bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome-Wide Analysis of the Cis-Prenyltransferase (CPT) Gene Family in Taraxacum kok-saghyz Provides Insights into Its Expression Patterns in Response to Hormonal Treatments
Authors: Zhang Liyu , He Huan , Wang Jiayin , Du Pingping , Wang Lili , Jiang Guangzhi , Liu Lele , Yang Lu , Jin Xiang , Li Hongbin , Xie Quanliang
Published: January 2025

Taraxacum kok-saghyz (TKS) is a natural rubber (NR)-producing plant with great development prospects. Accurately understanding the molecular mechanism of natural rubber biosynthesis is of great significance. Cis-prenyltransferase (CPT) and cis-prenyltransferase-like (CPTL) proteins catalyze the elongation of natural rubber molecular chains and play an essential role in rubber biosynthesis. In this study, we performed a genome-wide identification of the TkCPT/CPTL family, with eight CPT and two CPTL members. We analyzed the gene structures, evolutionary relationships and expression patterns, revealing five highly conserved structural domains. Based on systematic evolutionary analysis, CPT/CPTL can be divided into six subclades, among which the family members are most closely related to the orthologous species Taraxacum mongolicum. Collinearity analyses showed that fragment duplications were the primary factor of amplification in the TkCPT/CPTL gene family. Induced by ethylene and methyl jasmonate hormones, the expression levels of most genes increased, with significant increases in the expression levels of TkCPT5 and TkCPT6. Our results provide a theoretical basis for elucidating the role of the TkCPT/CPTL gene family in the mechanism of natural rubber synthesis and lay a foundation for molecular breeding of T. kok-saghyz and candidate genes for regulating natural rubber biosynthesis in the future.
Synergistic Effects of Zn-Rich Layered Double Hydroxides on the Corrosion Resistance of PVDF-Based Coatings in Marine Environments
Authors: Alqahtani Hissah A. , AlGhamdi Jwaher M. , Mu’azu Nuhu Dalhat
Published: January 2025

In this study, zinc–aluminum layered double hydroxide (ZLDH) and its calcined counterpart (CZLDH) were synthesized and incorporated into a poly(vinylidene fluoride) (PVDF) matrix to develop high-performance anti-corrosion coatings for mild steel substrates. The structural integrity, morphology, and dispersion of the LDH fillers were analyzed using FTIR, XRD, Raman spectroscopy, and SEM/EDS, while coating performance was evaluated through water contact angle (WCA), adhesion tests, and electrochemical techniques. Comparative electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization tests in a 3.5% NaCl solution revealed that the ZLDH/PVDF coating exhibited superior corrosion resistance and long-term stability compared to CZLDH/PVDF and pristine PVDF coatings. The intact lamellar structure of ZLDH promoted excellent dispersion within the polymer matrix, enhancing interfacial adhesion, reducing porosity, and effectively blocking chloride ion penetration. Conversely, calcination disrupted the lamellar structure of ZLDH, reducing its compatibility and adhesion performance within the PVDF matrix. This study demonstrates the critical role of ZLDH’s structural integrity in achieving enhanced adhesion, barrier properties, and corrosion protection, offering an effective anti-corrosion coating for marine applications.
Anti-Methicillin-Resistant Staphylococcus aureus Efficacy of Layer-by-Layer Silver Nanoparticle/Polyacrylic Acid-Coated Titanium Using an In-House Dip Coater
Authors: Puttawong Julinthip , Yingkajorn Mingkwan , Khongkow Pasarat , Thamphiwatana Soracha D. , Phairatana Tonghathai
Published: January 2025

The emergence of methicillin-resistant Staphylococcus aureus (MRSA) is still posing a global challenge in healthcare settings. This bacterial strain is a cause of severe periprosthetic infection, thereby impairing the success of implant insertion. To address this issue, implant surface modification is required. Herein, we developed a novel multilayered silver nanoparticle/polyacrylic acid-coated Ti plate (AgNPs/PAA/Ti) using an in-house dip coater. AgNPs were synthesized and characterized. The dip-coating process was optimized based on the dipping rate, evaporation time, and coating cycle number. Uniform and reproducible coatings were achieved on Ti surfaces, with consistency verified through SEM analysis. The average size of the AgNPs was approximately 36.50 ± 0.80 nm with a PDI of 0.443 ± 0.025, and the zeta potential was measured at around –23.3 ± 2.0 mV. The maximum coating thickness of 83.5 ± 1.3 µm was observed at 15 cycles of dip coating. Moreover, our developed AgNPs/PAA/Ti plate showed both antimicrobial and biofilm-resistant performance, while also exhibiting enhanced biocompatibility with cultured MG63 osteosarcoma cells, maintaining cell viability greater than 70%. We envisage that this material holds significant promise as a candidate for medical implant devices, offering protection against MRSA-associated infection at insertion sites with low vascularity in the future.
Heat-Responsive PLA/PU/MXene Shape Memory Polymer Blend Nanocomposite: Mechanical, Thermal, and Shape Memory Properties
Authors: Sanaka Rajita , Sahu Santosh Kumar , Sreekanth P. S. Rama , Giri Jayant , Mohammad Faruq , Al-Lohedan Hamad A. , Saharudin Mohd Shahneel , Ma Quanjin
Published: January 2025

This study investigates the fabrication and characterization of heat-responsive PLA/PU/MXene shape memory polymer blend nanocomposites with varying PLA content (10, 20, 30, and 50%) and a fixed MXene content of 0.5 wt.%. The results indicate significant improvements in mechanical properties, with the 50% PLA/PU/MXene blend showing a 300% increase in ultimate tensile strength and a 90% decrease in % elongation compared to pure PU. Additionally, the 50% blend exhibited a 400% increase in flexural strength. Microstructural analysis revealed dispersed pores and sea–island morphology in pure PU and the 50% PLA/PU/MXene blend. Thermal analysis using DSC showed an increase in crystallinity from 33% (pure PU) to 45% for the 50% PLA/PU/MXene blend, indicating enhanced crystalline domains due to the semi-crystalline nature of PLA and MXene’s influence on molecular ordering. TGA demonstrated a significant improvement in thermal stability, with the onset temperature rising from 185 °C (pure PU) to 212 °C and the degradation temperature increasing from 370 °C to 425 °C for the 50% blend, attributed to the rigid structure of PLA and MXene’s stabilizing effect. Shape memory testing revealed that the 30% PLA/PU/MXene blend achieved the best shape fixity and recovery with optimal performance, whereas higher PLA content diminished shape memory behavior.
Efficient CO2 Capture Using Nitrogen-Enriched Microporous Carbon Derived from Polybenzoxazine in a Single-Step Process for Environmental Sustainability
Authors: Periyasamy Thirukumaran , Asrafali Shakila Parveen , Lee Jaewoong
Published: January 2025

In this research, we successfully synthesized nitrogen-enriched microporous carbon through a meticulous process involving two different activation procedures. Initially, polybenzoxazine was carbonized at 800 °C to create a precursor material, which was then activated with two different activating agents (KOH and KMnO4) at the same temperature. This activation significantly enhanced the material’s porosity, increasing its specific surface area from 335 m2/g (KOH activated) to 943 m2/g (KMnO4 activated). XPS analysis confirmed the presence of nitrogen functionalities, including secondary-N, oxide-N, pyridone-N, and pyridine-N, which are critical for CO2 adsorption. Adsorption tests demonstrated a high CO2 uptake of 3.8 mmol/g at 25 °C and 1 bar, driven by a combination of physisorption (physical interaction with the surface area) and chemisorption (chemical interaction with nitrogen sites). This high adsorption capacity can be attributed to the carbon’s substantial surface area, significant micropore volume, and the interconnected network of pores, which together provide structural stability and facilitate the diffusion of CO2 molecules. These findings suggest that this nitrogen-enriched microporous carbon, derived from polybenzoxazine, holds significant promise as a highly efficient material for applications in CO2 capture and storage.
Viscoelastic Memory Effects in Cyclic Thermomechanical Loading of Epoxy Polymer and Glass-Reinforced Composite: An Experimental Study and Modeling Under Variable Initial Stress and Cycle Durations
Authors: Mishnev Maxim , Korolev Alexander , Zadorin Alexander , Alabugina Daria , Malikov Denis , Zyrianov Fedor
Published: January 2025

This article presents a study of the viscoelastic behavior of an epoxy polymer and a glass-reinforced composite based on it under cyclic thermomechanical loading. The goal is to model and explain the experimentally observed stress state formation, including the accumulation of residual stresses under various initial mechanical stress levels and heating/cooling cycle durations. An improved material model, implemented as a Python script, is used, allowing for the consideration of memory effects on thermomechanical loading depending on the level and nature (mechanical or thermal) of the initial stresses. A Python script was developed to determine the viscoelastic parameters (elastic modulus E1, elastic parameter E2, and viscosity) for the three-element Kelvin–Voigt model. These parameters were determined at different temperatures for both the polymer and the glass-reinforced composite used in the modeling. The accumulation of stresses under different ratios of mechanical and thermal stresses was also investigated. Experiments showed that high levels of residual stress could form in the pure epoxy polymer. The initial stress state significantly influences residual stress accumulation in the pure epoxy polymer. Low initial tensile stresses (0–1.5 MPa) resulted in substantial residual stress accumulation, exceeding the initial stresses by up to 2.7 times and reaching values of up to 2.1 MPa. Conversely, high initial stresses (around 4 MPa) suppressed residual stress accumulation due to the dominance of relaxation processes. This highlights the critical role of the initial loading conditions in predicting long-term material behavior. In the glass-reinforced plastic, the effect of residual stress accumulation was significantly weaker, possibly due to the reinforcement and high residual stiffness, even at elevated temperatures (the studies were conducted from 30 to 180 °C for the composite and from 30 to 90 °C for the polymer). The modeling results show satisfactory qualitative and quantitative agreement with the experimental data, offering a plausible explanation for the observed effects. The proposed approach and tools can be used to predict the stress–strain state of polymer composite structures operating under cyclic thermomechanical loads.
Toward Multi-Dimensional Separation of Nanoparticles in Tubular Centrifuges
Authors: Winkler Marvin , Gleiss Marco , Nirschl Hermann
Published: January 2025

The processing and preparation of particulate products is an important process in modern industry and science. The enormous potential for innovation in research and development is due to the complex interactions of solids with their environment. The aim of advanced particle production is to achieve high yields of narrowly distributed particle sizes, shapes or material compositions that provide advantageous product specifications. The integration of solid–liquid separation into these processes expands the process engineering scope in terms of product quality and efficiency. Designing these processes to accommodate a wide range of separation characteristics at small-particle-size scales is a major challenge. Taking these aspects into account, the present work aims to improve a dynamic simulation tool for tubular centrifuges that models the time- and space-dependent mass transport and thus, for the first time, can predict separation outcomes when processing both single- and multi-component systems. Utilizing an optical measurement technique, nanosuspension properties can be measured in real time during separation to support model validation. The simulation results align closely with experimental findings and offer plausible insights when addressing multi-dimensional property distributions of non-spherical particles. This study contributes to advanced modeling of separation experiments in tubular centrifuges in real time, taking into account multiple particle properties such as material density and particle form.
Stress Prediction Processes of Metal Pressure-Bearing Complex Components in Thermal Power Plants Based on Machine Learning
Authors: Wang Shutao , Shi Renqiang , Wu Jian , Ma Yunfei , Yang Chao , Liu Huan
Published: January 2025

The real-time stress assessment of metal pressure components is one of the key factors in ensuring the safe operation of thermal power plants. To address the challenge of real-time prediction of stress in the key areas of complex special-shaped metal pressure-bearing components in a certain domestic 300 MW thermal power plant, three typical complex metal pressure-bearing components, the main steam pipe tee (MSPT), the steam drum downcomer joint (DDJ) and the header ligament (HL), were taken as research objects. The stress distribution of the three complex metal pressure-bearing components under different conditions was analyzed through the finite element method, and the stress results at the dangerous points were used as samples to establish training sample data. Subsequently, different machine learning methods were employed to train the sample data. The training results indicate that neural networks (NNs) and the Auto-Sklearn Regression (ASR) models can accurately predict the stress of the key parts of complex metal pressure-bearing components in real time. The ASR method demonstrates better performance in stress prediction of the main steam pipe tee, with a prediction accuracy of ≥96%. The NN model shows better prediction for the header ligament, with a prediction accuracy of ≥94%. These research findings provide effective support for the high-temperature lifespan assessment and safe operation of thermal power plants.
St. Thomas Aquinas on God as Ipsum Esse Subsistens
Authors: Trabbic Joseph G.
Published: January 2025

St. Thomas Aquinas’s doctrine of God as ipsum esse subsistens is not easy to understand. Even some of his more informed interpreters appear to struggle with it. In this paper, I attempt to explain the doctrine in a way that I hope is intelligible to a fairly broad philosophical audience. I also respond to Norman Kretzmann’s interpretation of it, which I think is mistaken. The main problem with Kretzmann’s interpretation seems to be a failure to grasp what Thomas means by esse.
Seabed Depth Prediction Using Multi-Scale Gravity Anomalies and Fully Connected Deep Neural Networks: A Novel Approach Applied to the South China Sea
Authors: Yuan Jiajia , Yang Chen , Dong Di , Guo Jinyun , An Dechao , Yu Daocheng
Published: January 2025

Accurate seabed topography is crucial for marine research, resource exploration, and engineering applications. While deep learning techniques have been widely applied in seabed inversion, existing methods often overlook the multi-scale influence of gravity anomalies, particularly the critical role of short-wavelength gravity anomalies in resolving fine-scale bathymetric features. In this study, we propose a novel Fully Connected Deep Neural Network (FCDNN) approach that systematically integrates long-wavelength, short-wavelength, and residual gravity anomaly components for seabed topography inversion. Using multi-satellite altimetry-derived gravity anomaly data (SIO V32.1) and shipborne bathymetric data (NCEI), we constructed a high-resolution (1′ × 1′) seabed topography model for the South China Sea (108°E–121°E, 6°N–23°N), termed FCD_Depth_SCS. The workflow included multi-scale decomposition of gravity anomalies, linear regression-based residual calculation, and FCDNN-based nonlinear training to capture the complex relationships between gravity anomalies and water depth. The FCD_Depth_SCS model achieved a difference standard deviation (STD) of 44.755 m and a mean absolute percentage error (MAPE) of 2.903% when validated against 160,476 shipborne control points. This performance significantly outperformed existing models, including GEBCO_2024, SIOv25.1, DTU18, and GGM_Depth (derived from the Gravity–Geologic Method), whose STDs were 82.234 m, 108.241 m, 186.967 m, and 58.874 m, respectively. Notably, the inclusion of short-wavelength gravity anomalies enabled the model to capture fine-scale bathymetric variations, particularly in open-sea regions. However, challenges remain near coastlines and complex terrains, highlighting the need for further model partitioning to address localized nonlinearity. This study highlights the benefits of integrating multi-scale gravity anomaly data with a fully connected deep neural network. Employing this innovative and robust approach enables high-resolution inversion of seabed topography with enhanced precision. The proposed method provides significant advancements in accuracy and resolution, contributing valuable insights for marine environmental research, resource management, and oceanographic studies.
China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control
Authors: Shao Nan , Wang Qin , Bu Zhichao , Yin Zhenping , Dai Yaru , Chen Yubao , Wang Xuan
Published: January 2025

Water vapor is an active trace component in the troposphere and has a significant impact on meteorology and the atmospheric environment. In order to meet demands for high-precision water vapor and aerosol observations for numerical weather prediction (NWP), the China Meteorological Administration (CMA) deployed 49 Raman aerosol lidar systems and established the first Raman–Mie scattering lidar network in China (CARLNET) for routine measurements. In this paper, we focus on the water vapor measurement capabilities of the CARLNET. The uncertainty of the water vapor Raman channel calibration coefficient (Cw) is determined using an error propagation formula. The theoretical relationship between the uncertainty of the calibration coefficient and the water vapor mixing ratio (WVMR) is constructed based on least squares fitting. Based on the distribution of lidar in regions with different humidity conditions, the method of real-time calibration and quality control based on radiosonde data is established for the first time. Based on the uncertainty requirements of the World Meteorological Organization for water vapor in data assimilation, the calibration and quality control thresholds of the WVMR in regions with different humidity conditions are determined by fitting real-time lidar and radiosonde data. Lastly, based on the radiosonde results, the calibration algorithm established in this study is used to calibrate CARLNET data from October to December 2023. Compared with traditional calibration results, the results show that the stability and detection accuracy of the CARLNET significantly improved after calibration in regions with different humidity conditions. The deviation of the Cw decreased from 12.84~18.47% to 5.41~11.54%. The inversion error of the WVMR compared to radiosonde decreased from 1.05~0.46 g/kg to 0.82~0.34 g/kg. The reliability of the improved calibration algorithm and the CARLNET’s performance have been verified, enabling them to provide high-precision water vapor products for NWP.
TLSynth: A Novel Blender Add-On for Real-Time Point Cloud Generation from 3D Models
Authors: Pérez Emiliano , Sánchez-Hermosell Adolfo , Merchán Pilar
Published: January 2025

Point clouds are a crucial element in the process of scanning and reconstructing 3D environments, such as buildings or heritage sites. They allow for the creation of 3D models that can be used in a wide range of applications. In some cases, however, only the 3D model of an environment is available, and it is necessary to obtain point clouds with the same characteristics as those captured by a laser scanner. For instance, point clouds may be required for surveys, performance optimization, site scan planning, or validation of point cloud processing algorithms. This paper presents a new terrestrial laser scanner (TLS) simulator, designed as a Blender add-on, that produces synthetic point clouds from 3D models in real time. The simulator allows users to adjust a set of parameters to replicate real-world scanning conditions, such as noise generation, ensuring the synthetic point clouds closely mirror those produced by actual laser scanners. The target meshes may be derived from either a real-world scan or 3D designs created using design software. By replicating the spatial distributions and attributes of real laser scanner outputs and supporting real-time generation, the simulator serves as a valuable tool for scan planning and the development of synthetic point cloud repositories, advancing research and practical applications in 3D computer vision.
HILIC-DAD Method for Simultaneous Determination of Acid and Basic Drugs: Application to the Quantitation of Ibuprofen, Atenolol, and Salbutamol in Urine After Solid-Phase Extraction
Authors: Rosales-Conrado Noelia , Pedrera-Cajas Laura , Soliño-Rodríguez Elvira , León-González María Eugenia
Published: January 2025

A simple method has been developed for the simultaneous analysis of ibuprofen (acid drug), and salbutamol and atenolol (basic drugs) in urine samples at concentrations of 0.40 µg·mL−1. Simultaneous chromatographic separation has been possible using hydrophilic interaction liquid chromatography (Kinetex HILIC® column (2.1 mm × 150 mm, 2.6 μm particle size diameter and 100 Å pore size) combined with gradient elution by employing a mixture of acetonitrile–acetate buffer 5 mM at pH 6 (from 95:5 to 75:25 (v/v)) as the mobile phase. Detection was performed at 227 and 275 nm. The simultaneous preconcentration and cleaning of the sample has been possible by solid-phase extraction using the HLB ExtraBond® polymeric-type sorbent (which is a pyrrolidone-modified divinylbenzene polystyrene type). It has provided recoveries between (63 ± 9)% for salbutamol, (74 ± 8)% for ibuprofen, and (96 ± 9)% for atenolol in 10 mL of synthetic urine containing 4.0 μg of each of the drugs analyzed. The detection limits were 0.025 µg·mL−1 for ibuprofen, µg·mL−1 for salbutamol, and 0.007 µg·mL−1 for atenolol. The detection limits obtained allow the evaluation of the free forms of ibuprofen, atenolol, and salbutamol at the excreted concentration levels at the therapeutic doses usually administered. The coefficients of variation between days were in the range 4.5–10.9%.
The Impact of Differential Settlement on Sloshing Dynamics in Coastal Zone Storage Tanks Under External Excitation: Implications for Sustainable Development
Authors: Jin Heng , Lu Jintao , Liu Yi , Shen Jianmin , Zhang Fashui , Zhu Chenhao , Li Shu
Published: January 2025

Large storage tanks situated in coastal areas are vulnerable to environmental hazards, with earthquakes being one of the most destructive forces threatening their structural safety. Additionally, differential settlement can significantly alter conditions in the tank, including the inclination, thereby changing the direction of external applied excitation forces and affecting the liquid sloshing response. To investigate the coupled effects of structural settlement and external excitation, model tests were conducted in series to analyze liquid sloshing behavior in a tilted tank subjected to harmonic excitation. The results revealed that the liquid response under combined environmental loads displayed distinct characteristics compared with that under single excitation. While the inclination angle had minimal influence during the unstable sloshing stage, it became crucial during the stable stage, particularly for third-order resonant responses, leading to intensified sloshing. More specifically, as the tilt angle of the storage tank from 0° to 8°, the steady-state wave height at third-order resonance increased by approximately 69%. This highlights the amplified risks to the structural stability and safety posed by differential settlement. Furthermore, variations in steady-state wave heights due to differential settlement conditions were investigated. The water level elevation along the tank walls varies as the inclination angles increase, which leads to potential risks to the stability of liquid storage under forced motion, especially under symmetric structural designs, and increases the likelihood of structural instability, oil spills, and other coastal disasters. These results provide valuable insights into the safety risks and sustainable utilization of coastal infrastructure, serving a basis for assessing and mitigating the risks associated with structural settlement and seismic excitations.
Toward an International Grundnorm for Climate Change: Ensuring Sustainability Away from the Traditional Notion of Security
Authors: Jalil Sarkawt
Published: January 2025

Climate change has been considered a critical challenge that transcends traditional notions of security, demanding a shift in perspective toward environmental sustainability. Historically, security has been viewed as an inviolable boundary, shaped significantly by the aftermath of World War II, when the international community prioritized peace, territorial integrity, and political independence. However, humanity now faces unprecedented threats that cannot be addressed through rigid or outdated definitions of security. Climate change impacts the entire planet, affecting both living and non-living organisms, and has arisen primarily from anthropogenic activities over the past two centuries. Consequently, solutions must originate from within human societies, emphasizing sustainability alongside action. Despite extensive discourse, meaningful progress remains limited. This paper, drawing on scientific data about climate change’s far-reaching consequences, aims to highlight that climate change, despite theoretical and practical challenges, has the potential to supplant traditional State-centered security as the Grundnorm of international law, serving as the critical threshold that demands a comprehensive reform and reimagining of the international legal framework. It concludes that climate change’s new normativity represents opportunities to reform law and order to ensure life and sustainability.
Towards Environmental Sustainability: An Input–Output Analysis to Measure Industry-Level Carbon Dioxide Emissions in Egypt
Authors: Al-Ayouty Iman
Published: January 2025

Egypt’s average share of global carbon dioxide emissions has been rising from mid-1990s to date. This motivates the present study to identify industries that drive carbon dioxide emissions (as direct emitters and as total emitters with high emission multiplier effects). Environmental input–output analysis is applied to Egypt’s 2017–2018 input–output table to measure sectoral emissions. The industries identified as high emitters are linked to Egypt’s achievement of Sustainable Development Goals, namely, Goals 7, 8, 9, 12, and 13. The findings indicate that ten industries qualify as environmentally degrading (dirty), having the highest emission multiplier effects (in descending order): electricity, gas, and water; non-metallic mineral products; basic metals; rubber and plastic products; chemicals and chemical products; paper and paper products; food products; hotels and restaurants; transportation and storage; and textiles. Eight of these industries also have high output multiplier effects. This underscores that although potential investment in and the growth of these industries will generate output multiplier effects, they will also be coupled with emission multiplier effects. Five other industries had high emission multipliers, as follows: water and sewerage; beverages; coke and refined petroleum products; extraction of crude petroleum; and mining of metal ores. The growth of these industries would not be in favor of the achievement of SDGs. Policy measures are recommended.
Environmental Sustainability and Climate Change: An Emerging Concern in Banking Sectors
Authors: Saif-Alyousfi Abdulazeez Y. H. , Alshammari Turki Rashed
Published: January 2025

This study explores the crucial role of the banking industry in addressing climate change and promoting environmental sustainability. As climate change increasingly threatens global economies, ecosystems, and public health, financial experts recognize the potential for the banking sector to contribute to a low-carbon economy. By incorporating green-banking practices, which blend traditional financial services with environmental, social, and economic considerations, banks can foster sustainable development while reaping financial benefits. The research examines the dynamics of sustainable banking, focusing on its ability to drive efficiency improvements through eco-friendly programs and enhance profitability. Furthermore, the study discusses the challenges in adopting and implementing environmental sustainability, comparing the command-and-control regulatory model with voluntary approaches. The findings emphasize the importance of effective regulation and incentives for ensuring that banks adopt sustainable practices, ultimately contributing to a more resilient and low-carbon economic system. Through this analysis, this study underscores the banking industry′s pivotal role in shaping the transition towards a sustainable future.
Solvability of Boundary Value Problems for Differential Equations Combining Ordinary and Fractional Derivatives of Non-Autonomous Variable Order
Authors: Souid Mohammed Said , Benkerrouche Amar , Guedim Souad , Pinelas Sandra , Amara Abdelkader
Published: January 2025

This study introduces a novel approach for investigating the solvability of boundary value problems for differential equations that incorporate both ordinary and fractional derivatives, specifically within the context of non-autonomous variable order. Unlike traditional methods in the literature, which often rely on generalized intervals and piecewise constant functions, we propose a new fractional operator better suited for this problem. We analyze the existence and uniqueness of solutions, establishing the conditions necessary for these properties to hold using the Krasnoselskii fixed-point theorem and Banach’s contraction principle. Our study also addresses the Ulam–Hyers stability of the proposed problems, examining how variations in boundary conditions influence the solution dynamics. To support our theoretical framework, we provide numerical examples that not only validate our findings but also demonstrate the practical applicability of these mixed derivative equations across various scientific domains. Additionally, concepts such as symmetry may offer further insights into the behavior of solutions. This research contributes to a deeper understanding of complex differential equations and their implications in real-world scenarios.
Quality of Experience-Oriented Cloud-Edge Dynamic Adaptive Streaming: Recent Advances, Challenges, and Opportunities
Authors: Wang Wei , Wei Xuekai , Tao Wei , Zhou Mingliang , Ji Cheng
Published: January 2025

The widespread adoption of dynamic adaptive streaming (DAS) has revolutionized the delivery of high-quality internet multimedia content by enabling dynamic streaming quality adjustments based on network conditions and playback capabilities. While numerous reviews have explored DAS technologies, this study differentiates itself by focusing on Quality of Experience (QoE)-oriented optimization in cloud-edge collaborative environments. Traditional DAS optimization often overlooks the asymmetry between cloud and edge nodes, where edge resources are typically constrained. This review emphasizes the importance of dynamic task and traffic allocation between cloud and edge nodes to optimize resource utilization and maintain system efficiency, ultimately improving QoE for end users. This comprehensive analysis explores recent advances in QoE-driven DAS optimization strategies, including streaming models, implementation mechanisms, and the integration of machine learning (ML) techniques. By contrasting ML-based DAS approaches with traditional methods, this study highlights the added value of intelligent algorithms in addressing modern streaming challenges. Furthermore, the review identifies emerging research directions, such as adaptive resource allocation and hybrid cloud-edge solutions, and underscores potential application areas for DAS in evolving multimedia systems. With the aim of serving as a valuable resource for researchers, practitioners, and decision-makers in addressing the challenges of resource-constrained edge environments and the need for QoE-centric solutions, this comprehensive analysis endeavors to promote the development, implementation, and application of DAS optimization. Acknowledging the crucial role of DAS optimization in improving the overall QoE for the end users, we hope to facilitate the continued advancement of video streaming experiences in the cloud-edge collaborated environment.
On the Distribution of the Random Sum and Linear Combination of Independent Exponentiated Exponential Random Variables
Authors: Abd El-Raheem Abd El-Raheem M. , Hosny Mona
Published: January 2025

The exponentiated exponential distribution has received great attention from many statisticians due to its popularity, many applications, and the fact that it is an efficient alternative to many famous distributions such as Weibull and gamma distributions. Many statisticians have studied the mathematical properties of this distribution and estimated its parameters under different censoring schemes. However, it seems that the distribution of the random sum, the distribution of the linear combination, and the value of the reliability index, R=P(X2<X1), in the case of unequal scale parameters, were not known for this distribution. Therefore, in this article, we present the saddlepoint approximation to the distribution of the random sum, the distribution of linear combination, and the value of the reliability index R=P(X2<X1) for exponentiated exponential variates. These saddlepoint approximations are computationally appealing, and numerical studies confirm their accuracy. In addition to the accuracy provided by the saddlepoint approximation method, it saves time compared to the simulation method, which requires a lot of time. Therefore, the saddlepoint approximation method provides an outstanding balance between precision and computational efficiency.
Integrated Metabolomic and Transcriptomic Analysis Revealed the Mechanism of BHPF Exposure in Endometrium
Authors: Tan Xin , Ouyang Nengyong , Wang Wenjun , Qiu Junting
Published: January 2025

Fluorene-9-bisphenol (BHPF) has been increasingly used as a bisphenol A substitute in the synthesis of various products. Previous studies have suggested that BHPF can be released from plastic bottles into drinking water, and BHPF accumulation has been reported to cause various adverse effects in humans. Nevertheless, the impact of BHPF exposure on endometrial epithelial cells remains largely unexplored. Here, we investigated the effects of exposure to different concentrations of BHPF on endometrial cells and used integrated metabolomic and transcriptomic methods to elucidate the underlying molecular mechanisms. Our results revealed significant associations between specific metabolites and genes, indicating that low-concentration exposure to BHPF affects endometrial epithelial cells by targeting pathways related to primary immunodeficiency, in which the key genes are IL7R and PTPRC. High-concentration exposure to BHPF decreased cell viability by regulating the purine metabolism pathway, as well as dysregulating the expression of PGM1, PDE3B, AK9, and ENTPD8. Our study highlights that the health risk of BHPF exposure to endometrial epithelial cells is concentration-dependent and that integrated analysis of metabolomic and transcriptomic data not only revealed the biological effects of BHPF and its underlying mechanisms, but also provided key candidate target genes for further exploration.
Prediction of Individual Halo Concentrations Across Cosmic Time Using Neural Networks
Authors: Zhang Tianchi , Mao Tianxiang , Xu Wenxiao , Li Guan
Published: January 2025

The concentration of dark matter haloes is closely linked to their mass accretion history. We utilize the halo mass accretion histories from large cosmological N-body simulations as inputs for our neural networks, which we train to predict the concentration of individual haloes at a given redshift. The trained model performs effectively in other cosmological simulations, achieving the root mean square error between the actual and predicted concentrations that significantly lower than that of the model by Zhao et al. and Giocoli et al. at any redshift. This model serves as a valuable tool for rapidly predicting halo concentrations at specified redshifts in large cosmological simulations.
Gauge-Invariant Perturbation Theory on the Schwarzschild Background Spacetime Part I: Formulation and Odd-Mode Perturbations
Authors: Nakamura Kouji
Published: January 2025

This article is Part I of our series of full papers on a gauge-invariant “linear” perturbation theory on the Schwarzschild background spacetime which was briefly reported in our short papers by the present author in 2021. We first review our general framework of the gauge-invariant perturbation theory, which can be easily extended to the “higher-order” perturbation theory. When we apply this general framework to perturbations on the Schwarzschild background spacetime, gauge-invariant treatments of l=0,1 mode perturbations are required. On the other hand, in the current consensus on the perturbations of the Schwarzschild spacetime, gauge-invariant treatments for l=0,1 modes are difficult if we keep the reconstruction of the original metric perturbations in our mind. Due to this situation, we propose a strategy of a gauge-invariant treatment of l=0,1 mode perturbations through the decomposition of the metric perturbations by singular harmonic functions at once and the regularization of these singularities through the imposition of the boundary conditions to the Einstein equations. Following this proposal, we derive the linearized Einstein equations for any modes of l≥0 in a gauge-invariant manner. We discuss the solutions to the odd-mode perturbation equations in the linearized Einstein equations and show that these perturbations include the Kerr parameter perturbation in these odd-mode perturbations, which is physically reasonable. In the Part II and Part III papers of this series of papers, we will show that the even-mode solutions to the linearized Einstein equations obtained through our proposal are also physically reasonable. Then, we conclude that our proposal of a gauge-invariant treatment for l=0,1-mode perturbations is also physically reasonable.
Monitoring Urban European Hares (Lepus europaeus Pallas) with Citizen Science and a Thermal Spotter
Authors: Pagh Sussie , Jensen Lasse Lange , Pertoldi Cino , Larsen Hanne Lyngholm
Published: January 2025

Populations of the European hare (Lepus europaeus Pallas) have declined in agricultural areas throughout Europe, primarily due to habitat loss caused by the industrialization of agriculture. The growth of cities displaces native habitats, and a decline in hare densities would be expected also in cities; however, several medium-sized mammals thrive in urban areas. In this study, hares in two Danish cities, Aalborg and Aarhus (approx. 145,000 and 300,000 citizens, respectively), were monitored using a combination of citizen science and a thermal spotter. Citizen reports of hares (in all 1874) were highest in the center of the city (26 to 33 locations per km2). Hare observation densities declined significantly with increasing distance to the center. Breeding hares were recorded in both cities. The thermal spotter proved to be useful to spot hares in the city and it did not draw attention as the spotlights normally used to detect the light reflected from the hares’ eyes. Based on the hares spotted at 12 locations where citizens had reported hares, densities of 40.3 (±10.8 SE) hares per km2 were estimated. The increasing awareness for biodiversity and for not using pesticides in Danish cities allow for wild plants to be established in lawns, which benefits the hares.
A Methodological Approach to Measuring the Impact of TAK-003 for the Prevention of Dengue in Dourados, Brazil: Optimizing Strategies for Public Health
Authors: Ghezzi Benedetta , Valencia Cristina , Dias de Oliveira Roberto , Tsuha Daniel , Lucena Júnior Waldno , Di Pasquale Alberta , Mc Namara Morgan , Senra Juliana , Abud Denise , Croda Julio
Published: January 2025

Background/Objectives: Takeda’s tetravalent dengue vaccine TAK-003 has been approved by the Brazilian regulatory agency ANVISA for dengue disease prevention in individuals aged 4 to 60 years. Dourados, in the state of Mato Grosso do Sul, became the world’s first city to implement a mass vaccination campaign targeting approximately 120,000 individuals. An ongoing collaborative, observational, population-based study using national surveillance and vaccination data was planned to measure the impact of the vaccine on the reduction in dengue incidence. Methods: In this manuscript, the study’s methodology, including its programmatic steps and public health relevance, is described. A collaborative assessment with multidisciplinary researchers in Brazil was conducted to identify key programmatic areas for the successful implementation of the study. These areas included feasibility and site selection assessment, methodology selection, vaccination program implementation, and public health importance. Results/Conclusions: Identification of the public health problem and understanding the disease burden, local healthcare infrastructure, and strategic partnerships were critical for a robust feasibility assessment. One of the feasibility criteria identified was the ability of the Dourados Municipal Health Secretary and the principal investigator to conduct an active vaccination campaign, utilizing extramural activities and diverse communication channels to increase vaccine acceptance and coverage. The selection of analytical methods, such as time series analysis, was dependent on the national and local structures of the databases and data availability.
Assessment of Groundwater (Main Usable Aquifer) Vulnerability to Seawater Intrusion in the Polish Baltic Coastal Region
Authors: Winid Bogumiła , Maruta Michał
Published: January 2025

The inflow of saline water reduces water quality and limits its use as drinking water. The risk of seawater intrusion into groundwater along the Polish coastline was assessed using two methods. The vulnerability method (GALDIT) considered six aquifer parameters. The second method focused exclusively on the chemical parameters of groundwater: EC, seawater mixing index (SMI), rHCO₃/rCl, rNa/rCl, and the concentrations of Cl− and Br. The analysis focused on monitoring results collected from points located within 5 km of the Baltic Sea coastline. Both risk assessment methods used a division into three risk classes (low, moderate, and high), but the results differed between the two approaches. A comparison of the results from both classification methods was conducted, followed by a comprehensive risk assessment integrating the outcomes of both approaches. No straightforward relationship was observed between individual threat assessment parameters and distance from the sea. However, when the overall assessment, incorporating multiple parameters, was considered, such a relationship emerged. The classes of seawater intrusion risk differ in terms of the medians and ranges of individual parameters. Ratios such as rHCO3/rCl, rCa/rMg, and Cl/Br play a significant role in risk assessment, whereas the rNa/rCl ratio has a relatively smaller impact. Seawater intrusion risk should be assessed based on multiple parameters. The highest risk of seawater intrusion occurs within approximately 800 m of the coastline.
Empowering Regional Rainfall-Runoff Modeling Through Encoder–Decoder Based on Convolutional Neural Networks
Authors: Jiang Wei , Dang Xupeng , Zhang Rui
Published: January 2025

Regional rainfall-runoff modeling is a classic and significant research topic in hydrological sciences. Currently, the predominant modeling approach is developing data-driven models. This study proposes a rainfall-runoff model named ED-TimesNet (Encoder–Decoder-based TimesNet), which consists of convolutional neural networks. It transforms a one-dimensional time series into a two-dimensional matrix based on frequency-domain partitioning rules and subsequently employs a two-dimensional visual backbone to learn both local and global features of the hydrological time series. Compared to LSTM-based models and Transformer models, this model learns both intra-period and inter-period variations in hydrological series, simultaneously focusing on the relationships between adjacent and non-adjacent time points. It alleviates the temporal ambiguity problem inherent in attention mechanisms. This research validates the performance of the ED-TimesNet model in regional rainfall-runoff modeling tasks using the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) dataset. The model achieves a median and mean NSE of 0.8049 and 0.7808, respectively, across 448 basins, outperforming the benchmark LSTM, VIC, and mHM models, and achieving comparable performance to the Transformer model. This paper does not address the model’s performance on ungauged basins. The method of predicting runoff based on the periodic features of hydrological data provides a novel perspective for hydrological sciences.
Effect of the Shear Band on Water Migration in the Interface Between Lean Clay and an Engineering Structure: A Case Study of Loess-like Soil in Changchun Area, China
Authors: Wang Boxin , Fu Lanting , Wang Qing , Chen Huie , Feng Xue , Pan Jingjing
Published: January 2025

The entire deformation and overturning of numerous engineering structures commence from the failure of the interface between engineering structures and environmental soils, and the shear band formed by such failure results in variations in the water transfer law within the soil. In this study, a direct shear test was carried out to analyze the alterations in dry density of the soil both inside and outside the shear band before and after the disruption of the interface between lean clay and structure bodies, and the effect of the shear band on water migration in lean clay in the interface area under different shear displacements and normal stress values was examined. A numerical model of water transfer in lean clay with the shear band was constructed to predict the soil water distribution in the interfacial band across various temporal and spatial conditions. The results indicated that the existence of the shear band in the interface delayed the water migration; shear displacement and normal stress substantially affected the rate of water migration and volumetric water content in the interface region. The established water migration model could effectively simulate the migration patterns of water in the interface region and model the entire process of changes in free water in the soil under different spatial and temporal conditions. The research findings can provide a reference for the evaluation of structural permeability stability in hydraulic engineering.
Organization of provision of primary health care to the population of the Syzran district at medical outpatient clinics, paramedic-obstetric stations, offices of general doctors
Authors:   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital», Bykova O. A.
Published: January 2025

Thanks to the regional program for modernization of primary healthcare in the Samara region
for 2021–2025, implemented within the framework of the national project «Healthcare» initiated by the
President of the Russian Federation Vladimir Putin, six new modular paramedic-obstetric stations and
one medical outpatient clinic have opened their doors in the Syzran district.