bluuebunny/crossref_metadata_2025_split huggingface dataset:
Self-judgment on emotional items modulates memory resources in breast cancer patients: a longitudinal MRI study
Authors: Joue Gina , Perrier Joy , Dayan Jacques , Naveau Mikaël , Morel Nastassja , Villain Nicolas , Allouache Djellila , Noal Sabine , Levy Christelle , Joly Florence , Chételat Gaël , Eustache Francis , Giffard Bénédicte 
Published: August 2024

Abstract

Breast-cancer (BC) patients (PT) frequently report memory problems pre-and post-cancer treatments that are not always corroborated by memory tests. We hypothesized that self-reported problems actually coincide with structural brain changes and that the discrepancy partly stems from BC-related distressed self-image and stress that alter arousal at memory encoding. To detect such subtle changes before/after treatments, we leveraged on known memory advantages related to self-image and stress in a longitudinal MRI study: the self-reference effect (SRE; better memory for what concerns oneself) and the negativity effect (NE; better memory for items with emotionally negative associations). We tested women with non-metastatic BC, before and one year after chemotherapy, and age-matched healthy women (HC) at similar time lapses. Neither group had clinical anxiety or depression. At each visit, participants completed an episodic memory fMRI task involving attributing character traits to themselves or someone else. Overall memory accuracy and SRE were similar between groups, but only HC showed NE. PT showed greater activity for self-judged positive traits in brain regions implicated in self-representation and emotional memory regulation. Functional connectivity and structural changes in these regions varied with self-representation and anxiety, but multivariate analyses with unsupervised machine learning suggest differences only partially characterize PT.
Exploring the Impact of GAN-Based Data Augmentation and FGSM-Refined Images on Wear Size Estimation of Railway Switches and Crossings
Authors: Sassi Hichem , Najeh Tawfik , LIOUENE NOUREDDINE 
Published: August 2024

Abstract

The switch and crossing (S&C) is a crucial component of the railway infrastructure network, significantly affecting traffic delays and maintenance costs. This study aimed to predict wear across the entire S&C using medium-range accelerometer sensors. Vibration data were collected, processed, and converted into spectrograms to develop accurate data-driven models. However, due to weather constraints such as ice and snow, our database remains limited. To ensure the proper generalization of deep learning models, it is essential to expand this dataset. Therefore, we plan to employ Generative Adversarial Networks (GANs) to address this objective. GANs are a powerful class of networks capable of generating realistic new images from a specified database. This study aims to explore the use of deep learning techniques, particularly GANs combined with Convolutional Neural Networks (CNNs), for the classification of wear levels in switch and crossing (S&C) components. To enhance the robustness of CNN models, we employ the fine-tuning technique in conjunction with the adversarial images using Fast Gradient Sign Method (FGSM).
Machine learning analysis of CT images for the prediction of extracorporeal shock wave lithotripsy efficacy
Authors: Cao Yuanchao , Yuan Hang , Qiao Yi , Guo Yuting , Wang Xinning , Li Bin , Wang Xinsheng , Li Yanjiang , Jiao Wei 
Published: August 2024

Abstract

Objective
The study aimed to evaluate the use decision support analysis for the prediction of extracorporeal shock wave lithotripsy (ESWL) efficacy and to analyze the factors influencing outcomes in patients who underwent ESWL using machine learning (ML) methods.
Methods
This retrospective study analyzed the clinical data, including preoperative CT images, of 302 patients who received a single ESWL session treatment for urinary tract stone (UTS) between May and October 2022 in the Department of Urology. The data was preprocessed and incorporated into an ML model, and the dataset was validated at a ratio of 4:1. The AUC and the confusion matrix were used to evaluate the predictive efficacy of the model.
Results
The CT image-based ML model predicting ESWL efficacy for UTS removal achieved an AUC of 0.86, precision of 88.33%, F1 score of 86.57%, sensitivity of 82.86%, and specificity of 88.89%. The model showed increased predictive accuracty for stones in different locations, with an AUC of 0.95 for kidney stones, 95.45% precision, 96% F1 score, 100% sensitivity, and 90% specificity. The AUC value for upper ureteral stones was 0.89, with 89.14% precision, 88.05% F1 score, 83.33% sensitivity, and 94.51% specificity, while that for mid-ureteral stones was 0.85, with 82.93% precision, 84.09% F1 score, 74% sensitivity, and 96.88% specificity, and the success rate of ESWL for lower ureteral stones was 100%, with an AUC of 1.
Conclusions
ML analysis was used to predict outcomes following ESWL treatment for UTS. The ML-based model was found to be approximately 86% accurate. The use of ML algorithms can provide matched insights to domain knowledge on effective and influential factors for the prediction of ESWL outcomes.
SVM Classification with Steganography using Video Copy Detection based on Network Security with Machine Learning Framework
Authors: Karthika P , Balamurali S 
Published: August 2024

Abstract

Its incomplete duplicate detection in the videos problem aimed to identify whether each or many segments of a request video are already present in this study, even while giving data on related fraction time periods. At the moment, the most efficient incomplete copy detection techniques in videos have been designed in 3 components: extraction of features, pattern matching, as well as time integration. To those level, the isolation of the feature identification but also time alignment modules ignores the spatially information of an incomplete copy. In order to decrease the above loss, we begin by representing video frames but also extracting SVM features. As a result, in this paper, we examine the algorithm's performance on the particularly complex video duplicate recognition data-set VCDB, that also, once again, outperforms the government's incomplete copy detection method.
SequenceCraft: Machine learning-based resource for exploratory analysis of RNA-cleaving deoxyribozymes
Authors: Eremeyeva M. , Din Y. , Shirokii N. , Serov N. 
Published: August 2024

Abstract

Deoxyribozymes or DNAzymes represent artificial short DNA sequences bearing many catalytic properties. In particular, DNAzymes able to cleave RNA sequences have a huge potential in gene therapy and sequence-specific analytic detection of disease markers. This activity is provided by catalytic cores able to perform site-specific hydrolysis of the phosphodiester bond of an RNA substrate. However, the vast majority of existing DNAzyme catalytic cores have low efficacy in in vivo experiments, whereas SELEX based on in vitro screening offers long and expensive selection cycle with the average success rate of ~ 30%, moreover not allowing the direct selection of chemically modified DNAzymes, which were previously shown to demonstrate higher activity in vivo. Therefore, there is a huge need in in silico approach for exploratory analysis of RNA-cleaving DNAzyme cores to drastically ease the discovery of novel catalytic cores with superior activities. In this work, we develop machine learning based open-source platform SequenceCraft allowing experimental scientists to perform DNAzyme exploratory analysis via quantitative kobs estimation and data analysis tools. This became possible with the development of unique curated database of > 350 RNA-cleaving catalytic cores, property-based sequence representations allowing to work with both conventional and chemically modified nucleotides, and optimized kobs predicting algorithm achieving Q2 > 0.9. These findings represent the first step towards fully in silico exploratory analysis of catalytic DNAzymes.
Resting cardiac vagal tone predicts working memory performance: Evidence to Neurovisceral Integration Model
Authors: Vaasanthi Sinchana , Chandregowda Nandan , KrishnaPrasad BS , Sathyaprabha Talakad N , Udupa Kaviraja 
Published: August 2024

Abstract

This study investigates the intricate relationship between vagal tone, physical activity, and working memory in a carefully structured cohort. The participants were categorized into three cohorts: exercisers (Group A), yoga practitioners (Group B), and non-exercisers (Group C). Heart rate variability (HRV) parameters, namely RMSSD and HF Power, were utilized as indicators of vagal tone. Our study confirmed significant increase (p < 0.001) in both RMSSD and HF Power in people who exercise and meditate than those who do not exercise. Results highlighted a significant main effect of cohort on n-back error rates (p < 0.001). Correlation analyses unveiled significant associations between higher RMSSD and HF Power values and enhanced working memory performance, suggesting that individuals with elevated vagal tone demonstrated superior working memory capabilities. However, acute physical exercise/ yoga did not yield a significant effect, emphasizing the potential influence of long-term physical activity habits on working memory. These findings shed light on the crucial role of vagal tone in cognitive processes and the potential benefits of physical activities in enhancing working memory performance. Further research should address the limitations and extend this exploration to yield a more comprehensive understanding of these relationships.
Effects of tianeptine on mTORC1-mediated neuronal autophagy in primary rat hippocampal neurons under nutrient deprivation
Authors: Lee Jung Goo , Seo Mi Kyoung , Kim Hyewon , Choi Ah Jeong , Seog Dae-Hyun , Kho Weon-Gyu , Park Sung Woo 
Published: August 2024

Abstract

The aim of this study was to investigate the effects of the antidepressant tianeptine on the mechanistic target of rapamycin 1(mTORC1)-mediated autophagy pathway in primary hippocampal neurons exposed to B27-deprived conditions. When primary hippocampal neurons were treated with tianeptine at doses of 1, 10, 50, and 100 μM for 3 days under B27-deprived conditions, we observed that it activated autophagy and increased the formation of autophagosomes through the upregulation of autophagic proteins, including autophagy-activating kinase 1 (ULK1), Beclin 1, LC3B-II/I, and p62. And at a concentration of 100 μM tianeptine, the decrease in mTORC1 phosphorylation induced by B27 deprivation was significantly reversed. Changes in the expression of autophagic proteins induced by B27 deprivation were reversed by tianeptine treatment in a concentration-dependent manner, and tianeptine significantly reduced the increase in LC3B membrane number induced by B27 deprivation, an effect that was blocked by pretreatment with rapamycin. In conclusion, tianeptine attenuated the activity of mTORC1-mediated autophagy in primary rat hippocampal neurons under B27-deprived conditions. These results may suggest a novel mechanism by which tianeptine may affect autophagy in neurons.
Dynamics of HIV transmission among men who have sex with men in Taiwan: a mathematical modeling study
Authors: Sun Haoran , Kawasaki Hiromi , Tunematsum Miwako , Shimpuku Yoko , Chen Sanmei , Kagiura Fumiko , Kakehashi Masayuki 
Published: August 2024

Abstract

Background
In Taiwan, the human immunodeficiency virus (HIV) is primarily transmitted among men who have sex with men (MSM). Nonetheless, detailed epidemiological studies considering heterogeneity in susceptible and infectious populations remain lacking. Therefore, we modeled the HIV epidemic with heterogeneity, estimated parameters, and predicted future infection trends in order to better understand the HIV transmission dynamics among MSM.
Methods
We devised a computational approach to accurately estimate the number of infectious individuals during early surveillance years in Taiwan using monthly data of newly diagnosed patients with HIV from January 2005 to December 2006. Subsequently, using annual incident cases from 2005 to 2019, we estimated the susceptibility rate, transmission rates, and duration of risk and conducted short-term forecasts of HIV infection in the MSM population through mathematical modeling based on the susceptible-infected-removed model. Parameters and their values, such as the infection rates of HIV and acquired immunodeficiency syndrome (AIDS), and the removal rates of HIV and AIDS, were also estimated.
Results
A total of 850 infectious individuals with HIV were identified in 2005. From 2005 to 2019, approximately only 0.68% of Taiwan’s male population were estimated to be susceptible to HIV infection via MSM. The transmission rate did not significantly differ between individuals with HIV and individuals with AIDS (0.0110 and 0.107 per 10,000 individuals, respectively). The average duration of infection was 4.5 years between infection and the onset of AIDS and 2.1 years between the onset of AIDS and death. In 2019, the proportion of infectious infected individuals continuously decreased. By 2026, it is estimated that only 11.85% of individuals with HIV and 10.21% of AIDS individuals will be infectious.
Conclusions
Our study presents a new dynamic mathematical model for estimating infectious HIV cases among MSM in Taiwan. By accounting for heterogeneity of infectious HIV/AIDS within the MSM population, it was possible to effectively estimate the number of infections during early surveillance years and implement concentrated measures, thereby reducing infectious HIV/AIDS cases and contributing to the overall reduction in HIV/AIDS. We could better identify the target population and implement effective intervention measures at appropriate times.
An Optimized ARIMA Model for Emergency Medical Services Time Series Demand Forecasting Using Bayesian Methods
Authors: Hendi Hanaa Ghareib , Ibrahim Mohamed Hasan , Farrag Mohamed Hassan 
Published: August 2024

Abstract

Predicting future demand for emergency services through time series forecasting is a useful tool for emergency medical services (EMS). Accurate forecasting of emergency needs is critical to EMS success and efficiency. Spatial management can be improved by better transportation before incidents, leading to significant improvements in response time, prehospital care, better outcomes, and survival quantitative Autoregressive Integrated Moving Average (ARIMA) models are popularly used for time series forecasting. A systematic approach used a grid search to find the parameter space (p, d, q). Bayesian optimization was used to improve our model by identifying the best over-parameters of the ARIMA model, resulting in improved prediction performance f guarantees Our results suggest automatic and heuristic approaches to state together can be effective for optimizing EMS time-series forecasting, to provide valuable information to optimize EMS availability and resource management
Research on the design method of smart spring support for vibration damping of the multi-span shaft system
Authors: Li Miaomiao , Sun Xinyu , zhou Ran , Li Fanxuan , Ma Liangliang , Zhu Rupeng , Chen Weifang 
Published: August 2024

Abstract

When the helicopter tail transmission shafting is over-critical, the shafting vibration intensifies, which restricts the overall performance of the helicopter. Smart spring support is an active damping device, which can effectively suppress the vibration of multi-span shafting. In this paper, the configuration and structure design of the smart spring support for multi-span shafting are studied, and its vibration-damping performance is verified by experiments. Firstly, based on the vibration reduction principle of the smart spring support, the vibration characteristics of the smart spring are analyzed. The motion equation of the smart spring support was established, the influence of configuration parameters on its vibration characteristics was analyzed, and the configuration parameters of the smart spring support were determined. On this basis, three configuration schemes of the smart spring support are proposed, the structural design of the smart spring support is carried out, and the structural parameters are determined. The shafting vibration reduction test system with the smart spring support was built, and the smart spring vibration reduction tests were conducted under different control voltages. The results show that the smart spring support has a good suppression effect on the accelerated over-critical vibration response of the shaft system.
Barriers, Myths, and Misconceptions about Cervical Cancer Screening in Pregnancy and Postnatal Period; a qualitative grounded theory study
Authors: Wanjala Miriam , Wangui Fridah , Parker Robert K. , Cowles Cheryl 
Published: August 2024

Abstract

Background: Cervical cancer, a slow-growing malignancy, can be effectively treated if detected early during its precancerous stages. Pregnancy presents a critical opportunity for screening, especially in low-resource countries where healthcare access is limited. However, cervical cancer screening rates among pregnant mothers at Tenwek Hospital have consistently been below 1%. This study aims to identify the barriers, myths, and misconceptions surrounding cervical cancer screening during pregnancy and the postnatal period to develop educational materials and counseling guidelines for both pre-screening and post-screening.
Methods: This qualitative grounded theory study was conducted at Tenwek Hospital in rural Kenya. The study population comprised mothers attending antenatal follow-up and post-partum reviews up to six weeks post-delivery. We recruited 50 women, obtained informed consent, and conducted interviews using a semi-structured questionnaire with open-ended questions. Responses were recorded and analyzed thematically using SPSS.
Results: The majority (94%) of women had heard of cervical cancer screening, yet only 6% had been screened before. Fear of a cancer diagnosis (50%), discomfort (28%), and concerns about pregnancy complications (6%) were significant barriers. Despite these concerns, 70% of participants recommended screening during pregnancy and the postnatal period. Other misconceptions included the belief that screening is expensive (2%) or causes cervical cancer (2%).
Conclusion: The primary barrier to cervical cancer screening is the fear of diagnosis, necessitating increased education to dispel myths and misconceptions. Enhancing knowledge and awareness about the benefits and safety of screening during pregnancy can improve uptake and early detection, thereby reducing cervical cancer morbidity and mortality.
Control of Epidemic Process via Link Removal: Flattening the Infection Curve by Social Distancing
Authors: Doostmohammadian mohammadreza , Zarrabi Houman , Doustmohammadian Azam , Doustmohamadian Soraya , Doustmohammadian Najmeh , Rabiee Hamid 
Published: August 2024

Abstract

Spreading processes on complex networks have gained significant attention as a means to model the spread of infectious diseases in real social networks. This paper focuses on controlling epidemic processes and reducing the peak of contagion by removing highly central links. In practice, this translates to flattening the infection curve through the implementation of social distancing measures for high-risk social contacts. The identification of important links relies on centrality measures, e.g., node-degrees and edge-betweenness. Edge-betweenness evaluates link importance based on the fraction of shortest paths that contain the link, while node-degree-based centrality defines link centrality as the average degrees of the connected nodes. Our findings demonstrate that degree-based link removal is more effective in flattening the infection curve as compared to many other centralities including edge-betweenness. We analyze small-world and scale-free networks, examining the infection curves across various network clustering coefficients and small-worldness.
The First Scientific Research to Trace the Origins of Qin Sealing Clay
Authors: Guo Houze , Yang Lu 
Published: August 2024

Abstract

The sealing clay is the key physical example of the document sealing system of the Qin dynasty in ancient China. However, only the inscriptions and aesthetic values of the clay were discussed untill now, and the relevant sources were not traced from the perspective of scientific analysis. A total of 81 sealing clays unearthed in Xi’an were studied by means of ultra-depth of field microscopic observation, petrographic microstructure analysis and X-ray fluorescence spectroscopy. The relevant methods of tracing and making of mud samples are discussed based on the results of literature investigation and element analysis. The composition, technology and spatial links between different sealing clay collected from all over the country show that the highly organized sealing materials and systematic processes are an important part of the establishment of unified China, in order to provide detailed and effective scientific information for the subsequent sealing clay protection and archaeological research.
The Mediating Role of Rumination in the Relationship Between Fear of Disease Progression and Family Function in Ischemic stroke Patients
Authors: Wang Tianyi , Yuan Xiaorong , Yang Jin , Li Xiuchuan , Yao Qian , Ye Ting , Huang Yunman , Lan Junao , Zhang Xianqin , Luo Jian , Zhu Bin , Yang Zheng 
Published: August 2024

Abstract

Background This study investigates the mediating role of rumination in the relationship between family function and the fear of disease progression in Ischemic stroke patients. Methods A survey was conducted using a general information questionnaire, Fear of Progression-Questionnaire-Short Form(FoP-Q-SF), Family Assessment Device༈FAD༉, and Chinese Version of Event Related Rumination Inventory(C-ERRI) among 285 Ischemic stroke patients. Results The total score of fear of disease progression in Ischemic stroke patients was (SD = 28.12 ± 9.25). Correlation analysis revealed a negative correlation between fear of disease progression and family function (r = 0.69, P < 0.01), a positive correlation between fear of disease progression and total rumination,the invasive rumination (r = 0.46,0.60, P < 0.01), and an negative correlation between family function and total rumination,invasive rumination(r = 0.38,0.61,P < 0.01). The chain mediation model indicated that family function directly effect on fear of disease progression(β = 0.18,P < 0.01),The direct effect of family function on fear of disease progression had a 95% confidence interval [0.14–0.22].Invasive rumination has a partial mediating effect between family function and fear of disease progression༈β = 0.07,P < 0.01༉, the indirect effect had a 95% confidence interval [0.04–0.10].The proportion of the effect mediated was 28.16%. These results indicate that the partial mediating effect of invasive rumination is significant. Conclusions Fear of disease progression in Ischemic stroke patients is at a moderate level, and invasive rumination significantly mediate the relationship between family function and fear of disease progression.