTM) neural network to process nonlinear relationships and unexpected variations. The fusion model achieved R-squared values of 0.9928 and 0.9770 for morning access and evening egress flows, respectively, and reached 0.9535 and 0.9560 for morning egress and evening access flows. The xLSTM model demonstrates an 8% improvement in R2 compared to the conventional LSTM model in the morning egress flow scenario. For the morning egress and evening access flows, which exhibit relatively high variability, classical statistical models show limited effectiveness (SARIMA’s R2 values are 0.8847 and 0.9333, respectively). Even in scenarios like morning access and evening egress, where classical statistical models perform well, our proposed fusion model still demonstrates enhanced performance. Therefore, the proposed data–model dual-driven architecture provides a reliable data foundation for shared bike rebalancing and shows potential for addressing the challenges of limited robustness in statistical regression models and the susceptibility of deep-learning models to overfitting, ultimately enhancing transportation ecosystem sustainability.
Implementing Sustainable Fees in the Ship Waste Reception Service to Match with European Policy and Port Traffic Characterization
Authors: Verdesoto Verónica M. , Camarero Alberto , González Cancelas Nicoletta
Published: January 2025

The European Directive in force on port reception facilities for waste from ships applicable to both ports and ships has the aim of protecting the marine environment. To promote this goal, the directive imposes on every member state the availability of port reception facilities adequate in meeting the needs of the ships normally using the ports without causing undue delay in their operations. As an effective tool to discourage the discharges of waste at sea, the new policy requires ports to implement a cost recovery system for the waste reception service through mandatory fees to be paid by ships irrespective of the volume of waste delivered at port. In the context of the obligations that European ports must fulfill according to the new policy on waste from ships, the present study analyzes the Spanish ports’ database. The research relates traffic characterization with the economic results of the waste reception service in each port authority to ensure that the effective reception costs are covered. The findings will enable building a robust port fee system adapted to the ship typology with the aim of mitigating economic imbalances and ensuring that ships contribute to the port reception facilities’ costs according to their characteristics.
Parametric Analysis of the Factors Impacting the Spatial Distribution of Particles in a Bus Environment
Authors: Bahman Zadeh Zeinab , Cummings Bryan E. , Lo L. James
Published: January 2025

This study presents a parametric analysis of the factors impacting particle distribution within a bus environment using computational fluid dynamics (CFD) simulations, with a primary focus on the relative concentration (RC) of particles. The Novel Relative Concentration (RC) metric, which measures the deviation from a return concentration, was used to assess the effects of ventilation rates, the number and spatial arrangement of particle emitters, and thermal conditions. Our investigation reveals that increasing air changes per hour (ACHs) from 5.74 h−1 to 28.66 h−1 reduces the overall particle concentration by approximately 45%, but localized high concentration zones persist, with maximum RC values observed at 1.57. Scenarios with evenly distributed emitters achieved near-uniform particle distribution, with RC values averaging around 0.95, while clustered emitters resulted in localized high concentrations, with RC values exceeding 2.0. Thermal conditions were found to have a minimal effect on RC, with average values of 1.664 for cooling and 1.588 for heating, showing only a 4.68% difference. The RC metric provided clear insights into the non-uniformity of particle distribution, highlighting areas prone to higher concentrations, with some zones reaching RC values of 2.5, indicating concentrations 2.5 times higher than the well-mixed average. These findings underscore the importance of optimizing ventilation systems for both overall air exchange and uniform air distribution, offering practical implications for improving air quality and reducing the risk of airborne pathogen transmission in public transportation systems. Future research should explore real-time ventilation adjustments based on passenger load, the effects of different particle types, and the development of models incorporating human behavior and movement patterns.
The Impact of Differently Prepared Mixed Plastic Waste Granules on the Structure and Properties of Concrete
Authors: Malaiškienė Jurgita , Škamat Jelena , Kudžma Andrius , Boris Renata , Bačinskas Darius
Published: January 2025

The relatively low production cost and short lifespan of plastic products contribute significantly to the annual accumulation of plastic waste, raising serious environmental concerns. Conventional disposal methods like landfill and incineration not only waste valuable resources but also result in substantial secondary pollution. In response to the imperatives of sustainable development and environmental protection, in this work, different preparation methods (mechanical processing; heating and covering with milled sand and glass; covering plastic granules with polymers and then mineral materials such as microsilica and waste metakaolin; using other chemical additives) for plastic granules from waste and their influence on the properties of cementitious materials were studied. Lightweight concrete properties such as density, ultrasound pulse velocity, flexural and compressive strength, water absorption, and the interaction zone between the cement matrix and plastic granules were analyzed. It was determined that one-third by volume of natural aggregate can be replaced with specially prepared plastic granules from waste, obtaining a bending strength of the lightweight concrete of about 5 MPa, a compressive strength at 28 days of approximately 30 to 35 MPa, a density of about 1850 kg/m3, and an ultrasound pulse velocity of 3900 m/s.
To Be Digital Is to Be Sustainable—Tourist Perceptions and Tourism Development Foster Environmental Sustainability
Authors: Karim Rehmat , Goh Gerald Guan Gan , Lee Yvonne Lean-Ee , Zeb Ali
Published: January 2025

The Technology Acceptance Model (TAM) is widely used in many areas but is rarely applied to determine the link between tourists’ perceptions of tourism development and environmental sustainability. Therefore, this study aimed to (1) explore the relationships among tourism development, tourists’ perceptions, and environmental sustainability, (2) examine the mediating role of blockchain technology in these relationships, and (3) analyze the use of the TAM for sustainable practices in tourism. Data were collected from tourists on their perceptions of the impact of tourism on the environment, their use of information technology (IT) during their visits, and their willingness to pay for sustainable tourism practices. The data collected from 473 respondents were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings reveal that tourism development and perceptions have a significant impact on environmental sustainability. Furthermore, blockchain technology directly affects environmental sustainability and partially mediates the relationship between tourism development and tourists’ perception constructs on environmental sustainability. This study contributes to the understanding of the relationships among tourism development, tourist perceptions, and environmental sustainability, analyzed through the lens of the TAM. Although the TAM has been used in several technology adoption and behavioral studies, this is its first application in the context of sustainable tourism, specifically used in exploring perceptions of environmental sustainability, limited to the environmentally rich Gilgit-Baltistan region in Pakistan.
Green Transformation in Portfolio: The Role of Sustainable Practices in Investment Decisions
Authors: Li Xinyue , Khan Ikram Ullah
Published: January 2025

Amidst the green transformations around sustainable drives, organizations are striving to integrate green business strategies (GBSs) to enhance their financial viability. This research argues that green strategies promote organizational efficiency that, in turn, improves financial performance and channel investments. Checking the mediating role of organizational efficiency through process improvement, product improvement, and organizational innovation focuses on financial performance and investment decisions. The study further postulates the moderation of management control system on the links between GBS and organizational efficiency parameters. The data were gathered by using surveys of 552 firms’ managers and investors at the Shenzhen Stock Exchange, China. PLS-SEM was applied to check the psychometric properties and analyze the data. The results confirm that GBS improves organizational efficiency and financial performance, exerting significant mediation effects. The study finds that moderation helps transform the green business strategy into tangible financial goals by amplifying the positive impact of GBSs. The study enriches the understanding of GBSs, organizational efficiency and investment decisions. The study also lauds the integration of GBSs that effectively transform financial performance and investment decisions.
Evaluating the Impact of Urban Encroachment and Land Cover Changes on World Cultural Heritage Site Taxila: A Spatio-Temporal Analysis from 1990 to 2024
Authors: Butt Najam us Saqib Zaheer , Wang Xinyuan , Luo Lei , Ul Hussan Hammad
Published: January 2025

Rapid global urbanization during the late 20th and early 21st centuries has induced substantial land cover changes, posing significant threats to the United Nations Educational, Scientific and Cultural Organization’s (UNESCO) World Heritage Sites. In this study, we investigated the spatio-temporal change in urban development in response to land use transformations in the world cultural heritage site (CHS) of Taxila, Pakistan, to check the possible threats faced by the site. Land transfer matrices were used to assess the land cover change (LCC) between 1990 and 2024. Support vector machine and Getis–Ord Gi techniques were employed for LCC classification and spatial pattern interpretation, respectively, which were later evaluated by the high spatial resolution imagery of KH-9 (Keyhole-9), Google Earth Pro and Gaofen-2. The results indicate a significant increase in built-up area from 23.68 km2 to 78.5 km2, accompanied by a substantial rise in bare land from 8.56 km2 to 26.5 km2 between 1990 and 2024, which is quite irregular. LCC transformations were notable, with 13.1 km2 of cropland and 44.8 km2 vegetation being converted into 4.4 km2 of built-up area and 14.5 km2 into bare land during the 1990 to 2024 period. Getis–Ord Gi analysis observed a high Z-score value and showed low to high clustering patterns in the proximity of the Sarakhola and Bhir Mound sites from 1990 to 2024. Furthermore, high spatial resolution imagery indicates the loss of the core zone of the Sarakhola site from 0.0168 to 0.0032 km2 from 2004 to 2024, which was the major threat to its outstanding universal venue (OUV) status. The findings of the current study indicate that the CHS under study is facing an alarming situation for conservation due to rapid urban development and encroachment. Therefore, local government should strictly implement the heritage law and revisit their policies to promote conservation efforts to maintain the authenticity and integrity of this world CHS.
Calculation of Stray-Field Loss of TEAM P21 Model Under Complex Excitations Based on the Improved Energetic Hysteresis Model
Authors: Zhao Zhigang , Li Dehai
Published: January 2025

An efficient numerical calculation method of stray-field loss is investigated for typical magnetic load components (grain-oriented silicon steel sheets (GO), magnetic steel plate, and combined components of both materials) under non-sinusoidal excitations (NSE) containing symmetrical harmonic and DC to avoid the local overheating caused by high stray-field loss density. The paper investigates the stray-field loss with different types of load components and working conditions based on the leakage flux complementary-based measurement method, derives an analytical formulation calculating the energetic hysteresis model parameters under different magnetic flux densities to reduce the dependence on measurement data, establishes a loss calculation method considering the influence of non-sinusoidal magnetization on magnetic loss, and discusses the advantages and limitations of existing numerical approaches of additional loss to establish an effective computational strategy of stray-field loss. Finally, the effectiveness of the proposed method is verified by simulations and experiments.
Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization
Authors: Kim Dongok , Ahn Chulkyun , Kim Jong Hyo
Published: January 2025

Background/Objectives: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thickness has an adverse effect on the accuracy of the pulmonary nodule volumetry. Methods: We propose a deep learning based super-resolution technique to generate thin-slice CT images from thick-slice CT images. Analysis of the lung nodule volumetry and categorization accuracy was performed using commercially available AI-based lung cancer screening software. Results: The accuracy of pulmonary nodule categorization increased from 72.7 percent to 94.5 percent when thick-slice CT images were converted to generated-thin-slice CT images. Conclusions: Applying the super-resolution-based slice generation on thick-slice CT images prior to automatic nodule evaluation significantly increases the accuracy of pulmonary nodule volumetry and corresponding pulmonary nodule category.
The Current Status in Terms of Vaccination for Individuals Infected with Human Immunodeficiency Virus
Authors: Xu Nan , Shen Yanru , Huang Weijin , Nie Jianhui
Published: January 2025

Human immunodeficiency virus (HIV)-infected individuals have an increased risk of various infections due to their impaired host immune system, resulting in higher morbidity and mortality rates. These patients severely suffered during the COVID-19 epidemic, the influenza epidemic and the spread of monkeypox. Reducing serious infections is one of the most important measures to improve HIV-infected individuals’ quality and length of life. Based on the preparation processes and their antigenic properties, vaccines are divided into several types, including inactivated vaccines, attenuated live vaccines, recombinant protein vaccines, toxoid vaccines, polysaccharide vaccines, polysaccharide (protein) combined vaccines, nucleic acid vaccines, viral vector vaccines, etc. With the innovation of vaccine preparation technology in recent years and the acceleration of vaccine approval and market launch, more and more vaccine products suitable for HIV-infected individuals have become available. Because of their deficient immune systems, the type of vaccines and the schedule of vaccinations available to individuals living with HIV are sometimes different from those with healthy immune systems. This article reviewed the current status of vaccination in and shed light on the vaccination strategies for HIV-infected persons in terms of their safety and effectiveness.
Identification of Mycoviruses in Cytospora chrysosperma: Potential Biocontrol Agents for Walnut Canker
Authors: Mi Yingjie , Chen Shaohua , Liu Kexin , Tie Zhanjiang , Ren Junchao , Zhang Mingli , Liu Zheng , Zhao Sifeng , Xi Hui , Zhang Xuekun
Published: January 2025

Walnut canker is a common disease in the Xinjiang Uygur autonomous region of China, which is caused by Cytospora chrysosperma. To date, there is no effective control measure for this disease. Infection with mycoviruses has been widely proven to reduce the virulence of plant pathogenic fungi, with some mycoviruses even serving as potential biological control agents for plant diseases. In this study, mycoviruses associated with 31 strains of C. chrysosperma from Xinjiang Uygur autonomous region were identified by metatranscriptomic sequencing. Seven new mycoviruses were identified by BLAST and RT-PCR analysis, which were Botrytis cinerea partitivirus 5 (BcPV5), Gammapartitivirus sp-XJ1 (GVsp-XJ1), Botoulivirus sp-XJ2 (BVsp-XJ2), Luoyang Fusar tick virus 2 (LfTV2), Leptosphaeria biglobosa narnavirus 17 (LbNV17), Sclerotinia sclerotiorum narnavirus 6 (SsNV6), and Cytospora ribis mitovirus (CrMV3). Among these, BcPV5, GVsp-XJ1, BVsp-XJ2, CrMV3, and LfTV2 were found to co-infect C. chrysosperma strain WS-11 and significantly reduce both the colony growth rate and virulence of the host. After co-culturing the virus-free WS-FV strain with WS-11, the colony growth rate and virulence of the derivative strain were also decreased. These results provide potential biocontrol resources for the control of walnut canker.