bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Deformation of Metal Matrix on the Mechanical Properties of Poly(Ethylene Terephthalate) Inside It
Authors: Kechek’yan A. S. , Bazhenov S. L. , Monakhova K. Z. , Kurkin T. S.
Published: April 2024

The influence of different types of deformation of the metal matrix on mechanical behavior of the amorphous PET film upon its transverse compression in the ductile metal matrix has been investigated. Three deformation modes have been probed. In the first case, a disc-shaped polymer specimen has been put between two 5 mm thick discs of the lead–tin alloy and squeezed in the press. In the second and the third cases, planar elongation has been performed in the so called “dead channel”, i.e., the channel with fixed side walls, the film being elongated due to decrease in the width or thickness, respectively. The plots of true yield stress at different draw ratios have formed a common master curve. At high total draw ratio Λ, the true yield stresses have been close for the considered three types of drawing in the metal. At the draw ratio Λ 2.6, the neck has not appeared, and the specimen has been deformed uniformly. When the film in the channel is elongated due to the decrease in thickness at constant width, the specimen width has been mainly decreased during subsequent elongation in the testing machine. When the film in the channel is elongated due to the decrease in width at constant thickness, further elongation has mainly led to the decrease in the specimen thickness. The true stress Σ has been expressed as Σ = Σ0 + KΛ3, with K being a constant. Deformation of the polymer in the channel occurred with the formation of shear bands. At the preliminary draw ratio Λ = 1.82, the bands have been oriented at the angle 21.5° with respect to the stretching axis. The planar elongation has led to abnormally strong deformation softening of the polymer. The drawing has been accompanied by an increase in the elasticity modulus of the polymer. The obtained results have suggested that the macromolecules orientation is the main reason for strain hardening of the polymer.
MitoH3: Mitochondrial Haplogroup and Homoplasmic/Heteroplasmic Variant Calling Pipeline for Alzheimer’s Disease Sequencing Project
Authors: Zhu Congcong , Tong Tong , Farrell John J. , Martin Eden R. , Bush William S. , Pericak-Vance Margaret A. , Wang Li-San , Schellenberg Gerard D. , Haines Jonathan L. , Lunetta Kathryn L. , Farrer Lindsay A. , Zhang Xiaoling
Published: April 2024

Background:

Mitochondrial DNA (mtDNA) is a double-stranded circular DNA and has multiple copies in each cell. Excess heteroplasmy, the coexistence of distinct variants in copies of mtDNA within a cell, may lead to mitochondrial impairments. Accurate determination of heteroplasmy in whole-genome sequencing (WGS) data has posed a significant challenge because mitochondria carrying heteroplasmic variants cannot be distinguished during library preparation. Moreover, sequencing errors, contamination, and nuclear mtDNA segments can reduce the accuracy of heteroplasmic variant calling.

Objective:

To efficiently and accurately call mtDNA homoplasmic and heteroplasmic variants from the large-scale WGS data generated from the Alzheimer’s Disease Sequencing Project (ADSP), and test their association with Alzheimer’s disease (AD).

Methods:

In this study, we present MitoH3—a comprehensive computational pipeline for calling mtDNA homoplasmic and heteroplasmic variants and inferring haplogroups in the ADSP WGS data. We first applied MitoH3 to 45 technical replicates from 6 subjects to define a threshold for detecting heteroplasmic variants. Then using the threshold of 5% ≤variant allele fraction≤95%, we further applied MitoH3 to call heteroplasmic variants from a total of 16,113 DNA samples with 6,742 samples from cognitively normal controls and 6,183 from AD cases.

Results:

This pipeline is available through the Singularity container engine. For 4,311 heteroplasmic variants identified from 16,113 samples, no significant variant count difference was observed between AD cases and controls.

Conclusions:

Our streamlined pipeline, MitoH3, enables computationally efficient and accurate analysis of a large number of samples.
A Scoping Survey to Inform Design of Digital Dementia Risk Reduction Interventions for Adults Concerned about their Cognitive Health
Authors: Amos Jessica G. , Zheng Lidan , Eramudugolla Ranmalee , Andrews Sophie C. , Anstey Kaarin J.
Published: April 2024

Background:

Digital dementia risk reduction interventions are cost-effective and scalable. However, it is unknown how they are perceived by people already experiencing cognitive concerns or decline.

Objective:

To understand the current use, interest, and preferences for online learning courses and interest in learning about factors influencing brain health and dementia risk among adults ≥45. To explore potential differences between individuals experiencing cognitive concerns and those without.

Methods:

Adults aged 45 and older completed a survey on technology use and healthy ageing ( n = 249, Mean age = 65.6, 76.3% female). The Memory Assessment Clinic-Questionnaire was used to assess subjective memory decline, and 153 participants met the study criteria for cognitive concerns (≥25).

Results:

Almost all participants (98.4%) reported using two or more digital devices, and 51.8% reported increasing device usage following COVID-19. Most (92.1%) were interested in learning about healthy living and memory within an online course, and over 80% indicated a high interest in learning about dementia risk factors. People with cognitive concerns were more likely to report using a ‘routine or system’ to aid memory than people without (82.4% versus 62.9%, p = 0.001). However, no significant difference was found in technology use, course preferences, or interest in learning about different risk factors.

Conclusions:

We conclude that adults 45 years and over are interested in online methods for learning about brain health and offer unique insights into adapting dementia prevention programs for cognitive concerns.
Weakness Thresholds Are Differentially Linked to Cognitive Function by Obesity Status in Older Americans
Authors: Batesole Joshua , Tomkinson Grant R. , Erickson Kirk I. , Jurivich Donald , Lang Justin J. , McGrath Brenda M. , Robinson-Lane Sheria G. , Smith Ashleigh E. , McGrath Ryan
Published: April 2024

Background:

Weakness can be operationalized with several thresholds, which in turn, could impact associations with cognitive impairment when considering obesity status.

Objective:

We examined the associations of absolute, normalized, and collective weakness thresholds on future cognitive impairment by obesity status in older adults.

Methods:

We performed a secondary data analysis on the 2006–2018 waves of the Health and Retirement Study. A spring-type dynamometer collected handgrip strength (HGS). Males were categorized weak if their HGS was <35.5-kg (absolute), <0.45-kg/kg (body mass normalized), or <1.05-kg/kg/m2 (body mass index (BMI) normalized), while females were defined as weak if their HGS was <20.0-kg, <0.337-kg/kg, or <0.79-kg/kg/m2. The modified Telephone Interview of Cognitive Status examined cognitive function. Persons scoring ≤10 had a cognitive impairment. Obesity was categorized as BMI ≥30 kg/m2.

Results:

We included 7,532 and 3,584 persons aged ≥65-years living without and with obesity, respectively. Those without obesity but beneath the absolute weakness threshold had 1.54 (95% confidence interval (CI): 1.24–1.91) greater odds for future cognitive impairment. Persons with obesity and beneath each threshold also had greater odds for future cognitive impairment: 1.89 (95% CI: 1.28–2.78) for absolute, 2.17 (95% CI: 1.02–4.62) for body mass normalized, and 1.75 (95% CI: 1.10–2.80) for BMI normalized. Older Americans without obesity but underneath all the weakness thresholds had 1.32 (95% CI: 1.00–1.74) greater odds for impairment in cognitive function, while persons with obesity had 2.76 (95% CI: 1.29–5.93) greater odds.

Conclusions:

There should be consideration for how body size and different weakness thresholds may influence future cognitive outcomes.
Effect of whole-body vibration on postural stability in young adults with generalized joint hypermobility: A comparative study
Authors: Ewertowska Paulina , Formella Oskar , Poniatowski Łukasz , Zielińska Afrodyta , Krzysztofik Michał , Czaprowski Dariusz
Published: April 2024

BACKGROUND: Whole-body vibration (WBV) is being used in rehabilitation and sport. Studies confirm its positive impact on muscle strength and power or regulating muscle hypertension. However, there are some uncertainties regarding its influence on postural stability. This issue seems particularly interesting in the case of individuals with generalized joint hypermobility (GJH), for whom proprioceptive training and muscle strengthening exercises are recommended while techniques that decrease muscle tension are not advised. OBJECTIVE: The aim of the study was to evaluate the acute effect of WBV on postural stability in adults with GJH. METHODS: 60 participants were categorized into the groups: 1) hypermobility with vibration (GJH+WBV), 2) hypermobility without vibration (GJH–WBV), 3) control group with vibration (CTRL+WBV), 4) control group without vibration (CTRL–WBV). The first and the third group completed WBV (frequency: 15 Hz and 30 Hz, amplitude 3 mm, 3 × 3 min). The second and fourth groups participated only in measurement sessions. GJH was assessed using the Beighton test. Postural stability was measured as the overall stability index (OSI) on the Biodex Balance System on the stable and unstable platform with open and closed eyes. Measurements were taken before and after WBV for two weeks. RESULTS: At a frequency of 15 Hz, a significant time effect was observed for measurements Before and After in CTRL–WBV on the stable platform with open eyes (p= 0.012) and on the unstable platform with closed eyes (p= 0.000) for the GJH+WBV and CTRL+WBV groups. There were no significant interactions (p> 0.05) between factors. At a frequency of 30 Hz, there was a significant time effect Before and After (p= 0.047) on the stable platform with open eyes, but no interaction was found between factors (p= 0.835). CONCLUSION: There is no positive acute effect of WBV on postural stability in adults with and without GJH.
Relationship between onset of trunk muscle activities and pelvic kinematics in individuals with and without chronic low back pain
Authors: Nakata Akimi , Osuka Satoshi , Ishida Tomoya , Saito Yuki , Koshino Yuta , Samukawa Mina , Kasahara Satoshi , Tohyama Harukazu
Published: April 2024

BACKGROUND: Lumbopelvic movement patterns during prone hip extension has been proposed as a clinical screening method for trunk muscle dysfunction in patients with chronic low back pain (CLBP). However, correlations between trunk muscle onset and pelvic kinematics have not been investigated. OBJECTIVE: To examine the correlation between trunk muscle onset and pelvic kinematics during prone hip extension in participants with CLBP. METHODS: Fifteen patients with CLBP and 15 healthy individuals participated. We evaluated the muscle activities of the lumbar multifidus, the longissimus, and the semitendinosus via electromyogram and the displacement angles of the pelvic tilt, oblique and rotation. RESULTS: The onset of the multifidus at the ipsilateral side of hip extension was significantly delayed in the patients with CLBP compared to the control group (P< 0.001). The onset of the ipsilateral multifidus in the control group was significantly correlated with increased anterior pelvic tilt angle (P= 0.019, r= 0.597), whereas no significant correlation was observed in the CLBP group (P= 0.810, r=-0.068). CONCLUSION: The results suggest that pelvic kinematics during prone hip extension does not predict the delayed trunk muscle onset in patients with CLBP.
PRDM1 rs2185379, unlike BRCA1, is not a prognostic marker in patients with advanced ovarian cancer
Authors: Horackova Klara , Vocka Michal , Lopatova Sarka , Zemankova Petra , Kleibl Zdenek , Soukupova Jana
Published: April 2024

BACKGROUND: Ovarian cancer (OC) is mostly diagnosed in advanced stages with high incidence-to-mortality rate. Nevertheless, some patients achieve long-term disease-free survival. However, the prognostic markers have not been well established. OBJECTIVE: The primary objective of this study was to analyse the association of the suggested prognostic marker rs2185379 in PRDM1 with long-term survival in a large independent cohort of advanced OC patients. METHODS: We genotyped 545 well-characterized advanced OC patients. All patients were tested for OC predisposition. The effect of PRDM1 rs2185379 and other monitored clinicopathological and genetic variables on survival were analysed. RESULTS: The univariate analysis revealed no significant effect of PRDM1 rs2185379 on survival whereas significantly worse prognosis was observed in postmenopausal patients (HR = 2.49; 95%CI 1.90–3.26; p= 4.14 × 10 - 11) with mortality linearly increasing with age (HR = 1.05 per year; 95%CI 1.04–1.07; p= 2 × 10 - 6), in patients diagnosed with non-high-grade serous OC (HR = 0.44; 95%CI 0.32–0.60; p= 1.95 × 10 - 7) and in patients carrying a gBRCA1 pathogenic variant (HR = 0.65; 95%CI 0.48–0.87; p= 4.53 × 10 - 3). The multivariate analysis interrogating the effect of PRDM1 rs2185379 with other significant prognostic factors revealed marginal association of PRDM1 rs2185379 with worse survival in postmenopausal women (HR = 1.54; 95%CI 1.01–2.38; p= 0.046). CONCLUSIONS: Unlike age at diagnosis, OC histology or gBRCA1 status, rs2185379 in PRDM1 is unlikely a marker of long-term survival in patients with advance OC.
GameTable COST action: kickoff report
Authors: Piette Éric , Crist Walter , Soemers Dennis J.N.J. , Rougetet Lisa , Courts Summer , Penn Tim , Morenville Achille
Published: April 2024

The GameTable COST Action kickoff, focusing on “Computational Techniques for Tabletop Games Heritage,” took place at Leiden University in the Pieter de la Court Building from January 29th to 30th, 2024. This event aimed to convene researchers from diverse backgrounds involved in the Action, offering an opportunity to present an overview of the key research areas, share concrete case studies, and facilitate discussions and idea exchanges across fields that may not typically intersect, thereby enhancing the organization of the Action. This report provides a summary of the organization and discussions of the event, and future plans for GameTable.
CBDA: Chaos-based binary dragonfly algorithm for evolutionary feature selection
Authors: Liu Zhao , Wang Aimin , Bao Haiming , Zhang Kunpeng , Wu Jing , Sun Geng , Li Jiahui
Published: April 2024

The goal of feature selection in machine learning is to simultaneously maintain more classification accuracy, while reducing lager amount of attributes. In this paper, we firstly design a fitness function that achieves both objectives jointly. Then we come up with a chaos-based binary dragonfly algorithm (CBDA) that incorporates several improvements over the conventional dragonfly algorithm (DA) for developing a wrapper-based feature selection method to solve the fitness function. Specifically, the CBDA innovatively introduces three improved factors, namely the chaotic map, evolutionary population dynamics (EPD) mechanism, and binarization strategy on the basis of conventional DA to balance the exploitation and exploration capabilities of the algorithm and make it more suitable to handle the formulated problem. We conduct experiments on 24 well-known data sets from the UCI repository with three ablated versions of CBDA targeting different components of the algorithm in order to explain their contributions in CBDA and also with five established comparative algorithms in terms of fitness value, classification accuracy, CPU running time, and number of selected features. The results show that the proposed CBDA has remarkable advantages in most of the tested data sets.
An evolutionary approach to extreme individual impact opinions based on time sunk costs
Authors: Feng Zhuo , Du Yajun , Huang Jiaming , Li Xianyong , Chen Xiaoliang , Xie Chunzhi
Published: April 2024

Large-scale studies indicate that the distinct approach to opinion fusion employed by extreme agents exerts a more potent influence on overall opinion evolution when compared to regular agents. The presence of extreme agents within the network tends to undermine the development of opinion neutrality, which is harmful to the guidance of online public opinion. Notably, prior research often overlooks the existence of opinion extreme agents in social networks. However, existing researches seldom consider the time sunk cost in the evolution of opinions. Building upon this foundation, we introduce a temporal dimension to the opinion evolution, integrating the time sunk cost with the opinion evolution process. Furthermore, we devise an agent partitioning method that categorizes agents into four states based on their opinion values: watch state, subjective state, firm state, and extreme state, with extreme state agents generally expressing radical opinions. We constructed an agent network based on the phenomenon of time sunk costs and proposed a model for the evolution of extreme opinions in this network. Our study found that the information sharing among extreme agents significantly influences the extremization of opinions in various networks. After restricting the exchange of opinions on extreme agents, the number of extreme agents in the network decreased by 40% to 50% compared to the initial situation. Additionally, we also discovered that imposing restrictions on extreme agents in the early stages can help increase the possibility of network opinions moving towards neutral positions. When restriction of extreme agents(REA) was performed at the beginning of the experiment compared to REA in the midway of the experiment, the final number of extreme state agents decreased by 15.57%. The results show that extreme agents have a great influence on the spread and evolution of extreme opinions on platforms.
Heart rate variability: Obtaining the stress score from SDNN values
Authors: Salazar-Martínez Eduardo , Naranjo-Orellana José , Sarabia-Cachadiña Elena
Published: April 2024

BACKGROUND:

Heart Rate Variability (HRV) is a non-invasive method of assessing the autonomic nervous system response during exercise and fatigue.

OBJECTIVE:

The aim of the study was to analyze the validity and feasibility of the stress score index (SS) calculated from SDNN values during exercise.

METHODS:

18 Men performed 2 running tests: 1) incremental exercise test; 2) 10-minute constant load test. Subjects underwent HRV analysis during the constant load test, before both tests, and afterward in a seated position at 3 intervals (0’–5’, 5’–10’, 10’–15’). The relationship between SDNN and SD2 was analyzed before, during, and after the test. SS was calculated as 1/SD2*1000. The Bland-Altman test analyzed the reliability of ESS. The bias, limits of agreement (LoA), standard deviation of difference, intraclass correlation (ICC), and person coefficient were calculated.

RESULTS:

The bias was 0.15 [Formula: see text] 2.54 (UperLOA: 2.54; LowerLOA: [Formula: see text]2.23). In all conditions, SD2 and SDNN showed a positive linear relationship ([Formula: see text]2 [Formula: see text] 0.986); SS and ESS were correlated; and SS and ESS described a positive linear relationship ([Formula: see text]2 [Formula: see text] 0.993).

CONCLUSIONS:

The SS index calculation from SDNN is a reliable alternative during exercise.
Comparison of upper and lower trapezius electromyographic activity during Y-raise exercise with and without isometric adduction in healthy volunteers
Authors: Hwang Byeong-Hun , Jeon In-Cheol
Published: April 2024

BACKGROUND:

Lower trapezius (LT) plays an important role in maintaining the stability of the scapula. Sufficient activation of LT can reduce the risk of rotator cuff tear and shoulder impingement syndrome. The Y-raise exercise has been recommended for effective LT activation. However, the upper trapezius (UT) can be co-activated during universal Y-raise exercise.

OBJECTIVE:

This study aimed to compare the activity of the UT, LT, and serratus anterior (SA) during Y-raise exercise with and without isometric adduction (IAD) using Thera-Band.

METHODS:

21 healthy males voluntarily participated in the study. The participants were asked to perform Y-raise exercise with and without IAD using Thera-Band. Surface electromyography was used to measure the muscle activity of UT, LT, and SA during Y-raise exercise with and without IAD. Paired t-test was used to analyze the significance of the muscle activity of UT, LT, and SA as well as the activity ratio of LT/UT and LT/SA. The significance level was set at [Formula: see text] 0.05.

RESULTS:

Compared with Y-raise exercise without IAD, the muscle activity of UT and SA decreased ([Formula: see text] 0.001 and [Formula: see text] 0.003, respectively), whereas that of LT increased ([Formula: see text] 0.038) during Y-raise exercise with IAD. Additionally, the activity ratio of LT/UT and LT/SA was greater during Y-raise exercise with IAD ([Formula: see text] 0.001 and [Formula: see text] 0.001, respectively).

CONCLUSION:

Y-raise exercise with IAD using Thera-Band is recommended as an efficient exercise to selectively activate the LT and increase the activity ratio of LT/UT and LT/SA.
Combined Unet and CNN image classification model for COVID disease detection using CXR/CT imaging
Authors: Haennah J.H. Jensha , Christopher C. Seldev , King G.R. Gnana
Published: April 2024

Accurate SARS-CoV-2 screening is made possible by automated Computer-Aided Diagnosis (CAD) which reduces the stress on healthcare systems. Since Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly contagious, the transition chain can be broken through an early diagnosis by clinical knowledge and Artificial Intelligence (AI). Manual findings are time and labor-intensive. Even if Reverse Transcription-Polymerase Chain Reaction (RT-PCR) delivers quick findings, Chest X-ray (CXR) imaging is still a more trustworthy tool for disease classification and assessment. Several studies have been conducted using Deep Learning (DL) algorithms for COVID-19 detection. One of the biggest challenges in modernizing healthcare is extracting useful data from high-dimensional, heterogeneous, and complex biological data. Intending to introduce an automated COVID-19 diagnosis model, this paper develops a proficient optimization model that enhances the classification performance with better accuracy. The input images are initially pre-processed with an image filtering approach for noise removal and data augmentation to extend the dataset. Secondly, the images are segmented via U-Net and are given to classification using the Fused U-Net Convolutional Neural Network (FUCNN) model. Here, the performance of U-Net is enhanced through the modified Moth Flame Optimization (MFO) algorithm named Chaotic System-based MFO (CSMFO) by optimizing the weights of U-Net. The significance of the implemented model is confirmed over a comparative evaluation with the state-of-the-art models. Specifically, the proposed CSMFO-FUCNN attained 98.45% of accuracy, 98.63% of sensitivity, 98.98% of specificity, and 98.98% of precision.
Frequency domain model-augmented feature space transferable attack
Authors: Shi Jing , Zhang Xiao-Lin , Wang Yong-Ping , Gu Rui-Chun , Xu En-Hui
Published: April 2024

Deep neural networks (DNNs) are susceptible to adversarial attacks, and one important factor is that adversarial samples are transferable, i.e., adversarial samples generated by a particular network may deceive other black-box models. However, existing transferable adversarial attacks tend to modify the input features of images directly without selection to reduce the prediction accuracy in the alternative model, which would enable the adversarial samples to fall into the model’s local optimum. Alternative models differ significantly from the victim model in most cases, and while simultaneously attacking multiple models may improve transferability, gathering numerous different models is more challenging and expensive. We simulate various models using frequency domain transformation to close the gap between the source and victim models and improve transferability. At the same time, we destroy important intermediate layer features that influence the decision of the model in the feature space. Additionally, smoothing loss is introduced to remove high-frequency perturbations. Extensive experiments demonstrate that our FM-FSTA attack generates more well-hidden and transferable adversarial samples, and achieves a high deception rate even when attacking adversarially trained models. Compared to other methods, our FM-FSTA improved attack success rate under different defense mechanisms, which reveals the potential threats of current robust models.
Hosoya polynomial and wiener index of Abid-Waheed graph (AW)a8 and (AW)a10
Authors: Meenakshi A. , Bramila M.
Published: April 2024

Molecular structures are characterised by the Hosoya polynomial and Wiener index, ideas from mathematical chemistry and graph theory. The graph representation of a chemical compound that has atoms as vertices and chemical bonds as edges is called a molecular graph, and the Hosoya polynomial is a polynomial related to this graph. As a graph attribute that remains unchanged under graph isomorphism, the Hosoya polynomial is known as a graph invariant. It offers details regarding the quantity of distinct non-empty subgraphs within a specified graph. A topological metric called the Wiener index is employed to measure the branching complexity and size of a molecular graph. For every pair of vertices in a molecular network, the Wiener index is the total of those distances. In this paper, discussed the Hosoya polynomial, Wiener index and Hyper-Wiener index of the Abid-Waheed graphs (AW)a8  and (AW)a10. This graph is similar to Jahangir’s graph. Further, we have extended the research work on the applications of the described graphs.
Interactive design of intelligent wearable products based on network communication technology
Authors: Lin Jiayi
Published: April 2024

At this stage, network communication technology is increasingly mature, and intelligent wearable products are also widely used in human daily life. Wearable products are popular with users because of their numerous types, complete functions and convenient services. Wearable products integrate interaction technology, and users can interact with products. However, how to improve the user’s interaction experience and reduce the user’s cognitive burden on the interaction interface is an urgent problem in the current product interaction design. Therefore, based on the analysis of the types and related technologies of wearable products, this paper made a specific analysis of the interaction design of wearable products, and established an interaction design model. At the same time, the wearable fall detection system was also tested by machine learning algorithm. The experimental results showed that the average test result of the algorithm in this paper was 87.39%, while the average test result of the traditional algorithm was 83.79%. In terms of the missed alarm rate of fall detection, the average test result of this algorithm was 6.4%, while the average test result of the traditional algorithm was 12.33%. In terms of fall detection sensitivity, the average test result of this algorithm was 92.50%, while the average test result of the traditional algorithm was 88.24%. Compared with traditional algorithms, this method performs better, with lower missed detection rate and higher sensitivity. Innovative combination of machine learning algorithm, through three-dimensional coordinate system, differentiation and vector sum formula, improves the accuracy and reliability of fall detection. In conclusion, the algorithm in this paper can effectively optimize the relevant performance of the system, thus improving the accuracy of the system’s fall detection.
DMS-yolov8 A gesture recognition algorithm based on improved yolov81
Authors: Zhan Huawei , Han Chengju , Li Junjie , Wei Gaoyong
Published: April 2024

Aiming at the problems of slow speed and low accuracy of traditional neural network systems for real-time gesture recognition in complex backgrounds., this paper proposes DMS-yolov8-a gesture recognition method to improve yolov8. This algorithm replaces the Bottleneck convolution module in the backbone network of yolov8 with variable row convolution DCNV2, and increases the feature convolution range without increasing the computation amount through a more flexible feeling field. in addition, the self-developed MPCA attention module is added after the feature output layer of the backbone layer, which improves the problem of recognizing the accuracy of difference gestures in complex backgrounds by effectively combining the feature information of the contextual framework, taking into account the multi-scale problem of the gestures in the image, this paper introduces the SPPFCSPS module, which realizes multi-feature fusion and improves real-time accuracy of detection. Finally, the model proposed in this paper is compared with other models, and the proposed DMS-yolov8 model achieves good results on both publicly available datasets and homemade datasets, with the average accuracy up to 97.4% and the average mAP value up to 96.3%, The improvements proposed in this paper are effectively validated.
LR3S: A lightweight semantic segmentation model for road scenes based on improved DeepLabV3+
Authors: Zhao Xianhao , Wang Mingyang , Xin Chaoqun , Wang Xianjie
Published: April 2024

In the field of autonomous driving, driving systems need to understand and quickly respond to changes in road scenes, which makes it equally important to enhance the accuracy and real-time performance of semantic segmentation tasks in road scenes. This article proposes a lightweight road scene semantic segmentation model LR3S that integrates global contextual information based on the DeepLabV3+ framework. LR3S utilizes a lightweight GhostNetV2 network as the backbone to capture rich semantic information in images, and uses ASPP_eSE module to enhance the capture of multi-scale and detail level semantic information. In addition, a lightweight CARAFE upsampling operator is utilized to upsample feature maps, taking advantage of CARAFE’s large receptive field and low computational cost to prevent the loss of fine-grained features and ensure the integrity of semantic information. Experimental results demonstrate that LR3S achieves an MIoU of 74.47% on the Cityscapes dataset and obtains an MIoU of 76.01% on the PASCAL VOC 2012 dataset. Compared to baseline semantic segmentation models, LR3S significantly reduces the parameter amount while maintaining segmentation accuracy, achieving a good balance between model accuracy and real-time performance.
Secure and fine-grained access control of electronic health record using SAPCP-ABE technique in cloud
Authors: Pandiyarajan Abinaya , Jagatheesaperumal Senthil Kumar , Thayanithi Manonmani
Published: April 2024

This study explores how Electronic Health Records (EHR) might be transformed in the context of the rapid improvements in cloud computing and IoT technology. But worries about sensitive data security and access management when it moves to large cloud provider networks surface. Even if they are secure, traditional encryption techniques sometimes lack the granularity needed for effective data protection. We suggest the Secure Access Policy – Ciphertext Policy – Attribute-based Encryption (SAPCP-ABE) algorithm as a solution to this problem. This method ensures that only authorized users may access the necessary data while facilitating fine-grained encrypted data exchange. The three main phases of SAPCP-ABE are retrieval and decoding, where the system verifies users’ access restrictions, secure outsourcing that prioritizes critical attributes, and an authenticity phase for early authentication. Performance tests show that SAPCP-ABE is a better scheme than earlier ones, with faster encryption and decryption speeds of 5 and 5.1 seconds for 512-bit keys, respectively. Security studies, numerical comparisons, and implementation outcomes demonstrate our suggested approach’s efficacy, efficiency, and scalability.
Customized employment for transition-age youth in state vocational rehabilitation program PY2017 - PY2020: Analysis of service outcomes and related factors
Authors: Kim Jaeyoung , Park Sara , Castruita-Rios Yazmin , Weathers Marcus , Park Mirang , Inge Katherine , Riesen Tim , Keeton Beth , Avellone Lauren , Tansey Timothy
Published: April 2024

BACKGROUND: Customized employment (CE) is positively correlated with competitive integrated employment (CIE) outcomes and potentially supports transition-age youth in achieving sustainable employment. OBJECTIVE: This study examines the employment outcomes and related factors for transition-age youth with disabilities who received CE services through state vocational rehabilitation agencies (SVRAs) and their vendors from program year 2017 to 2020. METHODS: Employing a combination of descriptive analysis, binary logistic and multiple regression, chi-square tests, and t-tests, the study investigates the demographics, potential barriers, and vocational rehabilitation (VR) services received by the research sample using the RSA-911 dataset. RESULTS: The sample comprised 672 individuals with a mean age of 22.30 years. The most prevalent barrier to employment among CE participants was long-term unemployment, while Supplemental Security Income (SSI) was the most common social security benefit. Furthermore, only 13.2% of transition-age youth achieved CIE status, compared to 30.1% of adults. The key predictors of employment outcomes, including CIE status, weekly earnings, and working hours were identified. CONCLUSION: The research reveals significant differences in employment outcomes between transition-age youth and adult VR consumers. These insights emphasize the necessity for SVRAs to consider a range of factors, including demographics, potential employment barriers, and the effects of various VR services, to increase the CE service effectiveness for transition-age youth.
Reclaiming employment: A pilot study of online entrepreneurship training for individuals with psychiatric disabilities
Authors: Ostrow Laysha , Pelot Morgan , Burke-Miller Jane K. , Robinett Kila , Nemec Patricia B.
Published: April 2024

BACKGROUND: Many individuals with psychiatric disabilities face workplace challenges that motivate them to pursue self-employment, but accessible self-employment support is lacking. Using participatory action research, Reclaiming EmploymentTM (RE), an online interactive platform that provides self-employment education for people who experience mental health-related challenges around work, was developed to address these gaps. OBJECTIVE: An observational pilot study of RE examined usage, usability, self-efficacy, and self-employment income. METHODS: Participants (N = 97) used RE for six months; survey data was collected at three timepoints to measure entrepreneurial self-efficacy (ESE) and income generated from self-employment. Usability was assessed post-intervention using the System Usability Scale. RESULTS: More than 70% of participants used RE; there was no association between non-usage and demographic characteristics, nor prior use of other self-employment supports. RE users rated the platform at above average usability, although those who experienced long-term unemployment rated the platform significantly lower compared to wage or self-employed users. In longitudinal regression models, we found use of RE was significantly associated with increases in some ESE subscales and mean ESE. Use of RE was not associated with gains in income. CONCLUSION: This pilot study demonstrates acceptability, feasibility, and preliminary effectiveness of an online entrepreneurship training for individuals with psychiatric disabilities.
Multi-attribute decision-making methods based on Aczel-Alsina power aggregation operators for English blended teaching quality evaluation under single-valued neutrosophic sets
Authors: Wang Shuyan
Published: April 2024

As a new form of teaching, blended teaching can integrate the advantages of classroom teaching and online teaching and improve the overall quality and effectiveness of English teaching under the premise of changing the orientation of teachers and students. The English blended teaching quality evaluation is a multiple attribute decision making (MADM) issue. Aczel-Alsina t-norm and t-conorm operations have the true advantage of changeability by adjusting a decision parameter. power averaging (PA) operator allowed decision attributes to strengthen each other through weight information during fusion, thereby eliminating the influence of subjective weights on the decision results. Motivate through classical Aczel-Alsina operators, PA operator and the single-valued neutrosophic sets (SVNSs), in this paper, the single-valued neutrosophic number Aczel-Alsina power averaging (SVNNAAPA) operator and the single-valued neutrosophic number Aczel-Alsina power weighted averaging (SVNNAAPWA) operator are constructed under SVNSs. The SVNNAAPWA operator is built for MADM. Eventually, an example about English blended teaching quality evaluation and some selected comparative decision analysis is used to depict the SVNNAAPWA method.
Enhancing decision-making framework for talent cultivation quality evaluation using dual Hamy mean and prioritized aggregation operators
Authors: Yan Jing , Li Yinbing , Zheng Zheng
Published: April 2024

At present, the solidification of disciplines and majors in higher education, unclear training objectives, and the need to strengthen teacher information literacy are practical problems that constrain the optimization of the “artificial intelligence+” talent training model. Scientifically adjusting training objectives, upgrading the “artificial intelligence+” talent training model in higher education by integrating multi-disciplinary curriculum systems, strengthening school enterprise cooperation, industry education integration, establishing credit recognition mechanisms and diversified evaluation mechanisms. The quality evaluation of “Artificial Intelligence+” talent cultivation in higher education in the era of education informatization 2.0 is looked as the multiple-attribute decision-making (MADM) issue. In this paper, we extended the dual Hamy mean (DHM) operator and prioritized aggregation (PA) operator to 2-tuple linguistic neutrosophic sets (2TLNSs) to propose the 2-tuple linguistic neutrosophic prioritized DHM (2TLNPDHM) operator. Finally, a decision example for quality evaluation of “Artificial Intelligence+” talent cultivation in higher education in the era of education informatization 2.0 is employed to show the 2TLNPDHM operator. The main contributions of this study are summarized: (1) the 2TLNPDHM operator is built; (2) the 2TLNPDHM operator is designed to cope with the MADM with 2TLNNs; (3) an empirical real-life example for quality evaluation of “Artificial Intelligence+” talent cultivation in higher education in the era of education informatization 2.0 is supplied to proof the designed method; (4) some comparative decision studies are used to show the rationality of the 2TLNPDHM.
The effects of visual information deprivation and feedback balance training on balance in patients with stroke
Authors: Jeong Taewoong , Chung Yijung
Published: April 2024

BACKGROUND: Patients with stroke depend on visual information due to balance deficits. Therefore, it is believed that appropriate visual deprivation training could have an impact on improving balance abilities. OBJECTIVE: The purpose of this study was to compare the effects of balance training performed in visual deprivation and feedback conditions on balance in stroke survivors. METHODS: The 39 participants were randomly assigned to either the Visual Deprivation Group (VDG; n = 13), the Visual Feedback Group (VFG; n = 13), or the Control Group (CG; n = 13). The training sessions were conducted five times a week for three weeks. Participants completed the Berg Balance Scale (BBS), Timed Up and Go test (TUG), Four Square Step Test (FSST), and Limit of Stability (LOS) assessments. RESULTS: The VDG showed significant improvements in BBS, FSST, TUG, and LOS. In VFG, significant improvements were observed in BBS and TUG. There were statistically significant differences among the groups in all variables related to balance. CONCLUSION: The results of this study suggest that balance training under visual deprivation is effective in improving static and dynamic balance and gait in patients with stroke. In other words, patients with stroke need to reduce their over-reliance on visual information.
On n-Dimensional Maxwell and Dirac Equations in Curved Space-Time and Its Applications in SO(P,Q) Group Theoretic Image Processing
Authors: Parthasarathy Harish
Published: April 2024

Maxwell equations in p time and q spatial dimensions are formulated. Properties of the Green’s function for the associated (p,q)-wave operator are derived based on contour integration. The notions of electric and magnetic fields in (p,q)-dimensions is explored by analogy with four dimensional physics and the problem of far field computation of the radiation field generated by charges and currents in \((1,n-1)\) space-time is analyzed. SO(p,q) invariance properties of the Maxwell equations are deduced and used to formulate SO(p,q)-group theoretic image processing problems in (p,q)-dimensions. Dirac’s equation in (p,q)-dimensional space-time is derived using the Clifford algebra of the Dirac gamma matrices. SO(p,q)-invariance of the Dirac equation based on the spinor representation of \(SO(p,q)\) is mentioned. The Maxwell’s equations in (p,q)-dimensional curved space-time is analyzed using perturbation theory in the context of maximally symmetric spaces which play a fundamental role in \((p,q)\)-dimensional cosmological models for homogeneous and isotropic spaces. The Einstein-Maxwell equations for (p,q)-dimensional gravity and electromagnetism is studied and used to derive the equations of motion of point charges carrying mass moving under mutual gravitational and electromagnetic interactions in general relativity. Finally, Dirac’s equation in (p,q)-dimensional curved space-time interacting with the (p,q)-dimensional electromagnetic field is looked at. \(U(1)\)-Gauge, local SO(p,q) Lorentz and diffeomorphism invariance of this equation is analyzed. Local \(SO(p,q)\) invariance of the curved space-time Dirac equation is deduced based on transformation properties of the Dirac matrices under the spinor representation. The appendix presents some applications of group representation theoretic statistical image processing on a manifold to the situation when the image field is described by the six component electromagnetic field tensor on which the Lorentz group acts.
Ecological and Faunistic Analysis of Lumbricidae Species Composition of Natural Biogeocenoses and Man-made Territories
Authors:   Abai Kazakh National Pedagogical University, Seribekkyzy G. , Batyrova K.I. ,   Abai Kazakh National Pedagogical University, Еsimov B.K ,   Abai Kazakh National Pedagogical University, Saimova R.U. ,   Abai Kazakh National Pedagogical University, Aitpan A.M. ,   Kazakh-Russian Medical University, Koc H. ,   Mugla University
Published: April 2024

Earthworms make up the bulk of the soil mesofauna and play an important role in the transformation of organic matter, the formation of the pedosphere, the regulation of the flows of matter, energy and information in ecosystems. In this research, we have studied the species composition of earthworms in urban and suburban ecosystems of the foothills of the Trans Ili-Alatau. As a result of the work, 11 species of the Lumbricidae family of the Oligochaeta class were discovered. 6 species out of them have been discovered in our Republic: Aporrectodea rosea, Lumbricus rubellus, Lumbricus castaneus, Octolasion lacteum, Dendrobaena octaedra and Aporrectodea caliginosa are widespread. The genus Lumbricus is the most common in terms of the number of individuals in the studied territories. Significant differences have been established in the species composition of earthworms in technogenic and natural biogeocenoses. The lumbricides are the absolute dominants in two ecosystems. Along with the species composition of earthworms, seasonal dynamics were also studied, it was found that their maximum activity is observed at the most favorable ratio of temperature and humidity.
The Legal Regulations and Governmental Approaches towards Refugees in Jordan
Authors: Alma'aitah Meera
Published: April 2024

Jordan has long been a refuge for those fleeing conflict and persecution in neighbouring countries. As a result, the country has developed a robust set of laws and policies to protect refugees and provide them with the support they need to rebuild their lives. In this context, understanding the refugee laws in Jordan is crucial for anyone interested in the welfare of refugees and the broader humanitarian crisis in the region. With over 750,000 registered refugees, Jordan is home to one of the largest refugee populations in the world. The country has been praised for its generosity and commitment to protecting refugees, but also faces significant challenges in providing for the needs of such a large and diverse population. Understanding the legal framework that governs refugees in Jordan is essential to addressing these challenges and improving the lives of those affected by conflict and displacement. The ongoing conflict in Syria has resulted in a massive influx of refugees into neighbouring countries, including Jordan. To meet the needs of this growing population, the Jordanian government has established a set of laws and policies designed to provide refugees with protection, assistance, and access to essential services. This legal framework is a critical component of the countrys humanitarian response to the Syrian crisis and plays an essential role in the lives of hundreds of thousands of refugees living in Jordan.
Study of Variation in the Dialect of Various Region of India: Review
Authors: Patil Shweta , Shivani U Patole
Published: April 2024

‌Dialect refers to different characteristic of language of a specific group of speakers. These dialects are closely related and often mutually understandable, especially if close geographical region. Dialects can be sociolect, ethnolect, or regiolect, and can be associated with social class, ethnic group, or geographical/regional factors .Any variety of a language can classified as a dialect. Migration is most important factor for idiosyncrasy in languages in particular area. A region wise variation in language of people is know as dialect. Dialects is an important aspect of speaker variability. To express the individual  quality of specific  region. Children encounter multi-dialectal interactions. An review paper described techniques contributed for India regional language processing it gives information about sources of dataset for the Indian regional languages.
Історія України : метод. реком. для підгот. до практич. занять та самост. роб. здобув. першого (бакалаврського) рівня вищої освіти, галузі знань 05 «Cоціальні та поведінкові науки», спеціальності 052 «Політологія
Authors:   Національний університет ", Аніщук Ніна Володимирівна ,   Одеська юридична академія"
Published: April 2024

Методичні рекомендації з дисципліни «Історія України» за освітньо-професійною програмою «Політологія» підготовки здобувачів вищої освіти ступеня бакалавр на факультеті правової політології та соціології Національного університету «Одеська юридична академія» у галузі знань 05 «Соціальні та поведінкові науки», за спеціальністю 052 «Політологія». До методичних рекомендацій увійшли тематичний план навчального курсу «Історія України», який включає теми, що розглядаються на лекціях і практичних заняттях, а також теми, що передбачені в рамках самостійної роботи для підготовки до заліку. Методичні рекомендації мають допомогти здобувачам належним чином засвоїти матеріал з дисципліни «Історія України».