bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classification of ECG signals using CNN models
Authors: Chettaoui Hnia , Mouaddeb Rabeb , Moulahi Tarek , Bennaji Najoua 
Published: October 2024

Abstract

Electrical activity is essential for blood circulation, and any alteration in the orderly pattern of excitation waves propagating through the heart can lead to arrhythmias. The electrocardiogram (ECG) is a widely used tool for diagnosing arrhythmias, as it is rapid, affordable, and non-invasive. However, manual interpretation of ECG data is often time-consuming and subject to human error. With improved training, deep learning (DL) could provide a more effective alternative for rapid, automatic classification. This study presents a novel deep learning architecture, including a convolutional neural network (CNN), for classifying cardiac arrhythmias. Real ECG signals from the Heartbeat Categorization ECG dataset were used for training and validation. The models’ performance was evaluated using the confusion matrix, which determined precision, accuracy, recall, F1 score, mean, and AUC-ROC. Both models demonstrated exceptional performance, achieving accuracies of 0.995 and 0.996 on training and test datasets, outperforming existing methods in terms of accuracy and efficiency.
Perceived Effectiveness and Intrusiveness of School Security Countermeasures Among Parents, Students, and Staff
Authors: Byrd Katie , Kapadia Kevin , John Richard 
Published: October 2024

Abstract

This study evaluates the perceptions of school security countermeasures among parents, recent students, and staff (n = 1105) recruited via Prolific.com. The survey collected participants' perceptions of safety and countermeasure effectiveness and invasiveness. Results show broad acceptance of measures like emergency drills, door locks, and security cameras, while more invasive measures, including armed staff, bag inspections, and clear bag policies, generate discomfort. A binary logistic regression found that perceived safety was negatively predicted by a desire for additional countermeasures and positively predicted by perceptions of countermeasures as both comfortable and effective. Socioeconomic factors, like household income, were also positively related to students' sense of safety. Future research should examine the broader impacts of security measures on student well-being and the school environment.
Uncovering Adverse reactions following COVID-19 Monovalent XBB.1.5 Vaccination from Active Surveillance: A Text Mining Approach
Authors: Lee Hye Ah , Park Bomi , Kim Chung Ho , Kim Yeonjae , Park Hyunjin , Jun Seunghee , Lee Hyelim , Kwon Seunghyun Lewis , Heo Yeseul , Lee Hyungmin , Park Hyesook 
Published: October 2024

Abstract

Background
Unstructured text data collected through a surveillance system for vaccine safety monitoring can identify previously unreported adverse reactions and provide the information necessary to improve the surveillance system. Therefore, this study explored adverse reactions using text data gathered through an active surveillance system following monovalent XBB.1.5 COVID-19 vaccination.
Methods
A text mining analysis was conducted on 2,608 records from 1,864 individuals who reported any health conditions experienced within 7 days after vaccination in text format. Frequency analysis of key terms was performed, with subsequent analysis by sex, age, and concurrent influenza vaccination. Furthermore, semantic network analysis was conducted on terms reported simultaneously.
Results
The analysis identified various common (≥ 1%) adverse events, such as sleep disturbances, lumbago, and indigestion, which had not been frequently reported in prior literature. Moreover, although not common (≥ 0.1% to < 1%), adverse reactions affecting the eyes, ears, and oral cavity were also noted. These adverse reactions showed no significant differences in occurrence with or without simultaneous influenza vaccination. Through cooccurrence analysis and correlation coefficient assessments, associations were found between diarrhea and abdominal pain, as well as between musculoskeletal symptoms and cold-related symptoms.
Conclusion
This study used text mining to reveal previously unrecognized adverse reactions related to COVID-19 vaccination, thus expanding our understanding of the vaccine’s safety profile. The insights gained could further the scope of future investigations into adverse reactions to vaccines and improve the processing of text data in surveillance systems.
PF-MSVNet: A 3D Object Detection Model With Multi-scale Point- level Feature Fusion
Authors: wang Jinyan , Hu Xiaoyu , Yao Ziyu , Liu Bo , Hu Dianzhi 
Published: October 2024

Abstract

3D object detection aims to accurately determine the spatial location of objects and plays an important role in complex tasks such as autonomous driving and aircraft obstacle avoidance. However, 3D data lacks color and texture information, and traditional single-modality detection methods are prone to issues such as missed or false detections. To address this problem, we propose a 3D object detection model based on multi-scale point-level feature fusion (Point Fusion Mixed Sampling VoteNet, PF-MSVNet). First, we use image foreground information to divide the point cloud foreground and background point sets, and randomly downsample the foreground point sets. Then, we use residual connection to improve the point cloud feature extraction module to deepen the network layers and extract high-quality features. We construct a multi-scale point-level feature fusion network and introduce an attention mechanism to suppress image interference information, deepening the fusion of point cloud and image information at the feature level. Experimental results on outdoor KITTI dataset and indoor SUN RGB-D dataset shows that PF-MSVNet achieves a higher average detection accuracy of 8.61%, 5.86%, 3.65%, and 5.23% respectively compared to VoxelNet, SECOND, PointRCNN, and F-PointNet, reaching a maximum mAP of 67.17% among various models. The detection accuracy on small and difficult targets is significantly better than other models. This verifies that the proposed PF-MSVNet model can further improve the accuracy and robustness of object detection.
Peroxidase Mimicking V2O5 Nanozymes as the Spectrophotometric Sensor for the Determination of Glucose in Human Serum Sample Employing New Chromogenic Co-Substrates
Authors: Gangadhara Nikhil Y , B Manju. , Kumar P Kiran , Krishna Honnur , Shivakumar Anantharaman , Sadashivanna Ravishankar H , Krishnegowda Avinash 
Published: October 2024

Abstract

Enzyme mimics are developed as an alternative to natural enzymes to overcome the inherent limitations of natural enzymes. Among different types of enzyme mimics, nanozymes gained importance due to their tuneable catalytic properties. In this article, we discuss the peroxidase behaviour of different shape V2O5 nanoparticles (NPs). A simple spectrophotometric method is presented for the quantification of glucose and H2O2 using novel chromogenic reagents. The NPS are characterized with SEM, DLS, EDS, FTIR and XRD. From SEM images, based on the morphology, the NPs were named as vanadium nanosheets (VNShs), nanoflowers (VNFws) and nanospheres (VNSps). The average crystalline size of the nanoparticles is calculated using XRD data from Scherrer’s equation and Williamson-Hall plot and was found to be 45.42, 45.7nm for VNShs, 29.14, 32.5nm for VNFws, and 39.83, 38.7nm for VNSps respectively. The linearity of glucose was ranged from 0.0289 to 0.925mM for HRP, VNShs VNFws, and 0.925 to 0.0528mM for VNSps. The H2O2 was in good linear range between 0.003 to 1.9383mM in both rate and fixed time method for all nanozymes and HRP. For recovery study 10µL serum sample was directly used without dilution. The Km values were found to be 1.6239 mM for HRP, 0.7843 mM for VNShs, 0.6514 mM for VNFws, ands 0.6398 mM for VNSps concluding that NZs have better affinity towards substrate molecule. The detection limit and quantification limits were found to be 0.0548mM and 0.1662mM for HRP, 0.066mM and 0.2002mM for VNShs, 0.0425mM and 0.1287mM for VNFws and 0.1474mM and 0.4465mM for VNSps.
Incidences of secondary malignancies after androgen deprivation therapy for prostate cancer
Authors: Lee Junghoon , Cho Min Chul , Jeong Hyeon , Son Hwancheol , Yoo Sangjun 
Published: October 2024

Abstract

Purpose
We aimed to assess the effects of ADT on the incidence of secondary malignancies in patients with prostate cancer.
Methods
Prostate cancer patients who initially treated with ADT from 2009 were included and followed up until 2019. We additionally included female patients, male patients without prostate cancer, and male patients with prostate cancer who did not undergo ADT to build comparison. A 1:1:1:1 match based on age was performed, and 55,865 individuals from each group were selected for analysis.
Results
The incidence of common cancers was compared between the groups. All cancers, except thyroid and breast cancers, were more common in men than women. All cancers were more common in men with prostate cancer than in men without prostate cancer, regardless of ADT. After ADT, the incidences of thyroid and breast cancers increased, whereas the incidences of liver and pancreatic cancers decreased. In the multivariate analysis, all types of cancer were more common in men with prostate cancer than in men without prostate cancer, regardless of ADT. Among these, the incidence of liver and pancreatic cancers significantly decreased after ADT.
Conclusion
The incidence of several secondary malignancies was affected not only by sex but also by prostate cancer diagnosis and ADT. Although further studies are required, these data could be important for health checkups and the management of prostate cancer survivors, especially prostate cancer patients who have been treated with ADT.
Prevention and management of Pre-eclampsia related maternal mortality During ANC in the Buea Health District.
Authors: Mbaku Adeso Divine , Tankeu Ndassi Daonyle Vicky , Ngitah Andoh Magdalene , Atanga Sylvester Ndeso 
Published: October 2024

Abstract

The study highlights the significant issue of maternal mortality in Cameroon, where 12–13 women die daily from pregnancy-related causes, despite a global decline in maternal mortality rates. The research aimed to determine the prevalence of preeclampsia, a major factor in maternal mortality, and evaluate the effectiveness of antenatal care (ANC) practices in reducing its impact. Methods: A cross-sectional study was conducted, reviewing records from 2017–2021 in the BHD. The study used a simple random sampling technique to select facilities and pregnant women attending ANC. A sample of 200 women was assessed for their knowledge of ANC and factors hindering positive ANC practices. The study also measured the prevalence and management of preeclampsia among these women. Data were analyzed using SPSS Version 23. Results: Out of 4,707 records reviewed, the prevalence of preeclampsia was 4.97% (234 cases). Knowledge of ANC was high, with 84% of women understanding its importance. Significant associations were found between ANC knowledge and factors such as religion (X²=12.029, p = 0.007), education level (X²=10.641, p = 0.031), and income (X²=8.061, p = 0.045). Other socio-demographic factors showed no significant association. Multivariate analysis indicated that ANC is effective in managing preeclampsia, with 95.3% of women successfully managed during ANC. Logistic regression analysis identified long distance to facilities (40%), financial limitations (36.5%), and long waiting times (37.5%) as barriers to ANC attendance. Conclusion: The prevalence of preeclampsia among women attending ANC in the BHD is high. Most women have adequate knowledge of ANC, which is crucial for managing preeclampsia. Effective ANC utilization is essential, but factors like trust in healthcare, distance to facilities, and financial constraints significantly affect ANC attendance and frequency. Addressing these barriers could improve maternal health outcomes in Cameroon.
Impact of supportive psychotherapy on anxiety, night sleep quality, and medication adherence in maintenance hemodialysis patients
Authors: Chen Zewei , Wang Yong , Chen Peng , Wang Li , Liang Jianguo , Yin Bo , Xie Feiyan 
Published: October 2024

Abstract

Background
Anxiety is a common yet frequently overlooked psychiatric disorder in patients with end-stage renal disease (ESRD), which is related to decreasing the quality of life and survival. We examined whether supportive psychotherapy improved anxiety in maintenance hemodialysis (HD) patients.
Methods
Among the 69 participants enrolled in our dialysis center, 63 finished the study and were randomly assigned to the study group (n = 35) and the control group (n = 28). An intervention group was given 1 weekly session of supportive psychotherapy led by trained psychologists over 3 months while a control group synchronously received the usual treatment.
Results
An intragroup analysis was conducted on the GAD-7 (anxiety levels), PSQI (sleep quality), and MMAS-8 (medication adherence) scales. Mean scores for the control group showed no significant change at 3-month follow-up. The study group revealed significant improvements in the average scores of GAD-7 scores (p < 0.001), PSQI scores (p = 0.004), and MMAS-8 scores (p = 0.007). Correlation analysis demonstrated a positive relationship between anxiety levels, sleep quality, and medication adherence.
Conclusions
In summary, supportive psychotherapy resulted in significant improvements in anxiety, sleep quality, and medication adherence. It is recommended that further research be conducted to explore the efficacy of psychotherapy for mental disorders in populations with ESRD.
Unraveling the Benefits of Thermal Waters Enhancing Oral Health: a pilot study
Authors: Lopes Sara , Morgado Susana , Gomes Ana T. P. C. , Lopes Pedro C. , Couto Patrícia , Correia Maria J. , Flores-Fraile Javier , Veiga Nélio Jorge 
Published: October 2024

Abstract

Background: Oral health represents a public health problem due to its remarkable social impact and medical costs. Crenotherapy with sulfur water is shown to be a complementary, less toxic, and traumatizing therapy, but the number of studies that evaluate the effect of natural mineral waters in treatment of oral mucosa diseases (OMD) disorders is small. In Portugal there are no published studies. The aim of this work is to qualitatively assess the impact of thermal therapy on the perception of symptoms of OMD.
Methods: An observational, longitudinal and comparative study was designed, and 90 thermalists were randomly allocated to two treatment groups for 14 days: Thermal sulfuric natural mineral water of the Amarante Thermal baths group (TW_TA group) (n=45) or saline solution (control group) (n=45), in May 2022. The study was based on clinical observation and application of a self-response questionnaire involving sociodemographic data and quality of life assessment. The evaluation was carried out in 2 different moments: before and at the end of treatment (14 days).
Results: The initial symptom averages were 1.57±0.332 for the thermal water of Termas de Amarante (TW_TA) group and 1.49±0.355 for the control group. After the thermal treatment, these values decreased to 1.18±0.200 and 1.12±0.165, respectively. The evolution of parameters evaluated of life quality and oral pain were positive, with significant changes at the end of treatment. The results suggest that treatment with sulfuric natural mineral water carried out, may constitute an effective procedure to promote oral health.
Conclusions: The potential of the use of thermal waters in Portugal for the promotion of oral health has not been assessed. Although thermal waters are used in some oral care products, there is limited in-depth research into their interaction with the oral microbiome. This lack of research presents an opportunity to expand our understanding and optimize the use of thermal waters in oral health products.
Three-Dimensional Plasmonic Nanorod Location and Orientation Sensing Based on Double Fano Resonances
Authors: He Xiaoping , He Shuling , Li Guozhou 
Published: October 2024

Abstract

The sensing of spatial positions and orientations at the nanometre scale is of significance for studying complex macro-molecular and biological processes, as well as their dynamic evolution. Herein, plasmonic nanorod location and orientation sensing both inside and outside a three-dimensional (3D) plasmonic nano-system are achieved based on double Fano resonances. These two Fano resonances are found to originate from different physical mechanism. One is attributed to the excitation of the quadrupole mode supported by the upper nanorod pair, and the other arises from the excitation of the quadrupole mode in the lower nanorod pair. Owing to the different origins, these two Fano resonances exhibit quite different responses to the configuration changes inside and outside the plasmonic nano-system. Specifically, the configuration changes inside the nano-system are identified by retracing the first Fano resonance. When the foreign nanorod intrudes into the plasmonic nano-system, the second Fano resonance emerges. By reading out the second Fano resonance spectral response, which takes the first Fano resonance as the reference, the spatial positions and orientations of the foreign nanorod are determined. This work opens up new opportunities for developing advanced nano-optical devices, which can be applied to 3D macromolecule configuration information retrieval and dynamic biological process analysis.
Variation in sleep and circadian rhythms of elderly dementia patients living in group home residences
Authors: Kubota Naoko , Matsuura Noriko , Ebina Maiko , Suzuki Hitomi , Miyagi Nagomi , Masukawa Naoki , Kouga Fumihiro , Yamanaka Yujiro 
Published: October 2024

Abstract

In the present study, we investigated 70 elderly individuals with dementia residing in a group home in Japan (88.1±6.6 SD years; 12 males and 58 females). Sleep measurements were collected via an accelerometer placed under the mattress from March 2021 to January 2024. The accelerometer-derived activity counts were transformed and plotted as actograms. On the basis of the actograms, sleep patterns were categorized into three groups: regular nighttime sleep (Type 1, n=38, 54.3%), regular nighttime sleep with daytime naps (Type 2, n=29, 41.4%), and irregular sleep (Type 3, n=3, 4.3%). We compared accelerometer-derived sleep measures among these three groups. Interestingly, Type 2 individuals had a significantly longer bed in time and total sleep time. However, their sleep onset latency, time of wakefulness after sleep onset and sleep efficiency did not differ from those of Type 1 individuals. Additionally, we assessed the relationships between sleep patterns and dementia characteristics, such as type of dementia, independence in daily living, and level of care needed. No significant differences were observed in sleep measurements across these characteristics. To evaluate endogenous circadian rhythms, seven dementia patients wore a patch-type wearable temperature sensor for approximately 24 hours to estimate core body temperature (CBT). One patient exhibited a clear diurnal rhythm, with higher CBT during the day (active period) and lower CBT at night (sleep period). In contrast, the other patients did not show a distinct diurnal change in CBT. In summary, our findings indicate that dementia patients display varying sleep patterns that are independent of dementia characteristics. The dysfunction of sleep homeostasis and entrainment of circadian pacemakers might be due to the light environment in the group home residence or impairment of the circadian clock itself in dementia patients.
Assessing the Impact of Analyst Coverage and Political Connections on Audit Opinion Shopping in China's Corporate Sector
Authors: Wu Xinwei , Sun Han , Kang Hyoung-Goo , Lee JaeHo 
Published: October 2024

Abstract

This study builds on the framework established by Lennox (2002) to assess the likelihood of firms receiving modified audit opinions (MAOs) and explores the relationship between analyst coverage and audit opinion shopping among Chinese-listed firms, with a particular focus on the moderating effects of political connections and political leadership turnover. Leveraging a comprehensive dataset of 37,774 observations from 2004 to 2022, our findings indicate that analyst coverage significantly increases the propensity for audit opinion shopping, especially in firms with strong political ties. Additionally, we conduct an event study to examine the impact of analyst announcements within China’s A-share market. By analyzing reports from top-ranked analysts identified through the "New Fortune Best Analyst" rankings, we observe significant market reactions, suggesting that influential analyst coverage heightens the pressure on firms to secure favorable audit outcomes, particularly during critical financial periods. Furthermore, our analysis of political leadership turnover during the 17th, 18th, and 19th National Congresses reveals that changes in local political leadership, particularly the promotion of local officials, further amplify firms’ tendency to engage in audit opinion shopping. These findings underscore the intricate interplay between market scrutiny, political dynamics, and corporate audit practices, providing new insights into the factors that drive audit opinion shopping in China’s distinctive corporate landscape.
Integrating Color and Texture Features for Automated Plant Health Classification Using K-Means Clustering
Authors: Sood Ashima , Reddy Patlolla Venkat 
Published: October 2024

Abstract

In modern agriculture, the key to responding in a timely manner is the accurate judgement of plant health, which directly affects crop yield and quality. Many conventional techniques are essentially one or the other of color and texture analysis wherein performing either allows only a partial look into the information available to better classify these types of data. Summary to cope with the difficulties presented in the plant health classification task, a novel hybridized feature extraction framework combining color and texture features is proposed in this work.We use the average RGB values for color features and Grey-Level Co-occurrence Matrix (GLCM) focusing on contrast and dissimilarity properties for texture features. We merge these two features into a single feature vector which will be K-meansed. This method improves the distinction between healthy and diseased plants, which retains interpretability and accuracy better than that of traditional unsupervised classification techniques.