bluuebunny/crossref_metadata_2025 huggingface dataset:
Inter-Subject Correlations in Eating Disorder Symptoms and its Link with Amygdala Activation Strength and Pattern When Processing Angry Faces
Authors: Chuqiao Wei , Hu Ying , Li Xiang , Gao Yuanyuan , Im Hohjin , Zhu Yingying , Jiang Keying , Zhu Wenwei , Zhao Guang , Jia Xuji , Niu Xin , Chen Xiongying , Wang He , Wang Qiang
Published: August 2024

A key characteristic of eating disorders is atypical activity in the amygdala. However, risk factors for the development of eating disorder symptomology (EDS) and their underlying neural mechanisms are not well understood in non-clinical populations. We examined the role of amygdala reactivity to negative facial emotions in anorexia nervosa symptomology (ANS) and bulimia nervosa symptomology (BNS) using a classical face-matching task and an inter-subject representational similarity analysis (IS-RSA). Behavioral analyses showed a sequential-mediation effect, tracing a path from greed personality trait → depression → body dysmorphic disorder → EDS/ANS. Imaging analyses revealed that individuals with high EDS had decreased amygdala reactivity and altered activation patterns in the amygdala and visual pathways when processing angry faces. We found that variations in amygdala activation and its connectivity with the visual pathway mediated the effect of depression on EDS/ANS, but not BNS. Individuals with similar EDS showed similar spontaneous brain activity patterns, especially in regions associated with the default mode network, frontal-parietal network, visual network (VIS), and attention network. We also observed sequence-mediation effects, e.g., depression → VIS → body dysmorphic disorder → EDS/ANS, but not BNS. These findings highlight the role of amygdala activation in understanding eating disorders and the potential influence of greed personality traits and depression on disordered eating symptoms through the amygdala-visual pathway connection in non-clinical populations.
Triterpene esters from Uncaria rhynchophylla hooks are able as new selective inhibitors on HIV-1 protease and their molecular docking study
Authors: Lee JiSuk
Published: August 2024

Despite the remarkable advancements achieved with combination anti-retroviral agents (cART), the complete eradication of Human immunodeficiency virus (HIV) remains a formidable challenge due to various factors including adverse effects, adherence issues, and the emergence of viral resistance to existing therapies. Consequently, there is an urgent need for the development of safer and more effective drugs to combat modern resistant viral strains and advance acquired immunodeficiency syndrome (AIDS) therapeutics. Eight triterpene esters (1–8) were identified from Uncaria rhynchophylla hooks. These compounds exhibited selective inhibition of HIV-1 protease, with 3β-hydroxy-27-p-Z-coumaroyloxyurs-12-en-28-oic acid (8), showing the most potent inhibitory activity. Structure-activity relationship analysis highlighted the importance of an ursane moiety, a cis configuration, and a p-coumaroyloxy group for inhibitory activity. In silico docking results elucidate specific amino acid residues Asp29B, Lys45B, and Asn25A, interacting with the aromatic hydroxyl group at 7′, and carboxylic acid at 28. In addition, it interacts via π/anion and π/alkyl and alkyl hydrophobic interactions responsible for interactions and their mode of action. The study suggests that triterpene esters from U. rhynchophylla could represent a new class of selective HIV-1 protease inhibitors with less toxicity, suitable for combination antiretroviral therapy for AIDS.
Auditor: Accounting Data Handling Toolbox for Opportunistic Resources
Authors: Boehler Michael , von Cube Florian , Fischer Max , Giffles Manuel , Kleinemühl Raphael , Kroboth Stefan , Rottler Benjamin , Sammel Dirk , Schnepf Matthias , Schumacher Markus , Vijayakumar Raghuvar
Published: August 2024

Increasing computing demands and concerns about energy efficiency in high-performance and highthroughput computing are driving forces in the search for more efficient ways to use available resources. Sharing resources of an underutilised cluster with a high workload cluster increases the efficiency of the underutilised cluster. The software COBalD/TARDIS can dynamically and transparently integrate and disintegrate such resources.
However, sharing resources also requires accounting. AUDITOR (Accounting Data Handling Toolbox for Opportunistic Resources) is a modular accounting ecosystem that is able to cover a wide range of use cases and infrastructures. Accounting data are gathered via so-called collectors, which are designed to monitor batch systems, COBalD/TARDIS, cloud schedulers or other sources of information. The data is stored in a database, and access to the data is handled by the core component of AUDITOR, which provides a REST API along both Rust and a Python client libraries. So-called plugins can take actions based on accounting records.
Depending on the use case, one simply selects a suitable collector and plugin from a growing ecosystem of collectors and plugins. To facilitate the development of collectors and plugins for yet uncovered use cases by the community, libraries for interacting with AUDITOR are provided.
Insights from 3D Echocardiography: Unveiling the Prognostic Value of RV Function in Pulmonary Hypertension: A Systematic Review and Meta-analysis.
Authors: Ahmad Ashfaq , Wang Xiaoyu , Li Lingling , Liu Ting , Fan Fen-Ling
Published: August 2024

Background
The role of right ventricular (RV) dysfunction in pulmonary hypertension (PH) has garnered increasing interest in terms of outcomes. This systematic review and meta-analysis evaluated the prognostic utility of three-dimensional echocardiography (3DE) derived right ventricular ejection fraction (RVEF) in PH.
Methods
A systematic review and meta-analysis were performed using MEDLINE, Embase, and Scopus databases for publication reporting the hazard ratio (HR) of 3DE-derived RVEF in PH patients for the clinical end-points of composite outcome or all-cause mortality.
Results
Nine articles totaling 885 subjects were included, among which 67.23% had pulmonary arterial hypertension (PAH), with the remainder having a range of PH etiologies. The mean value of 3DE-derived RVEF was 35.5 ± 9.07% reflecting impaired RV function. The primary endpoint was all-cause mortality in three studies while the rest of the studies reported composite outcomes. Follow-up duration ranges from 6 months to 44 months. From seven publications the pooled HR by 3DE-derived RVEF was 0.91 (95% CI: 0.85 to 0.97, p = 0.001; heterogeneity: I2 = 62%, p = 0.004). In subgroup analysis, 3DE-derived RVEF was a significant prognostic factor for group 1 PH (HR: 0.90, CI: 0.86–0.94; heterogeneity I2 = 43%, p < 0.0001). From meta-regression analysis, only follow-up duration was found statistically significant with the HR of RVEF in the population (estimate: 0.028, p = 0.026).
Conclusion
3DE-derived RVEF provides important prognostic value in a large and mixed population of PH patients. Further accumulation of evidence is needed to perform a detailed subgroup analysis in each type of PH.
From heat wave Zoe to heat wave Vera: a two-year ex post evaluation of the categorization and naming heat wave system ProMeteo in Seville, Spain
Authors: Martin-Olalla Jose Maria , Baharav Yuval , Kalkstein Laurence , Sheridan Scott , Shickman Kurt , McLeod Kathy Baughman , Wellenius Gregory A
Published: August 2024

The heat wave Zoe in Seville (Spain) (July 24th, 2022) was the first heat wave event named after a health-based categorization system. It was followed in 2023 by their
siblings Yago, Xenia, Wenceslao, and Vera. We report here how the pilot project ProMeteo addressed the forecast, and the main climatic characteristics of the heat waves identified during those years. We also provided a comparison between model expectations and observed daily mortality.
Understanding the Contribution of Primary and Community Services to Health System Resilience During the COVID19 Pandemic in Aotearoa, New Zealand: A Qualitative Interview Study
Authors: Burholt Vanessa , Wiles Janine , Schneller Alison
Published: August 2024

Background
The COVID-19 pandemic, an unprecedented event, exposed varying levels of preparedness across health systems. This study examines the resilience of primary health and community services in Aotearoa New Zealand, focusing on their response to the needs of unpaid caregivers and older care recipients during the pandemic’s first waves. The objective is to inform future disaster preparedness and enhance health system resilience.
Methods
A multidisciplinary research team conducted qualitative research involving semi-structured interviews with service providers (SPs) who provided primary or community home-based services, care, support or information to older people and/or their caregivers across Aotearoa New Zealand. Views were sought from five service provider groups: national organisations, Māori, Pacific, or rural providers and dementia services. Data were collected between July 7 and October 4, 2020. Interviews focused on innovative practices, resources, and organizational settings. Notes from interviews were revised and validated by participants. Thematic coding and analysis were performed using NVivo 14 software to identify key themes and strategies.
Results
Twenty SP staff (Chief Executive Officers and representatives) from National (4), Māori (3), Pacific (5), rural (4), and regional dementia service (4) providers) were interviewed. Participants had 0-21 years in post (Mean=7.37, SD=6.56). Telephone interviews lasted 30-45 minutes. Government support, coordination by Civil Defence Emergency Management groups, and regional communication influenced SP resilience. Challenges included access to personal protective equipment (PPE), staffing, identifying vulnerable people, digital access, and accessing residential care facilities. Innovative practices and remote communication were essential for service continuity.
Conclusions
Aotearoa New Zealand managed COVID-19 effectively, but the pandemic exposed areas for improvement in health system resilience. Examples of absorptive and adaptive resilience in SPs’ and government responses highlighted both strengths and weaknesses. Insights from these experiences can inform transformative resilience, necessitating long-term strategic changes to address vulnerabilities and enhance capacity, ensuring the health system’s robustness and sustainability for future crises.
Impact of Helicobacter pylori infection on neoadjuvant chemotherapy in locally advanced gastric cancer: a retrospective analysis
Authors: Zhong Bin , Xiong Zhizhong , Zheng Jiabo , Mohamed Saddam Ahmed , Sun Jiachen , Huang Dayin , Deng Zijian , Guo Jianping , Peng Junsheng , Wang Huashe , Lian Lei
Published: August 2024

Background
Helicobacter pylori (H. pylori) infection may affect the efficacy of immunotherapy and adjuvant chemotherapy in gastric cancer patients. However, the role of H. pylori infection in neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC) remains unclear. This study investigated the effect of H. pylori infection on neoadjuvant chemotherapy and prognosis of patients with LAGC.
Methods
This retrospective study utilized data from patients with LAGC who underwent neoadjuvant chemotherapy and surgical treatment at the Sixth Affiliated Hospital of Sun Yat-sen University from January 1, 2010, to January 31, 2021. Patients were grouped according to their H. pylori infection status. The responses of the two groups to neoadjuvant chemotherapy and oncological outcomes were then compared.
Results
A total of 239 patients were included in the analysis, and the baseline characteristics of the H. pylori-positive (n = 51) and H. pylori-negative (n = 188) groups were comparable. Further analysis revealed that H. pylori infection was significantly associated with the major pathological response (P = 0.009). Multivariate analysis showed that factors related to major pathological response included; age ≤ 50 (OR: 0.423, 95% CI: 0.194–0.925), H. pylori infection (OR: 0.396, 95% CI: 0.183–0.854), pathological stage T 3/4 (OR: 0.524, 95% CI: 0.288–0.954), and CA125 > 35 U/mL (OR: 0.345, 95% CI: 0.132–0.904). Both overall survival (OS) and disease-free survival (DFS) rates were poorer in the H. pylori-positive group than in the H. pylori-negative group (OS: Log-Rank P = 0.035; DFS: Log-Rank P = 0.029).
Conclusion
This cohort study indicated that H. pylori infection may be associated with tumor response to neoadjuvant chemotherapy and survival outcomes in patients with LAGC.
Application of the Pecarn Prediction Rule for Febrile Infants up to 90 Days of Age: A Multi- Center Study
Authors: Hameed Tahir , Almadani Salma , Shahin Walaa , Ardah Husam , Almaghrabi Walaa , Alhabdan Mohammed , Alfaidi Ahmed , Abuthamerah Asma , Alahmadi Manar , Almalki Malik , Aldabbagh Mona
Published: August 2024

Background
Prediction rules using biomarkers to stratify young febrile infants at low risk for bacterial infections have been developed over the last decade in North America and Europe. The aim of this study was to validate the Pediatric Emergency Care Applied Research Network (PECARN) prediction rule for febrile infants 90 days of age and younger presenting to the emergency department (ED) in tertiary care centers in Saudi Arabia.
Methods
A multi-center retrospective study was conducted on febrile infants who presented to the ED at 3 Saudi hospitals between January 2018 and June 2021. Patients were included if they were full-term, 0–90 days of age, had documented fever, and procalcitonin (PCT) performed.
Results
A total of 327 patients met inclusion criteria. Fifty-three patients (16.2%) had SBIs, 33 with UTI alone and 20 invasive bacterial infections (IBIs) (bacteremia and/or bacterial meningitis). The mean absolute neutrophil count was 6.6 x 109/L in infants with SBIs as compared to 4.3 x 109/L in infants without SBIs (p = 0.0015). The mean PCT was 8.7 ng/mL in those with SBIs versus 0.5 ng/mL in those without SBIs (p < 0.0001). Nine patients who were classified as low-risk according to the PECARN rule had SBIs; 7 were infants with UTIs and 2 were infants under 3 weeks of age with IBIs. The sensitivity and negative predictive value of the PECARN prediction rule for SBIs was 80.4% and 92.1%, respectively.
Conclusions
SBIs are common in our population, and the PECARN prediction rule performed well in classifying febrile infants at low risk for SBIs. The prediction rule was very accurate in ruling out IBIs, with no misclassified cases in infants 3 weeks of age and older. Our study helps validate the applicability of the PECARN prediction rule in our setting.
The association between physical activity and depressive symptoms in U.S. adults is modulated by sleep duration: gender disparities
Authors: Yang Juxiang , Zheng Xi , Wang Yi , Wang Hongchu , Song Gang
Published: August 2024

Background
The aim of this study is to explore the independent and joint associations between physical activity (PA) and sleep duration with depressive symptoms.
Methods
We included and analyzed 18,052 participants (age ≥ 20 years) from the cross-sectional National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2014.
Results
After adjustment, both males and females showed a significant correlation between PA, sleep duration, and depressive symptoms. In the joint association analysis, we found: 1. The interaction between PA and sleep duration was statistically significant in males but not significant in females (P = 0.380). 2. Compared to individuals with the lowest PA level and not meeting the National Sleep Foundation's (NSF) guidelines, those with the highest PA level and recommended sleep duration had a 79% decrease in depression risk in males (odds ratio [OR] 0.21, 95% confidence interval [CI] 0.14–0.32) and a 74% decrease in females (OR 0.26, 95% CI 0.20–0.35). 3. In male participants adhering to NSF guidelines, each increase in PA quartile is associated with a 19% reduction in the risk of depression (OR 0.81, 95% CI 0.71–0.92). Conversely, among male participants not adhering to NSF guidelines, there is a 23% decrease in depression risk (OR 0.77, 95% CI 0.69–0.86). For female participants, the respective reductions in depression risk are 20% (OR 0.80, 95% CI 0.73–0.89) and 14% (OR 0.86, 95% CI 0.80–0.93).
Conclusion
For males, adherence to recommended sleep duration weakens the relationship between physical activity and depression, while the opposite is observed for females.
Laparoscopic versus transanal pelvic exenteration for locally advanced rectal cancer: A comparative study of perioperative and oncological outcomes
Authors: Nonaka Takashi , Tominaga Tetsuro , Shiraishi Toshio , Hashimoto Shintaro , Kaido Oishi , Noda Keisuke , Sawai Terumitsu , Matsumoto Keitaro
Published: August 2024

Background
This study aimed to retrospectively compare the surgical and oncological outcomes of laparoscopic and transanal pelvic exenteration (PE) for locally advanced rectal cancer.
Methods
Patients who underwent laparoscopic PE (L-PE, 6 patients) or transanal PE (Ta-PE, 17 patients) between April 2016 and September 2023 were retrospectively analyzed.
Results
Compared to the L-PE group, the Ta-PE group exhibited a shorter intraoperative time (P = 0.042) and higher anal sphincter preservation rate (P = 0.045). There were no significant differences in other perioperative clinical outcomes between the two groups. The median value for follow-up duration was 32 months and there were no differences in the 5-year overall survival (L-PE versus Ta-PE: 69.3% versus 19.7%; P = 0.155), disease-free survival (L-PE versus Ta-PE: 22.2% versus 45.4%; P = 0.494) or local recurrence-free survival (L-PE versus Ta-PE: 60.0% versus 93.8%; P = 0.189) rates.
Conclusions
Ta-PE is a promising approach for locally advanced rectal cancer in terms of improving perioperative outcomes compared with L-PE.
Can MLLMs Replace Humans in Writing Chinese Children’s Fairy Tales Based on Pictures?
Authors: Zhou Dibin , Liu Fuchang , Liu Wenhao , Du Jing
Published: August 2024

In the field of children's education, MLLMs have already been used to generate children's educational materials. Can MLLMs replace humans in writing Chinese children’s fairy tales based on pictures? This paper attempts to answer this question through three experiments involving 50 undergraduate students, 30 first-grade students, 81 second-grade students, and 917 parents to evaluate the content of children's fairy tales and assess parents' responses in different stimuli and conformity conditions. We found that the "generalization" and "discrimination" situations have no significant effect on parents' willingness to recommend MLLM-generated stories. Furthermore, the moderating effect of conformity also does not have a positive effect under the "generalization" situation. However, perceived content similarity and attitude towards the generated stories play mediating roles in the willingness to recommend. This study concludes that as long as MLLM-generated stories are similar to human-written stories, parents' willingness to recommend these generated children's stories is not influenced by stimuli and conformity effects. Similarly, people's inherent attitudes towards generated stories will not be easily changed by stimuli and conformity effects.
Application Of Tissue Engineering Tools in the treatment of rotator cuff injuries: a bibliometric and visual analysis
Authors: Meng Xiangji , Yang Yuxia , Zhang Jian , Dai Jihang , Wang Jingcheng , Fei Wenyong
Published: August 2024

Background Rotator cuff injury is one of the common injuries of the motor system, which is often manifested as shoulder joint pain, limited movement, weakness and even atrophy of the muscles around the shoulder joint, accounting for 50% ~ 85% of shoulder diseases. Tissue engineering uses synthetic or natural biological materials as scaffolds, combined with seed cells and cytokines to construct implants to repair tissue defects, replace or rebuild the structure of organs, and maintain or improve the function of tissues and organs. In recent years, the application of tissue engineering tools to the tendine-bone interface in addressing rotator cuff injury has emerged as a prominent research area. However, no authors have conducted bibliometric and visual analysis in this field.Methods In this study, articles related to muscular dystrophy omics research since 2000 were retrieved from WoSCC, and analyzed statistically and visually by CiteSpace, VOSViewer and R.Results A total of 340 papers were collected in this study, and the number of papers is increasing year by year. The papers were published in 150 journals by 1,588 co-authors from 450 institutions in 35 countries. A total of 16,116 papers in 2,758 journals were cited. Authors from US institutions published the most papers and were cited the most, and authors from other countries also made considerable contributions.Conclusion This is the first time that the published research results in the field of rotator cuff injury tissue engineering have been bibliometric and visualized through systematic data retrieval combined with a variety of bibliometric analysis tools. Through these data, we summarized the previous research of scholars and prospected the future research in this field.
Woody species composition and diversity of homegarden agroforestry systems and their Contributions to Rural Livelihood in Dendi District, Central Ethiopia.
Authors: Dereje Yeshareg , Mammo Siraj
Published: August 2024

Compared to other agroforestry systems, the homegarden agroforestry system primarily consists of complicated multi-strata. This study assessed the Contributions of homegardens agroforestry to woody plant species' floristic composition, diversity and Rural Livelihood improvements in Dendi District, Central Ethiopia. To undergo this study 4 rural kebeles were selected using a purposive sampling technique from the study district. Homegardens were chosen from each kebeles using a systematic random sampling technique. Woody Plant species inventory was carried out for 48 homegarden agroforestry, from 143 total households. All woody plant species were counted and recorded in 10 x 10 m plots. A total of 37 woody plant species belonging to 33 genera and 26 botanical families were recorded in the study homegardens. The most diversified woody plant family was Fabaceae with five species followed, by Rosaceae and Euphorbiaceae each represented by three species. The average value of Shannon-Wiener diversity indices for the study area is 2.44. The range of species evenness, which was from 0.67 to 0.72, indicates the distribution of species in the homegardens of Dendi District is more or less similar. The respondents classified homegarden agroforestry in the Dendi district into 10 functional uses. The result revealed that about 34.4% of the woody plant species in homegardens served the household's cash income generation. Others are accounted for medicine, building or fuel wood, live fence, home materials, spices, stimulants, shade, and ornamentals. In addition, it contributes to environmental sustainability. Homegarden agroforestry systems conserve several woody species diversity in their system and woody species were more or less evenly distributed, among the study sites. Generally, the present study showed that the homegarden agroforestry system plays a remarkable role in conserving woody species diversity and the improvements of rural livelihoods. Therefore, the focus should be given to extension services, management and sustainable use of woody species in homegarden agroforestry.
Structural health monitoring of railway truss bridge under moving train load using decision tree models and residual neural networks
Authors: Sunchikala Sharan Kumar , C Mohan S , Gopala Sai Dheeraj , P Swetha
Published: August 2024

This paper introduces an efficient machine learning-based structural health monitoring method for railway truss bridges, addressing the time-consuming and error-prone nature of traditional approaches. By utilizing measured vibration responses under train load, the technique employs wavelets, Fourier transforms, and spectrograms to extract damage-induced changes in signals for training machine learning models. Given the slow and impractical data collection from real-world bridges, the paper proposes generating data from a numerical model, onto which a moving train load is applied. The acceleration time history responses from nodes are recorded for various damage cases, forming the dataset. Decision trees and Residual Neural Networks are trained on this data, demonstrating accurate classification of damaged members. Despite the effectiveness, human interpretation remains necessary for structural health monitoring, emphasizing these models as tools to enhance efficiency and reduce human errors in the monitoring process.
Factors associated with unmet medical needs among middle-aged and older adults in China during COVID-19 Pandemic
Authors: Zheng Yiping , Zhang Baoquan , Wei Jin , Xue Dongyu , Li Changle , Dai Yue
Published: August 2024

Background The COVID-19 pandemic may negatively impact the accessibility of medical care in China. This cross-sectional study aimed to identify the factors associated with unmet medical needs among middle-aged and older adults in China during the COVID-19 Pandemic. Methods A cross-sectional analysis using data from the 2020 China Health and Retirement Longitudinal Study. The final sample consisted of 19,123 individuals. Multiple imputation was applied to handle missing values. A binary logistic regression was used to examine factors associated with unmet medical needs. Results During the COVID-19 pandemic, 11.18% of middle-aged and older adults did not receive needed medical care. In both urban and rural areas, middle-aged and older adults who were male, with higher educational attainment, rated poor health, suffering from chronic conditions, residing in a residential area completely shut, and often felt fears were more likely to lead to unmet medical needs. In urban areas, middle-aged and older adults with urban employee medical insurance (OR = 2.30, 95% CI: 1.36, 3.56) and urban and rural resident medical insurance (OR = 1.65, 95% CI: 0.96, 2.44) were more likely to have unmet medical needs. In rural areas, middle-aged and older adults over 75 years of age (OR = 0.46, 95% CI: 0.35, 0.62) were less likely to have unmet medical needs, and middle-aged and older adults who knew the preventive measures (OR = 2.16, 95% CI: 1.42, 3.29) had a higher probability of having unmet medical needs. Conclusions The findings indicate gender, age, educational attainment, occupation, living with a spouse, health insurance, number of health technicians per 10,000, self-rated health, chronic conditions, depression, knowing the preventive measures, and fear of pandemic associated with unmet medical needs. The unmet medical needs of vulnerable groups should receive priority attention in the future and facilitate rationalizing the allocation structure of medical resources.
Evaluating the Potential of Wearable Technology in Early Stress Detection: A Multimodal Approach
Authors: Darwish Basil A. , Salem Nancy M. , Kareem Ghada , Mahmoud Lamees N. , Sadek Ibrahim
Published: August 2024

Stress can adversely impact health, leading to issues like high blood pressure, heart diseases, and a compromised immune system. Monitoring stress with wearable devices is crucial for timely intervention and management. This study examines the efficacy of wearable devices in early stress detection using binary and five-class classification models. Significant correlations between stress levels and physiological signals, including Electrocardiogram (ECG), Electrodermal Activity (EDA), and Respiration (RESP), were found, validating these signals as reliable stress biomarkers. Utilizing the WESAD dataset, we applied ensemble methods, Majority Voting (MV) and Weighted Averaging (WA), achieving maximum accuracies of 99.96% for binary classification and 99.59% for five-class classification. Ten classifiers were evaluated, with hyperparameter optimization and 3 to 10 fold cross-validation applied. Time and frequency domain features were analyzed separately. We reviewed commercially available wearables supporting these modalities and provided recommendations for optimal configurations in practical applications. Our findings demonstrate the potential of multimodal wearable devices for early detection and continuous monitoring of psychological stress, suggesting significant implications for future research and the development of improved stress detection systems.
Development and validation of a machine learning model for prediction of cephalic dystocia
Authors: Huang Yumei , Ran Xuerong , Zhai Jinguo , Wang Xueyan , Wu Defang , Yao Zheng
Published: August 2024

Background Early detection of cephalic dystocia is challenging, and current clinical assessment tools are limited. Machine learning offers unique advantages, enabling the generation of predictive models using various types of clinical data. Our model aims to integrate objective ultrasound data with psychological and sociological characteristics and obstetric treatment data to predict the individual probability of cephalic dystocia in pregnant women.Methods We collected data from 302 pregnant women who underwent examinations and deliveries at Southern Medical University's Nanfang Hospital from January 2022 to December 2023. We utilized basic patient characteristics, foetal ultrasound parameters, maternal anthropometric data, maternal psychological measurements, and obstetric medical records to train and test the machine learning models. Our study analysed the effectiveness of three machine learning models: least absolute shrinkage and selection operator (LASSO) regression, decision tree, and random forest. The precision, accuracy, recall, and area under the receiver operating characteristic (ROC) Curve (AUC) were used to evaluate the performance of the models.Results Among the three machine learning models, the LASSO-based logistic regression model demonstrated the best predictive performance, with an AUC value of 0.833. We found that maternal ischial spine diameter, fetal biparietal diameter, fetal biophysical profile score, artificial rupture of membranes, labor analgesia, childbirth self-efficacy, and other variables were predictive factors for cephalic dystocia.Conclusions This study constructed and validated a prediction model for cephalic dystocia via three machine learning methods, which can help clinicians improve the probability of identifying pregnant women at risk for cephalic dystocia.
Network analysis of key factors influencing subjective well-being among elderly with chronic disorders: A study based on the 2020 CFPS
Authors: Liang Chenyu , Ye Zilan , Yan Haifeng , Tan Jianfeng
Published: August 2024

Objectives
This study aims to delve into the mechanisms influencing the subjective well-being of elderly individuals with chronic disorders within the context of aging population. It comprehensively analyzes these factors, including cognitive schemas, social relationships, and demographics to provide a scientific basis for enhancing the subjective well-being of elderly individuals.
Methods
This study utilized data from the 2020 China Family Panel Studies (CFPS) and selected 863 individuals aged 65 and above with chronic disorders as subjects for analysis. Network analysis was conducted using JASP.
Results
This study has identified all the relationships between factors in the research and subjective well-being among the elderly with chronic disorders, and we have visualized them in graphical form. The findings indicate that social relationships (S1) are most closely associated with subjective well-being (W1), followed by level of confidence in the future (C1) and social status (B7). Further analysis found that C1 and S1 could be a mediator affecting the impact of B7 on W1.
Conclusion
Identify and delineate the key factors influencing the subjective well-being of elderly individuals with chronic disorders, as well as their interrelationships. This helps to further investigate the factors influencing the subjective well-being of the elderly.
Optimizing Ventilated Disk Brake Design for Enhanced Thermal Performance: An Analytical and Experimental Approach
Authors: Agrawal Vikash K. , Patil Lalit N. , Panwar Vikas Singh , Chavan Kaustabh Vijay , Nimbalkar U. D.
Published: August 2024

The primary purpose of the present investigation is to contribute to the invention of a methodology for determining the innermost temperatures in disc brakes at any range from its mid plane employing the Fourier transformation and Laplace transforms. These methods were utilized to investigate the interior surface temperature throughout braking under pad stress and disc tension circumstances. The initial segment of the mathematical simulation of the innermost temperature within the brake disk showed that the disk surface were the most relevant factor among the parameters under investigation. In the next segment experimentation approach, the ambient temperature along the interface among the pads and disk fluctuate between 97.8°C to 306.7°C because the rotation speed fluctuates across 300 rpm to 1100 rpm and the load from 20 N to 80 N. Another benefit section studies the flow of air, convection heat exchange parameters, and speeds, with validations using CFD simulation. The interface ranges (36.45°C to 91.668°C) were estimated with CFD. The vented brake rotors component was created as a three-dimensional model in modeling software and then loaded analysis software for estimating the disc's entire heat transfer including total thermal surface flux. It is possible to examine brake disks with complex geometries and concepts, especially tapered rotor disks, three-hole disks, among four-hole disks. The tapered rotor four-hole design has the greatest heat flux (489.32 W/m°K) and the greatest heat transfer factor (171262.8 W/m²) relative to other designs, and reaches the lowest temperatures (101.2°C). Mathematical, CFD, and testing examination of the suggested tapered rotor four-hole disk brake design revealed optimal thermal dissipation.
Network Security Anomaly Node Detection Based on Graph Neural Network and Attention Mechanism
Authors: Zhang Deng , Wang Juan , Gao Hanjun , Ni ZhouWei , Zhang Hao
Published: August 2024

Protecting networks from malicious access is a highly challenging task. Identifying and detecting anomalous paths can effectively filter out potential network threats. Despite extensive research in this field, the advent of new network technologies and the increase in connected devices have led to more diverse network attacks. Traditional anomaly detection methods struggle to capture complex relationships between nodes. Graph Neural Networks (GNNs), with their multi-layer structures, can efficiently extract multi-attribute features of nodes.we propose an efficient method for anomalous path detection. By incorporating a multi-head attention mechanism into GNNs, we dynamically adjust node weights to capture complex dependencies. To accurately identify anomalous nodes, we also designed a new threat evaluation scoring formula, enhancing the robustness and accuracy of anomaly detection. Experimental results on the CIC-IDS-2017 dataset show that our model achieved nearly 100\% accuracy and the fastest response time. Compared with previous work, our model provides faster decision-making and significantly improved evaluation performance.Our research demonstrates the potential of GNNs and multi-head attention mechanisms in network security, offering strong support for addressing increasingly complex network threats.
A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network Security
Authors: Arreche Osvaldo , Abdallah Mustafa
Published: August 2024

New research focuses on creating artificial intelligence (AI) solutions for network intrusion detection systems (NIDS), drawing its inspiration from the ever-growing number of intrusions on networked systems, increasing its complexity and intelligibility. Hence, the use of explainable AI (XAI) techniques in real-world intrusion detection systems comes from the requirement to comprehend and elucidate black-box AI models to security analysts. In an effort to meet such requirements, this paper focuses on applying and evaluating White-Box XAI techniques (particularly LRP, IG, and DeepLift) for NIDS via an end-to-end framework for neural network models, using three widely used network intrusion datasets (NSL-KDD, CICIDS-2017, and RoEduNet-SIMARGL2021), assessing its global and local scopes, and examining six distinct assessment measures (descriptive accuracy, sparsity, stability, robustness, efficiency, and completeness). We also compare the performance of white-box XAI methods with black-box XAI methods. The results show that using White-box XAI techniques scores high in robustness and completeness, which are crucial metrics for IDS. Moreover, the source codes for the programs developed for our XAI evaluation framework are available to be improved and used by the research community.
The Transcriptome dynamics of the pituitary of turkey (Meleagris gallopavo) during broodiness
Authors: Bankizadeh Fatemeh , Sadr Ayeh Sadat , Safari Reza , Banabazi Mohammad Hossein
Published: August 2024

Broodiness is a maternal behavior and an instinct for natural breeding in poultry that inhibits egg production. The transition from the egg-laying to the brooding phase is a complex process that ultimately leads to gonadal regression, changes in neuroendocrine patterns, and termination of ovulation. The turkey is one of the species having strong brooding behavior and affecting the productivity of industry. genetic and environmental factors influencing broodiness in poultry have been extensively studied, but the molecular regulation mechanism of broodiness is somewhat unclear. Recently, the RNA sequencing technique has been applied to investigate gene expression profiles during the egg-laying period and brooding period. In this research, the pituitary transcriptome of commercial turkey birds were studied during the egg-laying and brooding period. A total of 334 differentially expressed genes were identified (fold change ≥ 1, P < 0.05). There were 229 upregulated expressed genes and 104 downregulated at egg-laying period compared with brooding period. In the present study, the results of GO and KEGG analysis revealed that the genes in the protein processing in the endoplasmic reticulum pathway, Spliceosome complex pathway and Regulation of actin cytoskeleton pathway (P < 0.05) are critical for controlling the hormonal cycle and autophagy. In addition, regulation of neurotransmitter secretion and regulation of neuronal synaptic plasticity were highly enriched in calcium ion related biological processes.
Dynamic changes in prokaryotic and eukaryotic communities and networks in a minimally managed cabbage-cultivated field soils
Authors: Ito Sentaro , Murakami Junya , Suzuki Mio , Hirose Yuu , Yamauchi Takahiro , Eki Toshihiko
Published: August 2024

In this study, we used DNA metabarcoding to investigate both terrestrial prokaryotes and eukaryotes in minimally managed cabbage-cultivated and uncultivated agricultural fields from February to August 2021. Analyses of the relative abundances of prokaryotic and eukaryotic sequence variants (SVs) and their β-diversities have clarified the dynamic changes in eukaryotic communities during cultivation. We investigated taxonomic changes in fungi-, protist-, and animal-derived SVs, as well as abundant SVs in each eukaryotic phylum. The results revealed that the fractions of predatory or parasitic protists and animals increased, whereas those of fungi and earthworm Enchytraeus spp. decreased. The fractions of abundant SVs derived from diatoms, Ciliophora, the class Vampyrellidae (Cercozoa), and mites increased and subsequently decreased during this period. These findings suggest that predatory protists and animals fed on bacteria and autotrophic eukaryotes, such as diatoms, propagated in spring, followed by their propagation and parasitism to host eukaryotes. The co-occurrence networks of the top 150 SVs also changed, especially prokaryotic networks that markedly changed from April to May, and those of eukaryotes from May to June– August, supporting the observations mentioned above. These findings indicate dynamic changes in eukaryotes in fields with minimal agricultural practices and are useful for sustainable natural farming.
Suitability evaluation of ecotourism activities in national parks --- a case study of the Qilian Mountain National Park
Authors: Huang Shan , Sheng Danhua , Wang Pengtao , Xiao Jianhua , Li Qiushuang , Liu Hanjun
Published: August 2024

Effective development of ecotourism is a strategy to improve the main functional areas of national parks, including scientific protection and utilization. For best results, suitability of ecotourism activities must be determined but methods and guidelines for suitability studies are lacking. Here, we used the Gansu area of the Qilian Mountain National Park in China as a case study and proposed a model AHP-PROMETHEE-GIS based on landscape units for the suitability evaluation of ecotourism activities. The PROMETHEE method was used in the Python software, and the suitability ranking was obtained for eco-tourism activities in 1641 landscape units. The first four levels of suitability ranking of landscape units were visualized with ArcGIS. The analysis showed that the Gansu area of the Qilian Mountain National Park is suitable for cross-country adventure, professional investigation, forest recreation, and other eco-tourism activities. A spatial layout of ecotourism was established in the non-core protected areas of the national park, with a goal to balance development of ecotourism and ecological protection, and to realise the unity of the ecological, economic, and social benefits of the Qilian Mountains National Park.
A label-free electrochemical aptamer sensor for sensitive detection of cardiac troponin I based on AuNPs/PB/PS/GCE
Authors: Jiang Liying , Li Dongyang , Su Mingxing , Chen Fenghua , Qin Xiaomei , Wang Lan , Gui Yanghai , Zhao Jianbo , Guo Huishi , Qin Xiaoyun , Zhang Zhen
Published: August 2024

Monitoring cardiac troponin I (cTnI) is of great value in the clinical diagnosis of acute myocardial infarction (AMI). In this paper, a highly sensitive electrochemical aptamer sensor was demonstrated by using polystyrene (PS) microspheres as the electrode substrate material, combined with Prussian blue (PB) and gold nanoparticles (AuNPs) for the sensitive and label-free determination of cTnI. PS microspheres were synthesized by emulsion polymerization and then dropped onto the glassy carbon electrode, PB and AuNPs were electrodeposited on the electrode in corresponding electrolyte solution step by step. The PS microsphere substrate provided a large surface area for loading mass of the biological affinity aptamers, while the PB layer improved the electrical conductivity of the modified electrode and the electroactive AuNPs exhibited excellent catalytic performance for subsequent electrochemical measurements. In view of the above-mentioned sensing platform, the fabricated label-free electrochemical aptamer sensor showed a wide detection range of 10 fg/mL ~ 1.0 µg/mL and a low limit of detection of 2.03 fg/mL under the optimal conditions. Furthermore, this biosensor provided an effective detection platform for the analysis of cTnI in serum samples. The introduction of this sensitive electrochemical aptamer sensor provides a reference for clinical sensitive detection of cTnI.
Design and Development on Multiple Physical Fields Simulation of High-Voltage Switchgear
Authors: Hou Kang , Yu Jiuhong , Huang Beiju , Hou Shen
Published: August 2024

This paper presents a simulation system software for the design and assembly of high-voltage switchgear components. For different kinds of high-voltage switchgear, the system uses STL forms to show three-dimensional (3D) solid models in model base, including the parts and assembly. The system software realizes seamless integration with analysis software COMSOL. In the system, the three-dimensional solid model is imported into the finite element analysis software, and the multi physical field (temperature field, electromagnetic field, air flow field) simulation of different high-voltage switchgears is realized through attribute setting, subdivision, parameter definition and other links.
RETRACTED: Support community perimenopausal women's health education: health coaching intervention study
Authors: Wan Hui , Yao Wenlian , Ma Jiahui , Xu Zhirong , Bai Yaru , Liu Guolian
Published: August 2024

The authors have requested that this preprint be removed from Research Square.
Adaptive Force/Position NN Control of Asymmetric Teleopertion System Based on Fuzzy CMAC
Authors: Chen Hua , Shi Baoyu
Published: August 2024

Metallurgical industrial robots play an increasingly indispensable role in modern industries. Today, with a significant increase in industrial automation, people continually demand higher performance from metallurgical industrial robots. The application of teleoperated system in the metallurgical field is becoming increasingly widespread. A teleoperation system consists of a master robot and a slave robot. Stability, tracking, and transparency are the performance requirements for teleoperation systems. Asymmetric teleoperation systems are more widely used than isomorphism teleoperation systems. This study chose an asymmetric teleoperation system in which the master robot is a novel form of 6-degree of freedom mechanism consists of series and parallel. The slave robot is Baxter robot. An Adaptive CAMC intelligent control algorithm was used for asymmetric teleoperation system force/position control. The experiment results showd that the Adaptive Fuzzy CAMC control algorithm outperforms Adaptive Fuzzy & PID control algorithm in terms of control performance for Asymmetric teleoperation systems. The experiment also demonstrates that the master hand satisfies the asymmetric teleoperation system..
An Efficient Cluster Based Spectrum Sharing System in Cognitive Wireless Environment
Authors: N Mahesh Kumar , SEGU RAMGOPAL , Harshitha B , N KEERTHY
Published: August 2024

With the expeditious progression of the Internet of Things (IoT), there is a growing need for robust connectivity solutions that can accommodate the increasing number of cell-edge users. These users often need help with the inferior signal quality compared to those at the cell centre. The User-Pairing NOMA (UPNOMA) system that integrates the Spatial Modulation (SM) with Non-Orthogonal Multiple Access (NOMA) named SM-UPNOMA enhanced the IoT connectivity and spectral efficiency in networks dominated by cell-edge users. However, the optimal time slots and bandwidth between the paired users are remarkable in obtaining these advantages. Hence, a novel Crayfish Optimized SM-UPNOMA (COSU) system that aims for optimal allocation of time and bandwidth. It offers two distinct variants: Time-sharing SM-UPNOMA (TSM-UPNOMA) and bandwidth-sharing SM-UPNOMA (BSM-UPNOMA). The designed method is meticulously crafted to optimize bit error rate (BER) performance and maximize the sum rate, effectively addressing the challenges of high spectral efficiency in dense cell-edge environments. The advantages of the proposed systems are manifold, including improved spectral efficiency and enhanced BER performance even under less-than-ideal successive interference cancellation (ISIC) conditions. By leveraging spatial modulation, the system effectively utilizes the spatial domain as an additional multiplexing dimension, enabling support for more users without significantly increasing complexity. This research focuses on wireless communication systems, specifically advanced signal processing techniques for Next-Generation Networks (NGNs). Through extensive simulations, this paper demonstrates the superior performance of SM-UPNOMA systems compared to conventional NOMA (C-NOMA), SM-aided conventional NOMA (SM-CNOMA), and SM-aided OMA (SM-OMA). Furthermore, the analytical verification of the BER performance for TSM-UPNOMA provides practical validation for the proposed model.