bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Lifelong Education Practice Experiences through Grounded Theory
Authors: YOON OK HAN
Published: November 2024

This study aims to provide insights into the direction of lifelong education practice by analyzing the experiences of lifelong education practice through grounded theory to enhance the professionalism of lifelong educators. To achieve the research objective, interviews with seven participants in lifelong education practice were analyzed using grounded theory, and the results are as follows. First, the central phenomenon regarding the experience of lifelong education practice was the re-establishment of the concept of lifelong education. Second, the process analysis using grounded theory revealed that the prospective lifelong educators went through stages of exploration, acceptance, adjustment, and establishment during their practice. Third, the core category that integrates and connects the categories in this study, which is also the central phenomenon, is the re-establishment of the concept of lifelong education. The outcomes include heightened expectations for lifelong education and the achievement of self-realization through lifelong education.
Semaphorin-4D Signaling in Recruiting Dental Stem Cells for Vascular Stabilization
Authors: Zhang Lili , Thalakiriyawa Dineshi Sewvandi , Liu Jiawei , Yang Shengyan , Wang Yan , Dissanayaka Waruna Lakmal
Published: November 2024

Background
Achieving a stable vasculature is crucial for tissue regeneration. Endothelial cells initiate vascular morphogenesis, followed by mural cells that stabilize new vessels. This study investigates the in vivo effects of Sema4D-Plexin-B1 signaling on stem cells from human exfoliated deciduous teeth (SHED)-supported angiogenesis, focusing on its mechanism in PDGF-BB secretion. We also explore macrophages as an endogenous source of Sema4D for vascular stabilization.
Methods
The in vivo Matrigel plug angiogenesis assay was conducted to examine the impact of Sema4D on vessel formation and stabilization supported by SHED. Knockdown of Plexin-B1 in human umbilical vein endothelial cells (HUVECs) and the application of PDGFR-β inhibitors were utilized to explore the fundamental regulatory mechanisms. Furthermore, the m6A methylation levels of total RNA and the expression of Methyltransferase-like 3 (METTL3) were assessed under conditions of Sema4D treatment in vitro. An ELISA was employed to measure the levels of Sema4D in the supernatants derived from THP-1 cell-mediated macrophages. Additionally, a three-dimensional vasculature-on-a-chip microfluidic device was employed to investigate the role of M2c macrophage-derived Sema4D in the stabilization of vascular structures.
Results
Sema4D induced the formation of a greater number of perfused vessels by HUVECs and enhanced the coverage of these vessels by SM22α-positive SHED (SM22α+SHED). Conversely, the knockdown of the Plexin-B1 receptor in HUVECs or inhibition of PDGFR-β reversed the Sema4D-induced vascular stabilization, thereby confirming the regulatory role of the Plexin-B1/PDGF-BB axis in the recruitment of mural cells mediated by Sema4D. Mechanistically, Sema4D was found to upregulate the expression of methyltransferases, specifically METTL3, and to elevate the level of m6A modification in HUVECs. This modification was determined to be critical for enhancing PDGF-BB secretion, suggesting that Sema4D activates an epigenetic regulatory mechanism. Additionally, we investigated the secretion of Sema4D by various macrophage phenotypes, identifying that M2c macrophages secrete significant levels of Sema4D. This secretion recruits SM22α+SHED as mural cells by inducing endothelial PDGF production on a vasculature-on-a-chip platform, indicating a potential role for macrophages in facilitating vascular stabilization.
Conclusions
Sema4D acts on Plexin-B1, inducing METTL3-mediated PDGF-BB secretion to recruit SHED to stabilize vessels. Macrophages could be a key source of Sema4D for vascular stabilization.
CFD-based Aerodynamic Optimization of the Fairing for a High- Speed Elevator
Authors: Shen Xiawei , Wang Aimin , Wanbing Liu , Wang Rongyang
Published: November 2024

This paper presents a computational fluid dynamics (CFD) analysis of the external flow field of a high-speed elevator car. A fairing with a varying cross-section is designed to improve the aerodynamics of the high-speed elevator car. An optimization study of the fairing is performed by combining the parametric optimization method and CFD. The cross-section of the fairing is parameterized by NURBS curves; then, the Latin experimental design method is used to generate test sample points, a mathematical model is formulated utilizing the response surface model approximation, and global optimization is conducted through the application of a multi-island genetic algorithm. The results show that by empirically adding the fairing, the aerodynamic resistance of the high-speed elevator car can be significantly reduced by 36.6% compared to that of the original model; moreover, by optimizing the designed fairing through modern optimization methods, the aerodynamic resistance of the high-speed elevator car can be further reduced by 39.3% compared to that of the original model. The structural parameters of the fairing have a significant impact on the aerodynamic performance of the high-speed elevator.
Fault analysis and Fault degree evaluation via an improved ResNet method for Aircraft Hydraulic System
Authors: Shen Kenan , Zhao Dongbiao
Published: November 2024

The hydraulic system is crucial for the safety of the aircraft, which is the key to ensuring the safety of both the aircraft and passengers. It is necessary to study and analyze the normal and fault mode of the system to provide a way for evaluating the fault degree of the hydraulic system. Therefor an improved ResNet based fault degree evaluation method was proposed to evaluate the fault degree of the aircraft hydraulic system. First, the aircraft hydraulic system is constructed by the AMESim, one normal and five fault modes are simulated. Then the effects of the parametric variations for the five fault models are studied, in which pump oil leakage is chosen for analysis. After the analysis of the 5 kinds of faults, each of them is divided to 3 different fault degree, then 16 kinds of states are definition. Second, using the SE-ResNet based method to evaluate the system fault degree. The structure of the two improved ResNet blocks are designed, after that the whole structure of the SE-ResNet fault degree evaluation model is given. Then the parameters of the SE-ResNet are optimization by simulation. After that the evaluate results are given and analysis, moreover the comparison between the SE-ResNet method with the other machine learning methods are given. The results show that the method in this paper has the best accuracy and shortest test time, therefor the method proposed in this paper has effective measures to improve the reliability of the aircraft hydraulic system.
Mechanical properties and damage constitutive model of frozen brain tumors under cryogenic-mechanical coupling effect
Authors: Hu Wenxuan , Wang Suran , Chen Youliang
Published: November 2024

Cryoablation, as an important method for tumor treatment, possesses the advantages of safety, efficiency, and minimally invasive characteristics. However, the phenomenon of intracranial pressure fluctuation caused by brain tumor cryoablation has not received sufficient attention. Investigating the mechanism behind the interaction between intracranial temperature and pressure may contribute to addressing this issue. Considering the coupling effect of temperature and confining pressure, the evolution equation and constitutive model of tumor mechanical damage after freezing were constructed to evaluate the influence of freezing on mechanical properties and damage law of biological tissues in a low temperature environment. Based on the Lemaitre's strain-equivalence principle, the microelement strength of tumor ice body under the coupling of low temperature and confining pressure is assumed to follow a Weibull distribution. The thermal and mechanical damage variables are introduced using continuous damage mechanics and statistical theory, and the microelement failure is in accordance with the SMP criterion. Adopts the numerical simulation of intracranial glioma cryoablation COMSOL temperature - mechanical coupling response mechanism, by numerical simulation and theoretical derivation method to obtain the required constitutive model parameters, the theory of stress-strain curve compared with simulated curve, accord well with those of two kinds of curve. The results show that the established damage statistical constitutive model can accurately reflect the stress-strain characteristics of biological tissues after freezing, and verify the rationality and reliability of the model and its parameter determination method.
A parametric investigation of binaural beats for brain entrainment and enhancing sustained attention
Authors: Melnichuk Anastasiia , Cooper Robert K. , Hawk Larry W.
Published: November 2024

Binaural beats (BBs) have garnered attention as a highly accessible, noninvasive method to enhance cognitive performance, putatively via brain entrainment. However, the few studies that have directly examined the impact of BBs on sustained attention report inconsistent findings, perhaps due to wide variation in methodology. This study experimentally varied BB parameters while testing the effects of BBs on both sustained attention and brain entrainment. Eighty undergraduate students participated in a within-subjects cross-over comparison of the effects of BBs vs. control auditory stimulation on a continuous performance task to measure sustained attention. Participants were randomized to different auditory stimulation parameters: beats frequency (beta or gamma), carrier tone (340 or 400 Hz), onset time (before or with task onset), and background masking noise (present or absent). EEG data were collected to validate brain entrainment. Gamma frequency BBs with a low carrier tone and white noise background improved general attention performance but did not reduce the vigilance decrement over time, suggesting BBs may modulate other cognitive aspects rather than sustained focus. EEG results confirmed brain entrainment, though entrainment varied with BB parameters and background noise. Further research should explore the interactions between BB parameters to optimize their use for cognitive enhancement.
The triglyceride-glucose index trajectories are associated with cardiovascular diseases in people living with HIV: evidence from a prospective cohort study in China, 2005-2022
Authors: Luo Yinsong , Sun Liqin , He Yun , Zhao Fang , Shan Duo , Bu Fan , Ge Lingyun , Li Xiaorui , Hu Yiyao , Xiao Xi , Lu Hongzhou , Liu Jiaye
Published: November 2024

Background
The triglyceride-glucose (TyG) index has been validated as a novel biomarker for cardiovascular disease (CVD) risk. However, the prospective relationship between baseline and long-term trajectories of the TyG index and CVD risk in people living with HIV (PLWH) remains unexplored.
Methods
This cohort study included 16,122 treatment-naive PLWH who initiated antiretroviral therapy (ART) at the Third People's Hospital of Shenzhen from 2005 to 2022. The TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Group-based trajectory modeling (GBTM) was used to identify distinct TyG index trajectories over the follow-up period. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using multivariate Cox proportional hazards models to assess the association between TyG index trajectories and CVD risk. Nonlinear relationships were investigated using a restricted cubic spline plot. Subgroup analysis was conducted to examine whether the association between the TyG index and CVD risk differed across various subgroups.
Results
During a median follow-up of 70 months, 214 PLWH developed CVD. Each 1-standard deviation (SD) increase in the baseline TyG index was associated with a 33% higher risk of CVD (HR = 1.33, 95% CI 1.18–1.51) after adjusting for traditional CVD risk factors. Participants were categorized into four distinct TyG trajectory groups: low-stable, low-moderate-stable, high-moderate-stable, and high-increasing. After multivariate adjustment, the high-increasing trajectory group had a 2.72-fold (95% CI 1.58–4.69) increased risk of CVD compared to the low-stable group. The restriction cubic spline plot showed an upward trend between the baseline TyG index and the CVD occurrence (P < 0.001), with the threshold at 8.479. Significantly positive correlations between the TyG index and CVD were observed both below the TyG threshold with HR 3.71 (95% CI 1.18, 11.68) and above the threshold with HR 1.39 (95% CI 1.03, 1.87) (both P < 0.05).
Conclusions
Higher baseline TyG index levels and the high-increasing trajectory were significantly associated with increased CVD risk in PLWH. Long-term trajectories of the TyG index could aid in identifying individuals at higher risk of CVD, highlighting the importance of incorporating TyG index monitoring into routine clinical assessments for tailored prevention strategies.
Stigma in Type 2 diabetes: a study from Southern India
Authors: Sri Aruna , Lakshmi Gumpeny , Srid Gumpeny Ramachandra
Published: November 2024

Among the many psychological and psychiatric disturbances in diabetes, stigma due to the disease (‘Diabetes stigma’) is one. It has been studied principally in subjects with type 1 diabetes. We report diabetes stigma in subjects with type 2 diabetes from southern India, in relation to demographic and lifestyle variables.
Subjects with type 2 diabetes mellitus presenting to a tertiary care diabetes and endocrine center in southern India were recruited (n:333; 196 men, 137 women age range 25-78 years). structured interview form to provide demographic, clinical and life style related information. They completed Diabetes Stigma Assessment Scale-2 (DSAS-2) to assess diabetes stigma.
ANOVA and t-test results showed that the tested demographic variables (age, gender, occupation, level of education and income), clinical and life style variables (diabetes duration, no. of stressors and exercise) had significant influence on the experience of diabetes stigma. When these associations were tested using two separate multiple regression models, only age was found to be a significant predictor of stigma in terms of total stigma experience, perception of being treated differently by others, self-stigma and blame & judgment by others. Interestingly, participants’ gender didn’t make any significant difference in this experience of stigma. Similarly, all the three tested clinical and life style variables emerged as significant predictors of various domains of diabetes stigma.
Diabetes stigma is closely linked with age and life style factors such as duration of diabetes, number of stressors being experienced and physical exercise among people with Type 2 diabetes.
Association between penicillin allergy labels and serious adverse events: a systematic review and meta-analysis
Authors: Zhang Shipeng , Dong Tianyi , Xian Jiawen , Xiao Xinyue , Yuan Jiaqing , Zeng Tong , Deng Kuan , Fu Rui , Wang Hanyu , Jiang Yanjie , Li Xueying
Published: November 2024

Background
To date, several studies have demonstrated that erroneous labeling of Penicillin allergy (PAL) can significantly impact treatment options and result in adverse clinical outcomes, while other studies have reported no negative effects. Therefore, to systematically evaluate these effects and investigate the association between adverse clinical outcomes and the Penicillin label, we conducted this meta-analysis.
Method
Searches were conducted in the PubMed, Embase, Cochrane Library, and Web of Science databases from inception to July 13, 2024. The search strategy utilized terms ("antibiotic allergy label," "penicillin allergy label," and "allergy label") and ("death," "readmission," "adverse outcome," and "clinical adverse outcome"). In the study selection process, the PICOS framework and stringent inclusion/exclusion criteria were applied. The quality of the initially included studies was independently assessed using the Newcastle-Ottawa Scale (NOS). Data from the included studies, including relative risk (RR) and 95% confidence intervals (CI), were extracted and analyzed using Stata 16.0. Sensitivity analyses were conducted to validate the results. Heterogeneity was assessed using the I² and Cochrane Q tests, and publication bias was evaluated using Egger’s test and funnel plot analysis.
Results
A total of 497 relevant studies were identified through four databases. Following a thorough screening process, 11 studies encompassing 1,200,785 participants were ultimately included. The combined evidence suggests that penicillin allergy labeling is associated with increased mortality RR = 1.06 (95% CI 1.06–1.07, I²=0.00%), acute heart failure(RR = 1.19, 95% CI 1.09–1.30, τ²=0.00, I²=92.39%), ICU events (RR = 1.10, 95% CI 1.01–1.19, τ²=0.00, I²=57.09%), and mechanical ventilation events (RR = 1.16, 95% CI 1.09–1.24, τ²=0.00, I²=23.11%). Additionally, there was no significant association with readmissions (RR = 1.05, 95% CI 0.95–1.16, I²=0.00%).
Conclusion
Our findings indicate that penicillin allergy labels are associated with an increased risk of mortality in patients, as well as being linked to acute heart failure, heightened ICU requirements, and mechanical ventilation.
Analysis of Multi-Scale Latent Heat Flux Remote Sensing Data Based on the RST Method and Its Application in Pre-Earthquake Thermal Anomalies
Authors: Zhang yuan , Zhou Hui , Li Xiang
Published: November 2024

This study explores the application of Robust Satellite Techniques (RST) for analyzing latent heat flux anomalies in relation to seismic activity, utilizing three datasets—GLEAM, PML, and ETMonitor—across various spatial resolutions. Focusing on four significant earthquakes in mainland China (Wenchuan, Ludian, Lushan, and Yushu), the research highlights consistent anomalous trends observed prior to these events, with notable increases in latent heat flux anomalies in the days leading up to each earthquake. The results reveal that RST values frequently approached or exceeded 1.5, particularly evident near the epicenter and along the fault zones, validating the correlation between latent heat flux anomalies and seismic activity.
The findings indicate varying spatiotemporal characteristics of anomalies across different earthquakes: the Wenchuan earthquake displayed longer-lasting anomalies, while the Lushan and Ludian earthquakes exhibited more concentrated and intense anomalies; the anomalies associated with the Yushu earthquake were less pronounced. Additionally, the analysis shows that land use types such as forests, medium to high cover grasslands, shrublands, and plain cultivated land—characterized by higher soil moisture content—were more likely to exhibit anomalies, aligning with previous research indicating that latent heat flux precursors are more prevalent in environmentally humid areas.
Overall, this study emphasizes the potential of using RST to detect thermal anomalies as precursors to earthquakes and suggests the need for further investigation into the background fields and anomaly thresholds at different spatial scales, as well as the relationship between latent heat anomalies and seismic events across various land surface types.
Determining the Levels of Mental Resilience and Imagery in National Team Athletes with Hearing Impairments
Authors: ÖZCAN Buşra
Published: November 2024

Background
National athletes with hearing impairments often face unique challenges that may impact their mental resilience and performance. Understanding the relationship between the levels of imagery and mental resilience in this population is critical for developing effective support strategies.
Aims
The purpose of this study is to examine the relationship between the levels of imagery and mental resilience in national athletes with hearing impairments.
Methods
A total of 54 professional athletes participated voluntarily in the research. After identifying outlier data through Box plot analysis, data from 2 participants were excluded, resulting in a final sample of 52 participants. Sociodemographic information was collected using a personal information form developed by the researcher. Measurement tools included the “Sport Imagery Questionnaire” and the “Sport Mental Resilience Inventory.” Normality of the score distribution was confirmed through skewness and kurtosis analysis. Descriptive statistics (frequency and percentage) were employed in accordance with these findings. For data analysis, the “Independent Sample T-Test” was utilized for comparisons between two independent groups, while the “One-Way ANOVA” was used for comparisons involving more than two groups. The “Pearson Correlation Test” examined the relationship between two numerical variables.
Conclusions
The study found that as the average scores from the mental resilience scale increased, levels of imagery in sports, scores from the sports imagery inventory, levels of motivational specific imagery, and levels of motivational general mastery also increased. This suggests a positive interaction between studies on imagery and mental resilience.
JEL Codes
C153, B150, C230, C310
Predicting the Impact of Extreme Weather on Agricultural Losses in the Delmarva Peninsula using Multi-Step Machine Learning and Financial Crop Loss Data
Authors: Nourali Zahra , Shortridge Julie E
Published: November 2024

The increasing occurrence of extreme weather events due to climate change presents significant challenges for agricultural production. Existing research on climatic impacts to agriculture has predominantly focused on changes in yield for major crops, providing limited insights into overall losses and impacts on diverse regional agricultural systems. This study addresses this gap by using financial crop loss data and crop insurance payouts to gain a more comprehensive understanding of agricultural impacts in diverse agricultural regions. To address the irregular data structure of financial loss data, we developed multi-step machine learning models to quantify the relationship between weather-related financial crop loss and contributing climatic factors. The Delmarva Peninsula in the Eastern United States is used as a case study location to demonstrate this methodology over the period from 1980 to 2018. Multi-step configurations of linear regression, random forest, and support vector machine approaches are compared in terms of their classification and estimation accuracy using a repeated hold-out cross-validation analysis. Results indicate that machine learning methods, particularly random forest, outperform both statistical approaches and our null baseline model, demonstrating superior generalizability in agricultural damage estimation. Multistep configurations that address irregular data distributions are shown to have a significant influence on models' capacity to detect and estimate damage occurrence. The study reveals a preference for simpler modeling approaches that minimize variance in handling unseen data, as well as the importance of accounting for seasonal patterns, spatial groupings, and persistent weather phenomena in accurately estimating agricultural losses.
Comparative Network Analysis under ABA and Chitosan Treatments: Unveiling Key Transcriptional Regulators of Valerenic Acid Biosynthesis in Valerian Hairy Roots
Authors: Mokhtari Arash , Azadi Pejman , Ebrahimi Morteza , Sobhani Ahmad , Zarghami Reza , Amirian Rasoul , Arezi Iman , Shafaei mozhdeh
Published: November 2024

Valerenic acid is a sesquiterpene compound found in Valeriana officinalis (valerian) and has gained attention for its potential as a natural remedy for anxiety, insomnia, and stress-related disorders due to its calming and sedative properties. The low compound content and slow plant growth have limited its production, so a biotechnological approach such as hairy root culture is needed to scale up valerenic acid without using natural resources. This study aims to elucidate the structural and dynamic features of the gene and transcription factor network underlying valerenic acid production in the hairy root cultures of valerian under ABA and chitosan elicitation. ABA treatment induced significant changes in the expression of BHLH and ERBP transcription factors. Their relative expression levels peaked on the second day. Among the genes encoding terpene synthase enzymes, TPS5 shows the strongest induction. When induced with chitosan, the transcription factors BHLH and ERBP play a critical role in enhancing valerenic acid accumulation by upregulating the expression of HMGR, TPS2, and TPS5. In addition, WRKY, ERBP, and MYB transcription factors act as critical regulators in the activation of terpene synthases. Chitosan treatment leads to the highest valerenic acid level (0.68 mg/g DW) on day 2. In comparison, ABA triggers the highest valerenic acid level (0.65 mg/g DW) on day 4. Our results have significant implications for the development of efficient and sustainable strategies for the large-scale production of valerenic acid, a valuable compound widely used in the pharmaceutical industry.
Nomophobia And Other Psycho-social Factors Affecting Sleep Quality Among Undergraduate Health Sciences Students: A Cross-Sectional Study
Authors: Khan Muhammad Anas , Lakhdir Maryam Pyar Ali , Azam Syed Iqbal , Asad Nargis
Published: November 2024

Background
Good sleep quality is crucial for overall health and wellbeing. Poor sleep quality has been linked with various factors including nomophobia, i.e., fear of not having a mobile phone. However, limited evidence is available in Pakistani setting therefore this study aims to determine the burden of nomophobia and poor sleep quality along with association between them among Pakistani undergraduate health sciences students.
Methods
We conducted a cross-sectional study at a private institute in Karachi, Pakistan. 551 undergraduate health sciences students were recruited via purposive sampling. The outcome variable is sleep quality status (Poor and good) and was measured using the Pittsburgh Sleep Quality Index. The primary exposure variable is degree of nomophobia and was assessed by the Nomophobia Questionnaire. Other psychosocial and demographic variables were also adjusted. Crude and adjusted prevalence ratios were computed with their 95% confidence intervals using Cox proportional algorithm.
Results
Nearly two-thirds of study participants, (n = 385, 69.1%) were females. among which 94.4%(520) were youth aged 15–24 years. 47.2%(260) students were enrolled from medical college as compared to 52.8%(291) from nursing. The prevalence of poor sleep quality was reported to be 45%. Moderate nomophobia was most prevalent at 56.8% followed by severe nomophobia (38.5%). The prevalence of poor sleep quality among students with severe nomophobia was 1.71 times (95% CI 0.9, 2.9) as compared to those with no or mild nomophobia. Prevalence of poor sleep quality among students with moderate nomophobia was 1.4 times as compared to those with no or mild nomophobia when all other variables are held constant.
Conclusion
Nomophobia and poor sleep quality were alarmingly prevalent among undergraduate health sciences indicating on the importance of drafting health policies concerning adolescents and young adults, with particular emphasis on medical students. Self-awareness and help-seeking can only be ensured to students if encouraged to share their feelings with unbiased discussion on the topic and are provided with a healthy support system. The curriculum also needs to be revised to address this issue, including providing regular counselling services and no smartphone campus days to raise awareness.
Deep Learning-Assisted Screening and Diagnosis of Scoliosis: Segmentation of Bare Back-Images via an Attention-Enhanced Convolutional Neural Network
Authors: Duan Xingyu , Ma Xiaojun , Zhu Mengqi , Wang Linan , You Dingqi , Deng Lili , Niu Ningkui
Published: November 2024

Background: Traditional scoliosis screening necessitates a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We have developed a deep learning-based image segmentation model to enhance the efficiency of scoliosis screening.
Methods: A total of 350 patients with scoliosis and 108 healthy subjects were included in this study. The dataset comprised bare back images and full-length anteroposterior and lateral X-ray images from 458 participants. An attention mechanism was incorporated into the original U-Net architecture to build an attention U-Net model for image segmentation. The entire dataset was divided into training (321 cases), validation (46 cases), and test (91 cases) sets at a 7:1:2 ratio. The training set was used to train the attention U-Net model, whereas the validation set was used to fine-tune hyperparameters and prevent overfitting during training. The performance of the model was evaluated via the test set. After automatic segmentation of the back contour, a back asymmetry index was calculated viacomputer vision algorithms. The severity of scoliosis was classified on the basis of this index, and the classification results were statistically compared to those of three clinical experts.
Results: Following the segmentation of bare-back images and the application of computer vision algorithms, the U-Net model achieved an accuracy, precision, and recall rate of over 90% in predicting severe scoliosis. Notably, the AUC values for diagnosing scoliosis were 0.93 for the U-Net model and 0.92 for the associate chief physician, while for identifying severe scoliosis, the AUC values were 0.95 and 0.96, respectively.
Conclusion: The attentionU-Net model developed in this study achieved accuracy and precision in determining scoliosis severity comparable to that of clinical physicians by analyzing bare-back images. The model's ability to diagnose scoliosis was also similar to that ofclinical professionals. The use of this model for scoliosis screening and diagnosis offers advantages such as being radiation-free and improving efficiency. This provides a novel, noninvasive, and effective approach, as well as a theoretical foundation, for large-scale scoliosis screening.
Smartphone-based monitoring of heart rate variability and resting heart rate predicts variability in symptom exacerbations in people with complex chronic illness
Authors: Aitken Annie , Sawyer Abbey , Iwasaki Akiko , Krumholz Harlan M. , Preston Rory , Leeming Harry , Tosto-Mancuso Jenna , Proal Amy , Osborne Michael A. , Putrino David
Published: November 2024

Background: Complex chronic conditions like Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome involve energy limitations and changes in heart rate variability (HRV) and resting heart rate (HR). Mobile health technologies now offer real-time, valid measurements of HRV and HR, advancing symptom monitoring and management. Using a high-density dataset from an observational longitudinal study, we aimed to describe, quantify, and predict within-person co-variations in daily biometric data and subsequent crash, fatigue, and brain fog symptom occurrences.
Methods: Leveraging data collected through a mobile health app (n=4,244), we developed predictive models using mixed-effects linear regression and logistic regression to explore how within-person fluctuations in biometrics (HR, HRV, and respiratory rate) predict dynamic change in symptomology (crash, fatigue, and brain fog). Predictive performance was assessed using 5-fold stratified cross-validation and compared to a 20% holdout set to evaluate model generalizability to new observations and individuals.
Results: Across all symptom domains, within-person changes in HRV and HR consistently emerged as key predictors of symptom change across all models, with higher HR and lower HRV conferring risk for crashes, fatigue, and brain fog. Moreover, 7-day biometric stability (or variable dispersion) was a robust predictor of symptom occurrence and severity. Models trained solely on biometric features achieved moderate predictive performance in the stratified cross-validation set; however, incorporating random effects to capture individual-specific variations and prior-day symptom reports substantially enhanced model accuracy, with AUC values reaching .91.
Discussion and Conclusion: This study is the first to use data-driven models to predict everyday symptom experiences in individuals with complex chronic illnesses based on biometric fluctuations. Findings demonstrate the potential utility of mobile health tools for real-time monitoring of symptoms and highlight the need for further research to refine these predictive models and integrate them into clinical decision-making processes.
Knowledge, Attitude, and Behavior Towards Oncofertility Among Female Breast Cancer Patients in China
Authors: McClam Maria , Yan Ruike , Su Yujing , Xiao Shuo , Zhang Xiaoxiao
Published: November 2024

Background
Increased cancer survival rates and advances in cancer treatments have allowed many adolescent and young adult-aged cancer patients to live long lives after having cancer. Cancer treatment-induced reproductive toxicities and infertility is important for cancer patients to understand so they can make informed decisions about their reproductive health. This study aimed to assess the knowledge, attitude, and behavior towards oncofertility and fertility preservation among female breast cancer patients in Sichuan, China.
Methods
We created an online questionnaire survey to examine 113 Chinese breast cancer patients’ demographics, knowledge, attitude, experience, and behavior regarding their cancer and fertility preservation.
Results
Results showed that there is an inadequate oncofertility knowledge among surveyed breast cancer patients. On average, patients answered only half (49%) of the questions assessing their knowledge of oncofertility correctly. Although most breast cancer patients reported not proceeding with fertility preservation, they view oncofertility as important and said there remains a lack of communication about oncofertility from providers to patients. Patients expressed a need for more information on how cancer treatment impacts fertility and what options there are for fertility preservation.
Conclusions
Our study demonstrates that there is a need to improve patients' oncofertility knowledge in China as well as increase communication between oncologists, fertility specialists, and their patients.
A JPEG Compressed Image Encryption Method Based on Shamir Secret Sharing Scheme
Authors: Guan Yulong , Wu Zhen , Yang Hui , Cheng Hongyuan
Published: November 2024

With the rise of cloud computing and social networks, images, as a significant representative of the multimedia big data era, hold undeniable value. Among them, JPEG images play a critical role in global image transmission and storage. To address security vulnerabilities and internet threats, both the academic world and the industrial world have proposed various security protection schemes for JPEG images. However, traditional JPEG encryption compression methods are overly reliant on keys, and once a key is lost, the integrity of the original image cannot be restored. To solve this issue, Secret Image Sharing (SIS) technology has demonstrated tremendous potential in modern data sharing, offering high security and fault tolerance, which effectively avoids excessive concentration of key dependency. In this paper, we propose a novel secret JPEG image sharing scheme that introduces Galois field-based SIS technology into the Huffman coding step of the JPEG compression process. This not only enhances the visual security of the compressed image but also resolves the problem of poor key loss tolerance. Furthermore, we improved the original scheme, making the encrypted ciphertext image harder to recognize while ensuring both the compression sharing and the restoration of the original image. Experimental results show that our scheme fully complies with the format requirements and exhibits high security.
Real-Time Smoke Detection Algorithm with Transformer
Authors: Wang Zhong , Lei Lanfang , Li Tong , Zu Xian , Shi Peibei
Published: November 2024

Smoke detection technology plays a crucial role in fire prevention and is vital for ensuring the safety of people's lives and property. However, existing smoke detection models face challenges such as false positives in complex environments and missed edge detections of smoke, especially for small smoke targets. Additionally, high computational and inference costs limit their application. To address these challenges, this paper proposes a Real-Time Smoke Detection Algorithm with Transformer, named RT-DETR-Smoke. First, to reduce computational costs, we introduce a real-time, end-to-end object detector, which includes a high-efficiency hybrid encoder and uncertainty minimization in query selection. Next, to address the issue of missed smoke edge detection, we employ Coordinate Attention to facilitate the fusion of smoke features across different spatial locations. Finally, to accommodate the multi-scale characteristics of fire and the complexity of various environments, we propose the WShapeIoU loss function to accelerate model convergence and improve smoke detection accuracy. Experimental results on a custom smoke dataset show that RT-DETR-Smoke achieves an accuracy of 87.75% mAP@0.5 and excels in real-time performance, with a processing speed of 445.50 FPS, demonstrating its potential for practical applications. Compared to existing models, the proposed method significantly improves both accuracy and speed.
Design, synthesis and antiviral activity of coumarin derivatives containing 1,3,4- oxadiazole/thidiazole
Authors: Hu Yuzhi , Sun Zhiling , Zeng Wei , Qiu Yujiao , Xu Zhiyuan , Zhang Jing , Feng Gang
Published: November 2024

In this paper, a series of oxadiazole/thidiazole containing coumarin derivative derivatives were designed, synthesized and characterized using NMR and HRMS. The evaluation of antiviral activity revealed that some of the synthesized compounds exhibited good in vivo antiviral efficacy against tobacco mosaic virus (TMV). Notably, compounds H6 and Y5 demonstrated exceptional therapeutic and protective effects against TMV, with EC50 values of 180.7, 190.3 and 215.8, 218.6 µg/mL, respectively, surpassing the efficacy of NingNanmycin, which exhibited EC50 values of 284.1 and 247.1 µg/mL. The preliminary mechanistic studies indicated that H6 and Y5 had ahigh binding affinity for the tobacco mosaic virus capsid protein (TMV-CP), potentially obstructing the self-assembly and replication processes of TMV particles. Furthermore, the chlorophyll content and superoxide dismutase (SOD) activity in tobacco leaves increased, while the malondialdehyde (MDA) content decreased. H6 has the potential to be developed as a novel antiviral.
The Central Nervous System 5-HT2B Receptor as a Potential Target for Regulating Ejaculatory Behaviour in Male Rats
Authors: Zhang Wei , Geng Hao , Zhou Tao , Zhang Xiansheng , Zou Ci
Published: November 2024

Objective: To investigate whether 5-HT and the newest member of the 5-HT2B receptor family 5-HT2B receptor in the central system, have a key role in ejaculation regulation by constructing an animal model of primary premature ejaculation.
Materials and Methods: A rat model of primary premature ejaculation was constructed, and the differential expression profiles of 5-HT2B and 5-HT in the central system were established.
Results: Compared with the "normal ejaculation " and "delayed ejaculation" rats’ group, the "rapid ejaculation" rats’ group had shorter mount latency and intromission latency, and fewer mount frequency and intromission frequency before the first ejaculatory. In the "rapid ejaculation", "normal ejaculation" and "delayed ejaculation" groups, there were significant differences in the levels of 5-HT in the hippocampus and raphe nucleus of rats. The 5-HT levels in the hippocampus and raphe nucleus of rats in the "rapid ejaculation" group were significantly lower than those in the "normal ejaculation" and "delayed ejaculation" groups. In the hippocampus and raphe nucleus of the central system of rats, the concentration of 5-HT was significantly lower than that of the "normal" and "delayed" groups. The expression levels of 5-HT2B receptor proteins were significantly higher in the "rapid ejaculation" group than in the "normal ejaculation" and "delayed ejaculation" groups.
Conclusion: We found that rats with different ejaculatory behaviors have a different 5-HT2B expression in the central nervous system. The expression of 5-HT2B receptors in different brain regions of the CNS is closely related to the different sexual behaviors of rats, suggesting that it may have a key role in the regulation of ejaculation in the central system of rats.
Trans-2-hexenal reduces postharvest mango stem-end rot by oxidative damage to Neofusicoccum parvum cell membranes
Authors: Tan Xiaoli , Jiang Xiaobing , Chen Xiumei , Reymick Okwong Oketch , Zhu Chen , Tao Nengguo
Published: November 2024

Neofusicoccum parvum is one of the most hazardous pathogens causing mango fruit decay. The present study utilized trans-2-hexenal (TH), a typical antifungal component of plant essential oils (EOs), to control N. parvum both in vivo and in vitro, and attempted to explore the mechanisms involved. The findings showed that at concentrations greater than 0.4 µL/mL, TH exhibited exceptional antifungal activity against N. parvum in vitro. TH application led to the disruption of the structural integrity of both cell walls and cell membranes, with a particular impact on the latter, as evidenced by the dramatically increased propidium iodide level, as well as reduced total lipids and ergosterol content. Further DCFH-DA staining experiments showed that TH induced mycelial reactive oxygen species (ROS) accumulation, which exacerbated cell membrane lipid peroxidation. For easier application of TH, we fabricated aerogel-loaded TH (ALTH) materials, which demonstrated excellent antifungal activity in vitro. Infestation studies on fruits demonstrated that ALTH mitigated mango stem-end rot in a dose-dependent fashion, with a concentration of 40 µL/L showing efficacy comparable to the conventional fungicide prochloraz, while maintaining fruit quality. In light of these results, TH works by inducing ROS buildup and oxidative damage to the cell membrane of P. parvum, and is a particularly promising preservative for preventing postharvest infections in mangoes.
Comparing the efficiency of forest mitigation strategies: climate change and windthrow as overarching drivers
Authors: Coșofreț Cosmin , Bouriaud Laura , Costa Maximiliano , Bouriaud Olivier
Published: November 2024

Context
Forests are being scrutinized for their capacity to store large amounts of carbon over long periods and for their contribution regarding climate change mitigation. However the interactions between climate change, forest management, and wind disturbances could challenge management strategies based on setting aside forests.
Objectives
This study aimed to compare the contribution of forests to mitigation according to three opposing strategies of forest management differing by their share area set aside (SA) from wood procurement: SA0, business as usual management; SA30, 30% of the forest areas are set aside; and SA100, 100% of the forest areas are set aside.
Methods
A dynamic forest landscape model (LandClim) was used to compare the effects of different management strategies on the potential for forest mitigation. The model outputs were used to quantify the potential for carbon sequestration and substitution under RCP2.6 and RCP8.5 climate scenarios.
Results
Under the RCP2.6 climate, the highest carbon storage capacity was achieved by the SA100 management. Wind-induced losses in the SA0 and SA30 remained at similar magnitudes until 2120. Thus, under RCP2.6 climate, the effects of substitution from SA0 exceeded the increase in storage expected from SA100.
Under the RCP8.5 climate, stocks increased for three decades but then collapsed. The management strategy did not influence these losses, which were negligible after 2080 owing to the very small standing stocks.
Conclusions
Strategies based on setting aside forests for carbon storage could be a viable solution in RCP2.6 climate. However, windthrow events strongly limit their potential.
Effects of Gut Microbiota and Inflammatory Cytokines on Anxiety Disorders: Two-Sample Mendelian Randomization Analysis and Mediation Analysis
Authors: Li Jun , Wu Dingze , Zhang Yongquan , Xu Litang , Jiang Ying
Published: November 2024

Background
Research has indicated that the gut microbiota may be associated with anxiety disorders. However, the causal connection between the gut microbiota and anxiety, and whether cytokines serve as a mediating role, remains uncertain. This study was intended to examine whether inflammatory cytokines mediate the pathway from the gut microbiota to anxiety disorders and to establish the causal relationships among the gut microbiota, inflammatory cytokines, and anxiety disorders.
Methods
Data regarding the gut microbiota, 91 inflammatory cytokines, and anxiety disorders were acquired from large-scale genome-wide association studies (GWAS). We employed Mendelian randomization (MR) to evaluate the causal relationships between the gut microbiota and inflammatory cytokines. Multivariate Mendelian randomization (MVMR) was utilized to further analyze whether inflammatory cytokines mediate the pathway from the gut microbiota to anxiety.
Results
We identified five negative causal relationships and one positive causal relationship between specific gut microbiota and anxiety disorders. The negative causal relationships were observed in class Clostridia (OR = 0.803, 95% CI = 0.691–0.931, P_IVW = 0.004, P_FDR = 0.023), genus Eubacterium nodatum group (OR = 0.902, 95% CI = 0.837–0.972, P_IVW = 0.007, P_FDR = 0.014), genus Ruminococcaceae UCG011 (OR = 0.905, 95% CI = 0.831–0.987, P_IVW = 0.023, P_FDR = 0.035), order Clostridiales (OR = 0.849, 95% CI = 0.734–0.983, P_IVW = 0.028, P_FDR = 0.028), and phylum Firmicutes (OR = 0.827, 95% CI = 0.725–0.943, P_IVW = 0.004, P_FDR = 0.013). A positive causal relationship was found in genus Lachnospiraceae UCG010 (OR = 1.251, 95% CI = 1.028–1.522, P_IVW = 0.025, P_FDR = 0.030).Three positive causal relationships were found between inflammatory cytokines and anxiety: macrophage colony-stimulating factor 1 (OR = 1.161, 95% CI = 1.001–1.348, P_IVW = 0.049, P_FDR = 0.049), fibroblast growth factor 5 (OR = 1.074, 95% CI = 1.025–1.124, P_IVW = 0.003, P_FDR = 0.013), and vascular endothelial growth factor A (OR = 1.076, 95% CI = 1.019–1.135, P_IVW = 0.008, P_FDR = 0.020). Notably, macrophage colony-stimulating factor 1 was identified as a mediator in the pathway from gut microbiota to anxiety.
Conclusion
There exists a causal relationship among intestinal flora, inflammatory cytokines, and anxiety. Some inflammatory cytokines mediated the pathway from the intestinal flora to anxiety.