bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of the Transient Heat Transfer of a Single-U-Tube Ground Heat Exchanger by Integrating a Forward-Difference Numerical Scheme with an Analytical Technique
Authors: Salilih Elias M. , Kerme Esa Dube , Fung Alan S. , Leong Wey H. , Leon-Salas Walter D.
Published: December 2024

This study presents the development of a novel computational technique for modeling the transient heat transfer in the outer and inner regions of a single U-tube ground heat exchanger. The modeling approach couples a forward-difference numerical technique with a well-established analytical method with the aim of reducing the two-dimensional axisymmetric heat transfer problem into a one-dimensional problem, which has the benefit of reducing the computational time. Furthermore, the suggested method is numerically stable compared to a full numerical scheme, and the solution converges for a time step of up to 150 min. This is because the suggested method computes the heat transfer of the streaming fluid in the U-tube, which has a lower thermal capacitance, using the analytical technique, resulting in numerical stability at a larger time step, while the full numerical scheme has stability issues at a large time step as it computes the heat transfer of the flowing fluid in the U-tube, which also requires more computational time than the suggested method. In this model, numerical and analytical analyses are coupled with borehole wall temperature. The time-varying temperature histories of the grout material inside the borehole, the borehole wall, and the surrounding soil are presented. In addition, the time variations in the exit fluid temperature and the energy storage within the grout and the outer soil material are presented. The results show that the energy storage in the grout material reaches 62 MJ at the end of 1000 h of ground heat exchanger charging operation, while the energy storage in the surrounding soil can be as high as 7366 MJ. This study also investigates the effect of mass flow rate on the heat transfer performance of the ground heat exchanger.
Study on CO2 Corrosion Behavior of Underground Gas Storage Pipe Columns and Establishment of Corrosion Inhibition System
Authors: Ma Yifeng , Gu Jianwei
Published: December 2024

Herein, we take an underground natural gas storage in the Ordos Basin as an example to explore the influence of temperature, CO2 flow rate, CO2 partial pressure, and chloride ion concentration on the corrosion rate of N80 and P110 steels in CaCl2 brine type. Meanwhile, in order to reduce the amount of chemical corrosion inhibitors and improve performance, a novel corrosion inhibitor with a quinoline quaternary ammonium structure named YS-QB was synthesized from 1-methyl-1,2,3,4-tetrahydroisoquinoline, epichlorohydrin, and oleic acid amide propyl dimethylamine. Under normal and high-pressure environments, YS-QB exhibits a superior corrosion inhibition effect to the market product of CX-1. In order to further reduce the amount of corrosion inhibitor and improve the corrosion inhibition effect, orthogonal experiments were conducted to optimize the formula system, and the optimal composite system was finally obtained by forming YS-QB, propargyl alcohol, hexamethylenetetramine, and isopropanol in a mass ratio of 12:1:1:2. At 80 °C, a dosage of 30 mg/L can suppress the CO2 corrosion rate below 0.076 mm/a, while a dosage of 60 mg/L can suppress the CO2 corrosion rate below 0.076 mm/a at a high-pressure environment of 120 °C. Combining weightlessness and electrochemical experiments, it is found that the composite corrosion inhibitor performs best when the dosage reached 100 mg/L, and a further increase in the dosage weakens the corrosion inhibition capacity. Based on the polarization curve changes with the dosage of the composite corrosion inhibitor, it can be determined that the final obtained composite corrosion inhibitor system was a cathodic corrosion inhibitor.
Observer Design for State and Parameter Estimation for Two-Time-Scale Nonlinear Systems
Authors: Xiao Zhenyu , Duan Zhaoyang
Published: December 2024

The design and calculation of nonlinear observers for parameter estimation in multi-time-scale nonlinear systems present significant challenges due to the inherent complexity and stiffness of such systems. This study proposes a framework for designing observers for two-time-scale nonlinear systems, with the objective of overcoming the aforementioned challenges. The design procedure involves reducing the original two-time-scale nonlinear system to a lower-dimensional model that captures only the slow dynamics while approximating the fast states through the use of an algebraic slow motion invariant manifold function. Subsequently, an exponential observer can be devised for this reduced system, which is valid for both state and parameter estimation. By employing the output from the original system, this observer can be adapted for online state and parameter estimation for the detailed two-time-scale system. The challenges associated with estimating parameters in two-time-scale nonlinear systems, the complexities of designing observers for such systems, and the computational burden associated with computing observers for ill-conditioned systems can be effectively addressed through the application of this design framework. A rigorous error analysis validates the convergence of the proposed observer towards the states and parameters of the original system. The viability and necessity of this observer design framework are demonstrated through a numerical example and an anaerobic digestion process. This study presents a practical approach for state and parameter estimation with observers for two-time-scale nonlinear systems.
Special Issue: “Petroleum Characterization and Bioprocesses: Numerical and Experimental Investigation”
Authors: Stratiev Dicho , Yordanov Dobromir , Guo Aijun
Published: December 2024

Petroleum is a valuable mineral source rich in hydrocarbons, which, after refining, can be used either as components in the production of internal combustion engine fuels, or in feeds for the production of chemicals [...]
Development of Functional Bread: Exploring the Nutritional, Bioactive and Microbial Potential of Carob (Ceratonia siliqua L.) Pulp Powder
Authors: Zahorec Jana , Šoronja-Simović Dragana , Petrović Jovana , Šereš Zita , Pavlić Branimir , Božović Danica , Perović Lidija , Martić Nikola , Bulut Sandra , Kocić-Tanackov Sunčica
Published: December 2024

For the development of a high-quality functional bread, it is of crucial importance to find a compromise between improving the functional value of the product and impairing its quality. Therefore, the primary aim of this work was to define the effects of carob pulp powder (CP; 10–20% on flour basis) on the rheological behavior of dough and quality parameters of bread. The introduction of CP caused a major increase in dough resistance to extension while significantly decreasing dough extensibility, resulting in a lower volume with a denser crumb structure of the obtained bread samples. The negative effects of the CP on the dough and bread characteristics were partially compensated by the addition of dry sourdough (DS) as an improver at the level of 5–10% (flour basis). It was determined that by combining 15% CP and 10% DS, bread of very good sensory quality can be produced. The content of total dietary fiber (6.48 g), Mn (0.76 mg) and Cu (0.21 mg) per 100 g of the mentioned bread was sufficient for the nutritional claims “high in fiber”, “high in manganese” and “source of copper”. The obtained bread had a content of total phenols 10 times higher than the control and 5.5, 12 and 26 times higher antioxidant activity determined by FRAP, DPPH and ABTS tests, respectively. Moreover, microbiological tests confirmed the durability of the bread with 15% CP and 10% DS of up to seven days. Therefore, carob pulp powder can be successfully applied in the production of bread whose characteristics are adapted to modern trends in nutrition.
Methodology for AI-Based Search Strategy of Scientific Papers: Exemplary Search for Hybrid and Battery Electric Vehicles in the Semantic Scholar Database
Authors: Wätzold Florian , Popiela Bartosz , Mayer Jonas
Published: December 2024

The rapid development of artificial intelligence (AI) has significantly enhanced productivity, particularly in repetitive tasks. In the scientific domain, literature review stands out as a key area where AI-based tools can be effectively applied. This study presents a methodology for developing a search strategy for systematic reviews using AI tools. The Semantic Scholar database served as the foundation for the search process. The methodology was tested by searching for scientific papers related to batteries and hydrogen vehicles with the aim of enabling an evaluation for their potential applications. An extensive list of vehicles and their operational environments based on international standards and literature reviews was defined and used as the main input for the exemplary search. The AI-supported search yielded approximately 60,000 results, which were subjected to an initial relevance assessment. For the relevant papers, a neighbourhood analysis based on citation and reference networks was conducted. The final selection of papers, covering the period from 2013 to 2023, included 713 papers assessed after the initial review. An extensive discussion of the results is provided, including their categorisation based on search terms, publication years, and cluster analysis of powertrains, as well as operational environments of the vehicles involved. This case study illustrates the effectiveness of the proposed methodology and serves as a starting point for future research. The results demonstrate the potential of AI-based tools to enhance productivity when searching for scientific papers.
Different Patterns of Religious Settlements Based on the Historic Landscape Approach: Cases of Buddhist Grottoes in Hexi Corridor
Authors: Chen Yueying , Wu Haichao , Wei Wenbin
Published: December 2024

Religious settlements can reflect regional culture and social development, preserve the continuity of spatial structures over time, sustain social networks, and perpetuate traditions. Buddhist settlements, as a particular type of religious settlement, reflect the social development and daily lives of monks and common people. This study used literature research, field investigations, and GISs to construct a framework of the landscape of religious settlements based on the theory of the historic landscape approach. Buddhist grottoes from the Sixteen Kingdoms Period to the Qing Dynasty (304–1912) in the Hexi Corridor of Gansu Province were selected as a case study, and the patterns of religious settlements were identified. According to the analysis, it was found that religious settlements tended to have large religious buildings at their centre, with small buildings and attachments scattered around. They were close to central cities, with a complete transportation network, and they had relatively stable belief spaces. There were clear boundaries between believers and non-believers in the settlements. Four patterns of religious settlements were also identified according to the relationships between geography, social properties, and cultural connotations. These findings diachronically offer a new perspective on the understanding of religious settlements and steps for improving the inheritance of religious culture.
The Anthropological and Social Consequences of the Triadic Logic: A Proposal for Adapting the Logic Model to Life Thinking
Authors: Aizpun Teresa
Published: December 2024

Modernity is characterised by a specific scientific paradigm based on binary logic. Neither freedom nor creativity have a place in this logical model. On the contrary, triadic logic enables rational consideration of an anthropological and social model compatible with both things: freedom and creativity, and therefore with Christianity. Furthermore, triadic logic provides us with a model of thought compatible with the current physical explanation of reality.
Transnational Karbala: From Rebellion to Reconciliation
Authors: Mirshahvalad Minoo
Published: December 2024

This article for the first time examines the activities of transnational information campaigns initiated by young Shiʿa Muslims across European, Russian, and Armenian cities. These campaigns aim to disseminate knowledge about Imam Hussain and his mission to non-Shiʿa audiences. The campaigns serve as vivid examples of the struggles faced by Muslims in relatively hostile contexts as they seek integration and acceptance as law-abiding and peaceful citizens. They also represent new avenues of Islamic activism, focusing on dismantling stereotypes and correcting “misunderstandings” within host societies. Drawing on semi-structured interviews, participant observation, and an analysis of campaign handouts and social media content between 2018 and 2024, this study explores how campaigners adapt the narrative of the Karbala tragedy—widely regarded as the metahistorical cornerstone of Shiʿa identity—to make it accessible and relevant to external audiences. These strategies enable campaigners to engage with out-group communities, testing and refining effective methods for presenting this pivotal historical event. The findings reveal that, through this process, the Karbala narrative undergoes both content-based and linguistic modifications, while the concept of justice—central to the commemoration of this tragedy—is reinterpreted in new contexts. This research contributes to the understanding of transnational Islamic activism and highlights the importance of strategic communication in fostering intercultural dialogue and promoting mutual understanding in diverse societies.
Emotional Instability and Financial Decisions: How Neuroticism Fuels Panic Selling
Authors: Khan Mostafa Saidur Rahim , Yoshimura Hiroumi , Kadoya Yoshihiko
Published: December 2024

This study investigates the relationship between neuroticism and panic-selling behavior among investors, particularly during market downturns. Building on the theoretical framework of behavioral finance, we hypothesize that higher levels of neuroticism are positively associated with an increased likelihood of panic selling. The data for this research were derived from a comprehensive survey titled Survey on Life and Money, which was conducted by Rakuten Securities in collaboration with Hiroshima University in November and December 2023, with a total sample size of 189,524 participants. Our results reveal that 9.46% of the respondents fully or partially panic-sold their stocks during market volatility. Additionally, the respondents demonstrated a tendency toward neuroticism, with an average score of 2.95 out of 5 on the neuroticism scale. Using a probit regression analysis, we examined the dependent variable of panic selling in relation to neuroticism as the independent variable, controlling for various demographic, socioeconomic, and behavioral characteristics. Our findings robustly support this hypothesis, indicating that individuals with higher neuroticism scores are more likely to engage in panic selling during periods of market volatility, with significance at the 5% level. This study contributes to the behavioral finance literature by highlighting the significant role of personality traits in investment decision making and underscores the importance of understanding investor psychology in financial markets. This study emphasizes the need for a nuanced understanding of how individual psychological factors, particularly neuroticism, drive market behavior and influence broader economic stability.
An Aircraft-Manipulator System for Virtual Flight Testing of Longitudinal Flight Dynamics
Authors: Ishola Ademayowa A. , Whidborne James F. , Tang Gilbert
Published: December 2024

A virtual flight test is the process of flying an aircraft model inside a wind tunnel in a manner that replicates free-flight. In this paper, a 3-DOF aircraft-manipulator system is proposed that can be used for longitudinal dynamics virtual flight tests. The system consists of a two rotational degrees-of-freedom manipulator arm with an aircraft wind tunnel model attached to the third joint. This aircraft-manipulator system is constrained to operate for only the longitudinal motion of the aircraft. Thus, the manipulator controls the surge and heave of the aircraft whilst the pitch is free to rotate and can be actively controlled by means of an all-moving tailplane of the aircraft if required. In this initial study, a flight dynamics model of the aircraft is used to obtain dynamic response trajectories of the aircraft in free-flight. A model of the coupled aircraft-manipulator system developed using the Euler method is presented, and PID controllers are used to control the manipulator so that the aircraft follows the free-flight trajectory (with respect to the air). The inverse kinematics are used to produce the reference joint angles for the manipulator. The system is simulated in MATLAB/Simulink and a virtual flight test trajectory is compared with a free-flight test trajectory, demonstrating the potential of the proposed system for virtual flight tests.
Large-Scale Maize Condition Mapping to Support Agricultural Risk Management
Authors: Birinyi Edina , Kristóf Dániel , Hollós Roland , Barcza Zoltán , Kern Anikó
Published: December 2024

Crop condition mapping and yield loss detection are highly relevant scientific fields due to their economic importance. Here, we report a new, robust six-category crop condition mapping methodology based on five vegetation indices (VIs) using Sentinel-2 imagery at a 10 m spatial resolution. We focused on maize, the most drought-affected crop in the Carpathian Basin, using three selected years of data (2017, 2022, and 2023). Our methodology was validated at two different spatial scales against independent reference data. At the parcel level, we used harvester-derived precision yield data from six maize parcels. The agreement between the yield category maps and those predicted from the crop condition time series by our Random Forest model was 84.56%, while the F1 score was 0.74 with a two-category yield map. Using a six-category yield map, the accuracy decreased to 48.57%, while the F1 score was 0.42. The parcel-level analysis corroborates the applicability of the method on large scales. Country-level validation was conducted for the six-category crop condition map against official county-scale census data. The proportion of areas with the best and worst crop condition categories in July explained 64% and 77% of the crop yield variability at the county level, respectively. We found that the inclusion of the year 2022 (associated with a severe drought event) was important, as it represented a strong baseline for the scaling. The study’s novelty is also supported by the inclusion of damage claims from the Hungarian Agricultural Risk Management System (ARMS). The crop condition map was compared with these claims, with further quantitative analysis confirming the method’s applicability. This method offers a cost-effective solution for assessing damage claims and can provide early yield loss estimates using only remote sensing data.
Early Wildfire Smoke Detection Method Based on EDA
Authors: Liu Yang , Chen Faying , Zhang Changchun , Wang Yuan , Zhang Junguo
Published: December 2024

Early wildfire smoke detection faces challenges such as limited datasets, small target sizes, and interference from smoke-like objects. To address these issues, we propose a novel approach leveraging Efficient Channel and Dilated Convolution Spatial Attention (EDA). Specifically, we develop an experimental dataset, Smoke-Exp, consisting of 6016 images, including real-world and Cycle-GAN-generated synthetic wildfire smoke images. Additionally, we introduce M-YOLO, an enhanced YOLOv5-based model with a 4× downsampling detection head, and MEDA-YOLO, which incorporates the EDA mechanism to filter irrelevant information and suppress interference. Experimental results on Smoke-Exp demonstrate that M-YOLO achieves a mean Average Precision (mAP) of 96.74%, outperforming YOLOv5 and Faster R-CNN by 1.32% and 3.26%, respectively. MEDA-YOLO further improves performance, achieving an mAP of 97.58%, a 2.16% increase over YOLOv5. These results highlight the potential of the proposed models for precise and real-time early wildfire smoke detection.
Landslide Thickness Estimated from InSAR-Derived 2D Deformation: Application to the Xiongba Ancient Landslide, China
Authors: Yang Yinghui , Xu Qian , Xie Liyuan , Xu Qiang , Hu Jyr-Ching , Chen Qiang
Published: December 2024

The thickness estimation of landslides is crucial for better landslide evaluation. Traditional non-contact mass conservation methods using 3D deformation may be unsuitable due to observation limitations. This study proposes a more feasible approach based on 2D deformation from two-track Interferometric Synthetic Aperture Radar (InSAR) observations, applied to the Xiongba landslide. The comparison with geological and drilling measurements confirms the reliability of this method. The mapped InSAR LOS deformation rate fields reveal two regions: a significantly deformed frontal zone and a relatively stable zone. Analysis suggests that surface uplift at the Xiongba-H2 landslide’s front edge results from rock–soil mass pushing in high-deformation areas. The estimated thickness ranges from 10 to 100 m, with an active volume of 6.17 × 107 m3. A thicker region is identified at the front edge along the Jinsha River, posing the potential for further failure. This low-cost, easily implemented approach enhances InSAR’s applicability for landslide analysis and hazard assessment.
SAR-MINF: A Novel SAR Image Descriptor and Matching Method for Large-Scale Multidegree Overlapping Tie Point Automatic Extraction
Authors: Li Shuo , Yang Xiongwen , Lv Xiaolei , Li Jian
Published: December 2024

The automatic extraction of large-scale tie points (TPs) for Synthetic Aperture Radar (SAR) images is crucial for generating SAR Digital Orthophoto Maps (DOMs). This task involves matching SAR images under various conditions, such as different resolutions, incidence angles, and orbital directions, which is highly challenging. To address the feature extraction challenges of different SAR images, we propose a Gamma Modulated Phase Congruency (GMPC) model. This improved phase congruency model is defined by a Gamma Modulation Filter (GMF) and an adaptive noise model. Additionally, to reduce layover interference in SAR images, we introduce a GMPC-Harris feature point extraction method with layover perception. We also propose a matching method based on the SAR Modality Independent Neighborhood Fusion (SAR-MINF) descriptor, which fuses feature information from different neighborhoods. Furthermore, we present a graph-based overlap extraction algorithm and establish an automated workflow for large-scale TP extraction. Experiments show that the proposed SAR-MINF matching method increases the Correct Match Rate (CMR) by an average of 31.2% and the matching accuracy by an average of 57.8% compared with other prevalent SAR image matching algorithms. The proposed TP extraction algorithm can extract full-degree TPs with an accuracy of less than 0.5 pixels for more than 98% of 2-degree TPs and over 95% of multidegree TPs, meeting the requirements of DOM production.
Gender Differences and Performance Changes in Sprinting and Long Jump Among Young Athletes
Authors: Bezuglov Eduard , Achkasov Evgeniy , Vakhidov Timur , Malyakin Georgiy , Kapralova Elizaveta , Kolesnichenko Vyacheslav , Vinogradov Mikhail , Zharikova Tatiana , Emanov Anton
Published: December 2024

This research aimed to examine the dynamics of changes in sprint and long jump performance and the age of gender divergence in well-trained young athletes specialising in athletics. Data were collected from 1249 male and 1497 female athletes aged 10 to 15 years who participated in the final round of the annual national athletics tournament “Shipovka Yunykh” from 2017 to 2019. The top 50 results in each age group for the 60-metre sprint and long jump were analysed. Boys showed significantly higher performance than girls in both events from ages 11 and 12. Significant performance improvements were noted between ages 12 and 13 for boys in the long jump and 10–11 in the sprint. Girls showed significant improvements between ages 12 and 13 in the long jump and 11–12 in the sprint. Gender divergence in sprint and long jump performance occurs around age 11. The dynamics of performance changes are influenced by the timing of the growth spurt, highlighting the need for age-specific competition categories in athletics.
Research Progress on the Synergistic Treatment of Multi Pollutants at Low Temperatures Using Carbon-Based Materials
Authors: Li Guoliang , Zhang Mingyu , Zheng Yang , Gao Jiajia , Yue Tao , Zhao Shichen , Liu Chuanchuan
Published: December 2024

Hg0, VOCs and NO are the main pollutants in sintering flue gas from the steel industry. In the wake of the swift progression of China’s steel sector over recent years, the separate removal of gaseous pollutants can no longer meet the current ultra-low emission requirements. The efficient collaborative management of multiple pollutants has low operating costs and conforms to the mainstream of ultra-low emission transformation. The efficient multi-pollutant synergistic treatment has low operating costs in comparison to traditional individual removal of gaseous pollutants. Furthermore, it aligns with the mainstream of ultra-low emission retrofit in China. How to achieve collaborative control of Hg0, VOCs and NO has become the focus of current research. Carbon-based materials (CBMs) have long been favored worldwide as the mainstream adsorbents for removing multiple air pollutants from flue gas. Based on the summary of the mechanisms for simultaneous removal of pollutants, this paper analyzes the future development directions of CBMs for the concurrent detoxification of Hg0, VOCs and NO, and provides a prospect for future research, providing technical support and theoretical basis for low-temperature cooperative control of pollutants in sintering, waste incineration and other processes.
WQI Improvement Based on XG-BOOST Algorithm and Exploration of Optimal Indicator Set
Authors: Liu Jing , Chu Qi , Yuan Wenchao , Zhang Dasheng , Yue Weifeng
Published: December 2024

This paper takes a portion of the Manas River Basin in Xinjiang Province, China, as an example and proposes an improved traditional comprehensive water quality index (WQI) method using Extreme Gradient Boosting (XG-BOOST) to analyze the groundwater quality levels in the region. Additionally, XG-BOOST is used to screen the existing dataset of ten water quality indicators, including fluoride (F), chlorine (Cl), nitrate (NO), sulfate (SO), silver (Ag), aluminum (Al), iron (Fe), lead (Pb), selenium (Se), and zinc (Zn), from 246 monitoring points, in order to find the dataset that optimizes model training performance. The results show that, in the selected study area, water quality categorized as “GOOD” and “POOR” accounts for the majority, with “GOOD” covering 48.7% of the area and “POOR” covering 31.6%. Regions with water quality classified as “UNFIT” are mainly distributed in the central–eastern parts of the study area, located in parts of the Changji Hui Autonomous Prefecture. Comparatively, water quality in the western part of the study area is better than that in the eastern part, while areas with “EXCELLENT” water quality are primarily distributed in the southern parts of the study area. The optimal water quality indicator dataset consists of five indicators: Cl, NO, Pb, Se, and Zn, achieving an accuracy of 98%, RMSE = 0.1414, and R2 = 0.9081.
Field Scale Soil Moisture Estimation with Ground Penetrating Radar and Sentinel 1 Data
Authors: Atun Rutkay , Gürsoy Önder , Koşaroğlu Sinan
Published: December 2024

This study examines the combined use of ground penetrating radar (GPR) and Sentinel-1 synthetic aperture radar (SAR) data for estimating soil moisture in a 25-decare field in Sivas, Türkiye. Soil moisture, vital for sustainable agriculture and ecosystem management, was assessed using in situ measurements, SAR backscatter analysis, and GPR-derived dielectric constants. A novel empirical model adapted from the classical soil moisture index (SSM) was developed for Sentinel-1, while GPR data were processed using the reflected wave method for estimating moisture at 0–10 cm depth. GPR demonstrated a stronger correlation within situ measurements (R2 = 74%) than Sentinel-1 (R2 = 32%), reflecting its ability to detect localized moisture variations. Sentinel-1 provided broader trends, revealing its utility for large-scale analysis. Combining these techniques overcame individual limitations, offering detailed spatial insights and actionable data for precision agriculture and water management. This integrated approach highlights the complementary strengths of GPR and SAR, enabling accurate soil moisture mapping in heterogeneous conditions. The findings emphasize the value of multi-technique methods for addressing challenges in sustainable resource management, improving irrigation strategies, and mitigating climate impacts.
How Gained Experience Influences Perceived Levers and Barriers of Reuse Practices: Learning from North Americans
Authors: Lambec Barbara , Bastien-Masse Maléna , Fivet Corentin
Published: December 2024

This study delves into how the perception of levers and barriers for building element reuse evolves over time as individuals and practices gain experience on this topic. Three periods of business development are compared: the genesis of practice; the current situation; and future projection. The results are drawn from semi-structured interviews with 35 stakeholders from industry, academia, and government in North America. They were invited to address questions about scales, means of demand generation and adaptation, tools and capacities, and stakeholder knowledge and skills. Questions to explore neutral aspects of their practice as well as levers or barriers were also asked. A post-interview analysis identified 14 factors that influence the overall perception of challenges. It also emphasized their interconnectedness over time, allowing for a more nuanced understanding than previous synchronic studies and prioritizing challenges for different stakeholder types. Unusualness, processes, and communication emerge as time-persistent challenges intricately linked with regulatory dynamics. This study also reaffirms challenges such as costs, community dynamics, and the imperative for a societal shift. This insight assists newcomers in anticipating challenges and selecting their paths while also shedding light on current barriers and informing future projections, guiding policymakers on necessary improvements.
Evolution Analysis of the Ecological Footprint and the Ecological Carrying Capacity of Water Resources at Different Spatial and Temporal Scales: A Case Study of Gansu Province
Authors: Liu Qi , Huo Aidi , Liu Yanran , Zhang Ping , Zhao Zhixin , Zhao Xuantao
Published: December 2024

Exploring the ecological footprint and ecological carrying capacity is an effective method to evaluate the sustainable development and utilization of natural resources. Gansu Province, one of the typical arid regions in northwest China that is primarily focused on agriculture, was selected to analyze the evolution of the water ecological footprint and carrying capacity in this paper. In addition, the breadth and depth of the water footprint were combined to further evaluate the current situation of water resource utilization and management across different regions. This study can complement the research on the ecological footprint in arid areas dominated by agriculture. The results showed that (1) the agricultural water footprint was the main footprint and the key to water conservation. The overall water ecological footprint indicated a slow decline trend from 2009 to 2022 in Gansu Province. There was a gradual reduction in the agricultural water footprint and a notable increase in the ecological environment water footprint, indicating water use structures were generally becoming reasonable. (2) During the period, the eco-capacity and per capita eco-capacity exhibited similar trends in fluctuation and change, and spatial distribution was relatively dispersed due to the precipitation, total water resources, and industrial structure in the regions. (3) For prefecture-level cities, the depth of the water ecological footprint showed obvious spatial agglomeration. According to the results, the water footprint breadth of Zhangye and Longnan was larger, and the water resource flow can meet the local water demand. The water footprint depth of Lanzhou, Jinchang, Baiyin, and Jiayuguan was high, indicating the stock of water resources needs to be consumed to satisfy social production and living. The results can provide a scientific basis for the effective management and rational conservation of water resources.
Promoting a Circular Economy in Mining Practices
Authors: Antony Jose Subin , Calhoun Joy , Renteria Otoniel B. , Mercado Pedro , Nakajima Shinichiro , Hope Colton N. , Sotelo Mario , Menezes Pradeep L.
Published: December 2024

Integrating circular economy (CE) principles into mining practices offers a promising path toward reducing environmental harm while promoting sustainable resource management. This shift boosts the industry’s efficiency and profitability and aligns it with global sustainability goals. This paper delves into strategies for closing material loops, such as waste valorization, resource recovery from mine tailings, and water reuse in mining processes. Additionally, this study highlights innovative technologies and their potential to transform traditional linear practices into sustainable, circular systems. This paper emphasizes the importance of strong collaboration among industry stakeholders and policymakers, including mining companies, researchers, and local communities, for the implementation of CE principles. This paper also discusses the role of emerging digital tools, automation, and artificial intelligence in advancing circular practices and improving operational efficiency. By exploring the economic, environmental, and social benefits of the CE, this paper demonstrates how these practices can contribute to sustainable mining. It addresses key challenges, including technological, economic, and regulatory hurdles, and offers recommendations for overcoming them to pave the way for a more sustainable and resilient mining industry.
Spatiotemporal Changes in Ecological Network Structure and Enhancing Territorial Space Management in Guilin, China
Authors: Hu Jinlong , Huang Tingting , Bin Zhenhong , Wang Yingxue
Published: December 2024

Accelerated urbanization and the excessive exploitation of the tourism industry are leading to a diminution of ecological spaces in tourist cities. Ecological networks are an effective method for improving patch connectivity and maximizing ecological space. However, previous research on ecological networks predominantly focuses on static snapshots, ignoring the fact that ecological networks are landscape entities with considerable spatiotemporal and structural dynamics changes. To fill this gap, we first constructed ecological networks of Guilin in 1990, 2000, 2010, and 2020, employing the integrated valuation of ecosystem services and tradeoffs (InVEST) model, the morphological spatial pattern analysis (MSPA) method, and circuit theory. Subsequently, we analyzed the spatiotemporal evolution of the ecological networks and proposed strategies for improving territorial space management. The results showed that ecological sources and corridors were generally decreasing in both number and areas (length), coupled with a notable increase in the number of ecological pinch points and barriers over the 30-year period. The spatiotemporal dynamics of ecological corridors, pinch points, and barriers were associated with ecological sources. Structural evaluation of the ecological networks revealed that during 1990~2020, the value of α (network closure) exceeded 0.7, the value of β (line point rate) surpassed 2, and the value of γ (network connectivity) was greater than 0.8, indicating robust overall connectivity within the ecological networks. The observed decline in these three indicators over time suggested a reduction in connectivity and the available dispersal pathways for species within the ecological networks, highlighting the need for protective measures and optimization strategies. Consequently, the ecological network conservation strategies and the development of ecological patterns were proposed to enhance ecological space management in Guilin. This study addresses a critical knowledge gap in the dynamics of ecological networks and offers valuable insights for mitigating habitat fragmentation and enhancing ecological space management of tourist cities.
Effects of Soil Properties and Altitude on Phylogenetic and Species Diversity of Forest Plant Communities in Southern Subtropical China
Authors: Xue Guangyu , Zeng Ji , Huang Jianyou , Huang Xuguang , Liang Fujiang , Wu Junduo , Zhu Xueping
Published: December 2024

The altitudinal distribution pattern of biodiversity is a hot topic in ecological research. This study specifically aims to investigate how altitude influences the spatial distribution of species and phylogenetic and functional diversity within plant communities. By examining three range-gradient communities of Daqing Mountain-Community I (0–300 m), Community II (300–600 m), and Community III (600–900 m), we explore the interrelationship between species diversity, phylogenetic indices, and environmental drivers (altitude, soil physical properties, and chemical properties). We found (1) a correlation between species diversity and phylogenetic structure in Daqing Mountain. Species diversity decreased and then increased with increasing altitude; phylogenetic diversity decreased with increasing altitude, and the phylogenetic structure changed from dispersed to aggregated; (2) Altitude and soil physical and chemical properties are important drivers of species richness, phylogenetic diversity, and phylogenetic structure along the altitude gradient; (3) The structural equations showed that soil physical properties and altitude rise were the key factors contributing to the decrease in biodiversity in Daqing Mountain, with total soil porosity directly influencing soil physical properties and soil water content indirectly. This study not only reveals the pattern of plant diversity along the altitude of Daqing Mountain but also provides a basis for plant conservation planning, habitat maintenance, and management coordination.
Preparation, Characterization and Application of Sustainable Composite Phase Change Material: A Mineral Material Science Comprehensive Experiment
Authors: Zhang Haomin , Gao Huan , Wang Xiaobo , Dai Huixing
Published: December 2024

Phase change materials (PCMs) play a significant role in achieving sustainable objectives for green buildings. Organic solid–liquid PCMs have excellent heat energy storage density and suitable working temperatures, making them a focal point of research attention. However, these materials face challenges such as potential leakage, low thermal conductivity, and limited fire resistance, which hinder their direct application in the construction industry. Therefore, mineral-based PCMs are highly regarded due to their safety features, environmental friendliness, non-toxicity, and cost-effectiveness within sustainable building development. In this work, a multistage porous kaolinite-based geopolymer encapsulation material using primary raw materials like kaolinite mineral, sodium silicate surfactants, and hydrogen peroxide was successfully synthesized. The PEG is used as the organic solid–liquid PCM while natural graphite mineral serves as a heat transfer enhancement agent to fabricate a novel and sustainable mineral-based composite PCM, which could be applied at the environment temperature from 35–60 °C approximately. Furthermore, a study on material properties was conducted to investigate influencing factors. Comprehensive experimental reform on mineral-based PCMs will offer proficiency in experimental operations and foster the talents’ capacity for comprehensive design, which holds immense significance for understanding and designing mineral materials. This work holds great significance for the sustainable development for education and green buildings.
A Hierarchy of Covariant Generalized Schwarz Maps in M2(ℂ)
Authors: Chruściński Dariusz
Published: December 2024

A class of linear maps in M2(C) displaying diagonal unitary and orthogonal symmetries is analyzed. Using a notion of ω-duality, we prove that a map which is ω-dual to a generalized Schwarz map is again generalized Schwarz. We introduce an infinite hierarchy of generalized Schwarz maps and study the property of an asymptotic limiting map. Interestingly, it is shown that the first example of Schwarz but not completely positive map found by Choi is an example of an asymptotic map.
Lepton Asymmetries in Cosmology
Authors: Lattanzi Massimiliano , Moretti Mauro
Published: December 2024

The cosmological lepton asymmetry, i.e., an excess of leptons over antileptons, is still only loosely constrained, and might be much larger than its tiny baryonic counterpart. If this is the case, charge neutrality requires the lepton asymmetries to be confined in the neutrino sector. We recall the observational effects of neutrino asymmetries on the abundance of light elements produced during Big Bang Nucleosynthesis and on the pattern of cosmic microwave background anisotropies. We point to the necessity of solving the neutrino transport equations, taking into account the effect of flavour oscillation, to derive general and robust constraints on lepton asymmetries. We review the current bounds and briefly discuss prospects for next-generation CMB experiments.
Real-Time Scheduling with Independent Evaluators: Explainable Multi-Agent Approach
Authors: Isakov Artem , Peregorodiev Danil , Tomilov Ivan , Ye Chuyang , Gusarova Natalia , Vatian Aleksandra , Boukhanovsky Alexander
Published: December 2024

This study introduces a multi-agent reinforcement learning approach to address the challenges of real-time scheduling in dynamic environments, with a specific focus on healthcare operations. The proposed system integrates the Human-in-the-Loop (HITL) paradigm, providing continuous feedback from human evaluators, and it employs a sophisticated reward function to attenuate the effects of human-driven events. Novel mapping between reinforcement learning (RL) concepts and the Belief–Desire–Intention (BDI) framework is developed to enhance the explainability of the agent’s decision-making. A system is designed to adapt to changes in patient conditions and preferences while minimizing disruptions to existing schedules. Experimental results show a notable decrease in patient waiting times compared to conventional methods while adhering to operator-induced constraints. This approach offers a robust, explainable, and adaptable solution for the challenging tasks of scheduling in the environments that require human-centered decision-making.
SDN-Based Integrated Satellite Terrestrial Cyber–Physical Networks with 5G Resilience Infrastructure: Future Trends and Challenges
Authors: Ayofe Oluwatobiloba Alade , Okafor Kennedy Chinedu , Longe Omowunmi Mary , Alabi Christopher Akinyemi , Tekanyi Abdoulie Momodu Sunkary , Usman Aliyu Danjuma , Musa Mu’azu Jibrin , Abdullahi Zanna Mohammed , Agbon Ezekiel Ehime , Adikpe Agburu Ogah , Anoh Kelvin , Adebisi Bamidele , Imoize Agbotiname Lucky , Idris Hajara
Published: December 2024

This paper reviews the state-of-the art technologies and techniques for integrating satellite and terrestrial networks within a 5G and Beyond Networks (5GBYNs). It highlights key limitations in existing architectures, particularly in addressing interoperability, resilience, and Quality of Service (QoS) for real-time applications. In response, this work proposes a novel Software-Defined Networking (SDN)-based framework for reliable satellite–terrestrial integration. The proposed framework leverages intelligent traffic steering and dynamic access network selection to optimise real-time communications. By addressing gaps in the literature with a distributed SDN control approach spanning terrestrial and space domains, the framework enhances resilience against disruptions, such as natural disasters, while maintaining low latency and jitter. Future research directions are outlined to refine the design and explore its application in 6G systems.
The Two Alternative Explosion Mechanisms of Core-Collapse Supernovae: 2024 Status Report
Authors: Soker Noam
Published: December 2024

In comparing the two alternative explosion mechanisms of core-collapse supernovae (CCSNe), I examine recent three-dimensional (3D) hydrodynamical simulations of CCSNe in the frame of the delayed neutrino explosion mechanism (neutrino mechanism) and argue that these valuable simulations show that neutrino heating can supply a non-negligible fraction of the explosion energy but not the observed energies, and hence cannot be the primary explosion mechanism. In addition to the energy crisis, the neutrino mechanism predicts many failed supernovae that are not observed. The most challenging issue of the neutrino mechanism is that it cannot account for point-symmetric morphologies of CCSN remnants, many of which were identified in 2024. These contradictions with observations imply that the neutrino mechanism cannot be the primary explosion mechanism of CCSNe. The alternative jittering jets explosion mechanism (JJEM) seems to be the primary explosion mechanism of CCSNe; neutrino heating boosts the energy of the jittering jets. Even if some simulations show explosions of stellar models (but usually with energies below that observed), it does not mean that the neutrino mechanism is the explosion mechanism. Jittering jets, which simulations do not include, can explode the core before the neutrino heating process does. Morphological signatures of jets in many CCSN remnants suggest that jittering jets are the primary driving mechanism, as expected by the JJEM.
mRNA Vaccines Against COVID-19 as Trailblazers for Other Human Infectious Diseases
Authors: Brandi Rossella , Paganelli Alessia , D’Amelio Raffaele , Giuliani Paolo , Lista Florigio , Salemi Simonetta , Paganelli Roberto
Published: December 2024

mRNA vaccines represent a milestone in the history of vaccinology, because they are safe, very effective, quick and cost-effective to produce, easy to adapt should the antigen vary, and able to induce humoral and cellular immunity. Methods: To date, only two COVID-19 mRNA and one RSV vaccines have been approved. However, several mRNA vaccines are currently under development for the prevention of human viral (influenza, human immunodeficiency virus [HIV], Epstein–Barr virus, cytomegalovirus, Zika, respiratory syncytial virus, metapneumovirus/parainfluenza 3, Chikungunya, Nipah, rabies, varicella zoster virus, and herpes simplex virus 1 and 2), bacterial (tuberculosis), and parasitic (malaria) diseases. Results: RNA viruses, such as severe acute respiratory syndrome coronavirus (SARS-CoV)-2, HIV, and influenza, are characterized by high variability, thus creating the need to rapidly adapt the vaccines to the circulating viral strain, a task that mRNA vaccines can easily accomplish; however, the speed of variability may be higher than the time needed for a vaccine to be adapted. mRNA vaccines, using lipid nanoparticles as the delivery system, may act as adjuvants, thus powerfully stimulating innate as well as adaptive immunity, both humoral, which is rapidly waning, and cell-mediated, which is highly persistent. Safety profiles were satisfactory, considering that only a slight increase in prognostically favorable anaphylactic reactions in young females and myopericarditis in young males has been observed. Conclusions: The COVID-19 pandemic determined a shift in the use of RNA: after having been used in medicine as micro-RNAs and tumor vaccines, the new era of anti-infectious mRNA vaccines has begun, which is currently in great development, to either improve already available, but unsatisfactory, vaccines or develop protective vaccines against infectious agents for which no preventative tools have been realized yet.