Estimating shear strength of dredged soils for marine engineering: experimental investigation and machine learning modeling by Zheng Yao, Kaiwei Xu, Zejin Wang, Haodong Sun, Peng Cui, Peng Cui

“…Drawing from the test data, a structured database was assembled, and a new learning framework was developed by combining the Logical Development Algorithm (LDA), Adaptive Boosting (BA), and Artificial Neural Networks (ANN). The motivation behind this hybridization lies in the need to effectively capture nonlinear interactions and latent logical patterns among influencing factors, which are often overlooked by traditional single-algorithm models. …”
Get full text

Serum testosterone partially mediates the adverse effects of organophosphate pesticides exposure on growth indicators of children and adolescents by Zhenao Zhang, Xiaoya Sun, Jingyi Ren, Yadong Zhang, Rui Wen, Huanting Pei, Siqi Zhu, Bowen Yin, Ziyi Wang, Yuxia Ma

“…The role of total testosterone (TT) as a mediator was assessed. Network pharmacology methods were used to identify key targets and therapeutic drugs. …”
Get full text

Non-destructive assessment of hemp seed vigor using machine learning and deep learning models with hyperspectral imaging by Damrongvudhi Onwimol, Pongsan Chakranon, Kris Wonggasem, Papis Wongchaisuwat

“…Particularly, an EfficientNetB0 convolutional neural networks achieved the most impressive results, demonstrating a high sensitivity of 98.85, a specificity of 99.22, and a Matthews correlation coefficient of 0.98. …”
Get full text

Efficient Sedimentary Facies Recognition Using Vision Transformer and Weakly Supervised Deep Multi-View Clustering by Hao Wu, Yu-Jie Dai, Xin-Yu Liu

“…Sedimentary facies recognition plays a crucial role in geological exploration and oil-gas resource evaluation. However, traditional recognition methods are limited by their ability to extract local features and efficiently utilize unlabeled data, making it difficult to effectively handle complex sedimentary facies characteristics. …”
Get full text

Research and analysis of the TCN-Multihead-Attention prediction model of landslide deformation in the Three Gorges Reservoir area, China by Huan Chen, Huan Chen, Yixuan Li, Yimin Liu

“…This paper proposes a TCN-Multihead-Attention prediction model for landslide deformation based on temporal convolutional networks (TCNs). We collected 8 years of monitoring data from the Huangniba Dengkan landslide in the Three Gorges Reservoir area, including surface deformation (horizontal displacement and elevation), rainfall, and reservoir levels. …”
Get full text

Reliable Breast Cancer Diagnosis with Deep Learning: DCGAN-Driven Mammogram Synthesis and Validity Assessment by Dilawar Shah, Mohammad Asmat Ullah Khan, Mohammad Abrar

“…This paper proposes a novel approach that utilizes deep convolutional generative adversarial networks (DCGANs) to effectively tackle the issue of limited data availability. …”
Get full text

Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation. by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…Although convolutional neural networks (CNNs) are commonly used for detecting these conditions, their performance is inadequate when applied to our heterogeneous and limited-scale EEG data. …”
Get full text

The functional near infrared spectroscopy applications in children with developmental diseases: a review by Jing Wang, Zhuo Zou, Haoyu Huang, Jinting Wu, Xianzhao Wei, Shuyue Yin, Yingjuan Chen, Yun Liu

“…Our synthesis uncovers distinct hemodynamic patterns associated with specific developmental disorders. …”
Get full text

Decoding vocal indicators of stress in laying hens: A CNN-MFCC deep learning framework by Suresh Neethirajan

“…This study leverages advanced Convolutional Neural Networks (CNNs) combined with Mel Frequency Cepstral Coefficients (MFCCs) to decode intricate vocalization patterns in laying hens experiencing acute environmental stress. …”
Get full text

Distinguishing Dyslexia, Attention Deficit, and Learning Disorders: Insights from AI and Eye Movements by Alae Eddine El Hmimdi, Zoï Kapoula

“…Machine learning models, including logistic regression, random forest, support vector machines, and neural networks, are trained using a GroupKFold strategy to ensure patient data are present in either the training or test set. …”
Get full text

Bibliometric analysis of the use of pathological techniques in camel research by Ahmed Aljazzar

“…However, there has been limited evaluation of research trends, thematic advancements, and international collaborations in this field. …”
Get full text

Machine learning-based analysis of defensive strategies in basketball using player movement data by Jianlong Li

“…The proposed hybrid model integrates LSTM to identify temporal features of players’ motion and CNN to recognize spatial patterns across the court. The model was trained and evaluated on the National Basketball Association’s (NBA) SportVU tracking data, which includes over 32,000 possessions. …”
Get full text

Probing the functional impact of sequence variation on p53-DNA interactions using a novel microsphere assay for protein-DNA binding with human cell extracts. by Maher A Noureddine, Daniel Menendez, Michelle R Campbell, Omari J Bandele, Monica M Horvath, Xuting Wang, Gary S Pittman, Brian N Chorley, Michael A Resnick, Douglas A Bell

“…Using a set of 26 bona fide REs, we observed distinct binding patterns characteristic of transiently expressed wild type and mutant p53s. …”
Get full text

Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

Get full text

VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…The performance of multiple machine learning classifiers, including Random Forest (RF), Logistic Regression (LoR), LightGBM (LGBM), and K-Nearest Neighbor Classifier (KNC), is evaluated alongside neural network techniques such as Convolutional Neural Networks (CNN) and VGG-19. …”
Get full text

Bioinformatics‑Based Analysis Reveals Diagnostic Biomarkers and Immune Landscape in Atopic Dermatitis by Yang M, Zhang X, Zhou C, Du Y, Zhou M, Zhang W

“…Weighted gene co-expression network analysis (WGCNA) was employed to identify gene modules. …”
Get full text

Transcriptome analysis revealed that ischemic post-conditioning suppressed the expression of inflammatory genes in lung ischemia-reperfusion injury by Liangen Lin, Congcong Sun, Yuanwen Ye, Peng Zhu, Keyue Pan, Linglong Chen

“…Additionally, protein-protein interaction (PPI) network analysis was carried out to examine associations among the DEGs. …”
Get full text

Genetic Spectrum of Lithuanian Familial Hypercholesterolemia Patients by Urte Aliosaitiene, Rimante Cerkauskiene, Aleksandras Laucevicius, Migle Vilniskyte, Viktoras Sutkus, Antanas Mainelis, Birute Burnyte, Jurate Barysiene, Zaneta Petrulioniene

“…The subjects were divided into four groups according to the Dutch Lipid Clinic Network (DLCN) criteria (definite, probable, possible, and unlikely). …”
Get full text

Origin-Destination Estimation Using Probe Vehicle Trajectory and Link Counts by Xianfeng Yang, Yang Lu, Wei Hao

Get full text

Inspiring Social Capital Through Community Green Space: Pathways and Implications by Lin YE, Shi HE, Yinghao LI, Zhaohui YAN, Lei HUANG

“…These institutional transformations have fundamentally reshaped social relationship patterns, eroding traditional kinship-based connections and resulting in fragmented community networks and a continuous decline in residents’ sense of belonging. …”
Get full text