bluuebunny/crossref_metadata_2025 huggingface dataset:
A Distributed Collaborative Navigation Strategy Based on Adaptive Extended Kalman Filter Integrated Positioning and Model Predictive Control for Global Navigation Satellite System/Inertial Navigation System Dual-Robot
Authors: Chen Wanqiang , Jing Yunpeng , Zhao Shuo , Yan Lei , Liu Quancheng , He Zichang
Published: February 2025

In the field of multi-robot cooperative localization and task planning, traditional filtering algorithms encounter synchronization and consistency issues during multi-source data fusion. These challenges result in cumulative localization errors and inefficient information sharing, which limits the system’s collaborative capabilities and control accuracy. To overcome these limitations, a distributed cooperative navigation strategy is introduced. Initially, a Distributed Adaptive Extended Kalman Filter (DAEKF) is implemented, which adaptively adjusts the noise covariance matrix to effectively manage nonlinearities and multi-source noise conditions. Subsequently, a Distributed Model Predictive Control (DMPC) framework is introduced. This framework predicts and optimizes each robot’s kinematic model, thereby improving the system’s collaborative operations and dynamic decision-making capabilities. Finally, the efficacy of this strategy is confirmed through detailed simulations and robotic experiments. The simulation results for cooperative localization demonstrate that DAEKF outperforms Kalman Filter (KF) and Extended Kalman Filter (EKF) in terms of localization accuracy. In the straight-line path-tracking experiments, DAEKF effectively reduced both lateral and heading errors for both robots. For Robot 1, DAEKF reduced the lateral error Root Mean Squared Error (RMSE) by 68.87%, 27.80%, and 25.76%, compared to No Filtering, KF, and EKF. In heading error, DAEKF reduced the RMSE by 52.29%, 41.89%, and 36.47%. For Robot 2, DAEKF reduced the lateral error RMSE by 51.30%, 22.88%, and 11.60%, compared to No Filtering, KF, and EKF. In heading error, DAEKF reduced the RMSE by 39.55%, 37.15%, and 26.00%. In the curved path-tracking experiments, both robots demonstrated high trajectory conformity while traveling along a predefined path combining straight-line and circular arc segments, with lateral errors in the straight-line segments all below 0.05 m. The strategy proposed in this study significantly enhanced the precision and stability of multi-robot collaborative navigation, demonstrating strong practicality and scalability.
Inverse Synthetic Aperture Radar Image Multi-Modal Zero-Shot Learning Based on the Scattering Center Model and Neighbor-Adapted Locally Linear Embedding
Authors: Jin Xinfei , Li Hongxu , Xu Xinbo , Xu Zihan , Su Fulin
Published: February 2025

Inverse Synthetic Aperture Radar (ISAR) images are extensively used in Radar Automatic Target Recognition (RATR) for non-cooperative targets. However, acquiring training samples for all target categories is challenging. Recognizing target classes without training samples is called Zero-Shot Learning (ZSL). When ZSL involves multiple modalities, it becomes Multi-modal Zero-Shot Learning (MZSL). To achieve MZSL, a framework is proposed for generating ISAR images with optical image aiding. The process begins by extracting edges from optical images to capture the structure of ship targets. These extracted edges are used to estimate the potential locations of the target’s scattering centers. Using the Geometric Theory of Diffraction (GTD)-based scattering center model, the edges’ ISAR images are generated from the scattering centers. Next, a mapping is established between the edges’ ISAR images and the actual ISAR images. Neighbor-Adapted Local Linear Embedding (NALLE) generates pseudo-ISAR images for the unseen classes by combining the edges’ ISAR images with the actual ISAR images from the seen classes. Finally, these pseudo-ISAR images serve as training samples, enabling the recognition of test samples. In contrast to the network-based approaches, this method requires only a limited number of training samples. Experiments based on simulated and measured data validate the effectiveness.
A Dual-Branch U-Net for Staple Crop Classification in Complex Scenes
Authors: Zhang Jiajin , Zhao Lifang , Yang Hua
Published: February 2025

Accurate information on crop planting and spatial distribution is critical for understanding and tracking long-term land use changes. The method of using deep learning (DL) to extract crop information has been applied in large-scale datasets and plain areas. However, current crop classification methods face some challenges, such as poor image time continuity, difficult data acquisition, rugged terrain, fragmented plots, and diverse planting conditions in complex scenes. In this study, we propose the Complex Scene Crop Classification U-Net (CSCCU), which aims to improve the mapping accuracy of staple crops in complex scenes by combining multi-spectral bands with spectral features. CSCCU features a dual-branch structure: the main branch concentrates on image feature extraction, while the auxiliary branch focuses on spectral features. In our method, we use the hierarchical feature-level fusion mechanism. Through the hierarchical feature fusion of the shallow feature fusion module (SFF) and the deep feature fusion module (DFF), feature learning is optimized and model performance is improved. We conducted experiments using GaoFen-2 (GF-2) images in Xiuwen County, Guizhou Province, China, and established a dataset consisting of 1000 image patches of size 256, covering seven categories. In our method, the corn and rice accuracies are 89.72% and 88.61%, and the mean intersection over union (mIoU) is 85.61%, which is higher than the compared models (U-Net, SegNet, and DeepLabv3+). Our method provides a novel solution for the classification of staple crops in complex scenes using high-resolution images, which can help to obtain accurate information on staple crops in larger regions in the future.
Feasibility Study of Photoelectrochemical Sensing of Glucose and Urea Using BiVO4 and BiVO4/BiOCl Photoanodes
Authors: Skruodiene Monika , Kovger-Jarosevic Jelena , Savickaja Irena , Juodkazyte Jurga , Petruleviciene Milda
Published: February 2025

This study investigates the photoelectrochemical (PEC) performance of molybdenum-doped bismuth vanadate (Mo-doped BiVO4) and its heterojunction with the BiOCl layer in glucose and urea sensing. Photoelectrochemical analyses, including cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), revealed that the formation of a heterojunction enhanced charge carrier separation. The impact of the interaction between the surface of the photoanode and analytes on sensing performance was systematically evaluated. Among the tested configurations, Mo-doped BiVO4 exhibited superior glucose sensing with a limit of detection (LOD) of 0.173 µM, while BiVO4/BiOCl demonstrated an LOD of 2.474 µM. In the context of urea sensing, Mo-doped BiVO4 demonstrated an LOD of 0.656 µM, while BiVO4/BiOCl exhibited an LOD of 0.918 µM. Notably, despite the enhanced PEC activity observed in heterostructured samples, Mo-doped BiVO4 exhibited superior sensing performance, attributable to good interaction with analytes. The photocurrent response trends—an increase with glucose concentration and a decrease with urea concentration—were attributed to oxidation and adsorption phenomena on the photoanode surface. These findings underscore the critical role of photoanode surface engineering in advancing PEC sensor technology, paving the way for more efficient environmental and biomedical applications.
Hydrogenated Amorphous Silicon Charge-Selective Contact Devices on a Polyimide Flexible Substrate for Dosimetry and Beam Flux Measurements
Authors: Menichelli Mauro , Aziz Saba , Bashiri Aishah , Bizzarri Marco , Buti Clarissa , Calcagnile Lucio , Calvo Daniela , Caprai Mirco , Caputo Domenico , Caricato Anna Paola , Catalano Roberto , Cazzanelli Massimo , Cirio Roberto , Cirrone Giuseppe Antonio Pablo , Cittadini Federico , Croci Tommaso , Cuttone Giacomo , de Cesare Giampiero , De Remigis Paolo , Dunand Sylvain , Fabi Michele , Frontini Luca , Grimani Catia , Guarrera Mariacristina , Hasnaoui Hamza , Ionica Maria , Kanxheri Keida , Large Matthew , Lenta Francesca , Liberali Valentino , Lovecchio Nicola , Martino Maurizio , Maruccio Giuseppe , Mazza Giovanni , Monteduro Anna Grazia , Morozzi Arianna , Nascetti Augusto , Pallotta Stefania , Papi Andrea , Passeri Daniele , Pedio Maddalena , Petasecca Marco , Petringa Giada , Peverini Francesca , Placidi Pisana , Polo Matteo , Quaranta Alberto , Quarta Gianluca , Rizzato Silvia , Sabbatini Federico , Servoli Leonello , Stabile Alberto , Talamonti Cinzia , Thomet Jonathan Emanuel , Tosti Luca , Mora Monica Setia Vasquez , Villani Mattia , Wheadon Richard James , Wyrsch Nicolas , Zema Nicola
Published: February 2025

Hydrogenated amorphous silicon (a-Si:H) devices on flexible substrates are currently being studied for application in dosimetry and beam flux measurements. The necessity of in vivo dosimetry requires thin devices with maximal transparency and flexibility. For this reason, a thin (<10 µm) a-Si:H device deposited on a thin polyimide sheet is a very valid option for this application. Furthermore, a-Si:H is a material that has an intrinsically high radiation hardness. In order to develop these devices, the HASPIDE (Hydrogenated Amorphous Silicon Pixel Detectors) collaboration has implemented two different device configurations: n-i-p type diodes and charge-selective contact devices.Charge-selective contact-based devices have been studied for solar cell applications and, recently, the above-mentioned collaboration has tested these devices for X-ray dose measurements. In this paper, the HASPIDE collaboration has studied the X-ray and proton response of charge-selective contact devices deposited on Polyimide. The linearity of the photocurrent response to X-ray versus dose-rate has been assessed at various bias voltages. The sensitivity to protons has also been studied at various bias voltages and the wide range linearity has been tested for fluxes in the range from 8.3 × 107 to 2.49 × 1010 p/(cm2 s).
A Framework for Effective Multi-Hazard Risk Assessment in Post-Mining Areas
Authors: Nalmpant-Sarikaki Dafni M. , Theocharis Alexandros I. , Koukouzas Nikolaos C. , Zevgolis Ioannis E.
Published: February 2025

This work presents a structured methodology for multi-hazard risk assessment in post-mining coal areas, addressing the complex interactions between natural, mining, and technological hazards. The methodology provides a flexible, semi-quantitative mixed-methods framework designed to evaluate multi-hazard risk scenarios through a seven-step process, which includes identification of hazards, analysis of hazard interactions, and calculation of the Multi-Hazard Index (MHI), Vulnerability Index (VI), and Multi-Risk Value (MRV). The MHI assesses the cumulative intensity of hazard interactions, while the MRV quantifies the socio-economic impacts of various multi-hazard scenarios. The framework also incorporates vulnerability assessments, using social and physical vulnerability indices, to better understand the potential risks to communities. The methodology aims to enhance the safety of post-mining areas by mitigating the cascading effects of hazard interactions and by systematically increasing the knowledge of hazard interdependencies. This approach is adaptable to diverse post-mining contexts, offering a comprehensive framework for assessing and managing multi-hazard risks. It aligns with the broader objectives of the European Green Deal by promoting sustainable land management and addressing the transition of coal regions toward a carbon-neutral economy. It equips stakeholders with necessary tools to enhance resilience and ensure the long-term socio-economic and environmental stability and safety of post-mining areas.
QTL Identification of Hull Color for Foxtail Millet [Setaria italica (L.) P. Beauv.] Through Four Phenotype Identification Strategies in a RIL Population
Authors: Ma Zhixiu , Chai Shaohua , Wu Yongjiang , Li Yujie , Han Huibing , Song Hui , Gao Jinfeng , Feng Baili , Yang Pu
Published: February 2025

The foxtail millet exhibits a diverse range of hull colors, which are crucial indicators for assessing its nutritional and economic value. However, the molecular regulatory mechanisms that govern the hull color of foxtail millet are largely unknown at present. This gap in knowledge significantly impedes efforts to enhance the quality traits of foxtail millet. This study utilized a population of 250 F6 recombinant inbred lines (RILs) generated from a cross between two foxtail millet varieties: Yugu18 (with light yellow seeds) and Hongjiugu19 (with red seeds). Four methods, the visual grouping method (I), the visual colorimetric method (II), the Lab determination method (III), and the RGB determination method (IV), were employed to determine the hull color of each line across four environments and QTL identification were conducted subsequently. It showed that there were 10, 12, 69 and 56 QTLs were detected for hull color through four methods, and these QTLs were integrated into 4, 6, 27 and 25 unique QTLs, respectively. There were three, four, four and four major QTLs. Of which, three major QTLs (qHC1.1, qHC1.2 and qHC9.3) on chromosomes 1 and 9 could be detected by all 4 methods. qHC9.1 was detected by all four methods except for method I. There were also one, one, seven and four minor identity QTLs identified across the 4 methods. Four minor QTLs (qHC3.1, qHC3.3, qHC4.1 and qHC5.1) can be stably detected only in method III, and two minor QTLs (qHC8.2 and qHC9.2) can be stably detected only in method IV. Generally, method I is fast, efficient and cost-effective, which is suitable for the rapid detection of hull color. Method II is also low-cost; however, it can detect more QTL for hull color, making it suitable for identifying major QTL loci in large populations. Methods III and IV can map more minor QTL and are more accurate in hull color characterization. This study identified four important hull color QTL for foxtail millet, which largely align with those reported in previous research. These findings establish a foundation for characterizing hull color indices and further advancing QTL mapping for grain color.
Experimental Study on Brine Storage for Overwintering by Using Salinity-Gradient Solar Pond in Zabuye Salt Lake, Tibet
Authors: Wu Qian , Wang Yunsheng , Zhang Jintao , Zhang Ke , Li Juntao , He Zhikui , Bu Lingzhong , Yu Jiangjiang , Nie Zhen
Published: February 2025

Known as the “white oil”, lithium is a key raw material to support strategic emerging industries and future industrial development. Zabuye Salt Lake is the only one in Tibet, China that has so far realized the industrialization of lithium extraction from the salt lake brine. The green and low-cost lithium extraction technology by using the salinity-gradient solar pond (SGSP) adopted has always been paid much attention by lithium-related practitioners and researchers. In order to improve the lithium yield and grade of a single crystallization pond, the cross-year brine mixing method can be used to increase the initial temperature and CO32− concentration of the raw brine for making the SGSP. The premise is to ensure that the summer brine with low Li+ and high CO32− prepared in the previous year could be stored safely for overwintering with a minimal change in brine composition, for use in brine mixing in February and March of the next year, which can be realized by using the SGSP. In this paper, two experiments of brine storage for overwintering were carried out in the Zabuye mining area, Tibet in 2020 and 2021 by using the large-scale SGSP with an area of nearly 4000 m2. The results show that during the operation of the SGSP in winter, the brine temperature in the lower convective zone (LCZ) can still rise to more than 20 °C and remain relatively stable, indicating that the coverage of surface ice layer not only has an effect of heat preservation and insulation on the SGSP, but also plays a positive role in the thermal storage capacity of the SGSP. The vertical distributions of brine temperature, density and salinity in the pond showed the ideal gradient curves increasing from top to bottom, and the concentrations of Li+ and CO32− in the brine only decreased slightly. The structure of the salinity-gradient layer tended to stabilize faster when the brine filling depth was larger, but the boundary between the upper convective zone (UCZ) and the non-convective zone (NCZ) was relatively blurred. It is completely feasible to store the brine for overwintering by using the SGSP in the Zabuye mining area, and the experimental results could be directly scalable to larger industrial applications. It can not only provide high-quality raw brine for cross-year brine mixing, but also reduce the pressure of brine production, and a small amount of lithium mixed salt collected is helpful to increase the output of a single crystallization pond. Additionally, the potential challenges of maintaining the SGSP system during extreme winter conditions are described, and effective measures and suggestions are proposed to make the technology feasible in diverse climates.
Analysis of Aging in Spain: Contemporary Sociological and Demographic Implications
Authors: Pérez Fructuoso María José , García Revilla Raquel , Martinez Moure Olga , Cea Moure Ramiro
Published: February 2025

Aging, as a phenomenon of profound social significance, has important repercussions. In this work, which focuses on Spain, aging and population structure indicators are analyzed. This basis for demographic analysis becomes useful later in preparing a sociological essay on the most pressing challenges facing Spanish society concerning population aging. The methodology used, as is usual within the framework of the social sciences, involves a combination of quantitative and qualitative approaches. Specifically, from an eminently quantitative perspective, the important methodological shift of the 2021 Population and Housing Census is considered. It is also considered how the Statistics on Migrations and Changes of Residence emerge with the intention of measuring the migratory phenomenon between two consecutive censuses, as this phenomenon is also of great social significance in our country. The work culminates with a brief sociological interpretation of the challenges facing Spanish society as a consequence of the population dynamics studied.
“They Steal Our Food”: Food Insecurity as a Barrier to Social Cohesion Between Refugee and Host Communities in Uganda
Authors: Nanfuka Esther Kalule , Luwangula Ronald , Ssenfuuma James Thomas , Tibengana Samuel Baker , Canocakacon Jordan , Ndagire Magdalene , Irumba Joseph , Kahuma John-Baptist , Walakira Eddy Joshua
Published: February 2025

Although maintaining social cohesion between refugees and host communities is a major policy goal, due to protracted refugee situations, research on potential barriers is scant, particularly in low- and middle-income countries where a majority of the world’s refugees live. This article provides insights into food insecurity as a barrier to refugee–host community social cohesion in the wake of food aid cuts to refugees globally. We conducted 24 focus group discussions, 3 in-depth interviews, and 8 key informant interviews with refugee and host community members, local leaders, and staff of entities overseeing refugee affairs in two settlements in Southwestern Uganda. We found that refugees experiencing food insecurity and limited coping resources resort to negative and socially unacceptable means, such as theft and aggression, to obtain food. This causes social tensions and social fragmentation that directly contribute to the deterioration of social cohesion by undermining trust, inhibiting cooperation, and weakening the sense of shared purpose between refugees and their host communities. Food insecurity is a significant threat to the social integration of refugees, as it weakens their social connections in the host community. Measures to address food insecurity among refugees are imperative to mitigate its potential deleterious effects on the social integration of refugees in protracted situations.
Natural Resources Management as Drivers of Economic Growth: Fresh Insights from a Time Series Analysis of Saudi Arabia
Authors: Alfalih Abdulaziz A. , Azid Toseef , Jaboob Mohammad , Tahir Muhammad
Published: February 2025

Natural resources management has played an important role in uplifting the growth performance of countries over the years. However, for the Kingdom of Saudi Arabia (KSA), very little is known regarding the influence of natural resources on economic growth. Therefore, this study focused on investigating the relationship between natural resources and economic growth by focusing on the KSA. This study was based on data for the period 1973–2022 analyzed through “Autoregressive Distributed Lag (ARDL)” modeling. To identify the directions of the relationships between the selected variables, the present study carried out causality testing. The findings indicate that natural resources improved the growth of KSA, which was an indication of the “resource blessing” hypothesis. Other variables, such as education, employment, and investment, also contributed positively to the growth of the KSA economy. Surprisingly, openness to trade decelerated the growth performance. In the short run, again, we found a positive impact of natural resources, education, investment, and employment on growth. Finally, openness to trade maintained its negative impact on growth in the short run. The causality analysis displayed both one-way and two-way relationships between the selected variables. This study suggests that KSA authorities must focus on gearing up the process of economic diversification. Moreover, increased investment, both in physical and human capital, is needed to improve and sustain long-term growth.
Ethics as a Missing Link Between Human Happiness and Environmental Sustainability
Authors: Carron Katherine , Lioubimtseva Elena
Published: February 2025

This pilot study examines the complex interplay between human happiness and environmental sustainability through the lens of environmental ethics. Using a mixed-methods approach with surveys and interviews, it investigates how self-reported happiness is related to access to nature, environmental concerns, attitudes towards sustainability, and ethical values. Both surveys and interviews revealed a dominance of biospheric and altruistic ethical values and strong environmental concerns among the participants, often expressed from an anthropocentric perspective. The findings suggest that fostering environmental ethics could bridge the gap between happiness and sustainability. Despite the study limitations, such as geographical constraints and a small survey sample, it contributes a novel framework that can be replicated and adapted for larger-scale cross-cultural studies.
Sustainable Insulating Materials for High-Voltage Equipment: Dielectric Properties of Green Synthesis-Based Nanofluids from Vegetable Oils
Authors: Siddique Abubakar , Shahid Muhammad Usama , Aslam Waseem , Atiq Shahid , Altimania Mohammad R. , Munir Hafiz Mudassir , Zaitsev Ievgen , Kuchanskyy Vladislav
Published: February 2025

This study aimed to develop a cost-effective, environmentally sustainable, and technologically advanced dielectric fluid by utilizing the beneficial properties of natural ester-based vegetable oils, offering a promising alternative for transformer insulation and cooling applications. The novelty of this research lies in the formulation of a nanofluid that combines three distinct vegetable oils—castor, flaxseed, and blackseed—creating a unique base fluid. SiO2 nanoparticles were incorporated into the fluid to leverage their multiple advantageous characteristics. Extensive experiments were conducted to evaluate the superior properties of the proposed nanofluid, focusing on key dielectric properties, such as relative permittivity (εr) and the dielectric dissipation factor (tan δ). Comparative analyses with conventional mineral oil, which was used as a benchmark, demonstrated the significant advantages of the vegetable oil-based nanofluid. The novel formulation outperformed all other tested samples, highlighting its exceptional performance. Additionally, three preparation methods were examined, with the green synthesis technique producing the nanofluid with better dielectric properties. Through a detailed presentation of empirical data and compelling arguments, this study confirms the potential of natural ester-based vegetable oil nanofluids as a highly promising alternative, driven by their intrinsic properties and the environmentally friendly synthesis method employed.
Production Costs and Growth Performance of Tilapia (Oreochromis niloticus) in Intensive Production Systems: A Review
Authors: Rodríguez-Hernández Martha Elena , Martínez-Castellanos Gustavo , López-Méndez María Cristina , Reyes-Gonzalez David , González-Moreno Humberto Raymundo
Published: February 2025

The aquaculture sector is experiencing remarkable growth, and its economic success depends mainly on an efficient production strategy and cost management, which are essential to guarantee the profitability and sustainability in this sector. The main objective of this study was to analyze the production costs and growth performance of Oreochromis niloticus in the most successful intensive production systems: Recirculating Aquaculture System (RAS), Aquaponic System (AS), and Biofloc Technology (BFT). Data collection involved extensive searches in various academic and scientific databases, resulting in the selection of 52 published articles from 2008 to 2024, following a rigorous analysis of inclusion criteria. Results showed that the rentability of the aquaculture production systems for Tilapia production is underexplored in the scientific community, with less than 20% of articles reporting economic variables, while around 80% of them reported growing variables and water quality without considering economic variables. Costs associated with production and economic indicators must also be viewed as important indicators for aquaculture producers as a reference for the investment in RAS, AS, and BFT technologies. The research in the aquaculture field has seen a resurgence in studies on production, design, water quality, and the recent integration of technologies to increase production.
Automation and Its Influence on Sustainable Development: Economic, Social, and Environmental Dimensions
Authors: Almusharraf Ahlam I.
Published: February 2025

This study investigates the complex duality of automation and its impact on sustainable development, encompassing the factors of economic growth, social equity, and environmental sustainability. Innovations in artificial intelligence, robotics, and machine learning are driving automation and transforming industries through improved production, operational efficiency, and resource optimization. However, the rapid integration of automation has created a paradox. While it offers opportunities for resource optimization and technological advancement, it exacerbates challenges such as income inequality, environmental degradation, and social displacement. These issues underline the need for balanced and inclusive approaches to automation’s implementation. Automation contributes substantively to GDP growth because it raises labor productivity, yet it has arguably enhanced income inequality by eliminating low-skilled jobs. Automation improves energy efficiency and aids in renewable energy integration but increases overall energy effectiveness, leading to concerns regarding ecological sustainability. This study applied a quantitative methodology using longitudinal data from 2000 to 2023 and regression models to examine sustainability metrics influenced by automation. The findings highlight the potential of automation to reform effective forms of manufacturing, encourage environmental innovation, and identify the need for systemic governmental policies. Specifically, the results indicate that automation has contributed to a 25% increase in labor productivity across sectors, a 15% reduction in energy intensity per unit of GDP, and a 12% rise in the Gini index, signaling growing income inequality. These quantitative outcomes emphasize both the opportunities and challenges posed by automation. By integrating technological advancements with sustainability goals, automation can act as a transformative instrument to promote ecological conservation, equitable economic development, and social justice. The paper concludes with recommendations for governments and industry leaders to incorporate automation into sustainable development objectives, ensuring the equitable distribution of its advantages, while alleviating socio-environmental hazards.
Optimal Recovery: Unveiling the Success of Conservative Management for Proximal Phalanx Fractures in Adults—A Scoping Review
Authors: Arcuri Pasquale , Boccolari Paolo , Bulli Mattia , Scarpelli Filippo , Donati Danilo , Tedeschi Roberto
Published: February 2025

Background: Proximal phalanx fractures of the hand are common and can significantly impact hand function. Conservative treatments, including splinting and dynamic mobilization, are often used, but their efficacy compared to surgical interventions needs thorough evaluation. Methods: A scoping review was conducted by analyzing studies focused on conservative treatments for proximal phalanx fractures in adults. Inclusion criteria encompassed studies with adult populations, conservative management methods, and clearly reported outcomes. Data from eight selected studies were synthesized to evaluate treatment efficacy, patient outcomes, and complication rates. Results: The review found that conservative treatments, including splinting, buddy taping, and dynamic mobilization, were highly effective for stable, extra-articular proximal phalanx fractures. These methods promoted early functional recovery and had high patient satisfaction rates. Studies comparing conservative and surgical treatments indicated excellent outcomes for both, with fewer complications observed in the surgical groups for unstable fractures. Dynamic and traction splints facilitated significant improvements in total active motion (TAM) and grip strength. Younger patients with transverse fractures showed better outcomes with conservative treatments. Conclusions: Conservative management strategies are effective for stable proximal phalanx fractures, promoting satisfactory functional recovery and minimizing complications. Surgical intervention is recommended for unstable or complex fractures to achieve better functional outcomes. Standardized treatment protocols and long-term follow-up are essential to validate these findings and optimize patient care. Further research with larger sample sizes and standardized outcome measures is needed to establish clear guidelines for the conservative management of proximal phalanx fractures in adults.
Using AI and NLP for Tacit Knowledge Conversion in Knowledge Management Systems: A Comparative Analysis
Authors: Zaoui Seghroucheni Ouissale , Lazaar Mohamed , Al Achhab Mohammed
Published: February 2025

Tacit knowledge, often implicit and deeply embedded within individuals and organizational practices, is critical for fostering innovation and decision-making in knowledge management systems (KMS). Converting tacit knowledge into explicit forms enhances organizational effectiveness by making this knowledge accessible and reusable. This paper presents a comparative analysis of natural language processing (NLP) algorithms used for document and report mining to facilitate tacit knowledge conversion. This study focuses on algorithms that extract insights from semi-structured and document-based natural language representations, commonly found in organizational knowledge artifacts. Key NLP strategies, including text mining, information extraction, sentiment analysis, clustering, classification, recommendation systems, and affective computing, are evaluated for their effectiveness in identifying and externalizing tacit knowledge. The findings highlight the relative strengths and limitations of these techniques, offering practical guidance for selecting suitable algorithms based on organizational needs. Additionally, this paper identifies challenges and emerging opportunities for advancing NLP-driven tacit knowledge conversion, providing actionable insights for researchers and practitioners aiming to enhance KMS capabilities.
V2X Communications in Highway Environments: Scheduling Challenges and Solutions for 6G Networks
Authors: Kanavos Athanasios , Kaloxylos Alexandros
Published: February 2025

As the automotive industry moves toward fully autonomous driving, the goal is to enable vehicles to operate safely without human control in all environments. Implementing Vehicle-to-Everything (V2X) communications in highway environments poses considerable challenges. Several critical services have strict network performance requirements as they deal with safety features. Existing fifth-generation (5G) base station schedulers do not discriminate among critical and non-critical automated driving functions. Therefore, in cases of increased traffic load, there is a significant drop in their performance, and, consequently, increased risk for accidents. Our paper discusses these issues and provides an adaptive scheduler called SOVANET+. The new scheduler acknowledges the Radio Access Network (RAN) load, and the requirements of critical, automated driving applications, together with channel quality, and optimizes the allocation of resources to critical services. The performance of SOVANET+ is evaluated through extensive simulations in the highway environment, an area less examined than urban scenarios. Results indicate that the adoption of SOVANET+ presents clear advantages to critical services compared to existing solutions.
Air Pollution Exposure and Gestational Diabetes Mellitus Risk: A Retrospective Case–Control Study with Multi-Pollutant Analysis in Wuhan, Hubei Province
Authors: Dai Mengyang , Liu Jianfeng , Hu Min , Zhang Feng , Wang Yanjun , Dai Fangfang , Qu Rui , Fang Zhixiang , Yang Jing
Published: February 2025

Ambient air pollution has been associated with gestational diabetes mellitus (GDM); however, evidence regarding trimester-specific effects from China remains limited. This case–control study study analyzed data from pregnant women who delivered in Wuhan, China, between 2017 and 2022 (164 GDM cases and 731 controls), integrating geographic information, air quality measurements, and maternal characteristics. Using Inverse Distance Weighting interpolation and Generalized Linear Mixed Models (GLMM), we assessed associations between air pollutant exposure and GDM across different gestational periods. Results indicated that NO2 demonstrated the strongest association with GDM compared to other pollutants. Specifically, increased NO2 exposure was consistently associated with higher GDM risk throughout pregnancy. PM2.5 exposure showed significant associations during early and mid-pregnancy, while SO2 exposure was significantly associated with GDM risk exclusively in early pregnancy. Sensitivity analyses stratified by urban maternity status and maternal age revealed the stability of the study’s findings. These findings underscore the importance of reducing air pollution exposure during pregnancy and implementing targeted interventions for high-risk populations to prevent GDM development.
Acute Respiratory Viral Infections Among Adult Patients in Edirne, Turkey
Authors: Bukavaz Sebnem , Gungor Kultural , Köle Merve , Ekuklu Galip
Published: February 2025

Background/Objectives: This study aimed to evaluate the prevalence of viral agents identified by Multiplex PCR in acute respiratory viral infection (ARVI) patients at Edirne Sultan 1, Murat State Hospital, from April 2023 to April 2024, and to investigate the relationship between monthly average humidity and viral positivity rates. Methods: The study included 764 adult patients (aged 18 and older) diagnosed with influenza symptoms. Respiratory viral samples were collected and analyzed for COVID-19, influenza A and B, and RSV using Multiplex PCR, with results evaluated retrospectively. Continuous variables in the study were compared using a t-test, and categorical variables were compared with a chi-square test. A logistic regression analysis was performed for the analysis of COVID-19. In this analysis, PCR positivity was the dependent variable, while age, gender, and humidity level served as independent variables. Results: COVID-19 PCR positivity was detected in 142 patients (18.6%), with INF-A (influenza A) in 13 (3.7%), INF-B (influenza B) in 15 (4.2%), and RSV in 2 (0.6%). Higher humidity (over 60%) was associated with reduced viral PCR positivity rates for COVID-19 and influenza B, while low (up to 40%)/normal (40–60%) humidity correlated with positivity rate (p < 0.05 for both). Logistic regression analysis indicated that high humidity levels offer protection against COVID-19 (OR: 0.356; 95% CI: 0.245–0.518). Conclusions: Our study provides essential epidemiological data by summarizing monthly virus distribution in Edirne.
Outer Membrane Proteins as Vaccine Targets Against Lawsonia intracellularis in Piglets
Authors: Aves Kara L. , Fresno Ana H. , Nisar Sajid , Saraiva Mauro M. , Goecke Nicole B. , Sander Adam F. , Nielsen Morten A. , Olsen John E. , Guerra Priscila R.
Published: February 2025

Background: Lawsonia intracellularis (LI) is the agent of proliferative enteropathy in swine, a common disease that affects pigs for up to eight weeks after weaning. Aim: To evaluate the effectiveness of two novel subunit vaccines targeting outer membrane proteins on LI. Methods: The two vaccines included OMP2c.cVLP, where the OMP2c antigen was anchored on the surface of capsid virus-like particles (cVLP); and MBP.INVASc, where antigens were anchored to an MBP fusion protein. Groups of six mice, as proof of concept, and six piglets were immunized with either OMP2c.cVLP, MBP.INVASc., or PBS as a control using a prime-boost regime. Results: Both OMP2c.cVLP and MBP.INVASc subunit vaccines induced strong antigen-specific serum IgG and IgA responses. There were no significant differences in weight gain among the groups. Mild-to-moderate clinical signs of LI infection were observed, but vaccinated groups showed lower inflammatory scores and fewer animals tested positive for bacteria by immunohistochemistry. Although neither vaccine completely prevented clinical signs of LI infection, both effectively reduced inflammation and lowered the pathogen load, thereby mitigating the severity of the disease, particularly the MBP.INVASc vaccine. Conclusions: These findings suggest that both vaccines have the potential for further development and optimization to enhance their protective efficacy against LI infections.
Epidemiological Study of Cryptococcus gattii Complex Infection in Domestic and Wild Animals in Oregon
Authors: Ballard Sophia , Montgomery Alexandria , Rose Ian , Lockhart Shawn , DeBess Emilio , Bermudez Luiz E.
Published: February 2025

The members of the Cryptococcus gattii species complex are the etiologic agents of potentially fatal human infection. C. gattii causes disease in both immunocompetent and immunocompromised hosts. In the early 2000s, infection caused by C. gattii emerged in the Pacific Northwest of the US. While many studies have been published about the human infection, the epidemiological characteristics of the infection in animals, with a possible role in human infection, have not been in investigated. Cases of C. gattii diagnosed in animals in Oregon from 2008 to 2019 were cataloged by county, species of animal, site of the infection, season of the year, and C. gattii genotype. One hundred and nine cases were diagnosed, and among the genotypes of C. gattii, VGII (Cryptococcus deuterogatti) with the genotypes VGIIa, VGIIb, and VGIIc was responsible for 98% of the cases. VGIIa was identified in more than 50% of the animals, and Cryptococcus bacilliporus (VGIII) was only isolated from cat patients. The majority of the infections were diagnosed in dogs and cats, although caprines, equines, camelids, ovines, and elk were also seen with the disease. The most common site of infection in dogs was the brain; that in cats was the nasal cavity and the skin, while the lung was the most affected site in caprines, equines, camelids and elk. Marion and Lane Counties account for the majority of the infections, followed by Clackamas, Benton, and Multnomah Counties. The infection was predominantly identified during the Fall and Winter months, except for Benton County, where it was seen more commonly during the Summer months. This study reviews all the cases identified by the Department of Public Health and by the veterinarians in Oregon in the years between 2008 and 2019.
Comparison of Medical Imaging Quality Related to Embalming Solutions in Canine Cadavers
Authors: Oh Ahsa , Nam Sung-Min , Nahm Sang-Soep , Eom Ki-Dong , Kim Woosuk
Published: February 2025

(1) Background: This study evaluated the quality of medical imaging acquired using radiography, ultrasonography, and computed tomography (CT) in canine cadavers prepared with formalin solution, Thiel solution (TS), and saturated salt solution (SS). Additionally, the duration whereby image quality could be properly reproduced was investigated. (2) Methods: Nine dog cadavers, divided into three groups per embalming solution, were imaged pre- and post-embalming at 6 and 12 weeks using three different imaging modalities. Image quality was qualitatively scored based on human medicine guidelines criteria. The score was assigned as follows: “0 = not invisible, 1 = poorly invisible, 2 = adequately reproduced, 3 = very well reproduced”. (3) Results: On plain radiography, most scores were > 1.34, although the quality of all embalming solutions in thoracic and abdominal images decreased over time. Using ultrasound to image the liver, spleen, and kidney, the SS group was evaluated as poorly visible and scored < 0.82 at 6 and 12 weeks. CT images showed a tendency to degrade over time, but all solution groups had properly implemented images and scored > 1.62. (4) Conclusions: Regarding image quality and ease of application, TS is considered the most suitable embalming solution for medical imaging acquisition and is usable over time in all imaging modalities.
A SMA-SVM-Based Prediction Model for the Tailings Discharge Volume After Tailings Dam Failure
Authors: Liu Gaolin , Zhao Bing , Kong Xiangyun , Xin Yingming , Wang Mingqiang , Zhang Yonggang
Published: February 2025

Tailings ponds can recycle water resources through the water recirculation system by clarifying and purifying the wastewater discharged from the mining production process. Due to factors such as flooding and heavy rainfall, once a tailings dams burst, the spread of heavy metals in the tailings causes underground and surface water pollution, endangering the lives and properties of people downstream. To effectively assess the potential impact of tailings dams bursting, many problems such as the difficulty of taking values in predicting the volume of silt penetration through empirical formulae, model testing, and numerical simulation need to be solved. In this study, 65 engineering cases were collected to develop a sample dataset containing dam height and storage capacity. The Support Vector Machine (SVM) algorithm was used to develop a nonlinear regression model for tailings discharge volume after tailings dam failure. In addition, the model penalty parameter C and kernel function g were optimized using the powerful global search capability of the Slime Mold Algorithm (SMA) to develop an SMA–SVM prediction model for tailings discharge volume. The results indicate that the volume of tailings discharged increases nonlinearly with increasing dam height and tailings storage capacity. The SMA-SVM model showed higher prediction accuracy compared to the predictions made by the Random Forest (RF), Radial Basis Function (RBF), and Least Squares SVM (LS-SVM) algorithms. The average absolute error in tailings discharge volume compared to actual values was 30,000 m3, with an average relative error of less than 25%. This is very close to practical engineering scenarios. The ability of the SMA-SVM optimization algorithm to produce predictions with minimal error relative to actual values was further confirmed by the combination of numerical simulations. In addition, the numerical simulations revealed the flow characteristics and inundation area of the discharged sediment during tailings dam failure, and the research results can provide reference for water resource protection and downstream safety prevention and control of tailings ponds.
Exploring the Multidimensional Poverty Index: National and Children’s Dimensions in Malaysia
Authors: Ismail Mohd Khairi , Zailani Suhaiza Hanim Mohamad , Muhamad Muhamad Zahid , Alias Nurul Ashikin , Zailani Muhammad Nooraiman
Published: February 2025

The COVID-19 pandemic has exacerbated the challenges faced by children in Malaysia, particularly in terms of poverty and hardship. This has led to concerns about the long-term impact on children’s welfare, particularly in terms of educational and economic inequalities. The multidimensional nature of poverty is often overlooked in public policy discussions, and most countries use National Multidimensional Poverty Indices (MPIs) to define child poverty levels within a nation. This article aims to compare the results of a child-specific Multidimensional Poverty Index (MPI) with those of a household-specific MPI, considering the uncertainty surrounding the capacity of Household MPIs to accurately identify multidimensionally impoverished children. This study, conducted in Pahang, Malaysia, uses survey data to examine the multidimensional child poverty status and its dynamic changes. The modified child poverty headcount ratio, using the Alkire–Foster methodology, evaluates both the traditional headcount ratio of child poverty and the mean level of deprivation among disadvantaged children. The results indicate low poverty rates in Pahang and its districts. Increased policy attention has been called for due to rising unemployment among parents and the increasing number of bereaved children due to the pandemic.
Los programas para la actividad física en adolescentes: Una revisión sistemática
Authors: Vera Zambrano Jorge Froilan , Villafuerte Alvarez Carlos Alberto
Published: February 2025

La actividad física desempeña un papel fundamental en la salud y el bienestar de los adolescentes, favoreciendo el desarrollo de sus capacidades condicionales, como la fuerza, la velocidad, la resistencia y la flexibilidad. Este estudio tuvo como objetivo analizar la percepción de los estudiantes sobre el impacto de los programas de actividad física en la educación secundaria y su relación con el rendimiento académico. Se llevó a cabo una revisión sistemática siguiendo las directrices PRISMA. Se consultaron bases de datos como Scopus, Web of Science y PubMed, utilizando la ecuación de búsqueda: ("actividad física" OR "ejercicio") AND ("capacidades condicionales" OR "rendimiento académico") AND ("adolescentes" OR "educación secundaria"). Se seleccionaron 18 estudios publicados entre 2019 y 2023, priorizando aquellos con metodología cuantitativa y cualitativa. Los resultados evidenciaron que la actividad física mejora la concentración, la oxigenación sanguínea y el estado de ánimo, favoreciendo el aprendizaje. Se concluye que es necesario diseñar programas con participación parental y capacitación docente.