bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing land-use changes and carbon storage: a case study of the Jialing River Basin, China
Authors: Yang Shuai , Li Liqin , Zhu Renhuan , Luo Chao , Lu Xiong , Sun Mili , Xu Benchuan 
Published: July 2024

AbstractLand-use change is the main driver of carbon storage change in terrestrial ecosystems. Currently, domestic and international studies mainly focus on the impact of carbon storage changes on climate, while studies on the impact of land-use changes on carbon storage in complex terrestrial ecosystems are few. The Jialing River Basin (JRB), with a total area of ~ 160,000 km2, diverse topography, and elevation differences exceeding 5 km, is an ideal case for understanding the complex interactions between land-use change and carbon storage dynamics. Taking the JRB as our study area, we analyzed land-use changes from 2000 to 2020. Subsequently, we simulated land-use patterns for business-as-usual (BAU), cropland protection (CP), and ecological priority (EP) scenarios in 2035 using the PLUS model. Additionally, we assessed carbon storage using the InVEST model. This approach helps us to accurately understand the carbon change processes in regional complex terrestrial ecosystems and to formulate scientifically informed land-use policies. The results revealed the following: (1) Cropland was the most dominant land-use type (LUT) in the region, and it was the only LUT experiencing net reduction, with 92.22% of newly designated construction land originating from cropland. (2) In the JRB, total carbon storage steadily decreased after 2005, with significant spatial heterogeneity. This pattern was marked by higher carbon storage levels in the north and lower levels in the south, with a distinct demarcation line. The conversion of cropland to construction land is the main factor driving the reduction in carbon storage. (3) Compared with the BAU and EP scenarios, the CP scenario demonstrated a smaller reduction in cropland area, a smaller addition to construction land area, and a lower depletion in the JRB total carbon storage from 2020 to 2035. This study demonstrates the effectiveness of the PLUS and InVEST models in analyzing complex ecosystems and offers data support for quantitatively assessing regional ecosystem services. Strict adherence to the cropland replenishment task mandated by the Chinese government is crucial to increase cropland areas in the JRB and consequently enhance the carbon sequestration capacity of its ecosystem. Such efforts are vital for ensuring the food and ecological security of the JRB, particularly in the pursuit of the “dual-carbon” objective.
Flood risk assessment of the Garita River in the urban zone of San Luis Potosí City, by hydrodynamic modeling
Authors: Onchi-Ramos Katya , Rodríguez-Cuevas Clemente , Couder-Castañeda Carlos , Padilla-Pérez Diego-Alfredo 
Published: July 2024

AbstractRapid and uncontrolled urban growth and land use changes in watersheds worldwide have led to increased surface runoff within metropolitan areas, coupled with climate change, creating a risk for residents during the rainy season. The city of San Luis Potosí is no exception to this phenomenon. One affected watercourse is the Garita Stream, which flows inside the city near urbanization. It is essential to analyze the effects of urban sprawl on this stream based on historical precipitation data for the town. Hydrological and topographical information were required to conduct this research. The hydrological study of the basin involved analyzing the region’s geomorphology and historical climatological data. For the stream’s topography, aerial photogrammetry using an unmanned aerial Vehicle (UAV) and Global Navigation Satellite System (GNSS) equipment was employed to conduct topographic surveys in the area. To find out when the Garita stream would overflow and which areas are most likely to flood, numerical modeling was done using 1D, 2D, and 3D programs like SWMM5 (Storm Water Management Model), HEC-RAS (Hydrologic Engineering Center’s River Analysis System), and EDFC Explorer (Environmental Fluid Dynamics Code). These models simulated different return periods and their correlation with current flooding events recorded in the area, thereby further proposing solutions to mitigate overflow issues. By conducting these simulations and analyzing the results, solutions can be suggested to address the overflow problems in the area based on historical flood events at various return periods caused by the Garita Stream.
Asymmetric affective polarization regarding COVID-19 vaccination in six European countries
Authors: Filsinger Maximilian , Freitag Markus 
Published: July 2024

AbstractWhile recent research has shown that supporters and opponents of COVID-19 vaccination have polarizing political attitudes and beliefs, we lack a thorough understanding of how these two groups think about each other. To investigate the feelings and stereotypes between supporters and opponents of COVID-19 vaccination, this study draws on cross-sectional survey data from six European countries (France, Germany, Italy, Spain, Switzerland, and the United Kingdom), collected between January and March 2022 (n = 6379). Our findings indicate an opinion-based affective polarization between supporters and opponents of COVID-19 vaccination. Both groups not only adopt different positions on the issue but also display dynamics of in-group favoritism and out-group hostility. Most notably, our assessment of thermometer scores and character trait ratings shows that this affective polarization is asymmetric, as it is stronger among the pro-vaccination group. Our findings are critical to the control of infectious diseases because affective polarization has been shown to influence health behaviors such as compliance with government policies. The issue is even more pressing as globalization boosts the threat of pandemic emergence and accelerates the global transmission of diseases.
Inconsistent advice by ChatGPT influences decision making in various areas
Authors: Ikeda Shinnosuke 
Published: July 2024

AbstractThe ChatGPT technology is increasingly becoming a part of our daily lives and is starting to be utilized in various decision-making contexts. The current study builds upon prior research, demonstrating that people’s moral decision-making is influenced by ChatGPT across three perspectives, as evidenced by two studies (total n = 1925). The findings suggested that ChatGPT advice impacted decision-making similarly to expert advice, although not all decisions were susceptible to influence, particularly those based on negative emotions. Additionally, ChatGPT advice affected decisions beyond moral judgments, but no effect was observed when the advice recommended immediate low rewards. Moreover, individuals with a higher tendency for personal fear of invalidity were more likely to be influenced by both expert and AI advice, but this was not related to trust in AI.
Electrochemical exfoliation of graphene from pencil lead
Authors: Jiwarawat Natchanon , Leukulwatanachai Thapan , Subhakornphichan Kunbhass , Limwathanagura Siwagorn , Wanotayan Sittinadh , Atthi Nithi , Pankiew Apirak , Pungetmongkol Porpin 
Published: July 2024

AbstractAddressing an ever-increasing demand for graphene in recent years, simple, accessible, and effective graphene synthesis methods are essential. One of such methods is to use a highly oriented pyrolytic graphite (HOPG) to perform an electrochemical exfoliation. While this is one of the simplest and most cost-effective methods, the limited availability and price of HOPG hinders its usage. Our study proposed a simple and economical electrochemical exfoliation of pencil lead, producing graphene with properties comparable to that produced from HOPG. The electrical properties are determined by depositing graphene onto a screen-printed electrode. Graphene from pencil leads can achieve an electrical resistance as low as 1.86 kΩ, marking over 80% improvement in electrical performance compared to bare electrodes. This finding provides an alternative for the synthesis of graphene, increasing its availability and the cost-effectiveness as well as contributing towards a potential commercialization of the method in the future.
Optimizing bioremediation techniques for soil decontamination in a linguistic intuitionistic fuzzy framework
Authors: Alolaiyan Hanan , Hayat Misbah , Shuaib Umer , Razaq Abdul , Salman Mohammed Abdullah , Xin Qin 
Published: July 2024

AbstractBioremediation techniques, which harness the metabolic activities of microorganisms, offer sustainable and environmentally friendly approaches to contaminated soil remediation. These methods involve the introduction of specialized microbial consortiums to facilitate the degradation of pollutants, contribute to soil restoration, and mitigate environmental hazards. When selecting the most effective bioremediation technique for soil decontamination, precise and dependable decision-making methods are critical. This research endeavors to tackle the aforementioned concern by utilizing the tool of aggregation operators in the framework of the Linguistic Intuitionistic Fuzzy (LIF) environment. Linguistic Intuitionistic Fuzzy Sets (LIFSs) provide a robust framework for representing and managing uncertainties associated with linguistic expressions and intuitionistic assessments. Aggregation operators enrich the decision-making process by efficiently handling the intrinsic uncertainties, preferences, and priorities of MADM problems; as a consequence, the decisions produced are more reliable and precise. In this research, we utilize this concept to devise innovative aggregation operators, namely the linguistic intuitionistic fuzzy Dombi weighted averaging operator (LIFDWA) and the linguistic intuitionistic fuzzy Dombi weighted geometric operator (LIFDWG). We also demonstrate the critical structural properties of these operators. Additionally, we formulate novel score and accuracy functions for multiple attribute decision-making (MADM) problems within LIF knowledge. Furthermore, we develop an algorithm to confront the complexities associated with ambiguous data in solving decision-making problems in the LIF Dombi aggregation environment. To underscore the efficacy and superiority of our proposed methodologies, we adeptly apply these techniques to address the MADM problem concerning the optimal selection of a bioremediation technique for soil decontamination. Moreover, we present a comparative evaluation to delineate the authenticity and practical applicability of the recently introduced approaches relative to previously formulated techniques.
Controlling hypersonic boundary layer transition with localized cooling and metasurface treatments
Authors: Oz Furkan , Kara Kursat 
Published: July 2024

AbstractThis study investigates a novel method to control hypersonic boundary layer transition using a combined local cooling and local metasurface treatment. The method’s effectiveness was investigated on a 5-degree half-angle blunt wedge with a nose radius of 0.0254 mm at a freestream Mach number of 6.0 using direct numerical simulations and linear stability theory. We explored four cases: (i) adiabatic baseline case, (ii) locally cooled case, (iii) local metasurface case, and (iv) combined local cooling-local metasurface case. Results showed that the combined local cooling-local metasurface treatment significantly reduced both wall pressure disturbance amplitude and the density perturbation amplitude around the sonic line, indicating a potential for controlling hypersonic boundary layer transition. In the local cooling-local metasurface case, the disturbance amplitude at the end of the computational domain was 270 times lower than the baseline case. The study also examined the impact of Reynolds numbers, ranging from 25.59 million per meter to 32.80 million per meter. Unsteady simulations revealed that the Reynolds number had a negligible effect on the local cooling-local metasurface performance, indicating that the proposed method applies to a wide range of flight conditions.
Saltwater intrusion and human health risks for coastal populations under 2050 climate scenarios
Authors: Mueller William , Zamrsky Daniel , Essink Gualbert Oude , Fleming Lora E. , Deshpande Aniruddha , Makris Konstantinos C. , Wheeler Benedict W. , Newton John N. , Narayan K. M. Venkat , Naser Abu Mohd , Gribble Matthew O. 
Published: July 2024

AbstractPopulations consuming saline drinking water are at greater risk of high blood pressure and potentially other adverse health outcomes. We modelled data and used available datasets to identify countries of higher vulnerability to future saltwater intrusion associated with climate change in 2050 under Representative Concentration Pathways (RCP)4.5 and RCP8.5. We developed three vulnerability criteria to capture geographies with: (1) any coastal areas with projected inland saltwater intrusion of ≥ 1 km inland, (2) > 50% of the population in coastal secondary administrative areas with reliance on groundwater for drinking water, and 3) high national average sodium urinary excretion (i.e., > 3 g/day). We identified 41 nations across all continents (except Antarctica) with ≥ 1 km of inland saltwater intrusion by 2050. Seven low- and middle-income countries of higher vulnerability were all concentrated in South/Southeast Asia. Based on these initial findings, future research should study geological nuances at the local level in higher-risk areas and co-produce with local communities contextually appropriate solutions to secure equitable access to clean drinking water.
Perceived social fairness and trust in government serially mediate the effect of governance quality on subjective well-being
Authors: Ma Yongqiang , Ma Baobin , Yu Lichun , Ma Mingyang , Dong Yibing 
Published: July 2024

AbstractGovernance quality refers to how well the processes and institutions of public governance function and is widely recognized as having an important influence on human well-being. We developed and tested a theoretical model that elucidates the relationship between governance quality and the subjective well-being of residents in China by revealing the serial mediation effects of perceived social fairness and trust in government. Using data from the nationally representative Chinese Social Survey conducted in 2021 (n = 5019), we performed structural equation modeling to empirically examine our hypotheses. The results indicated that governance quality exerted a significant positive fully indirect impact on subjective well-being through perceived social fairness, trust in government, and their serial mediation effects. This study contributes to the literature by providing valuable insights into the determinants of subjective well-being and highlighting the serial mediating roles of perceived social fairness and trust in government in the relationship between governance quality and subjective well-being. The findings also provide practical insights for policymakers, as they indicate that promoting perceived social fairness and fostering trust in government are essential to translate governance quality into subjective well-being.
An edge‐based event‐triggered delayed distributed algorithm for economic dispatch in smart grids
Authors: Ren Chengze , Hu Xuguang , Zhao Haoran , Sun Qiuye 
Published: July 2024

AbstractThis paper presents an edge‐based event‐triggered delay distributed algorithm for solving the economic dispatch problem (EDP) in smart grids. The objective of the EDP is to minimize the total generation cost by allocating power to individual generators, each with its local generation constraint. To save the overhead of communication resources between agents, an edge‐based event‐triggered mechanism is suggested. By setting distinct triggering thresholds for each communication edge, the agent may efficiently regulate the communication frequency among all neighbors. However, in practice, owing to the instability of the network, the agent may receive information regarding its neighbors, leading to communication lags for every communication link. The virtual agent technique and double‐stochastic matrix augmentation technique provide an equivalent delay‐free EDP. It is demonstrated that the proposed algorithm can asymptotically converge to the global optimal solution as long as the communication delay is arbitrary, time‐varying, and random, but bounded. Objective and clear evidence is provided through a case study in smart grids to verify the algorithm's feasibility.
GR‐Former: Graph‐reinforcement transformer for skeleton‐based driver action recognition
Authors: Xu Zhuoyan , Xu Jingke 
Published: July 2024

AbstractIn in‐vehicle driving scenarios, composite action recognition is crucial for improving safety and understanding the driver's intention. Due to spatial constraints and occlusion factors, the driver's range of motion is limited, thus resulting in similar action patterns that are difficult to differentiate. Additionally, collecting skeleton data that characterise the full human posture is difficult, posing additional challenges for action recognition. To address the problems, a novel Graph‐Reinforcement Transformer (GR‐Former) model is proposed. Using limited skeleton data as inputs, by introducing graph structure information to directionally reinforce the effect of the self‐attention mechanism, dynamically learning and aggregating features between joints at multiple levels, the authors’ model constructs a richer feature vector space, enhancing its expressiveness and recognition accuracy. Based on the Drive & Act dataset for composite action recognition, the authors’ work only applies human upper‐body skeleton data to achieve state‐of‐the‐art performance compared to existing methods. Using complete human skeleton data also has excellent recognition accuracy on the NTU RGB + D‐ and NTU RGB + D 120 dataset, demonstrating the great generalisability of the GR‐Former. Generally, the authors’ work provides a new and effective solution for driver action recognition in in‐vehicle scenarios.
A collaborative WSN‐IoT‐Animal for large‐scale data collection
Authors: Abdoul Aziz Hamayadji , Abba Ari Ado Adamou , Ndam Njoya Arouna , Djedouboum Assidé Christian , Mohamadou Alidou , Thiare Ousmane 
Published: July 2024

AbstractIn recent years, large‐scale data collection systems have developed rapidly in many fields, including agriculture, transport and many others. The internet of things (IoT), whose main platform is wireless sensor networks (WSNs), is behind this development. Comprising thousands of sensors of different kinds, their main purpose is to collect and transmit data. Several data collection techniques have been proposed, including static, mobile and hybrid approaches. The challenges faced by these techniques are considerable, and include energy conservation, planning and trajectory optimisation during data collection, most importantly, the challenges related to the communication between the static sensors generally distributed in a more or less large geographical space and the mobile data collection system (UAV, vehicle, robot etc.). Not to mention the cost, which remains enormous for the agricultural sectors. A hybrid WSN‐IoT‐Animal that is self‐configured to improve data acquisition over large agricultural areas is presented. The main objective and originality of the heterogeneous semi‐modern scheme proposed here oscillating between traditional agriculture and precision agriculture is the use of animals as data collection tools. The main contribution here is the design of a simple and efficient model of data collection that is easily accessible by farmers by adapting the available resources. This model describes and adopts a sensor deployment method based on the notion of the hypergraph, which provides adequate coverage and ensures communication between the mobile sink and a subset of peripheral sensors chosen in alternation. Simulation results verify the effectiveness of the proposed protocol in terms of network lifetime compared to other works. In addition, the amount of data received by the mobile sink demonstrates the importance of this approach in terms of connectivity for large‐scale data collection.
Revealing the inner workings of the lensed quasar SDSS J1339+1310: Insights from microlensing analysis
Authors: Fian C. , Muñoz J. A. , Jiménez-Vicente J. , Mediavilla E. , Chelouche D. , Kaspi S. , Forés-Toribio R. 
Published: July 2024

Aims. We aim to unveil the structure of the continuum and broad-emission line (BEL) emitting regions in the gravitationally lensed quasar SDSS J1339+1310 by examining the distinct signatures of microlensing present in this system. Our study involves a comprehensive analysis of ten years (2009–2019) of photometric monitoring data and seven spectroscopic observations acquired between 2007 and 2017.
Methods. This work focuses on the pronounced deformations in the BEL profiles between images A and B, alongside the chromatic changes in their adjacent continua and the striking microlensing variability observed in the r-band light curves. We employed a statistical model to quantify the distribution and impact of microlensing magnifications and utilized a Bayesian approach to estimate the dimensions of various emission regions within the quasar. To establish a baseline relatively free of microlensing effects, we used the cores of the emission lines as a reference.
Results. The analysis of the r-band light curves reveals substantial microlensing variability in the rest-frame UV continuum, suggesting that image B is amplified relative to image A by a factor of up to six. This finding is corroborated by pronounced microlensing-induced distortions in all studied BEL profiles (Lyα, Si IV, C IV, C III], and Mg II), especially a prominent magnification of image B’s red wing. These microlensing signals surpass those typically observed in lensed quasars, and the asymmetric line profile deformations imply an anisotropic broad-line region (BLR). We estimated the average dimensions of the BLR to be notably smaller than usual: the region emitting the blue wings measures R1/2 = 11.5 ± 1.7 light-days, while the red wings originate from a more compact area of R1/2 = 2.9 ± 0.6 light-days. From the photometric monitoring data, we inferred that the region emitting the r-band is R1/2 = 2.2 ± 0.3 light-days across. Furthermore, by assessing the gravitational redshift of the UV Fe III blend and combining it with the blend’s microlensing-based size estimate, we calculated the central SMBH’s mass to be MBH ∼ 2 × 108 M⊙.