bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Gender Differences in Falls and Mobility Patterns Among Older Adults in Lebanon
Authors: Khatib Sarah El , Malham Carmela Bou , Sacre Hala , Rassy Rachelle , Hajj Aline , Salameh Pascale , Saadeh Danielle
Published: July 2024

Introduction:
Falls represent a significant public health concern affecting the elderly, yet epidemiological studies within Lebanese institutions are scarce. This study aimed to explore gender differences in falls and mobility patterns and assess causes, potential risks, and protective factors against falls among institutionalized elderly in the Chouf district, Lebanon.
Methods
This cross-sectional pilot study involved an elderly healthcare institution. Data were collected using an anonymous, custom-designed questionnaire and patient medical records. Fall risk was evaluated with the Tinetti Balance and Gait Assessment, the Timed Up and Go Test, the Morse Fall Assessment, and other tools. Relative risks were estimated using odds ratios (OR), and logistic regression was stratified by gender to control confounders and assess the associations between fall episodes and potential risk and protective factors.
Results
This study included 300 institutionalized elderly aged 65 years and older, with 57.7% females. The mean age was 79.27 ± 7.61. Among the participants, 197 (65.7%) reported at least one fall in the past twelve months, with a higher prevalence among women compared to men (69.9% vs. 59.8%). Elderly women exhibited higher levels of depression and consumed more sleeping pills and mood-enhancing medications, which were positively associated with increased falls (p = 0.003). Among elderly men, unsteady walking was positively associated with the history of falls (p = 0.004).
Conclusion
This study found a higher incidence of falls among institutionalized women, possibly associated with the intake of sleeping pills and mood stabilizers. These findings have positive implications for future research in Lebanon and neighboring countries, with the potential to inform preventive measures to reduce falls among the elderly.
Be Aware of Your Text Messages: Fraud Attempts Identification Based on Semantic Sequential Learning for Financial Transactions through Mobile Services in Bangladesh
Authors: Khushbu Sharun Akter , Jaigirdar Fariha Tasmin , Anwar Adnan , Tuhin Ohidujjaman
Published: July 2024

The growth of mobile financial services over the last decade is well accepted by the people of Bangladesh. However, although reported here and there, a complete understanding of illegal payments and fraudulent transactions is still missing. This paper studies one of the popular and experienced financial transaction services of Bangladesh, Bkash, to identify fraudulent text messages through the service. We propose an improved classification method for fraudulent messages through feature extraction and a hybrid deep learning (DL) approach with ML, which combines a convolutional neural network with sequential learning, referred to as the customized Bkash fraud semantic sequential learning (CBF-SSL) model. Seven machine-learning classifiers and five deep-learning sequential models are experimentally evaluated within the hybrid classifier. The performance of the fraud detection system is assessed using the loss function and confusion matrix on a dataset of 500 Bengali text messages. The performance evaluation demonstrates that the hybrid model of convolution neural network (CNN) using long short-term memory (LSTM) outperforms all other classifiers with the lowest error 1 rate of 0.2532%, the highest F1-measure of 75.00% with the highest test accuracy. The proposed text features in combination with CNN and LSTM prove to be highly effective in detecting fraudulent messages.
A novel Federated Learning method with Domain Adaptation and Model Selection for Intrusion Detection
Authors: Li Xiaoyu , Su Kai , Liu Jingjing , Wu Weifei , Bao Liying
Published: July 2024

At present, the intrusion detection data of a single organization is insufficient, the intrusion detection data of each organization cannot meet the conditions of independent and identical distribution, and the distribution of each organization in different geographical locations will also cause the transmission difficulties of data and data leakage problems, which poses a huge challenge to the existing intrusion detection methods based on machine learning. To remedy the problem, a novel Federated Learning Algorithm with Domain Adaptation and Model Selection for Intrusion Detection (FEDTLDAM) is proposed in this paper. FEDTLDAM uses the proposed transfer deep learning model under the federation learning framework to train the local learning model on each organization's local intrusion detection data (source domain) and the global model of the public server (target), and t the designed local model selection method was used to select the local model. Only the local model parameters that meet the conditions are uploaded to the public cloud server to share the knowledge of each organization model, improve the intrusion detection effect of the target model, and ensure the security and privacy of the data of each organization. The domain adaptation strategy of the transfer deep learning model not only considers the difference of distribution between marginal probability and conditional probability, but also utilized the designed weighted method to measure the importance of the above two distribution differences to improve the model learning effect. The model selection method reduces the influence of bad local models, reduces the communication overhead, and improves the global model detection performance. The proposed algorithm FEDTLDAM is verified by experiments on three intrusion detection datasets ISCX2012, NSL-KDD and CICIDS2017, and the results show that compared with the benchmark algorithms, the proposed method has significantly improved the detection accuracy, training efficiency and other key performance indicators. In addition, FEDTLDAM also has good ability of generalization and data privacy protection, and significant application potential in the field of network security.
Integrating Tagged Neutron Inspection with Explainable AI for Threat Material Identification
Authors: Shahabinejad Hadi , Sudac Davorin , Nad Karlo , Espagnon Isabelle , Foy Clotilde de Sainte , Perot Bertrand , Carasco Cedric , Sardet Alix , Friedmann Edwin , Poli Jean Philippe , Delgado Jessica , Pino Felix , Moretto Sandra , Mer Christine , Sannie Guillaume , Obhodas Jasmina
Published: July 2024

Here we present an innovative approach for detecting threat materials within a sealed container by integrating tagged fast neutron activation analysis with Explainable Artificial Intelligence (XAI). Two AI models, a Feed-Forward Neural Network (FFNN) and a Convolutional Neural Network (CNN), were developed to analyze the emitted gamma rays to identify materials like explosives and drugs based on depth profiles of carbon, nitrogen, and oxygen concentrations. XAI was applied to make the models' decision-making process transparent. The method is adaptable to various spectrometric analyses. We demonstrate its effectiveness using data obtained by the Rapidly Relocatable Tagged Neutron Inspection System (RRTNIS), which is irreplaceable for inspecting sealed cargo containers, despite challenges such as variable material placement, background noise, and shielding effects. Our approach successfully locates and categorizes threat materials, both alone and within surrounding materials, at various locations within sealed cargo containers.
DenseNet Structured Neural Network-based Chaos Prediction for Stepped-chamber Tapered Air Bearing System
Authors: Wang Cheng-Chi , Kuo Ping-Huan , Oshima Masahide , Hong Song-Wei
Published: July 2024

Stepped-chamber tapered air bearing (STAB) systems are advanced bearing arrangements designed for applications requiring superior stability at high rotational speeds, along with precise control and stiffness. These systems generate multidirectional supporting forces and offer higher stiffness, making them ideal for high-performance mechanical designs. Despite their advantages, STAB systems can exhibit chaotic motion due to factors like nonlinear pressure distributions, gas imbalances, and design flaws. To understand and control non-periodic motions, a comprehensive analysis is essential. Analytical methods, including dynamic trajectories, spectral responses, bifurcation diagrams, Poincaré maps, and Lyapunov indices, are employed. The study reveals that chaotic phenomena are sensitive to eccentricity and bearing number variations. The interplay of these factors is thoroughly examined. To address chaotic behavior, a DenseNet-structured neural network (DSNN) is developed. This computational framework predicts chaos by evaluating the maximum Lyapunov index of the STAB system. Comparative assessments demonstrate the superior predictive efficacy of the DSNN model, making it a robust tool for anticipating and managing chaotic behavior in STAB systems. These findings enhance our understanding of dynamic intricacies in STAB systems and provide practical design guidelines for industrial applications prioritizing precision, rotational speed, and stiffness.
Stereodynamics effects on van der Waals molecule formation through three-body recombination
Authors: Wang Yu , Pérez-Ríos Jesús
Published: July 2024

In this work, we present a study on the role of atomic configurations in forming van der Waals molecules through three-body recombination. Fixing the angle between the two momenta associated with the Jacobi vectors, we calculate the reaction probability for a specific configuration. In this way, we elucidate the nature of the total reaction probability in reactions X + He + He$\rightarrow$XHe + He, which is essential for understanding van der Waals molecules formation in molecular beams and buffer gas cells.
Use of social media increases the risk of anxiety depression globally: results from 113 countries
Authors: Ranabhat Chhabi Lal , Marion Jason W
Published: July 2024

Background
Generalized anxiety and depression is the initial stage of mental illness and reflects a mood disorder reflected in sadness, hopelessness, nervousness, and worry. There are different factors associated with general anxiety and depression (GAD). Together with basic demographic and economic factors, we observed the use of social media by GAD. The aim of this study is to explore globally the influence of social media on self-reported general anxiety and depression.
Methodology
We chose different factors associated with anxiety and depression affected for more than 2 weeks from the 2020 Wellcome Global Monitor from the available secondary data. The samples from each country are nationally representative of the resident population aged 15 and older with access to a phone in 113 countries. The research design process was completed by leading researchers and subject experts; cognitive testing was conducted in ten countries to ensure questions could be understood across countries and by various demographic groups; and pilot tests were conducted in 10 countries. Independent variables were demographic variables: age, gender, economics, education, employment status, belief factors, and trends in social media use. Univariate variables were presented in frequency and percentage; bivariate analysis was performed with cross-tabulation using the chi square test; and logistic regression was used among significant variables by adjusted odds ratios and 95% CI as multivariate analysis.
Results
The prevalence of self-reported generalized anxiety depression (GAD) was 20% out of 119,234 in 113 countries. More than 38.27% were between the ages of 30 and 49, with 51% being male, more than half having completed high school, and 27% falling into the 4th and 5th quintiles (rich group). Similarly, more than 63.4% were employed, 81.3% believed in science, 42.3% believed in traditional healers, and 81.5% used social media, which was significantly associated with self-reported GAD. Adjusted odds ratio (aOR) showed that young age (15–30) years 1.24 times, females 1.21 times, elementary and primary education 1.34 times, the poorest twenty 1.39 times, and those who use social media several times an hour are more likely to be GAD with reference to early old age, males, higher education, the richest twenty, and those who did not use social media in the past 30 days. At the same time, the older age group (65+), those who trusted science and traditional healers and did not use social media in the past 30 days, were less likely to be GAD.
Conclusions: There is an increasing risk of GAD worldwide, and young adults and females are more vulnerable. Excessive use of social media is a challenging and risky factor.
The association of lifestyle with cardiovascular and all-cause mortality based on machine learning: A Prospective Study from the NHANES
Authors: Guo Xinghong , Wu Jian , Ma Mingze , Tarimo Clifford Silver , Fei Fengyi , Zhao Lipei , Ye Beizhu
Published: July 2024

Background
It is currently unclear whether machine learning based methods using lifestyle factors can effectively predict the probability of all-cause mortality and cardiovascular disease mortality.
Method
A prospective cohort study was conducted using a nationally representative sample of adults aged 40 years or older, drawn from the US National Health and Nutrition Examination Survey from 2007 to 2010. The participants underwent a comprehensive in-person interview and medical laboratory examinations, and subsequently, their records were linked with the National Death Index for further analysis.
Result
Within a cohort comprising 7921 participants, spanning an average follow-up duration of 9.75 years, a total of 1911 deaths, including 585 cardiovascular-related deaths, were recorded. The model predicted mortality with an area under the receiver operating characteristic curve (AUC) of 0.848 and 0.829. Stratifying participants into distinct risk groups based on ML scores proved effective. All lifestyle behaviors exhibited an inverse association with all-cause and cardiovascular mortality. As age increases, the discernible impacts of dietary scores and sedentary time become increasingly apparent, whereas an opposite trend was observed for physical activity.
Conclusion
We develop a ML model based on lifestyle behaviors to predict all-cause and cardiovascular mortality. The developed model offers valuable insights for the assessment of individual lifestyle-related risks. It applies to individuals, healthcare professionals, and policymakers to make informed decisions.
Decision-Tree-Based Distributed Learning for IoT Devices
Authors: Yamashita Yui , Taya Akihito , Wada Takumi , Tobe Yoshito
Published: July 2024

Recently, people have known the concept of the Internet of Things (IoT). Moreover, they have widely used smart devices, such as smartphones and wearable devices, because they are getting smaller and easier to wear. These devices have many sensors so that they can collect many data and process these data using machine learning. Most studies processing sensing data use deep neural network (DNN). However, DNN is not suitable for smart sensing devices because of its high computational complexity. Therefore, this paper adopts ensemble learning of decision trees, especially random forest and gradient boost decision trees (GBDT), to obtain prediction models without many computational resources. In addition, machine learning requires a large amount of data to train highly accurate prediction models. An easy way to gather various data is by uploading data obtained by each device to a server. Although this scheme can collect data easily, it requires the server to be maintained. Further, there is the challenge of the concentration of data and models. To solve these problems, a decentralized machine learning algorithm that works without a server should be developed. This paper proposes a decentralized ensemble learning algorithm for decision trees, with which multiple devices communicate directly with each other to share information without a server. The proposed method can be applied to situations where data are non-independent and identically distributed (non-IID).
Magneto electric switching Parameters in Single-Phase co-doped Multiferroic Material for Spintronic Applications: DFT Calculations
Authors: Tariq Muhammad , Chaudhary Kashif , Shaari Amiruddin , Ahmed Rashid , Yamusaa Shehu Aminu
Published: July 2024

Bismuth ferrite, BiFeO3 (BFO), has garnered significant attention as a thoroughly studied multiferroic material with promising prospects for future spintronic applications, owing to its unique combination of magnetic and electric polarization within a single-phase structure. Frist principle calculations were performed to examine the spin-polarized electronic and magnetic characteristics of BFO in the hexagonal phase, both in its pure state and when doped with lanthanum (La) at A-site and cobalt (Co) at B-site for magnetic switching parameters of spintronic RAM. The inclusion of La and Co atoms leads to alterations in spin polarization in both the spin-up and spin-down channels, resulting in an observed upsurge in the density of energy states (DOS). The observed changes in DOS across both spin channels have a pronounced effect on the magnetic moment. Introducing Co atoms into BFO, both individually and in combination with La, results in an enhancement of the magnetic moment. In the La-Co co-doped substitutional system, a significant volume magnetization of 1.26 (MA/cm) and a linear magneto-electric coupling coefficient of 2.63 ×10− 7 (sec m− 1) have been documented. Particularly, for data transmission within a nano-magnet of a spintronic device, Co-doped BFO demonstrates an exceptionally robust magnetic force of 0.05 T.
Genome-wide analysis of the PYL gene family and identification of PYL genes that respond to cold stress in Triticum boeoticum
Authors: Liu Xin , Zhao Xin , Shen Mang , Feng Ruizhang , Wei Qin , Zhang Minghu , Zhang Lianquan , Yan Yue
Published: July 2024

Abscisic acid (ABA) is a key plant hormone that regulates plant growth and stress responses. Pyrabactin resistance 1-like (PYR/PYL) proteins are ABA receptors involved in the initial steps of ABA signaling. Triticum boeoticum is an important germplasm resource for wheat. In this study, we identified 15 PYL genes from wild emmer wheat and found that they were distributed across five chromosomes. Based on phylogenetic analysis, we classified these genes into three subfamilies. Members of each subfamily have similar gene structures and contain a common motif. Furthermore, we found that their promoters have multiple hormone-related elements. We found 7, 33, and 49 collinear gene pairs in three different ploidy wheat species (T. urartu, T. turgidum and T. aestivum), indicating that PYL genes are relatively conserved during evolution. Additionally, interaction networks and miRNA targets were predicted, revealing interactions between PYL proteins and key components of the abscisic acid signaling network. miR9666b-3p may serve as a central factor in PYL involvement in the abscisic acid network. Through RNA-seq analysis and qPCR validation, four genes were found to potentially play a role in cold stress. These findings lay the groundwork for further research on PYL genes in T.boeoticum.
Adaptive Chaotic Gaussian Lens Snake Optimization Algorithm for Improved Cotton Field Sensor Coverage and Utilization
Authors: Ban Chenglong , Liu Xiang , Tian Min , Lu Zhonghua , Xiang Ruoxue , Zhou Jie
Published: July 2024

Soil Temperature Wireless Sensor Networks (STWSNs) are crucial in monitoring soil temperature in cotton fields. These networks assist farmers in optimizing agricultural activities based on real-time temperature data, thereby increasing cotton yields and reducing production costs. However, achieving maximum network coverage while minimizing the number of nodes remains a significant challenge. This paper proposes an Adaptive Chaotic Gaussian Lens Snake Optimization Algorithm (ACGLSOA) to address this issue. The ACGLSOA adaptively tunes parameters to enhance robustness and optimization accuracy. Additionally, it incorporates two new adaptive factors to improve local search capabilities and introduces enhanced chaos operators to refine the initial solution. The improved Gaussian operator and lens reflection mechanism extend the search space, thus enhancing global search performance. Experimental results show that the network coverage of the STWSN optimized by ACGLSOA reaches 98.91%, and the node utilization efficiency is 73.8%. Compared with the optimization results of the Snake Optimizer (SO), Artificial Bee Colony Algorithm (ABC), RIME Optimization Algorithm (RIME), and Particle Swarm Optimization Algorithm (PSO), the coverage of STWSN is improved by 9.74%, 8.24%, 14.45%, and 29.68%, respectively. Furthermore, the node utilization efficiency is improved by 7.27%, 6.15%, 10.78%, and 22.13%, respectively. Therefore, optimizing the node deployment of STWSNs through ACGLSOA enables the network to provide better coverage to the target area more cost-effectively.
Region Gradient-Guided Diffusion Model for Underwater Image Enhancement
Authors: shao Jinxin , Zhang Haosu , Miao Jianming
Published: July 2024

Underwater image enhancement (UIE) is a critical challenge in marine visual perception and underwater robotics due to complex aquatic environments that severely degrade image quality. This paper introduces the Region Gradient-Guided Diffusion Model (RGGDM), a novel framework that addresses the fundamental trade-off between local detail preservation and global consistency in UIE. RGGDM innovatively integrates a region gradient-guided mechanism with a hybrid Swin-ConvNeXt architecture, introducing a spatially adaptive denoising process governed by gradient discrepancies between input and target images. We propose a learnable parameter $\delta$ that dynamically modulates denoising intensity, focusing computational resources on semantically salient regions. Our approach is underpinned by rigorous mathematical analysis, demonstrating convergence properties under mild assumptions and providing theoretical guarantees for the model's stability and effectiveness. The synergistic combination of Swin Transformer and ConvNeXt enhances feature representation, significantly improving both perceptual quality and pixel-level accuracy. Extensive experiments on benchmark datasets demonstrate RGGDM's superior performance, consistently outperforming state-of-the-art methods across multiple evaluation metrics. Notably, RGGDM achieves a Peak Signal-to-Noise Ratio (PSNR) of 25.48 dB and an Underwater Image Quality Measure (UIQM) of 4.37 on the UIEB dataset. Furthermore, enhanced images show substantial improvements in downstream tasks such as SIFT feature matching, with an average increase of 132.19\% in matching points. These results underscore RGGDM's potential in advancing underwater visual perception and its broader implications for marine robotics and environmental monitoring applications.
Photonic generation of frequency agile LFM signals for ISAC systems
Authors: Zhou Yixiao , Zhao Shanghong , Li Xuan , Wang Guodong
Published: July 2024

A compact photonic method to generate frequency agile linearly frequency modulated (LFM) signals is proposed demonstrated by experiment and simulation. A Mach-Zehnder modulator driven by an LFM waveform train and an electrical controlled optical tunable delay line driven by a coding sequence is employed. According to time-frequency linear relationship of LFM signals, the initial frequency of the generated signals can be shifted by adjusting the introduced time delay. Experiments are carried out to verify the feasibility of the proposed generator. Frequency agile LFM signals under 2FSK and 4FSK modulation with symbol rate of 4 Msps and 8 Msps are successfully obtained. 0.15 m range resolution and 4 Mbps communication data rate are achieved with a 1-1.5 GHz driving LFM signal. This scheme features compact structure and excellent tunability, which are promising to find applications in anti-jamming ISAC systems.
Development of Bioplastics with Essential Oil for Bioactive Applications: Characterization and Evaluation
Authors: Raposo Ana Karoliny da Silva , Soares Ana Carolina Soares e , Santos Casi Santos dos , Silva Pablo Daniel Sena , Paixão Louryval Coelho , Brasil Gabrielle Vieira da Silva , Everton Gustavo Oliveira , Arévalo-Pinedo Aroldo , Firmino Wellysson da Cunha Araújo , Júnior Aluísio Alves Cabral , de Menezes Alan Silva , Ribeiro Geyse Adriana Corrêa , Filho Alla Kardec Duailibe Barros , Santana Audirene Amorin
Published: July 2024

Progress in the development of bioplastics has been widely studied, especially as an alternative to non-biodegradable products derived from petrochemicals, which have significant environmental impacts after disposal. One promising approach is the addition of essential oils of plant origin, aiming to impart bioactive properties to bioplastics and accelerate the healing of skin wounds. In this study, we used the casting method and an experimental design to investigate the characteristics of a bioproduct resulting from the combination of copaiba oil, glycerol alginate and a crosslinking agent. We evaluated parameters such as moisture content, water solubility, thickness, and water vapor permeability (PVA). The results showed variations in moisture levels (from 7.87% to 48.87%), water solubility (from 15.38% to 93.13%), thickness (from 0.060 to 0.165 mm) and PVA (from 1.784 to 8.018 g·mm/m²·day·kPa). With the use of optical and scanning electron microscopy (SEM) techniques to characterize the morphology of the films, while Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) were used to identify the presence of sesquiterpenes and caryophyllene, active components of copaiba oil in the selected films. The results showed the formation of crystals observed in the SEM, as well as crystalline peaks detected in the XRD, indicative of the desired structure. The FTIR analysis confirmed the effective incorporation of the bioactive compounds, suggesting that the films maintain the antioxidant and antibacterial properties of copaiba oil.
Zooming Fusion Network: A Multi-scale Approach for Precise Crowd Counting and Individual Localization in Low-Angle Scenarios
Authors: Liu Yiran , Li Yu , Zhang Qi , Liu Chengao , Guan Yu , Jiao Jianbin , Li Yuan
Published: July 2024

Crowd counting is pivotal in critical domains like security surveillance, urban planning, and traffic management. It is typically accomplished byaccurately detecting the number of individuals in a scene, thereby offering essential early warning and preventative mechanisms. Currently, the widely adopted method in the industry for dense crowd counting is based on density maps. However, this method relies on the use of Gaussian kernels to create intermediate representations (density maps), making it susceptible to the accumulation of background noise and loss of density. Moreover, it fails to provide precise individual location information, which hinders downstream tasks such as crowd movement trajectory analysis and abnormal behavior detection. To overcome these limitations, we propose a point-based framework named the Zooming Fusion Network (ZFNet), which integrates multi-scale inputs with an attention mechanism module to enhance the model's adaptability to complex scenes and its focus accuracy on crowd regions.. To validate the effectiveness of the proposed method, we conduct experiments on two public datasets. The results demonstrate that ZFNet achieves leading performance, compared to other existing state-of-the-art crowd counting methods. Furthermore, to address the lack of low-angle scenes in public datasets, we introduce a LIB_CC_500 dataset, specifically tailored for low-angle crowd counting. LIB_CC_500 The model's performance is validated on this new dataset, with results indicating its good generalization capabilities.
Electron transfer mediated contaminant activates periodate to generate 1O2 by charge-confined single-atom catalyst
Authors: Zou Jianping , Tang Qianqian , Wu Bangxiang , Huang Xiaowen , Ren Wei , Liu Lingling , Tian Lei , Chen Ying , Zhang Longshuai , Sun Qing , Kang Zhibing , Ma Tianyi
Published: July 2024

The electron transfer process (ETP) is able to avoid the redox cycling of catalysts by capturing electrons from contaminants directly. However, the ETP usually leads to the formation of oligomers and the reduction of oxidants to anions. Herein, the charge-confined Fe single-atom catalyst (Fe/SCN) with Fe-N3S1 configuration was designed to achieve ETP-mediated contaminant activation of the oxidant by limiting the number of electrons gained by the oxidant to generate 1O2. The Fe/SCN-activate periodate (PI) system shows excellent contaminant degradation performance due to the combination of ETP and 1O2. Experiments and DFT calculations show that the Fe/SCN-PI* complex with strong oxidizing ability triggers the ETP, while the charge-confined effect allows the single-electronic activation of PI to generate 1O2. In the Fe/SCN + PI system, the 100% selectivity dechlorination of ETP and the ring-opening of 1O2 avoid the generation of oligomers and realize the transformation of large-molecule contaminants into small-molecule biodegradable products. Furthermore, the Fe/SCN + PI system shows excellent anti-interference ability and application potential. This work pioneers the generation of active species using ETP’s electron to activate oxidants, which provides a new perspective on the design of single-atom catalysts via the charge-confined effect.
Evaluation of Stroke-Related Dysphagia using surface electromyographic biofeedback and their management by Related Exercise
Authors: Yang Yuan , Zhu Zhang , Star Sparkle
Published: July 2024

Introduction: Poststroke oropharyngeal dysphagia increases pneumonia risk and lowers life quality. Speech therapy uses unfamiliar tasks to change habits. The repeatability of tests limits the use of precise feedback for motor learning. Neuromuscular biofeedback from surface electromyography (sEMG) benefits muscle function. In dysphagia therapy, biofeedback improves control, engagement, and brain activation. Biofeedback's efficacy in dysphagia is unclear, however, swallow (ES) exercises are advised.
Aims and Objectives: This study examines the feasibility of using surface electromyography (sEMG) biofeedback to assess stroke-related dysphagia and guide exercise-based treatment.
Method: From September 2022 to August 2023, a Chinese hospital observed healthy volunteers using the Functional Oral Intake Scale (FOIS) to determine dysphagia severity. Participants were randomly assigned to biofeedback or non-biofeedback activities during the Effortful Swallow exercise in two sessions to verify its repeatability and applicability. Regular and effortful swallowing was examined using neck electrode sEMG data and questionnaire feedback.
Result: Table 1 shows demographics for 30 stroke patients and 40 healthy controls. Age variability is shown by stroke patients' median age of 74.5 years and controls' 75.00. Both categories have more men. Healthy and stroke participants have different sEMG biofeedback questionnaire preferences, as shown in Table 2. Figure 1 shows age-related sEMG amplitude changes during effortful swallowing. Figure 2 shows how feedback helps both groups swallow. Figure 3 illustrates that electromyographic biofeedback increases swallowing activity in healthy people, suggesting therapeutic potential that needs additional study.
Conclusion: In conclusion, sEMG biofeedback may improve muscle engagement and patient motivation in stroke dysphagia treatment, warranting future investigations.
Burst-like swarms and periodical VT events in the accelerating unrest phase of Campi Flegrei caldera (2021-2024)
Authors: Macedonio Giovanni , Giudicepietro Flora , Avino Rosario , Sessa Eliana Bellucci , Bevilacqua Andrea , Bonano Manuela , Caliro Stefano , Casu Francesco , De Cesare Walter , De Luca Claudio , De Martino Prospero , Traglia Federico Di , Vito Mauro Di , Dolce Mario , Esposito Antonietta , Lanari Riccardo , Manunta Michele , Minopoli Carmine , Tobar Fernando Monterroso , Neri Augusto , Ricciolino Patrizia , Rufino Francesco , Santi Alessandro , Scarpato Giovanni , Striano Pasquale , Tramelli Anna , Chiodini Giovanni
Published: July 2024

Since 2021, peculiar seismic sequences became evident and frequent in Campi Flegrei caldera (Italy), while deformation, seismicity and gas emission showed an acceleration. We distinguished burst-like swarms and periodical VT sequences. The earthquakes of both types of sequences resulted located in an area that includes the main hydrothermal field, and a zone affected by a geodetic anomaly, which clearly appeared in 2021. Burst-like swarms (max Md = 4.4) are accompanied by a pseudo-tremor, suggesting a mechanism involving near-continuous brittle failure. The periodical VT sequences are shallow and appear linked to the dynamics of the Mt Olibano lava dome, which deforms non-uniformly compared to the rest of the caldera and coincides with the geodetic anomaly. This peculiar seismicity, described in the Campi Flegrei for the first time in this study, has been associated with phreatic explosions and critical phases of unrest in other volcanoes, and currently characterizes the rapidly evolving state of activity of this high-risk volcano.
A study of Mohalla clinic scheme in Delhi: Delivery of primary healthcare to poor people residing in urban areas.
Authors: Rizvi Tehmeena
Published: July 2024

Both the public and private healthcare systems in India offer services, however the poor and marginalised populations cannot afford the private systems due to their higher costs. India's public healthcare system is currently overwhelmed despite being largely free. Most of the poor/marginalised people living in Delhi are dependent on primary health care centres for minor ailments and for prolonged illnesses as well. Mohalla clinics were started as a flagship scheme for healthcare services by the Delhi Government in July 2015. The primary motive of these clinics was to make healthcare easily affordable and accessible. This scheme has become popular in Delhi and a number of other Indian states are trying to establish similar centres. This report indicates that the main beneficiaries of this scheme are women, children and elderly. The research on the Mohalla clinic scheme in Delhi was primarily conducted to understand the feasibility of this scheme, and also to understand the dynamics of primary, secondary and tertiary healthcare systems in India.
A novel experimental approach to the evaluation of thermal expansion parameters of solid materials
Authors: Altzoumailis A. F. , Kytopoulos V. N.
Published: July 2024

In this work a micromagnetic emission – aided experimental approach is presented by which the coefficients of thermal expansion (CTE) and related thermoplastics Young's as well as respective plastic moduli of various solids can optimally be evaluated. For this scope, certain well- established characteristics of stress (strain) – correlated ferromicromagnetic properties of Ni (nickel) material were used as basic- reference measuring parameters. In this context a well- determined Ni- based layer was produced by vapor deposition on the surface of tested substrate material. This layer in turn was utilized as a suitable sensor for its micromagnetic emission – response to stresses (strains) developed during simultaneous thermal cooling of Ni – layer and respective substrate. The substrate form of metallic oxides were prepared by suitable thermal oxidation treatment of the respective metal, where the desired quality and thickness of obtained oxide scale could be achieved with acceptable tolerance. As such, the reliability, versatility and conveniency of the proposed measuring technique was tested on the basis of titanium and nickel as well as three types of metallic oxides, i.e. MgO (magnesia) TiO2 ( rutile) and Mn3O4 (Hausmannite). This was possible by subjection of these materials to controlled thermal cooling procedure within given temperature ranges. In this way one can demonstrate that the obtained experimental data concerning the overall- average as well as instantaneous CTE of these materials are in reasonable agreement with those found in the related literature. It was also found that the order of magnitude of the evaluated thermoelastic and plastic moduli were also in reasonably agreement with data in the respective literature. It should, however, be mentioned that owing to the scarcity of detailed data on these parameters, a more systematic and reliable assessment of the obtained values could not be made.
Sports Events in the USSR as a Tool for Promoting Soviet Social Values (on the Example of the 1st Spartakiad of the Peoples of the USSR)
Authors: Tiguntsev Sergey A. ,   Irkutsk State Medical University
Published: July 2024

The author made an attempt to consider sports events in the system of propaganda of Soviet values as a research task. The 1st Spartakiad of the Peoples of the USSR in 1956 was used as an example, designed to demonstrate the sporting achievements of the Soviet society and to involve the broad masses of the population in sports. We made a review of legal documents of all-Union and regional significance aimed at preparing for the upcoming competitions. The stages and structure of the regional competitions within the framework of the Spartakiad are analyzed. Particular attention is paid to agitation and propaganda work in the region dedicated to the 1st Spartakiad of the peoples of the USSR. The role of holding sports and mass events, star relay races and the “Relay Race of Youth” in the promotion of sports in remote areas of the region is revealed. The importance of the regional councils of voluntary sports societies and the regional committee of the All-Union Leninist Young Communist League in organizing these events was emphasized. The results of the performance of national teams and individual athletes of the Irkutsk region at different stages of the Spartakiad of the Peoples of the USSR are analyzed in detail. The article summarizes already published sources on the topic under study and also it introduces into scientific circulation new data obtained on the basis of documents from the State Archives of the Irkutsk Region. A statistical analysis of the dynamics of the development of physical culture in the Angara region in the course of preparation for the 1st Spartakiad of the peoples of the USSR is given. The author substantiates the hypothesis that, thanks to the preparations for the Spartakiad in the Irkutsk region, it was possible to expand the propaganda of Soviet sports, update the material and technical base, improve the quality of personnel and increase the number of people involved in physical culture. Thus, sport became a significant element in the system of Soviet social values.
Dialogue Between Authorities and Believers: Prehistory of Ivolginsky Datsan Foundation
Authors: Batomunkueva Soelma R. ,   Institute for Mongolian, Buddhist and Tibetan Studies, Siberian Branch, Russian Academy of Sciences
Published: July 2024

The article is devoted to the early history of the Khambinsky sume temple better known as Ivolginsky datsan. The work is based on the documents from the State Archive of the Republic of Buryatia, which regards to its history. The author also attracted documents characterizing the events that relate to the period 1944–1946. We note that despite the fact that the foundation of the datsan fell on the difficult period of post-war times, believers and the clergy did a lot of work not only to found the temple but also to restore and relegalize the Buddhist religion in the BMASSR after the repressive policy of the Soviet state. As an important issue, the author singles out the patriotic appeal of Did Khambo Lama Khaidap Galsanov, which preceded these events, in which he called on believers to support the Motherland and to start raising funds for the defense fund. The article also contains information obtained during conversations with Bimba Lama Dorzhiev, who carefully keeps the memories of his fellow villagers, his elders, who were direct witnesses of the events of those days. Despite the fact that most of the archival documents mentioned in the article have already been published at different times, this article builds a chronology of events and documents of the first steps in the formation of the temple, with accompanying references to other documents that clarify some details. In addition, information from informants, despite its lack of evidence, and, moreover, some of them contradict official sources, have the right to be published for coverage of a wide audience. The article also presents some information about the personalities who took an active part in the founding of the sume, later called Ivolginsky datsan.
Chinese Migrants as a Social Group in Socio-Humanitarian Knowledge: Theory and Practice
Authors: Shchetkina Irina A. ,   Transbaikal State University, Jiang Dan Jiang Dan , Sundueva Dina B. ,   Transbaikal State University,   Transbaikal State University
Published: July 2024

The modern world is characterized by dynamism, changing social, economic, and political realities. Migration is becoming one of the phenomena developing rapidly due to new forms of communication, digital ways of transmitting information and interaction. The result of migration processes is the creation of social groups of migrants in the host country, which perform the functions of ensuring the adaptation of their members in a new social space for them. In this regard, the theoretical study of migrants as a social group, the description of the functional characteristics of Chinese migrants as a social group is relevant. The purpose of the article is to identify in scientific concepts and social reality the main characteristics and functions of migrants as a social group, to highlight the system-forming features of the social group of Chinese migrants. In the article, social groups are considered as associations of people interacting with each other in the course of their life on the basis of tional and innovative values, norms and rules of behavior, associations of people performing certain functions in society. As a result of the conducted research, the system-forming features of the social group of Chinese migrants are identified, including interaction, consideration of oneself as a member of this social group, development of norms and rules of behavior, common goals and objectives of activity, etc. The study showed that the social groups of Chinese migrants mean diasporas, social communities, enclaves. The theoretical analysis of the social group allows us to conclude that there is no unified understanding of the concept of “social group” in the scientific literature. This is determined by the dynamism of the social reality itself, which makes certain adjustments to the research of the social group, as well as by the constant change in the role of social groups in the space of their life activity
Herbal Medicine as an Adjunct in the Treatment of Periodontal Diseases - A Systematic Review
Authors: Abu Tamam Akram Nabil , Kukreja Bhavna Jha , Ramachandra Srinivas Sulugodu , Reddy M Sesha , Souza Jovita Lawrence D. , Abdelmagyd Hossam Abdelatty Eid
Published: July 2024

Background

In recent times, a shift has been observed among both researchers and dental patients towards opting for herbal remedies and products to address issues like dental caries, gingivitis, periodontitis, periimplantitis, and dentin hypersensitivity. These herbal solutions encompass herbs, herbal constituents, formulations, and products derived from genuine plant components or other plant-derived materials.

Objective

This study aims to provide a comprehensive overview of the current body of literature regarding the added advantages of herbal medicinal products in managing periodontal and peri-implant conditions.

Methods

RCT published in English from 2013 till Sep 2023 in the terms “medicinal plants,” “plant medicine,” “dental herbs,” “medical herbs,” and “phytomedicine” were utilized to identify pertinent research papers. These search phrases were applied across the databases of PubMed, Scopus, and Web of Science. Case reports, case series, longitudinal studies, and retrospective analyses were not included. PRISMA standards were followed in this review.

Results

A total of fifteen (n=24) randomized clinical trials about herbal drugs and periodontal implications and three (n=3) trials on dental hypersensitivity were assessed. The trials assessed the use of various herbal products in treating periodontal and per-implant conditions.

Conclusion

Plant-based phytochemicals have anti-inflammatory effects that could be used as an alternative to treat periodontal and peri-implant conditions. Recent research on the different active components included in this study show significant improvements in the clinical parameters. To suggest them as substitutes for the non-herbal elements, more research is necessary.
SINTESIS DAN KARAKTERISASI NANOSELULOSA SEKAM PADI SEBAGAI BAHAN PENGUAT MATERIAL KEDOKTERAN GIGI
Authors: Noviyanti Agus Imam Dian , Budi Purnama Ryana , Sunendar Purwasasmita Bambang
Published: July 2024

Latar belakang: Tanaman padi merupakan tanaman pangan pokok yang banyak tumbuh di Indonesia. Limbah pertanian seperti sekam padi dapat dimanfaatkan untuk mendapatkan selulosa. Selulosa berukuran nano atau yang disebut nanoselulosa memiliki beberapa keunggulan diantaranya berskala nano, high surface area dan sifat optis yang baik sehingga partikel nanoselulosa dapat berpotensi digunakan sebagai penguat polimer dan aditif produk yang biodegradabel. Tujuan: untuk mensintesis dan mengkarakterisasi nanoselulosa berbahan sekam padi dengan menggunakan Fourier Transform Infrared (FTIR) dan Transmission Electron Microscopy (TEM). Metode: eksperimental kualitatif. Sampel penelitian berupa gel hasil sintesis nanoselulosa berbahan sekam padi yang diuji dengan menggunakan Transmission Electron Microscopy (TEM) untuk melihat morfologi mikrostruktur dan serbuk nanoselulosa diuji menggunakan Fourier Transform Infrared (FTIR) untuk melihat gugus fungsi yang terkandung dalam nanoselulosa sekam padi. Hasil: Hasil karakterisasi menggunakan Fourier Transform Infrared (FTIR) menunjukkan terbentuk selulosa dari olahan sekam padi, sedangkan hasil Transmission Electron Microscope (TEM) menunjukkan ukuran partikel selulosa dalam skala nanometer dan morfologi partikel yang berbentuk nano-whisker. Kesimpulan: Sintesis nanoselulosa berbahan sekam padi dengan metode hidrolisis asam berhasil dilakukan dan diharapkan mampu memberikan potensi untuk meningkatkan sifat mekanis material kedokteran gigi.