Endostatin as a biomarker of systemic sclerosis: insights from a systematic review and meta-analysis by Arduino A. Mangoni, Arduino A. Mangoni, Angelo Zinellu

Get full text

Experimental Investigation of Mechanical Properties and Pore Characteristics of Hipparion Laterite Under Freeze–Thaw Cycles by Tengfei Pan, Zhou Zhao, Jianquan Ma, Fei Liu

“…We innovatively integrated F-T cycling tests with ring-shear experiments to establish a hydro-thermal–mechanical coupled multi-scale evaluation framework for assessing F-T damage in the slip zone material. …”
Get full text

The role of mitochondria-related genes and immune infiltration in carotid atherosclerosis: identification of hub targets through bioinformatics and machine learning approaches by Dan Liu, Kun Guo, Min Li, Xiaochen Yu, Xue Guan, Xiuru Guan

“…These findings may provide new insights into therapeutic monitoring and prognosis evaluation.…”
Get full text

Prognostic risk modeling of endometrial cancer using programmed cell death-related genes: a comprehensive machine learning approach by Tianshu Chen, Yuhan Yang, Zhizhong Huang, Feng Pan, Zhendi Xiao, Kunxue Gong, Wenguang Huang, Liu Xu, Xueqin Liu, Caiyun Fang

“…Key methodologies included differential gene expression analysis, weighted gene co-expression network analysis, functional enrichment studies, immune landscape evaluation, and multi-dimensional risk stratification. …”
Get full text

EEG–fNIRS signal integration for motor imagery classification using deep learning and evidence theory by Mohammed E. Seno, Niladri Maiti, Maulik Patel, Mihirkumar M. Patel, Kalpesh B. Chaudhary, Ashish Pasaya, Babacar Toure

“…For EEG signals, spatiotemporal features are extracted using dual-scale temporal convolution and depthwise separable convolution, and a hybrid attention module is introduced to enhance the network's sensitivity to salient neural patterns. …”
Get full text

Comparative Analysis of AlexNet, ResNet-50, and VGG-19 Performance for Automated Feature Recognition in Pedestrian Crash Diagrams by Baraah Qawasmeh, Jun-Seok Oh, Valerian Kwigizile

“…By employing cutting-edge technological methods, the research aims to uncover and extract hidden features from pedestrian crash data in Michigan, thereby enhancing the understanding and prevention of such incidents. This study evaluates the effectiveness of three Convolutional Neural Network (CNN) architectures—VGG-19, AlexNet, and ResNet-50—in classifying multiple hidden features in pedestrian crash diagrams. …”
Get full text

Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks by Ahmad Almadhor, Shtwai Alsubai, Imen Bouazzi, Vincent Karovic, Monika Davidekova, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The CICEVSE2024 (EVSE-A and EVSE-B) datasets are used to assess the framework, where one dataset is used to train and store weights, and the second is used to evaluate the learned patterns using transfer learning. …”
Get full text

A novel transformer-based dual attention architecture for the prediction of financial time series by Anita Hadizadeh, Mohammad Jafar Tarokh, Majid Mirzaee Ghazani

“…Second, the Nonprice Attention Network (NAN) is proposed as a parallel network that processes related financial features. …”
Get full text

Destripe Any Scale: Effective Stripe Removal Via Multiscale Decomposition Using the Luojia3-02 Stripe-Noise Dataset by Ru Chen, Mi Wang, Yingdong Pi, Ru Wang, Tao Peng, Fan Yang, Rongfan Dai

“…We first introduce the Luojia3-02 stripe-noise dataset, constructed from Luojia3-02 (Wuhan-1) satellite imagery, including stripe-noise patterns across multiple spatial scales. Building upon this dataset, we propose a multilevel perceptual stripe-noise-removal network. …”
Get full text

Downscaling of the surface temperature forecasts based on deep learning approaches by Guangdi Chen, Xiefei Zhi, Shuyan Ding, Gen Wang, Liqun Zhou, Dexuan Kong, Tao Xiang, Yanhe Zhu

Get full text

Resilient Operation of Electric Vehicles considering Grid Resiliency and Uncertainties by Seyed Mostafa Armaghan, Fatemeh Asgharzadeh, Babak Yousefi-Khanghah, Hamid Reza Ashrafi

“…This paper proposes a novel short-time optimization method based on a resiliency enhancement strategy for a smart distribution network during adverse weather conditions. The key idea is to integrate various electric vehicles (EVs) with different behaviour patterns and other distributed energy resources into emergency tools of distribution network operation such as topology reconfiguration and grid-supported services. …”
Get full text

Charting the spatial transcriptome of the human cerebral cortex at single-cell resolution by Songren Wei, Meng Luo, Pingping Wang, Rui Chen, Xiyun Jin, Chang Xu, Chenyang Li, Xiaoyu Lin, Zhaochun Xu, Hongxin Liu, Rui Cheng, Wenyi Yang, Yideng Cai, Guangfu Xue, Peng Huang, Zhigang Liu, Haoxiu Sun, Jiangping Xu, Qinghua Jiang

Get full text

Altered functional brain connectivity in Dyt1 knock-in mouse models by R. Z. Adury, B. J. Wilkes, P. Girdhar, Y. Li, D. E. Vaillancourt, D. E. Vaillancourt, D. E. Vaillancourt

“…We also hypothesized that EMX mice would exhibit altered functional connectivity and activation patterns, supporting the idea that TorsinA dysfunction in the sensorimotor cortex alone can induce network abnormalities. …”
Get full text

Potential distribution of native freshwater fish in Tabasco, Mexico by Paula Andrea Castillo-Torres, Enrique Martínez-Meyer, Fernando Cordova Tapia, Luis Zambrano

“…We implemented an ecological niche modeling approach to: 1) identify the potential richness distribution patterns of native fish; 2) evaluate the relative importance of climatic and topographic variables in fish distribution, and 3) analyze if the natural protected areas correspond to areas with higher potential species richness. …”
Get full text

The fortified defence of the west of the Santaver Cora through geographic information systems (GIS): a multidisciplinary study by Leonor Parra-Aguilar

“…The GIS study has made it possible to evaluate the defensive patterns created. One of these patterns shows the existence of towers capable of observing over a long distance: 50 km. …”
Get full text

Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The selected data set is pre-processed and feature selection for the optimization for the improvement in accuracy, and automation decision making the framework of the convolution neural network along with the ensemble boosted tree classifier developed is optimized using the jellyfish optimization and Recurrent Neural Network and Long Short-Term Memory (RNN-LSTM) model for the recognition of patterns and numerical vectors in the real-world data after processing of output then it is sent back as the input for the recurrent network to make the decision in the shipbuilding process. …”
Get full text

Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

“…We compared a rule-based method, a support vector machine (SVM), fully convolutional semantic neural network (UNet), region proposal network (Faster R-CNN), and recurrent neural network for electrocardiographic signals (DENS-ECG). …”
Get full text

Evolution of foraging behaviour induces variable complexity-stability relationships in mutualist-exploiter-predator communities. by Lin Wang, Ting Wang, Xiao-Wei Zhang, Xiao-Fen Lin, Jia Li, Jin-Bao Liao, Rui-Wu Wang

“…Here, we explored an adaptive network model to evaluate how the evolution of foraging preference to determine the relationship between network complexity (i.e., connectance) and stability (i.e., community persistence at steady state) in mutualist-exploiter-predator communities (MEST). …”
Get full text

Unmasking Nuances Affecting Loneliness: Using Digital Behavioural Markers to Understand Social and Emotional Loneliness in College Students by Malik Muhammad Qirtas, Evi Zafeiridi, Eleanor Bantry White, Dirk Pesch

“…Our objectives were to (1) identify behavioural patterns linked to social and emotional loneliness, (2) evaluate the predictive power of these patterns for classifying loneliness types, and (3) determine the most significant digital markers used by machine learning models in loneliness prediction. …”
Get full text

Comprehensive Analysis of N6-Methyladenosine (m6A) RNA Methylation Regulators and Tumour Microenvironment Cell Infiltration Involving Prognosis and Immunotherapy in Gastroesophagea... by Duanrui Liu, Mingjie Yuan, Zongming Wang, Liping Sun, Yusong Fang, Xiaoli Ma, Lulu Zhang, Yuanxin Xing, Jingyu Zhu, Yunyun Liu, Wenshuai Zhu, Shuqin Bao, Yanfei Jia, Yunshan Wang

“…In this study, we examined the TME of GEA using assessments of the RNA-sequencing data focusing on the distinct m6A modification patterns from the public databases. Intrinsic patterns of m6A modification were evaluated for associations with clinicopathological characteristics, underlying biological pathways, tumour immune cell infiltration, oncological outcomes, and treatment responses. …”
Get full text