bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy-Efficient and Robust QoS Control for Wireless Sensor Networks Using the Extended Gur Game
Authors: Zhong Xiaoyang , Liang Yao , Li Yimei
Published: January 2025

Outdoor wireless sensor networks (WSNs) operate autonomously in dynamic and unattended real-world environments, where sensor nodes are typically powered by their batteries. In hash outdoor settings, such as mountainous regions or underwater locations, recharging or replacing sensor node batteries is particularly challenging. For these WSN deployments, ensuring quality of service (QoS) control while conserving energy is crucial. This paper presents a novel QoS control algorithm for WSNs, built on extensions to the Gur game framework. The proposed approach not only enhances QoS performance compared to existing Gur game-based WSN control algorithms but also addresses their fundamental energy consumption challenges, enabling sustainable communication and extended network lifetimes. We evaluate the approach through comprehensive TinyOS-based WSN simulations and comparisons with existing algorithms. The results demonstrate that our approach, referred to as the robust Gur game, significantly enhances QoS control and achieves a 27.33% improvement in energy efficiency over the original Gur game and shuffle algorithms, showcasing the significant benefits of the proposed method.
A Discussion on Sensitivity Optimization in Reflective-Mode Phase-Variation Permittivity Sensors Based on Semi-Lumped Resonators
Authors: Su Lijuan , Vélez Paris , Casacuberta Pau , Canalias Xavier , Kurniawati Nazmia , Martín Ferran
Published: January 2025

Typically, the operating frequency in single-frequency reflective-mode phase-variation permittivity sensors based on semi-lumped resonators (e.g., step-impedance resonators—SIRs) is set to the resonance frequency of the sensing resonator when it is loaded with the so-called reference (REF) material, f0,REF. For the case of an SIR-based sensor, if the ratio between the inductance and the capacitance is high (corresponding to a high-Q resonator), the sensitivity in the limit of small perturbations of the dielectric constant (in the vicinity of that of the REF material) is also high. However, the optimum frequency for sensitivity optimization in the limit of small perturbations neither corresponds to the resonance frequency nor coincides with the frequency of maximum phase slope. Such frequencies are calculated in this paper, and it is shown that the optimum frequency for sensitivity optimization is located between the frequency of maximum phase slope and the resonance frequency, although such frequencies tend to coincide for high-Q sensing resonators. This aspect is validated in this paper from electromagnetic simulation and experiment.
Comparison of Total Hemispherical Reflectance and Emittance Values Between Metformin Extended-Release Tablets Stored Under Ambient and Stress Conditions
Authors: Sarecka-Hujar Beata , Meisner Michał
Published: January 2025

Type 2 diabetes is a serious health problem worldwide. Metformin as the first-line drug in diabetes treatment mainly inhibits glucose production in the liver. Diabetes is often accompanied by other diseases, so patients may take many medications at the same time and have trouble controlling the therapy. This, in turn, may result in medications being stored in different, sometimes random places in the patient’s home where elevated temperatures or long-term exposure to solar radiation are possible. In this study, we aimed to analyze whether the total hemispherical reflectance and emittance values of metformin extended-release tablets would distinguish tablets stored correctly from those stored inconsistently with the manufacturer’s recommendations. Unexpired and expired extended-release tablets containing 750 mg metformin were tested. Unexpired tablets were analyzed in two ways i.e., 15 randomly selected tablets were stored as recommended (day 0), and the 15 next tablets in the blister were stored on a windowsill, where they were exposed to daylight for several hours during the day in mid-spring 2024 for 20 days (day 20). Total hemispherical reflectance (THR) was measured within seven spectral ranges from 335 nm to 2500 nm with a 410-Solar Reflectometer while emittance was analyzed within six spectral infrared ranges from 1500 nm to 21 microns with an ET 100 emissometer. The day 0 tablets showed the highest THR values in five spectral ranges from 400 to 1700 nm compared to expired and day 20 tablets. In the further infrared ranges, from 1.5 to 21 microns, unexpired tablets on day 0 had the lowest reflectance compared to day 20 tablets and expired tablets. This means that a greater amount of IR beam was absorbed by this type of tablet. Therefore, higher emittance was demonstrated by day 0 tablets than by other analyzed tablets. In addition, the emittance values for day 0 tablets decreased with increasing temperature. In conclusion, the storage of metformin extended-release tablets under unfavorable conditions may affect the physical structure of this drug form, which is manifested by changes in the reflectance and directional and hemispherical thermal emittance.
Enhanced Pure Pursuit Path Tracking Algorithm for Mobile Robots Optimized by NSGA-II with High-Precision GNSS Navigation
Authors: Jiang Xiongwen , Kuroiwa Taiga , Cao Yu , Sun Linfeng , Zhang Haohao , Kawaguchi Takahiro , Hashimoto Seiji
Published: January 2025

With the rapid development of automation and intelligent technology, mobile robots have shown wide application potential in many fields, and accurate navigation systems are the key to robots completing tasks. This paper proposes an enhanced pure pursuit path tracking algorithm for mobile robots, which is optimized using NSGA-II, with high-precision GNSS navigation for accurate positioning. The improved algorithm considers the dynamic characteristics and real–world operating conditions of the robot, optimizing steering decisions to enhance path tracking accuracy. Experimental results demonstrate the effectiveness of the algorithm: with a look–ahead distance of 0.5 and a maximum linear velocity of 3, the average absolute pose error (APE) is reduced by 14.63%, while a velocity of 4 reduces the APE by 55.94%. The enhanced algorithm significantly reduces path deviation and improves navigation performance.
PPBI: Pose-Guided Partial-Attention Network with Batch Information for Occluded Person Re-Identification
Authors: Cui Jianhai , Chen Yiping , Deng Binbin , Liu Guisong , Wang Zhiguo , Li Ye
Published: January 2025

Occludedperson re-identification (ReID) tasks pose a significant challenge in matching occluded pedestrians to their holistic counterparts across diverse camera views and scenarios. Robust representational learning is crucial in this context, given the unique challenges introduced by occlusions. Firstly, occlusions often result in missing or distorted appearance information, making accurate feature extraction difficult. Secondly, most existing methods focus on learning representations from isolated images, overlooking the potential relational information within image batches. To address these challenges, we propose a pose-guided partial-attention network with batch information (PPBI), designed to enhance both spatial and relational learning for occluded ReID tasks. PPBI includes two core components: (1) A node optimization network (NON) that refines the relationships between key-point nodes of a pedestrian to better address occlusion-induced inconsistencies. (2) A key-point batch attention (KBA) module that explicitly models inter-image interactions across batches to mitigate occlusion effects. Additionally, we introduce a correction of hard mining (CHM) module to handle occlusion-related misclassification and a batch enhancement (BE) model to strengthen key-point attention across image batches. Extensive experiments on occluded and holistic ReID tasks validate the effectiveness of PPBI. Our framework achieves a 2.7% mAP improvement over HoNeT on the Occluded-Duke dataset, demonstrating its robust performance.
MonoDFNet: Monocular 3D Object Detection with Depth Fusion and Adaptive Optimization
Authors: Gao Yuhan , Wang Peng , Li Xiaoyan , Sun Mengyu , Di Ruohai , Li Liangliang , Hong Wei
Published: January 2025

Monocular 3D object detection refers to detecting 3D objects using a single camera. This approach offers low sensor costs, high resolution, and rich texture information, making it widely adopted. However, monocular sensors face challenges from environmental factors like occlusion and truncation, leading to reduced detection accuracy. Additionally, the lack of depth information poses significant challenges for predicting 3D positions. To address these issues, this paper presents a monocular 3D object detection method based on improvements to MonoCD, designed to enhance detection accuracy and robustness in complex environments. In order to effectively obtain and integrate depth information, this paper designs a multi-branch depth prediction with weight sharing module. Furthermore, an adaptive focus mechanism is proposed to emphasize target regions while minimizing interference from irrelevant areas. The experimental results demonstrate that MonoDFNet achieves significant improvements over existing methods, with AP3D gains of +4.09% (Easy), +2.78% (Moderate), and +1.63% (Hard), confirming its effectiveness in 3D object detection.
Transformer-Driven Affective State Recognition from Wearable Physiological Data in Everyday Contexts
Authors: Li Fang , Zhang Dan
Published: January 2025

The rapid advancement in wearable physiological measurement technology in recent years has brought affective computing closer to everyday life scenarios. Recognizing affective states in daily contexts holds significant potential for applications in human–computer interaction and psychiatry. Addressing the challenge of long-term, multi-modal physiological data in everyday settings, this study introduces a Transformer-based algorithm for affective state recognition, designed to fully exploit the temporal characteristics of signals and the interrelationships between different modalities. Utilizing the DAPPER dataset, which comprises continuous 5-day wrist-worn recordings of heart rate, skin conductance, and tri-axial acceleration from 88 subjects, our Transformer-based model achieved an average binary classification accuracy of 71.5% for self-reported positive or negative affective state sampled at random moments during daily data collection, and 60.29% and 61.55% for the five-class classification based on valence and arousal scores. The results of this study demonstrate the feasibility of applying affective state recognition based on wearable multi-modal physiological signals in everyday contexts.
Considerations on UAS-Based In Situ Weather Sensing in Winter Precipitation Environments
Authors: Azevedo Gustavo Britto Hupsel de , Avery Alyssa , Schvartzman David , Landolt Scott , DiVito Stephanie , Revard Braydon , Jacob Jamey D.
Published: January 2025

Freezing rain and freezing drizzle can produce nearly undetectable hazards, with potentially catastrophic consequences for aircraft within low altitudes (e.g., the terminal area). However, the lack of direct observations of the low-altitude freezing precipitation environment creates a challenge for forecasters, flight crews, dispatchers, and air traffic controllers. This research demonstrates how unmanned aerial vehicles (UAVs) can be designed and instrumented to create unmanned aerial weather measurement systems (WxUAS) capable of characterizing the low-altitude freezing precipitation environment and providing insight into the mechanisms that govern it. In this article, we discuss the design considerations for WxUAS-based in situ sampling during active precipitation. We present results from controlled experiments at the Oklahoma Mesonet’s calibration laboratory as well as results from intercomparison studies with collocated well-established ground-based instruments in Oklahoma and Colorado. Additionally, we explore the insights provided by high-resolution thermodynamic and cloud droplet size distribution profiles and their potential contributions to a better understanding of the low-altitude freezing precipitation environment.
Impact of Conservation Agriculture on Soil Quality and Cotton–Maize System Yield in Semi-Arid India
Authors: Nthebere Knight , Tata RamPrakash , Bhimireddy Padmaja , Chandran Latha P. , Gudapati Jayasree , Admala Meena , Sinha Nishant K. , Srikanth Thumma B. , Prasad Kavuru
Published: January 2025

Intensive agriculture is the chief cause of soil degradation, particularly in regions with low soil organic carbon status, such as semi-arid southern India. In the quest to attain sustainable yield and improved soil quality, conservation agriculture (CA) is being advocated and adopted globally, including in India. In this experiment, CA was implemented to investigate the synergistic impacts of tillage and weed management on soil quality index and system yield and to identify a remunerative treatment combination that can sustain system yield and enhance soil quality. Contrasting tillage practices (main plots) included the T1: conventional tillage with cotton–conventional tillage with maize–fallow, i.e., no Sesbania rostrata (Farmers’ practice), T2: conventional tillage with cotton–zero tillage with maize–zero tillage with Sesbania rostrata and T3: zero tillage with cotton + Sesbania rostrata residues–zero tillage with maize + cotton residues–zero tillage with Sesbania rostrata + maize stubbles. Weed management tactics (sub-plots) were W1: chemical weed control, W2: herbicide rotation, W3: integrated weed management and W4: single hand-weeded control in a split-plot design with cotton–maize–Sesbania cropping system over 3 years, in a split-plot design. Principal component analysis (PCA) was performed using the soil quality index (SQI)-CAL Version 1.0 software tool to extract minimum datasets from measured soil properties. A total of 40 soil variables were analyzed at 60 DAS and after the maize harvest, then subjected to principal component analysis (PCA) and subjected to PCA in soil quality index (SQI)-CAL software as to choose variables, minimum dataset and obtain soil quality index. The following soil properties, soil organic carbon (SOC), silt fraction, available soil zinc (Zn), iron (Fe), potassium (K), nitrogen (N), pH, electrical conductivity (EC), soil carbon to nitrogen (C:N) and cation exchange capacity (CEC), were selected as indicators based on correlations, calculated PCA and adept opinions on texture and lime concretions of experimental soil. The soil quality index improved by 23.34% in the T3W4 compared to T1W1. The system yield was 51.79% higher with the adoption of T3W3 compared to T3W4 combinations. Therefore, considering both system yield and soil quality index, T3 and W3 were remunerative and the best treatment combination among all others to sustain both soil and crop productivity in this region.
Thermal Processing Effects on Biomass Ash Utilization for Ceramic Membrane Fabrication
Authors: de Oliveira Heloísa Maria , de Lucena Lira Hélio , de Lima Santana Lisiane Navarro
Published: January 2025

Biomass carbon-rich ash is proposed as a sustainable alternative in the production of ceramic materials. This study investigated this waste product, combined with kaolin and alumina for the production of ceramic membranes. The formulations were defined based on the Al2O3-SiO2-MgO ternary diagram with 51 wt% biomass ash, 36 wt% kaolin, and 13 wt% alumina. The shaping of the green body samples was conducted by using the uniaxial pressing method at 40 MPa and sintering at temperatures ranging from 1050 to 1150 °C. Several properties, such as morphology, porosity, pore diameter, mechanical strength, and chemical resistance, were investigated. It was revealed that the increase in temperature occasioned decreased porosity and water absorption; conversely, it increased bulk density, pore size, diametrical shrinkage, and flexural strength. Moreover, the samples demonstrated minimal weight loss (<0.6 wt.%) in acidic and basic solutions. The samples with porosity ranging from 31.5% to 44.4%, pore size from 1.0 μm to 1.5 μm, and flexural resistance from 9.0 MPa to 21.0 MPa were tested for pure water flux at 1.0 bar and an enhanced flux at a higher temperature, attributed to increased pore size resulting from higher sintering temperatures, was observed. The best-performing sample was sintered at 1050 °C with an average flux of 1716.8 L.h−1.m−2. Also, according to TGA/DTA data, these membranes have greater stability. These membranes are suitable for the treatment of effluents and contribute to reducing environmental impact and increasing sustainability by promoting the efficient utilization of resources.
Compliance with COVID-19 Regulations in Cities vs. Suburbs: The Role of Communities’ Forms of Capital in Communities’ Health Sustainability
Authors: Israel Emil , Feder Tal
Published: January 2025

Urban areas are regarded as a sustainable form of settlement, while the planned and built environments of cities are considered essential for the development of healthier communities. Nonetheless, urban sprawl has caused disparities in the health of those living in cities vs. suburbs. One explanation for this disparity is the willingness of residents to comply with the recommendations and instructions of health care experts or public directives. Compliance is an essential part of what makes communities resilient. However, we know little about the factors that influence this compliance. To fill this gap, we examined data from Israeli municipalities in cities and suburbs about compliance with the government’s COVID-19 regulations. We investigated whether social and physical aspects of cities and suburbs explain differences in compliance. We researched how the residents’ economic, social, and cultural capital, as well as their spatial distribution, influenced their compliance during the pandemic. The results demonstrate the important role of the spatial distribution of these various forms of capital in the residents’ compliance. Specifically, those living in suburban areas benefited from their capital accumulation, making them more inclined to adhere to the health regulations. This new perspective on the dynamics between cities and suburbs may strengthen community resilience and help mitigate regional disparities.
Building a Sustainable Future: The Nexus Between Artificial Intelligence, Renewable Energy, Green Human Capital, Geopolitical Risk, and Carbon Emissions Through the Moderating Role of Institutional Quality
Authors: Iqbal Amir , Zhang Wei , Jahangir Sayeda
Published: January 2025

Countries worldwide are focusing on energy efficiency, economic sustainability, and responsible resource management to address climate change and meet sustainable development goals (SDGs). This study investigates how factors such as artificial intelligence, renewable energy, green human capital, geopolitical risk, natural resource rent, and information and communication technology influenced CO2 emissions in 36 countries between 2000 and 2021. The study also explores how institutional quality moderates these relationships. We employed advanced econometric techniques to address this gap, including panel-correlated standard errors (PCSE) and the Driscoll–Kraay estimations (DKSE) models. A two-step system GMM approach was also used to strengthen the robustness of our findings. The findings reveal that green human capital, renewable energy consumption, and institutional quality can significantly reduce CO2 emissions. Conversely, artificial intelligence, geopolitical risk, natural resource rent, and information communication technology contribute to increased CO2 emissions. Institutional quality enhances the positive impact of green human capital and renewable energy on emission reduction. However, it has the opposite effect on artificial intelligence, leading to an even greater increase in CO2 emissions. These findings underscore the importance of green policies in achieving sustainable development goals. We recommend that policymakers prioritize investing in clean energy and green human capital while strengthening institutional quality to effectively mitigate carbon emissions and meet SDGs. They also regulate AI and ICT carbon footprints and address geopolitical risks through energy diversification and international cooperation.
Evaluating China’s New Energy Vehicle Policy Networks: A Social Network Analysis of Policy Coordination and Market Impact
Authors: Wang Chunning , Yin Yifen , Hu Haoqian , Yu Yuanyuan
Published: January 2025

Since 2015, China has witnessed a rapid increase in new energy vehicle (NEV) market penetration, achieving global leadership in this sector. This study employs social network analysis (SNA) and Granger causality tests to examine how policy coordination has influenced China’s NEV market development from 2015 to 2023. We evaluated policy coordination using six network metrics: network density, average path length, transitivity, average clustering coefficient, number of components, and size of largest component. Our findings reveal both correlative and causal relationships between policy coordination and market performance. The analysis demonstrated strong positive correlations between network metrics and market performance indicators (ρ = 0.800–0.850, p < 0.01), while Granger causality tests identified significant temporal effects, particularly in the long term (F = 284.051–281,486.748, p < 0.001). Notably, the largest component size shows immediate causal effects on market performance (F = 4.152, p < 0.05). Based on these results, we recommend establishing a multi-level policy coordination system, optimizing the policy network structure with emphasis on core components, implementing dynamic policy adjustment mechanisms considering time-lagged effects, and strengthening collaborative supervision of policy implementation to further advance China’s NEV market development.
Estimation of the Water Footprint of Wood Construction in Chile Using a Streamlined Input–Output-Based Model
Authors: Vallejos Ximena , Hidalgo Steven , González Belén , Neumann Patricio
Published: January 2025

Wood construction is often proposed to reduce the construction sector’s greenhouse gas emissions due to its carbon sequestration potential. However, forestry significantly impacts natural water flows and increases water use—a critical concern in Chile. This study evaluates the water footprint of wood construction in Chile, considering direct and indirect water consumption under various scenarios. An input–output model was developed to quantify economic interactions, incorporating a new wood-construction sector based on data from a model house. An environmental extension matrix was also created to account for blue water (groundwater and surface water extraction) and green water (rainwater absorbed from soil) consumption. Future scenarios for the residential building sector were defined based on different growth rates for wood-based construction and current construction methods, and the model was resolved using the scenarios as demand vectors. The results indicate that wood construction’s water footprint is 2.38–2.47 times higher than conventional construction methods, with over 64% linked to forestry’s green water demand. By 2050, increased wood construction could raise the sector’s total water footprint by 30.0–31.8%. These findings underscore the need to assess water consumption as a critical sustainability parameter for wood construction and highlight the value of tools like the water footprint to guide decision-making.
Energy–Carbon Coupling Modeling of Integrated Energy Systems in Low-Carbon Parks
Authors: Wu Kaibin , Qiu Zejing , Yue Mengmeng , Zhang Xudong , Shao Deyi , Li Jingsheng , Li Hongru
Published: January 2025

In integrated energy system modeling, extant research predominantly addresses single-energy system optimization or carbon emission flow models, failing to adequately elucidate the mechanisms of combined energy and carbon flow modeling in complex energy systems. This deficiency hampers a thorough analysis of the coupling relationships between energy and carbon flows, thereby posing significant challenges for resource allocation and carbon mitigation within integrated energy systems. This paper presents an innovative energy–carbon coupling model, constructing a unified framework for energy and carbon flow modeling centered on the energy hub, thereby overcoming the limitations of traditional approaches that are unable to model both energy and carbon flows concurrently. The model comprehensively examines the coupling nodes and carbon density correlations among energy conversion devices within multi-energy systems, precisely quantifying carbon emission paths and distribution across devices. This provides a novel methodology for carbon emission management in integrated energy systems. Case studies on typical integrated energy systems demonstrate the proposed model’s efficacy in low-carbon economic dispatch. The energy–carbon coupling model developed in this study offers a high-adaptability solution for integrated energy systems in multi-energy, low-carbon parks, achieving an optimal balance between economic efficiency and environmental performance under dual objectives of energy demand and carbon emission minimization.
The Impact of Exogenous Variables on Soybean Freight: A Machine Learning Analysis
Authors: Marsola Karina Braga , Oliveira Andréa Leda Ramos de , Utino Matheus Yasuo Ribeiro , Mann Paulo , Conceição Thayane Caroline Oliveira da
Published: January 2025

Predicting road freight prices is a challenging task influenced by multiple factors. Understanding which variables have the greatest impact is essential for building more accurate models, and consequently for enhancing the competitiveness of Brazilian soybeans in the global market. This study aims to evaluate the influence of different exogenous variables on soybean freight prices and to analyze how this influence varies across different distance ranges. To achieve this, a combination of machine learning techniques was applied to a comprehensive dataset containing information on freight costs, regional characteristics, production, fuel prices, storage, and commercialization. The results indicate that distance is the most significant variable in determining freight costs, directly reflecting operational expenses such as fuel consumption and labor costs. Additionally, macroeconomic factors such as the exchange rate and export volume play a crucial role, highlighting the global context of Brazil’s soybean exports. Stratified analysis by distance ranges reveals distinct patterns; short-distance freight is predominantly related to domestic markets, while medium- and long-distance freight are strongly linked to export logistics.
Stimulating Engineering Students’ Potential for Sustainable Development
Authors: Nakad Mantoura , Gardelle Linda , Abboud Rami J.
Published: January 2025

Engineers can play a critical role in achieving sustainable development (SD). Despite this, there is a lack of specialized courses delivered in the undergraduate engineering curricula in Lebanon. The purpose of this study is to assess the outcomes of a newly developed core course on sustainability for engineering students integrated into the undergraduate engineering curriculum at one university in Lebanon. The study makes an original contribution as no similar course, in its current structure, has been found in the existing literature. A quantitative methodology was employed through a survey administered to the students both before and after course delivery. The survey aimed to assess the effectiveness of the course in changing students’ awareness, perceptions, practices, and views on the engineering profession and how it relates to sustainability. The findings indicate that the course has significantly enhanced the understanding and awareness of the engineering students regarding sustainable development. This enhancement impacted positively on their perceptions, practices, and views regarding the importance of sustainable development in engineering education. This study presents an interdisciplinary course integrated into the engineering curriculum and augmented the students’ awareness and knowledge on how to incorporate sustainable development into their design processes.
Satisfaction-Based Optimal Lane Change Modelling of Mixed Traffic Flow and Intersection Vehicle Guidance Control Method in an Intelligent and Connected Environment
Authors: Dong Luxi , Xie Xiaolan , Zhang Lieping , Cheng Xiaohui , Qiu Bin
Published: January 2025

The information interaction characteristics of connected vehicles are distinct from those of non-connected vehicles, thereby exerting an influence on the conventional traffic flow model. The original lane-changing model for non-connected vehicles is no longer applicable in the context of the new traffic flow environment. The modelling of the new hybrid traffic flow, comprising both connected and ordinary vehicles, is set to be a pivotal research topic in the coming years. The objective of this paper is to present a methodology for optimal mixed traffic flow dynamic modelling and cooperative control in intelligent and connected environments (ICE). The study utilizes the real-time perception and information interaction of connected vehicles for traffic information, taking into account the access characteristics of both connected and non-connected vehicles. The satisfaction-based free lane-changing and mandatory lane-changing models of connected vehicles are designed. Secondly, a mixed traffic flow lane-changing model based on influence characteristics is constructed for the influence area of connected vehicles. This model takes into account the degree of influence that connected vehicles have on non-connected vehicles, with different distances being considered respectively. Subsequently, a vehicle guidance strategy for mixed traffic flows comprising grid-connected and conventional vehicles is proposed. A variety of speed guidance scenarios are considered, with an in-depth analysis of the speed optimization of connected vehicles and the movement law of non-connected vehicles. This comprehensive analysis forms the foundation for the development of a vehicle guidance strategy for mixed traffic flows, with the overarching objective being to minimize the average delay of vehicles. In order to evaluate the effectiveness of the proposed method, the intersection of Gaota Road and Fangshui North Street in Yanqing District, Beijing, has been selected for analysis. The results of the study demonstrate that by modifying the density of the mixed traffic flow, the overall average speed of the mixed traffic flow declines as the density of vehicles increases. The findings reported in this study reflect the role of connected vehicles in enhancing road capacity, maximizing intersection capacity and mitigating the occurrence of queuing phenomena, and improving travel speed through the mixed traffic flow lane-changing model based on impact characteristics. This study also provides some guidance for future control of the mixed traffic flow formed by emergency vehicles and social vehicles and for realizing a smart city.
Enhancing Utilization of Municipal Solid Waste Bottom Ash by the Stabilization of Heavy Metals
Authors: Kokalj Filip , Alivojvodić Vesna , Lešnik Luka , Petronijević Nela , Radovanović Dragana , Samec Niko
Published: January 2025

Waste-to-energy (WtE) is a key part of modern waste management. In the European Union, approximately 500 WtE plants process more than 100 million tons of waste yearly, while globally, more than 2700 plants handle over 500 million tons. Roughly 20% of the waste processed is bottom ash (BA). However, this ash can contain heavy metals in concentrations that may render it hazardous. This paper presents a study focusing on stabilizing municipal solid waste incineration BA using simple and industrially viable treatments. The Slovenian WtE plant operator wishes to install the stabilization process; thus, the samples obtained from the plant were treated (1) with a CO2 gas flow, (2) with water spraying, and (3) with a combination of water spraying and a CO2 gas flow under laboratory conditions. Thermodynamic calculations were applied to define potential reactions during the treatment processes in the temperature range from 0 to 100 °C and to define the equilibrium composition of the treated ash with additions of CO2 and water. The standard leaching test EN 12457-4 of treated ash shows a reduction of over 40% in barium concentration and over 30% in lead concentration in leachates.
Paralytic Shellfish Toxin Concentrations Measured in Alaskan Arctic Clams Using ELISA and HPLC Methods
Authors: Charapata Patrick , Bowers Emily K. , Hardison Donnie Ransom , Kibler Steve , Anderson Donald M. , Fachon Evangeline , Lefebvre Kathi A.
Published: January 2025

Clams are efficient vectors of potent algal neurotoxins, a suite of saxitoxin (STX) congeners collectively called paralytic shellfish toxins (PSTs), to higher trophic levels. The Alaskan Arctic is a region facing an expanding threat from PSTs due to ocean warming, yet little is known about PSTs in clams from this region. Quantifying total toxicity in bivalves requires analytical techniques, such as high-performance liquid chromatography (HPLC). Enzyme-linked immunosorbent assays (ELISAs) are an efficient but only semi-quantitative method for measuring clam toxicity. PSTs (STX eq.) were measured in split clam samples (n = 16) from the Alaskan Arctic using ELISA and HPLC methods to develop a preliminary linear model for conservatively estimating total toxicity in clams from ELISA toxin values (R2adj = 0.95, p < 0.001). Profiles of PST congeners and total toxicity using HPLC were also assessed in additional clams (n = 36 additional, n = 52 total). Clams contained mostly potent PST congeners, and over half of the clams had PST concentrations above the seafood regulatory limit. These data will help assess the exposure risks of PSTs in Arctic marine food webs, as harmful algal bloom activity is predicted to increase as the Arctic continues to warm.
Vertical and Horizontal Transmission of Neosporosis in Three Consecutive Pregnancies of Naturally Infected Pregnant Cows and the Effect of Vaccination on Abortion Rates
Authors: Tirosh-Levy Sharon , Blinder Elena , Yasur-Landau Daniel , Lavon Yaniv , Doekes Jacob Joost , Mazuz Monica L.
Published: January 2025

Background/Objectives:Neosporosis is a major cause of abortions in cattle worldwide. Primary results showed that the administration of a live attenuated vaccine during the mid-pregnancy stage of naturally infected cows may assist in preventing abortions. In this study, the effect of vaccination was evaluated in five dairy herds, with a follow-up of three consecutive pregnancies and re-vaccination during the subsequent pregnancies of some of the cows. Methods: A total of 1059 heifers were serologically tested during their first pregnancy, and 260 and 21 of them were re-tested during their second and third pregnancies. Vaccination was administered to 193 of 420 cows with antibody titers of 1:800 or higher, and 23 of them were re-vaccinated. Data were collected regarding the outcome of each pregnancy, the number of inseminations required and removal from the herd. Vertical transmission was evaluated in 136 pre-colostral calves born from 29 vaccinated and 107 unvaccinated dams. Results: The total seroprevalence using a cutoff titer of 1:800 was 33.1, 36.5 and 85.7% during the three consecutive pregnancies. The antibody titers of individual cows fluctuated over time. Abortion rates and the rate of removal from the herd were significantly higher in seropositive cows. The rate of vertical transmission increased in correlation with the dam’s antibody titer. Immunization resulted in lower abortion rates at two of the farms. Vaccine efficacy ranged from a negative effect to 54% at different farms, with an overall efficacy of 10.4%. The effect of vaccination on abortions, reproductive performance, antibody titers, vertical transmission and removal from the herd was not significant. Conclusions: These results demonstrate varying vaccine efficacies among farms and suggest that neosporosis is a multifactorial disease that cannot be solely controlled by vaccination.
Developing T Cell Epitope-Based Vaccines Against Infection: Challenging but Worthwhile
Authors: Tang Xian , Zhang Wei , Zhang Zheng
Published: January 2025

T cell epitope-based vaccines are designed to elicit long-lived pathogen-specific memory T cells that can quickly activate protective effector functions in response to subsequent infections. These vaccines have the potential to provide sustained protection against mutated variants, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which are increasingly capable of evading neutralizing antibodies. Recent advancements in epitope discovery, T cell receptor analysis, and bioinformatics have enabled the precise selection of epitopes and the sophisticated design of epitope-based vaccines. This review outlines the development process for T cell epitope-based vaccines. We summarize the current progress in T cell epitope discovery technologies, highlighting the advantages and disadvantages of each method. We also examine advancements in the design and optimization of epitope-based vaccines, particularly through bioinformatics tools. Additionally, we discuss the challenges of validating the accurate processing and presentation of individual epitopes and establishing suitable rodent models to evaluate vaccine immunogenicity and protective efficacy.
Evaluation of Zein Nanoparticles as Delivery Agents of SARS-CoV-2 Antigens
Authors: Márquez-Escobar Verónica Araceli , Alonso-Cerda María José , Rosales-Mendoza Sergio , Betancourt-Mendiola María de Lourdes
Published: January 2025

Background/Objectives: Nanovaccines have significant potential to enhance immunization strategies by improving efficacy, safety, and cost-effectiveness. In particular, organic nanoparticles hold promise for the generation of low-cost nanovaccines obtained by environmentally friendly methods. In this study, the feasibility of using zein nanoparticles (NPs) as carriers for an antigenic peptide (p30) and the receptor binding domain (RBD) from SARS-CoV-2 spike protein was explored. Methods: A synthesis method for zein NPs was established by combining previously reported techniques, and the resulting NPs were characterized in terms of morphology, particle size, polydispersity index (PDI), surface charge, and colloidal stability using dynamic light scattering (DLS) and transmission electron microscopy (TEM). Tween 20 was employed as a surfactant to enhance particle stability and prevent aggregation. Results: The zein NPs were deemed safe based on an in vitro cytotoxicity assay using Vero cells. Immunogenicity assessments demonstrated that zein NPs:p30 and zein NPs:RBD induced IgG responses in test mice, whose magnitude was comparable to those achieved with alum as an adjuvant. Conclusions: These findings support the use of zein NPs as promising vaccine delivery vehicles with adjuvant effects due to their ease and environmentally friendly synthesis, high stability, and low cost.
Luteolin Alleviates Inflammation Induced by Staphylococcus aureus in Bovine Mammary Epithelial Cells by Attenuating NF-κB and MAPK Activation
Authors: Guo Yingfang , Zhang Jinxin , Yuan Ting , Yang Cheng , Zhou Qingqing , Shaukat Aftab , Deng Ganzhen , Wang Xiaoyan
Published: January 2025

The internalization of S. aureus in bMECs is a major pathogenic mechanism leading to mastitis, causing significant economic losses in the dairy industry. Numerous plants contain Lut, a natural flavonoid with anti-inflammatory and antioxidant properties. However, little is known about Lut’s ability to reduce inflammation caused by S. aureus in bMECs. This research aimed to evaluate the mechanism by which Lut reduces S. aureus-induced inflammation in bMECs. Through GO and KEGG enrichment analysis, researchers analyzed the differentially expressed genes in bMECs infected with S. aureus in NCBI GEO (GSE139612) and also analyzed the targets of Lut predicted by various online platforms. These studies identified two overlapping signaling pathways, the NF-κB and the MAPK pathways. We stimulated bMECs with S. aureus for two hours and then added Lut for ten hours, with a total duration of twelve hours. The expression levels of TLR2-MyD88-TRAF6 components, inflammatory cytokines, and protein phosphorylation associated with the MAPK and NF-κB signaling pathways were then assessed. Based on all of the results, Lut inhibited the generation of inflammatory cytokines in bMECs that were induced by S. aureus through the TLR2, NF-κB, and MAPK signaling pathways. This process might account for the anti-inflammatory properties of Lut.
The Effect of Maternal Obesity on Placental Autophagy in Lean Breed Sows
Authors: Tian Liang , Su Fen , Zhu Xueyi , Zou Xingyue
Published: January 2025

This study aimed to evaluate the influence of back-fat thickness (BF), at mating of sows, on autophagy in placenta and the potential mechanism. The sows were divided into two groups according to their BF at mating: BFI (15–20 mm, n = 14) and BFII (21–27 mm, n = 14) as the maternal obesity group. The placental samples used for investigating autophagic function and fatty acid profiles were obtained by vaginal delivery. Our results demonstrated that autophagy defects were observed in placenta from BFII sows along with altered circulating and placental fatty acid profiles. Indicative of impaired autophagy, reduced autophagic vesicles as well as LC3-positive puncta were linked to decreased mRNA or protein expression of autophagy-related genes, including ATG5, ATG7, Beclin1, ATG12, LC3, LAMP1 and LAMP2 in the placenta of BFII sows (p < 0.05). Meanwhile, we found reduced conversion of LC3-I to LC3-II and up-regulated protein content of p62 in the placenta from BFII group (p < 0.05). Furthermore, excessive back-fat was also associated with increased activation of AKT/mTOR signaling and decreased mRNA content of transcription factors regulating the autophagic pathway, including PPARα and PGC1α, but increased mRNA expression of NcoR1 in placenta. Together, these findings indicate that maternal obesity incites autophagy injury in pig term placenta, which may contribute to augmented placental lipid accumulation and therefore impaired placental function.
Safe use of fluoride-containing toothpastes for caries prevention in children
Authors: Khamadeeva A. M. , Popov N. V. , Baimuratova L. R. , Kozupitsa G. S. , Petrukhina I. K. , Sazanova K. N. , Nogina N. V. , Marsykaeva D. R.
Published: January 2025

Relevance. Following environmental rehabilitation efforts in Chapayevsk, Samara Region, an increase in the prevalence and severity of dental caries has been observed, particularly among preschool-aged children.

Objective. To evaluate the safety of fluoride use for preventing dental caries in children.

Material and methods. A survey was conducted among 124 parents of children aged 5–6 years attending preschools and 361 adolescents aged 12 and 15 years, using the WHO questionnaire (2013). Responses regarding oral hygiene habits were analyzed. Fluoride ion concentrations were measured in drinking water using the potentiometric method (GOST 4386-89 S.6), in urine according to GOST 8.563-96, and in toothpastes following GOST 7983-2016. The availability and popularity of fluoride-containing toothpastes in pharmacies and supermarkets were also assessed. Statistical analysis was performed using IBM SPSS Statistics v.26 (IBM Corporation).

Results. Over the past 15 years, the fluoride content in drinking water decreased from 0.78–0.91 mg/L to 0.49– 0.71 mg/L following the city’s environmental rehabilitation efforts, remaining suboptimal for caries prevention. Analysis of fluoride excretion via the kidneys indicated low overall fluoride intake from water, toothpaste, and food. A weak correlation was found between the DMFT (decayed, missing, and filled teeth) index and urinary fluoride levels (ρ = 0.35), as well as estimated systemic fluoride levels (ρ = 0.36). These results indicate low fluoride intake, eliminating concerns about toxic effects on health. An analysis of toothpaste preferences showed that the population primarily chooses fluoride-free toothpastes or those with fluoride levels below 1000 ppm. This trend is influenced by the product range available, low adherence to preventive dental care, and misinformation from online sources that often attribute negative effects to fluoridation or raise safety concerns. The actual fluoride content in toothpastes was found to be within acceptable technological limits.
Compte-rendu de la mini-session de la Société Botanique de France au nord du massif des Bauges du 10 au 12 juin 2022
Authors: Rocher Michel , Delahaye Thierry
Published: January 2025

cet article détaille les herborisations menées lors d’une mini-session dans le massif des Bauges, sur les pas d’Octave Meyran (1838-1944), botaniste lyonnais, qui avait parcouru la région en 1889.
Ethnobotanique en Charente-Maritime : quelques plantes d’intérêt.
Authors: Botineau Michel
Published: January 2025

Sont exposées successivement : plantes alimentaires (avec espèces sauvages, espèces d’origine sauvage puis cultivées, espèces cultivées), plantes médicinales, plantes toxiques, plantes utilitaires, plantes diverses, plantes et paysages avec toponymie, enfin quelques noms locaux.
Compte rendu de la mini-session dans l’Aube du 6 au 8 mai 2022
Authors: Lanfant Patrice , Royer Jean-Marie
Published: January 2025

Ce court article décrit les herborisations de la mini-session dans l’Aube de mai 2022.
Cohabitation agriculteurs-éleveurs autour des barrages périurbains à Katiola (centre-nord de la Côte d’Ivoire)
Authors: Koffi Simplice Yao
Published: January 2025

En Côte d’Ivoire, les conflits entre agriculteurs et éleveurs sont fréquents, notamment dans les régions de savanes. Cette étude se concentre sur les conflits autour des barrages périurbains à Katiola, un sujet peu exploré. La recherche révèle que ces espaces sont utilisés par divers acteurs, tels que maraîchers et éleveurs, ce qui génère des tensions. La plupart des conflits sont résolus à l’amiable, mais une sensibilisation est nécessaire pour encourager une utilisation commune et pacifique des barrages.