Predicting the Event Types in the Human Brain: A Modeling Study Based on Embedding Vectors and Large-Scale Situation Type Datasets in Mandarin Chinese by Xiaorui Ma, Hongchao Liu

“…Meanwhile, event types exhibit strong predictive capabilities for exploring collocational patterns between words, making them crucial for Chinese teaching. …”
Get full text

Asynchronous Teledermatology for Non-Scarring Alopecia: A Retrospective Study by Aliyyat Afolabi, Elijah Brown, Edra K. Ha, Joseph C. English

“…Asynchronous teledermatology has emerged as a potential solution to extend care to these groups. Objective: To evaluate the diagnostic utility and treatment patterns of asynchronous teledermatology for non-scarring alopecia and examine its role in improving care access across diverse populations within the University of Pittsburgh Medical Center (UPMC) network. …”
Get full text

Multi-source Data-driven Analysis of Deformation and Influencing Factors for Expansive Soil Canal Slopes by ZHANG Yuhan, HU Jiang, LI Xing

“…Deformation serves as a direct indicator of slope stability, making the analysis of deformation patterns and trends essential for assessing stability. …”
Get full text

An EWS-LSTM-Based Deep Learning Early Warning System for Industrial Machine Fault Prediction by Fabio Cassano, Anna Maria Crespino, Mariangela Lazoi, Giorgia Specchia, Alessandra Spennato

“…This research details the creation and evaluation of an EWS that incorporates deep learning methods, particularly using Long Short-Term Memory (LSTM) networks enhanced with attention layers to predict critical machine faults. …”
Get full text

Exploring Pre-Trained Models for Skin Cancer Classification by Abdelkader Alrabai, Amira Echtioui, Fathi Kallel

“…In this paper, the performance of four pre-trained models—two convolutional neural networks (ResNet50 and VGG19) and two vision transformers (ViT-b16 and ViT-b32)—is evaluated in distinguishing malignant from benign skin cancers using a publicly available dermoscopic dataset. …”
Get full text

Systematic review and meta-analysis of disease clustering in multimorbidity: a study protocol by Andrew Wister, Kate Smolina, Felicity Clemens, Mike A Irvine, Jennifer Ferris, Boah Kim, Lean K Fiedeldey, Sogol Haji Hosseini

“…We will assess the stability of obtained disease clusters across the research literature to date, in order to evaluate the strength of evidence for specific disease patterns in multimorbidity.Ethics and dissemination This study does not require ethics approval as the work is based on published research studies. …”
Get full text

Comparative analysis of digital safety training programs for minors by Marcos Gómez Puerta, Esther Chiner, Andrea Oliver-Ridaura

“…The aim is to identify common patterns, divergences, and gaps that will help guide future actions in critical digital literacy and online risk prevention. …”
Get full text

Integrating plot-based methods for monitoring biodiversity in island habitats under the scope of BIODIVERSA + project BioMonI: Tree monitoring in Terceira, Tenerife and Réunion Isl... by Paulo Borges, Leila Morgado, Rosalina Gabriel, Rui Elias, Mirana Gauche, Claudine Ah-Peng, Rüdiger Otto, Lea de Nascimento, Dominique Strasberg, Nathaly Guerrero-Ramírez, Holger Kreft, José María Fernández-Palacios

“…We are assembling data from BioMonI-Plot, a long-term vegetation plot network to understand biodiversity and ecosystem change. …”
Get full text

Antimicrobial Susceptibility Profiles of <i>Escherichia coli</i> Isolates from Clinical Cases of Geese in Hungary Between 2022 and 2023 by Ádám Kerek, Ábel Szabó, Ákos Jerzsele

“…Cluster analysis and principal component analysis (PCA) were applied to identify resistance patterns. Co-resistance relationships were examined through network analysis, while Monte Carlo simulations were used to estimate the expected prevalence of MDR strains. …”
Get full text

Human mobility and malaria risk in peri-urban and rural communities in the Peruvian Amazon. by Joaquin Gomez, Alessandro Grosso, Mitchel Guzman-Guzman, Stefano Garcia Castillo, Marcia C Castro, Katherine Torres, Joseph M Vinetz, Dionicia Gamboa

“…This study focuses on identifying the sources of malaria transmission and patterns of human mobility in order to understand the movement and transmission of the parasite.…”
Get full text

Estimation of state of health for lithium-ion batteries using advanced data-driven techniques by Smitanjali Rout, Sudhansu Kumar Samal, Demissie Jobir Gelmecha, Satyasis Mishra

“…Advanced machine learning models, including Adaboost, Xgboost, Ridge Regression, Decision Trees, Random Forests, Artificial Neural Networks, and Long Short-Term Memory Networks (LSTM), are employed to analyze battery performance. …”
Get full text

Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment by Aleš Procházka, Daniel Martynek, Marie Vitujová, Daniela Janáková, Hana Charvátová, Oldřich Vyšata

“…The study employs a range of machine learning methods, including support vector machines, Bayesian analysis, and neural networks, to evaluate the balance of various physical activities. …”
Get full text

High-performance glass classification using advanced machine learning and deep learning algorithms with a comprehensive feature analysis by Mohammed Bouziane, Abdelghani Bouziane, Samia Larguech, Khatir Naima, Mohammad Salman Haque, Younes Menni

“…Advanced learning algorithms like Random Forest (RF), XGBoost, Support Vector Machines, and Bidirectional Long Short-Term Memory (BiLSTM) networks are applied for classification. Findings prove RF and XGBoost to provide the highest classification accuracy, and BiLSTM to be the best in recognizing complex data patterns. …”
Get full text

Sustainable Supplier Selection through Multi-Criteria Decision Making (MCDM) Approach: A Bibliometric Analysis by Khoiron Khulud, Ilyas Masudin, Fien Zulfikarijah, Dian Palupi Restuputri, Abdul Haris

“…In the recent past, researchers have carried out a significant amount of research in this field over the course of several years; <i>Methods</i>: a total of 121 scientific publications sourced from the Scopus database were chosen for analysis, employing the bibliometric method and graphical visualization of the VOS viewer application to visually analyze and map research networks and collaboration patterns, aiding in the evaluation of scientific impact and knowledge dissemination; <i>Results</i>: the findings of this study indicate that the research trend in sustainable supplier selection through MCDM witnessed its most significant growth in the year 2019. …”
Get full text

Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Existing tiered storage systems predominantly employ reactive policies that respond to observed access patterns, leading to suboptimal performance under dynamic workloads and failing to address multi-objective optimization requirements. …”
Get full text

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

Integrating computational approaches to uncover β-lactamase-associated resistance in diarrheagenic Escherichia coli from pediatric patients by Taru Singh, Chandra Shekhar, Saurabh Singh, Shukla Das

“…Structural modeling, phylogenetic analysis, and molecular docking were used to evaluate evolutionary patterns and drug interactions with ceftriaxone and amoxicillin. β-lactamase enzymes in DEC strains exhibited varying thermal stability and were frequently co-produced. …”
Get full text

Constraint-Induced Movement Therapy Promotes Contralesional Red Nucleus Plasticity and Increases Bilateral Motor Cortex-to-Red Nucleus Projections After a Large-Area Stroke by Peile Liu, Jian Hu, Beiyao Gao, Yan Hua, Ying Xing, Yulong Bai, Nan Liu

“…For decades, scientists have explored the patterns of neural network remodeling that occur after a stroke. …”
Get full text

Machine Learning Traffic Flow Prediction Models for Smart and Sustainable Traffic Management by Rusul Abduljabbar, Hussein Dia, Sohani Liyanage

“…This study contributes to this objective by developing and evaluating advanced machine learning models that leverage multisource data to predict traffic patterns more effectively, allowing for the deployment of proactive measures to prevent or reduce traffic congestion and idling times, leading to enhanced eco-friendly mobility. …”
Get full text

Transformer Versus LSTM: A Comparison of Deep Learning Models for Karst Spring Discharge Forecasting by Anna Pölz, Alfred Paul Blaschke, Jürgen Komma, Andreas H. Farnleitner, Julia Derx

“…Deep learning models can capture complex relationships due to their ability to learn non‐linear patterns. This study evaluates the performance of the Transformer in forecasting spring discharges for up to 4 days. …”
Get full text