bluuebunny/crossref_metadata_2025 huggingface dataset:
High-fidelity immersive virtual reality environments for gait rehabilitation exergames
Authors: Schalbetter Laura , Grêt-Regamey Adrienne , Gutscher Fabian , Wissen Hayek Ulrike
Published: January 2025

Introduction

Virtual reality (VR) used for healthcare, particularly through exergames, is promising for improving therapeutic outcomes. However, effectively engaging patients and providing realistic environments for everyday situations remain major challenges. The technical aspects of developing engaging VR applications for rehabilitation are largely unexplored. This research presents the development of a head-mounted display VR (HMD-VR) exergame for gait therapy. The novelty lies in the use of high-fidelity immersive environments implementing 3D geospatial data and motion to create targeted therapeutic applications that closely mimic reality while harnessing the environment’s restorative functions.

Methods

We integrated 3D point clouds from laser scans and geolocated ambisonic sound recordings into a game engine. We combined different techniques for user motion tracking, while we used point cloud manipulation for integrating specific training elements. Feedback on the quality of the HMD-VR exergame was received from the first implementations.

Results

Our methodology demonstrates the successful, highly realistic VR replication of restorative real-world environments using 3D point clouds and environmental sounds. We illustrate the adaptability of the environment for therapeutic use through manipulation of the 3D point cloud, facilitating customizable training difficulty levels while promoting immersive experiences. Participant feedback (sample size: 49 sessions) confirms the HMD-VR exergame’s applicability as a restorative experience (ClinicalTrials.gov NCT06304077).

Discussion

Our research introduces a pioneering HMD-VR game for gait rehabilitation, leveraging immersive VR environments grounded in the real world. This innovative approach offers new possibilities for efficient and effective rehabilitation interventions. Future studies will analyze effects on gait patterns across different environments and their restorative functions and evaluate the HMD-VR xergame in clinical settings.
Perceptions of swine euthanasia among Brazilian caretakers from non-integrated swine farms
Authors: Alves Laya Kannan Silva , Pairis-Garcia Monique Danielle , Arruda Andréia Gonçalves , de Melo Cecília Archangelo Ferreira , Gomes Nadia de Almeida Ciriaco , Hoshino Roberta Yukari , Garbossa Cesar Augusto Pospissil
Published: January 2025

Timely and humane euthanasia is crucial for animal welfare on swine farms, yet challenges persist in its implementation, particularly in Brazil, where the responsibility often falls to caretakers lacking training. This study aimed to assess the knowledge, attitudes, and practices of swine caretakers regarding euthanasia across non-integrated farms (ranging from 1,000 to 3,500 housed sows) and different experience levels (from less than a month to 40 years working with pigs). A total of 117 people directly working with pigs participated in a survey designed to evaluate their decision-making skills, euthanasia competencies, and understanding of Brazilian guidelines for euthanasia methods. Using Cluster analysis, we identified two distinct groups of caretakers: (1) Empathetic, self-sufficient, apathetic about euthanasia; and (2) Empathetic, knowledge seeker, uncomfortable with euthanasia. Both Clusters exhibited high empathy toward pigs and confidence in identifying sick animals but differed in their attitudes toward euthanasia. The risk factor analysis showed a tendency for younger respondents (under 36 years old) and those from smaller farms (less than 2,000 sows) were more likely to belong to Cluster 2, while older caretakers (over 36 years) and those working on larger farms (more than 2,000 housed sows) tended to belong to Cluster 1. Furthermore, a significant proportion of caretakers lacked knowledge of the euthanasia Brazilian guidelines, as evidenced by incorrect responses regarding acceptable euthanasia methods, such as performing cardiac perforation or using non-penetrating captive bolt guns on growing-finishing pigs. This study highlights the variability in caretaker experience and attitudes toward euthanasia, suggesting a critical need for targeted training programs and euthanasia protocols that address both emotional and practical aspects. Improved understanding of caretaker attitudes can enhance both human and animal welfare on farms.
Case report: Generalized granuloma annulare successfully treated with baricitinib in two cases
Authors: Yunoki Marina , Kondo Shumpei , Otsuka Masaki , Tokura Yoshiki
Published: January 2025

Treatments are challenging in generalized granuloma annulare. We reported two cases of generalized granuloma annulare without diabetes mellitus; one exhibited non-annular papules and the other did patch/annular lesions. Since they were refractory to multiple treatments, we treated them with JAK inhibitor baricitinib at 2 mg daily. After 1–2-month treatment, they responded well to baricitinib with good tolerance. Given increased JAK1 signaling, high interferon-α and -γ production and macrophage activation in granuloma annulare, JAK inhibitors are considered to be a reasonable choice for recalcitrant generalized granuloma annulare. In addition to the reported cases, our two cases further support the effectiveness of JAK inhibitors for generalized granuloma annulare.
One Hundred Years for One Goal: Centenary Reflections on the Mission of the Magyar Nemzeti Bank
Authors: Matolcsy György
Published: January 2025

This paper pays tribute to the history of the Magyar Nemzeti Bank, which has been working to establish and maintain price and financial stability and to support sustainable growth in the Hungarian economy for the past one hundred years. We seek to find out what the Hungarian economy has looked like from a central bank perspective over the past hundred years. The study thus covers the decisive periods since 1924, encompassing the time between the two world wars, the socialist economic system built up after World War II and the milestones of the era following the regime change. The analysis is primarily intended to draw lessons from history to offer a guideline amid the challenges currently faced. The historical periods show the importance of preserving the independence of the central bank and coordinating the activities of the branches of economic policy, in order to achieve and maintain price and financial stability, support economic development and prepare for future challenges, such as the green transition. Over the past 12 years, the Magyar Nemzeti Bank has gradually opened up opportunities that support the achievement of these goals in the present day and age.
Fighting Inflation without Massive Transfers to Banks
Authors: De Grauwe Paul , Ji Yuemei
Published: January 2025

The major central banks now operate in a regime of abundant bank reserves. As a result, they can only raise the money market rate by increasing the rate of remuneration of bank reserves. This, in turn, leads to large transfers of central banks’ profits to commercial banks that will become unsustainable and renders the transmission of monetary policies less effective. We propose a two-tier system of reserve requirements that would only remunerate the reserves in excess of the minimum required. This would drastically reduce the giveaways to banks, allow the central banks to maintain their current operating procedures and make monetary policies more effective in fighting inflation.
Determination of the Standardized Ileal Amino Acid Digestibility of U.S. Tannin-Free Sorghum in Broilers
Authors: Sasia Santiago , Bridges William , Arguelles-Ramos Mireille
Published: January 2025

This study aimed to assess the standardized ileal amino acid (AA) digestibility (SIAD) values in broilers (3 weeks of age) for tannin-free sorghum samples collected from the Southeastern region of the USA as well as provide a general comparison between sorghum vs. corn. An incomplete block design was implemented using the direct method to assess the SIAD of eight sorghum samples and one corn sample as the standard. Three of these sorghum samples were obtained from North Carolina (NC-PL, NC-T2, NC-LW), four samples from South Carolina (SC-Flo, SC-Pei, SC-Tub, SC-Experience), and one from Georgia (GA-Gf). Each tested grain was assigned to eight cages, with thirteen birds/cage. Birds were reared for 3 wks using the last 4 d as the experimental phase when ileal digesta were collected for SIAD assessment. Each sorghum sample’s digestibility was compared to that of corn. Generally, the South Carolina sorghum varieties showed the lowest AA digestibility values, except for SC-Flo, which had the highest digestibility, surpassing corn in Lys, Thr, Gly, and Asp (p < 0.05). Then, the sorghums’ SIAD values were pulled together for a general comparison to corn. Overall, the sorghum SIAD was comparable to corn (p > 0.05), but variations were noted among the AAs. Sorghum had better digestibility for Lys, Thr, and Asp while corn had more digestible Met, Leu, Pro, and Phe (p < 0.05). By integrating the crude protein content with SIAD data, this study provides an updated assessment of tannin-free sorghum’s protein quality. The findings suggest that tannin-free sorghum could serve as a practical alternative to corn in poultry feed, providing a comparable nutritional profile.
Electric Discharge-Generating Devices Developed for Pathogen, Insect Pest, and Weed Management: Current Status and Future Directions
Authors: Kusakari Shin-ichi , Toyoda Hideyoshi
Published: January 2025

Electrostatic techniques have introduced innovative approaches to devise efficient tools for pest control across various categories, encompassing pathogens, insects, and weeds. The focus on electric discharge technology has proven pivotal in establishing effective methods with simple device structures, enabling cost-effective fabrication using readily available materials. The electric discharge-generating devices can be assembled using commonplace conductor materials, such as ordinary metal nets linked to a voltage booster and a grounded electric wire. The strategic pairing of charged and grounded conductors at specific intervals generates an electric field, leading the charged conductor to initiate a corona discharge in the surrounding space. As the applied voltage increases, the corona discharge intensifies and may eventually result in an arc discharge due to the breakdown of air when the voltage surpasses the insulation resistance limit. The utilization of corona and arc discharges plays a crucial role in these techniques, with the corona-discharging stage creating (1) negative ions to stick to pests, which can then be captured with a positively charged pole, (2) ozone gas to sterilize plant hydroponic solutions, and (3) plasma streams to exterminate fungal colonies on leaves, and the arc-discharging stage projecting electric sparks to zap and kill pests. These electric discharge phenomena have been harnessed to develop reliable devices capable of managing pests across diverse classes. In this review, we elucidate past achievements and challenges in device development, providing insights into the current status of research. Additionally, we discuss the future directions of research in this field, outlining potential avenues for further exploration and improvement.
Exploring the Potential Effects of Soybean By-Product (Hulls) and Enzyme (Beta-Mannanase) on Laying Hens During Peak Production
Authors: Shuaib Muhammad , Hafeez Abdul , Paneru Deependra , Kim Woo Kyun , Tahir Muhammad , Pokoo-Aikins Anthony , Ullah Obaid , Sufyan Abubakar
Published: January 2025

This study determined the interaction between soybean hulls (SHs) and enzymes (β-mannanase) to improve the sustainability and efficacy of feeding programs for laying hens during peak production while ensuring the best health and efficiency. In a completely randomized design (CRD), 200 golden-brown hens were fed for four weeks (33 to 36 weeks) and randomly distributed into four groups, each containing four replicates of ten birds, with one group receiving a control diet (P0) and the others receiving diets that contained four combinations of SHs and enzymes (ENZs). e.g., 3% SHs and 0.02 g/kg ENZs (P1), 3% SHs and 0.03 g/kg ENZs (P2), 9% SHs and 0.02 g/kg ENZs (P3), and 9% SHs and 0.03 g/kg ENZs (P4). Although most egg quality measures remained similar, the P2 group showed enhanced (p = 0.630) egg weight, albumen weight, and height. Moreover, the P2 group improved gut (p < 0.05) shape by increasing villus width, height, crypt depth, and surface area throughout intestinal sections, while the P4 group markedly improved total cholesterol and LDL (p = 0.022) levels. The P1, P2, and P4 groups exhibited a significant enhancement in dry matter (p = 0.022) and crude fiber (p = 0.046) digestibility, while the P2 group demonstrated superior crude protein digestibility (p = 0.032), and the P1 and P2 groups showed increased crude fat digestibility compared to the other groups. In conclusion, adding 3% of SHs and 30 mg/kg of ENZs (β-mannanase) to the feed may help laying hens, enhance gut health and some egg quality indices, and decrease blood cholesterol and LDL levels without compromising nutrient digestibility.
Stock Dynamics of Female Red King Crab in a Small Bay of the Barents Sea in Relation to Environmental Factors
Authors: Dvoretsky Alexander G. , Dvoretsky Vladimir G.
Published: January 2025

Stock–recruitment relationships depend on the total abundance of females, their fecundity, and patterns of their maturation. However, the effects of climatic conditions on the abundance, biomass, and mean weight of female red king crabs, Paralithodes camtschaticus, from the introduced population (Barents Sea) have not yet been studied. For this reason, we analyzed long-term fluctuations in stock indices and the average weight of an individual crab in a small bay of the Barents Sea and related these parameters to the dynamics of temperature conditions (temperature in January–December, mean yearly temperature, and temperature anomaly) in the sea. The average weight of a crab at age 6–9 had strong negative correlations with water temperature at lags 8 and 9, indicating faster female maturation in warm periods. Positive relationships were registered between temperature and stock indices for 15–19-year-old females at lag 4 and for 10–14-year-old females at lag 10, supporting the idea of higher survival rates of juveniles and their rapid development being a response to a pool of warm waters. Both redundancy and correlation analyses revealed seawater temperatures in June–August being the most important predictors of female abundance and biomass, indicating that favorable temperature conditions in the first 3 months of crab benthic life result in high survivorship rates for red king crabs.
Seasonal and Altitudinal Effects on Chemical Composition and Rumen Degradability of Blackberry Leaves in Northwestern Italian Alps
Authors: Tassone Sonia , Barbera Salvatore , Glorio Patrucco Sara , Kaihara Hatsumi , Abid Khalil
Published: January 2025

The blackberry poses a threat as an invasive plant in various regions worldwide, where it aggressively competes with native species and risks delicate ecosystems. Livestock grazing has emerged as a potential strategy to mitigate its spread. This study investigated the effects of seasonal variations and altitude on the chemical composition and in vitro degradability of blackberry leaves. The leaves accessible to goats were collected in the Northwestern Italian Alps across all seasons at three altitudes (low: 450 m, medium: 700 m, high: 1000 m). The findings indicated that blackberry leaves can serve as a cost-effective, high-protein, and high-fiber feed for ruminants in these regions. However, the goats exhibited a limited capacity for fiber degradation. Furthermore, the nutritional value of these leaves was significantly influenced by the season, altitude, and their interaction. Spring leaves had the highest protein content (241.9 g/kg dry matter) and the best digestibility, with lower lignin levels (69 g/kg dry matter). At higher altitudes, lignin content decreased significantly during winter compared to the other seasons, resulting in a significant increase in fiber degradability. These insights offer crucial guidance for optimizing the utilization of the blackberry plant in goat feeding systems and underscores the necessity of considering both seasonal and altitudinal factors in grazing management practices.
Evaluation of the Effects of Autologous Leukocyte- and Platelet-Rich Fibrin Membranes for Treating Chronic Wounds: A Prospective Study
Authors: Aragosa Federica , Fatone Gerardo , Caterino Chiara , Cavalli Stefano , Piscitelli Alfonso , Vallefuoco Rosario , Lamagna Francesco , Della Valle Giovanni
Published: January 2025

(1) Background: The aim of this prospective study was to evaluate the efficacy of topical application of leukocyte- and platelet-rich fibrin (L-PRF) membranes for treating chronic cutaneous wounds in dogs. (2) Methods: Chronic wounds unresponsive to conventional treatments were assessed on digital photographs and classified using the Bates-Jensen Wound Assessment Tool (BWAT). Each lesion was treated with L-PRF membranes. Epithelialization, granulation tissue formation, wound healing rate, and contraction were statistically analyzed during follow-up. (3) Results: All but one of the cases were treated with a single application of L-PRF for a median of 30 days after onset. All wounds healed after a median of 22 days. The BWAT score, total wound area, and granulation tissue decreased significantly over time while wound contraction increased. The most significant reduction in the total wound area was observed within the first 3 weeks after treatment. None of the dogs required the administration of antibiotics. (4) Conclusions: L-PRF membrane promoted the wound healing process in dogs and is a valuable and cost-effective tool for treating chronic wounds, thereby reducing the need for antibiotics administration.
A Structural Effect of the Antioxidant Curcuminoids on the Aβ(1–42) Amyloid Peptide
Authors: Santoro Angelo , Ricci Antonio , Rodriquez Manuela , Buonocore Michela , D’Ursi Anna Maria
Published: January 2025

Investigating amyloid–β (Aβ) peptides in solution is essential during the initial stages of developing lead compounds that can influence Aβ fibrillation while the peptide is still in a soluble state. The tendency of the Aβ(1–42) peptide to misfold in solution, correlated to the aetiology of Alzheimer’s disease (AD), is one of the main hindrances to characterising its aggregation kinetics in a cell-mimetic environment. Moreover, the Aβ(1–42) aggregation triggers the unfolded protein response (UPR) in the endoplasmic reticulum (ER), leading to cellular dysfunction and multiple cell death modalities, exacerbated by reactive oxygen species (ROS), which damage cellular components and trigger inflammation. Antioxidants like curcumin, a derivative of Curcuma longa, help mitigate ER stress by scavenging ROS and enhancing antioxidant enzymes. Furthermore, evidence in the literature highlights the effect of curcumin on the secondary structure of Aβ(1–42). This explorative study investigates the Aβ(1–42) peptide conformational behaviour in the presence of curcumin and six derivatives using circular dichroism (CD) to explore their interactions with lipid bilayers, potentially preventing aggregate formation. The results suggest that the synthetic tetrahydrocurcumin (THC) derivative interacts with the amyloid peptide in all the systems presented, while cyclocurcumin (CYC) and bisdemethoxycurcumin (BMDC) only interact when the peptide is in a less stable conformation. Molecular dynamics simulations helped visualise the curcuminoids’ effect in an aqueous system and hypothesise the importance of the peptide surface exposition to the solvent, differently modulated by the curcumin derivatives.
Antioxidant Properties of Albumin and Diseases Related to Obstetrics and Gynecology
Authors: Watanabe Kazushi , Kinoshita Hiroyuki , Okamoto Tomohito , Sugiura Kazumasa , Kawashima Shingo , Kimura Tetsuro
Published: January 2025

Albumin, the most abundant protein, contributes significantly to various physiological processes, indicating its multifunctional properties. It has drawn the attention of scientists and physicians because of its primary role in maintaining osmotic pressure and involvement in transporting numerous small molecules, including hormones, fatty acids, and drugs. A growing body of evidence has recently illustrated an additional aspect of albumin’s antioxidant properties. Therefore, based on recent research findings, this review article delves into the molecular and biochemical aspects of albumin’s antioxidative capabilities. We highlight the multifaceted significance of proteins in oxidative stress and their relation to pathologies in obstetrics and gynecology. In particular, we focused on preeclampsia, in which oxidative stress is closely involved in the pathogenesis, and renal dysfunction leads to increased albumin excretion into the urine, resulting in hypoalbuminemia. In addition, we discussed the role of albumin in preeclampsia pathogenesis, diagnosis, and patient prognosis. Understanding the antioxidant properties of albumin opens new avenues for therapeutic intervention and sheds light on novel strategies for combating preeclampsia associated with oxidative damage. In this study, we employed the PubMed database to search for articles that assessed the antioxidant properties of albumin, with a specific focus on obstetric diseases, particularly preeclampsia. The last update of the search was conducted in November 2024.
Research on Adhesion Characteristic Experiment of Carbon Particles in Transformer Oil on the Surface of Epoxy Resin Under DC Electric Field
Authors: Zhong Jiarong , Zhang Zhanlong , Dong Zijian , Xue Zhixuan , Cheng Jiaqi , Deng Jun , Wang Fan
Published: January 2025

Transformer oil will inevitably be contaminated by impurity particles in the actual operation process; Carbon particles are the most abundant conductive particles in transformer oil. The adhesion behavior on the internal insulating surface will cause electric field distortion, which will pose a serious threat to the safe and stable operation of oil-immersed power equipment. To this end, this paper builds an experimental platform for simulating the adhesion behavior of carbon particles in transformer oil, studies the adhesion characteristics of carbon particles, and analyzes the influence of electric field, particle size, oil flow velocity, and other factors on the adhesion of carbon particles. The results show that: the DC electric field is the main factor driving the adhesion of carbon particles on the surface of epoxy resin (with the increase in electric field strength, the degree of adhesion of carbon particles firstly rises and then decreases); the smaller the size of the carbon particles, the easier it is to adhere, and the corresponding electric field strength is different for different sizes of carbon particles when the degree of adhesion is the largest; the velocity of the transformer oil will have a significant impact on the adhesion behavior of the carbon particles (with the increase in the flow velocity, the degree of adhesion of carbon particles firstly rises and then decreases). The research conclusion of this article is helpful in guiding the evaluation of insulation performance and the optimization of insulation structure design in the converter transformer valve-side bushing considering the phenomenon of particle adhesion.
Deep Learning and Recurrence Information Analysis for the Automatic Detection of Obstructive Sleep Apnea
Authors: Padovano Daniele , Martinez-Rodrigo Arturo , Pastor José M. , Rieta José J. , Alcaraz Raul
Published: January 2025

Obstructive sleep apnea (OSA) represents a significant health concern. While polysomnography (PSG) remains the gold standard, its resource-intensive nature has encouraged the exploration of further alternative approaches. Most of these were based on the heart rate variability (HRV) analysis, but only a few of them have presented a recurrence-based approach. The present paper addresses this gap by integrating convolutional neural networks (CNNs) with HRV recurrence analysis. Employing three different and publicly available databases from PhysioNet’s official repository (Apnea-ECG, MIT-BIH, and UCD-DB), the presented method was able to expose concealed patterns within the distance matrix of HRV’s phase space, which is discernible at an appropriate level of abstraction through CNNs. Under the challenging context of external validation (MIT-BIH and UCD for training, and Apnea-ECG for testing), the results obtained were comparable to those presented in the state of the art, achieving a peak accuracy of 75%, while maintaining balanced sensitivity and specificity at 74% and 75%, respectively. Moreover, these results obtained by the proposed CNN-based recurrence analysis of HRV also outperformed traditional time–frequency models, which have yielded values of accuracy lower than 65%. Hence, this paper highlights the importance of the proposed method in gaining new insights into OSA’s HRV dynamics, offering a contribution that adds to the existing analytical approaches in the state of the art.
Acute Effects of a Single-Bout Session of High-Intensity Functional Training and Moderate-Intensity Functional Training on Cognitive Functions, Anxiety, and Stress in Healthy Adults
Authors: Trujillo-Gutiérrez Francisco José , López-Aguilar José , Álvarez-Salvago Francisco , Morente-Oria Honorato , Jiménez-García José Daniel
Published: January 2025

Background: Currently, it has been observed that a fast-paced lifestyle, along with factors such as work pressure and economic and political uncertainty, among others, negatively impacts cognitive functions and increases levels of anxiety and stress in the population. In this context, physical exercise has been shown to be an effective means of alleviating these effects. The aim of this study is to analyze the acute effects of a single-bout session of high-intensity functional training (HIFT) and a single-bout session of moderate-intensity functional training (MIFT) on cognitive functions and psychological responses such as anxiety and stress. Methods: The study presents an experimental design with an analytical approach, involving 57 healthy adults in a 30 min functional exercise circuit. The HIFT group, with 28 participants, performed a high-intensity exercise circuit (>85% HR max). The MIFT group, with 29 participants, performed a moderate-intensity exercise circuit (70–80% HR max). To evaluate the dependent variables of executive function, attention, memory, anxiety, and stress, the Stroop Test, d2 Test, Word-Recall Test, STAI, and PSS were used, respectively. These tests were administered, in the order mentioned, immediately before and immediately after the training session. Results: Both groups (HIFT and MIFT) showed significant improvements in executive function, attention, and memory, as well as significant reductions in anxiety and stress after the intervention (all p values ranged between p < 0.001 and p < 0.04). However, the HIFT group demonstrated greater improvements in cognitive function and more pronounced reductions in anxiety and stress when compared to the MIFT group. Conclusions: Both HIFT and MIFT can improve cognitive function and reduce anxiety and stress, but high-intensity exercise appears to offer greater benefits.
Oxidative Thermolysis of Sulfobutyl-Ether-Beta-Cyclodextrin Sodium Salt: A Kinetic Study
Authors: Ledeți Ionuț , Temereancă Claudia , Ridichie Amalia , Ledeți Adriana , Ivan Denisa Laura , Vlase Gabriela , Vlase Titus , Tomoroga Carmen , Sbârcea Laura , Suciu Oana
Published: January 2025

Sulfobutyl-ether-beta-cyclodextrin sodium salt (SBECD) is a modified cyclodextrin widely used in the pharmaceutical industry to enhance the solubility and stability of poorly water-soluble drugs. As a derivative of beta-cyclodextrin, it is produced by introducing sulfobutyl ether groups into the beta-cyclodextrin molecule, which significantly increases its water solubility and decreases its toxicity compared to unmodified cyclodextrins. This study investigates the spectral and PXR diffraction characterization of SBECD, its thermal stability profile, and decomposition mechanism using isoconversional methods. Since the simple ASTM E698 method does not provide realistic data, the Flynn–Wall–Ozawa, Friedman, and NPK methods were employed, leading to the kinetic triplet that characterizes the oxidative thermolysis of this compound.
FD-YOLO: A YOLO Network Optimized for Fall Detection
Authors: Hwang Hoseong , Kim Donghyun , Kim Hochul
Published: January 2025

Falls are defined by the World Health Organization (WHO) as incidents in which an individual unintentionally falls to the ground or a lower level. Falls represent a serious public health issue, ranking as the second leading cause of death from unintentional injuries, following traffic accidents. While fall prevention is crucial, prompt intervention after a fall is equally necessary. Delayed responses can result in severe complications, reduced recovery potential, and a negative impact on quality of life. This study focuses on detecting fall situations using image-based methods. The fall images utilized in this research were created by combining three open-source datasets to enhance generalization and adaptability across diverse scenarios. Because falls must be detected promptly, the YOLO (You Only Look Once) network, known for its effectiveness in real-time detection, was applied. To better capture the complex body structures and interactions with the floor during a fall, two key techniques were integrated. First, a global attention module (GAM) based on the Convolutional Block Attention Module (CBAM) was employed to improve detection performance. Second, a Transformer-based Swin Transformer module was added to effectively learn global spatial information and enable a more detailed analysis of body movements. This study prioritized minimizing missed fall detections (false negatives, FN) as the key performance metric, since undetected falls pose greater risks than false detections. The proposed Fall Detection YOLO (FD-YOLO) network, developed by integrating the Swin Transformer and GAM into YOLOv9, achieved a high mAP@0.5 score of 0.982 and recorded only 134 missed fall incidents, demonstrating optimal performance. When implemented in environments equipped with standard camera systems, the proposed FD-YOLO network is expected to enable real-time fall detection and prompt post-fall responses. This technology has the potential to significantly improve public health and safety by preventing fall-related injuries and facilitating rapid interventions.
Influence of Vinyl Acetate-Based and Epoxy-Based Compatibilizers on the Design of TPS/PBAT and TPS/PBAT/PBSA Films
Authors: Martín-Poyo Cristina , Cerisuelo-Ferriols Josep P. , Badia-Valiente Jose D.
Published: January 2025

The study investigated the effect of Vinnex® (vinyl acetate polymer) and Joncryl® (epoxy-based copolymer) as compatibilizers on the mechanical properties of thermoplastic starch (TPS) and polybutylene adipate-co-terephthalate (PBAT) and polybutylene succinate-co-adipate (PBSA) films. Due to TPS’s hydrophilicity and brittleness, blending it with biodegradable polyesters like PBAT enhances its properties but may introduce compatibility challenges. This research evaluated three formulations (TPS/PBAT with Vinnex, TPS/PBAT with Joncryl, and TPS/PBAT with both additives) along with the inclusion of a polybutadiene succinate-co-adipate (PBSA) matrix to further improve performance. Mechanical testing (tensile strength, elongation at break, Young’s modulus) reveals that Vinnex and Joncryl enhance plasticization and polymer compatibility, positively impacting TPS/PBAT’s mechanical properties. The introduction of the PBSA matrix further improves tensile strength and elongation. Scanning electron microscopy (SEM) confirms better additive dispersion and interfacial adhesion within the blend. Complementary analysis includes melt flow index, melt density, DSC, and TGA, providing a comprehensive understanding of how these additives optimize TPS/PBAT compounds for sustainable applications. Mechanically, the compatibilized blends showed improved performance: Vinnex mainly enhanced stiffness, Joncryl primarily improved elongation, and a synergistic effect was observed with their combination.
Finite-Element-Based Time-Dependent Service Life Prediction for Carbonated Reinforced Concrete Aqueducts
Authors: Zhang Lan , He Ri-Sheng , Zhang Long-Wen , Chen Yan-Ye
Published: January 2025

This study proposes a time-dependent reliability analysis method for aqueduct structures based on concrete carbonation and finite element analysis. The primary goal of this study is to improve the reliability assessment of reinforced concrete aqueducts by incorporating environmental factors such as carbonation over time. First, a three-dimensional finite element model of a reinforced concrete aqueduct is established using the Midas 2022 Civil software, incorporating a time-varying function derived from a predictive model of concrete carbonation depth. Point estimation is then integrated with structural finite element analysis to calculate the first four moments of random variables as functions of concrete carbonation. Additionally, the original performance function is transformed into a normal distribution using dual power transformation and the Jarque–Bera test. The high-order unscented transformation (HUT) is subsequently employed to estimate the first four moments of the transformed performance function, facilitating the calculation of time-varying reliability indices for the carbonated concrete aqueduct. Based on the time-varying reliability index data, a reliability function corresponding to different time points is fitted and applied to service life prediction. The results demonstrate that the proposed method effectively reduces large errors associated with the fourth-moment method in calculating large reliability indices. Furthermore, the comparison with Monte Carlo simulation (MCS) results validates the high efficiency and accuracy of the proposed method, offering a valuable tool for addressing the reliability challenges of aqueducts exposed to carbonation and other environmental factors over time.
Enhancing Disaster Situation Awareness Through Multimodal Social Media Data: Evidence from Typhoon Haikui
Authors: Gao Songfeng , Yang Tengfei , Xu Yuning , Mou Naixia , Wang Xiaodong , Huang Hao
Published: January 2025

Emergency situation awareness during sudden natural disasters presents significant challenges. Traditional methods, characterized by low spatial and temporal resolution as well as coarse granularity, often fail to comprehensively capture disaster situations. However, social media platforms, as a vital source of social sensing, offer significant potential to supplement disaster situational awareness. This paper proposes an innovative framework for disaster situation awareness based on multimodal data from social media to identify social media content related to typhoon disasters. Integrating text and image data from social media facilitates near real-time monitoring of disasters from the public perspective. In this study, Typhoon Haikui (Strong Typhoon No. 11 of 2023) was chosen as a case study to validate the effectiveness of the proposed method. We employed the ERNIE natural language processing model to complement the Deeplab v3+ deep learning image semantic segmentation model for extracting disaster damage information from social media. A spatial visualization analysis of the disaster-affected areas was performed by categorizing the damage types. Additionally, the Geodetector was used to investigate spatial heterogeneity and its underlying factors. This approach allowed us to analyze the spatiotemporal patterns of disaster evolution, enabling rapid disaster damage assessment and facilitating emergency response efforts. The results show that the proposed method significantly enhances situational awareness by effectively identifying different types of damage information from social sensing data.
Kinematic Analysis of Short and Long Services in Table Tennis
Authors: Bańkosz Ziemowit , Winiarski Sławomir , Malagoli Lanzoni Ivan
Published: January 2025

Background: The kinematics of table tennis is a growing topic of scientific research. This study aimed to assess the kinematics and determine the coordination of the movements of most body segments during the execution of two types of serves (short and long) in table tennis, as well as to indicate the main differences between these serves when performed by high-level athletes. Methods: The study involved 15 male table tennis players. Each participant performed two tasks, performing short and long forehand serves with back-sidespin rotation, with up to 10 hits in the designated field for each type. The players’ movements were registered using an IMU system. Results and Conclusion: The research allowed for the development of a model for executing two types of serves in table tennis. The differences between short and long serves were mainly in the ranges of movement and angular velocities (higher for long serves). These were found in the shoulder rotation, elbow joint and wrist joint (primarily the flexion–extension movement), hand supination, and movement in the elbow joint, which also played an important role. Coaches and players should seriously consider these joints and movements in the training process. In the coordinated movement of the performed serves, a phenomenon of movement variability was observed, manifested by a large variability in execution and a low variability in the maximum speeds of the hand with the racket.
A Trip Purpose Inference Method Considering the Origin and Destination of Shared Bicycles
Authors: Xiao Haicheng , Shen Xueyan , Yang Xiujian
Published: January 2025

This study advances the inference of travel purposes for dockless bike-sharing users by integrating dockless bike-sharing and point of interest (POI) data, thereby enhancing traditional models. The methodology involves cleansing dockless bike-sharing datasets, identifying destination areas via users’ walking radii from their start and end points, and categorizing POI data to establish a correlation between trip purposes and POI types. The innovative GMOD model (gravity model considering origin and destination) is developed by modifying the basic gravity model parameters with the distribution of POI types and travel time. This refined approach significantly improves the accuracy of predicting travel purposes, surpassing standard gravity models. Particularly effective in identifying less frequent but critical purposes such as transfers, medical visits, and educational trips, the GMOD model demonstrates substantial improvements in these areas. The model’s efficacy in sample data tests highlights its potential as a valuable tool for urban transport analysis and in conducting comprehensive trip surveys.
Design and Implementation of a Reconfigurable Test Environment for Network Measurement Tools Based on a Control and Management Framework
Authors: Abut Fatih , Kızıldağ Mehmet
Published: January 2025

To be applicable to real-world networks, a realistic evaluation of network measurement tools requires the conditions of the test network to be as similar as possible to the networks in which they are later deployed. Thus, having an existing real-world network which can be utilized for testing, while also allowing the reconfiguration of certain characteristics and features, is of significant interest to researchers. Providing the researchers with corresponding management tools with which they can introduce artificial conditions and topology changes into the network would help in realizing more realistic testbed setups and scenarios. The purpose of this study is to develop a configurable test environment based on the Control and Management Framework (OMF) to support researchers in a realistic empirical evaluation of network measurement tools. The proposed OMF-enabled test environment has the merit of automatizing the deployments and executions of any measurement experiments, collecting their final estimates, and then transporting them back to a single experiment controller without requiring any physical access to the corresponding experimental nodes used. It is demonstrated how the test environment can be used for the evaluation of network measurement experiments based on four representative case studies. These include validating the accuracy of end-to-end round-trip time and available bandwidth estimation tools, measuring the TCP and UDP throughput, and analyzing the impact of packet loss and jitter on VoIP performance, all conducted over dynamically adjusted testbed configurations. These case studies highlight the versatility and effectiveness of the OMF-enabled test environment, positioning it as a valuable tool for advancing the realistic evaluation of network measurement tools in controlled yet adaptable settings.
Quinolone and Colistin Resistance Genes in Extended-Spectrum Beta-Lactamase (ESBL)-Producing Escherichia coli of Diverse Phylogenetic Groups Isolated from Seafood in Mumbai, India
Authors: Dhanush Chandrashekar K. , Lekshmi Manjusha , Girisha Shivani Kallappa , Nayak Binaya Bhusan , Kumar Sanath H.
Published: January 2025

Contamination of coastal-marine environment with multidrug-resistant Escherichia coli has resulted in such bacteria increasingly being detected in the seafood chain. This study aimed to determine the quinolone and colistin resistance genes in extended spectrum-β-lactamase (ESBL)-producing E. coli from seafood. ESBL-producing E. coli isolates (n = 269) were tested for quinolones and colistin resistance phenotypes by disk diffusion and broth microdilution methods, respectively. The isolates were further PCR screened for the plasmid-mediated quinolone resistance (PMQR) genes qnrA, qnrB, and qnrS, genomic mutations in gyrA and parC genes, and the colistin resistance genes mcr-1 and mcr-2. Phylogroup was determined by PCR using the Clermont E. coli phylotyping method. Of 269 isolates tested, 73.60% of E. coli isolates were resistant to moxifloxacin and 8.55% to ofloxacin, the least of all the quinolones tested. Further, 150 (55.76%) E. coli isolates carried at least one of the three PMQR genes tested, where qnrS was the most prevalent gene (53.90%). The colistin resistance gene (mcr-2) was detected in 38 (14.12%) isolates. Twenty-one of these isolates (55.26%) had a colistin minimum inhibitory concentration (MIC) of 16 µg/mL. Based on the Clermont E. coli phylotyping of the isolates harboring at least one of the qnr genes, 66 (44%) belonged to the phylogroup B1, followed by 23 (15.33%) to phylogroup A. Among 38 E. coli isolates carrying colistin resistance gene mcr-2, 27 (71.05%) isolates belonged to phylogroup B1, followed by 4 (10.52%) isolates to phylogroup A. The results suggest that E. coli phylogroups B1 and A harboring plasmid-mediated quinolone and colistin resistance genes are predominant in the seafood supply chain.
Adaptive Navigation in Collaborative Robots: A Reinforcement Learning and Sensor Fusion Approach
Authors: Tiwari Rohit , Srinivaas A. , Velamati Ratna Kishore
Published: January 2025

This paper presents a new approach for enhancing autonomous vehicle navigation and obstacle avoidance based on the integration of reinforcement learning with multiple sensors for navigation. The proposed system is designed to enable a reinforcement learning decision algorithm capable of making real-time decisions in aiding the adaptive capability of a vehicle. This method was tested on a prototype vehicle with navigation based on a Ublox Neo 6M GPS and a three-axis magnetometer, while for obstacle detection, this system uses three ultrasonic sensors. The use of a model-free reinforcement learning algorithm and use of an effective sensor for obstacle avoidance (instead of LiDAR and a camera) provides the proposed system advantage in terms of computational requirements, adaptability, and overall cost. Our experiments show that the proposed method improves navigation accuracy substantially and significantly advances the ability to avoid obstacles. The prototype vehicle adapts very well to the conditions of the testing track. Further, the data logs from the vehicle were analyzed to check the performance. It is this cost-effective and adaptable nature of the system that holds some promise toward a solution in situations where human intervention is not feasible, or even possible, due to either danger or remoteness. In general, this research showed how the application of reinforcement learning combined with sensor fusion enhances autonomous navigation and makes vehicles perform more reliably and intelligently in dynamic environments.
Approximation Characteristics of Weighted Sobolev Spaces on Sphere in Different Settings
Authors: Qiu Jiayi , Chen Guanggui , Xu Yanyan , Luo Ying , Ren Hang
Published: January 2025

This article primarily examines the approximation properties of a weighted Sobolev space W2,κr defined on a sphere Sd−1 equipped with Gaussian measures. Specifically, this study focuses on both the average case and probabilistic case settings. The exact asymptotic orders of the Gel’fand n-width and the linear n-width of W2,κr on Sd−1 are derived for these settings, providing a comprehensive understanding of their approximation characteristics.
Topic Analysis of the Literature Reveals the Research Structure: A Case Study in Periodontics
Authors: Galli Carlo , Colangelo Maria Teresa , Meleti Marco , Guizzardi Stefano , Calciolari Elena
Published: January 2025

Periodontics is a complex field characterized by a constantly growing body of research, which poses a challenge for researchers and stakeholders striving to stay abreast of the evolving literature. Traditional bibliometric surveys, while accurate, are labor-intensive and not scalable to meet the demands of such rapidly expanding domains. In this study, we employed BERTopic, a transformer-based topic modeling framework, to map the thematic landscape of periodontics research published in MEDLINE from 2009 to 2024. We identified 31 broad topics encompassing four major thematic axes—patient management, periomedicine, oral microbiology, and implant-related surgery—thereby illuminating core areas and their semantic relationships. Compared with a conventional Latent Dirichlet Allocation (LDA) approach, BERTopic yielded more contextually nuanced clusters and facilitated the isolation of distinct, smaller research niches. Although some documents remained unlabeled, potentially reflecting either semantic ambiguity or niche topics below the clustering threshold, our results underscore the flexibility, interpretability, and scalability of neural topic modeling in this domain. Future refinements—such as domain-specific embedding models and optimized granularity levels—could further enhance the precision and utility of this method, ultimately guiding researchers, educators, and policymakers in navigating the evolving landscape of periodontics.