Fracture resistance and failure modes of endodontically-treated permanent teeth restored with Ribbond posts vs other post systems: a systematic review and meta-analysis of in vitro... by Meghana Aditya Vartak, Vibha Rahul Hegde, Sanitra Rahul Hegde, Ushaina Fanibunda

Get full text

Technical variability and safety of sleeve gastrectomy: a nationwide survey of bariatric centers in Poland by Przemysław Sroczyński, Piotr Major, Michał R. Janik

“…While considered technically straightforward, significant variation exists in the operative technique, which may affect safety outcomes. Aim: This study aimed to analyze the technical aspects and complication rates of SG across Polish bariatric centers in 2023. …”
Get full text

Temporal stability of soil moisture in banana cropping area in the Brazilian semiarid region by Diego C. dos S. Araújo, Suzana M. G. L. Montenegro, Abelardo A. de A. Montenegro, Daniella P. dos Santos, Renato A. S. Rodrigues

“…The temporal stability technique allowed the identification of points that represent the mean behavior of soil moisture throughout the area. …”
Get full text

Teaching vocabulary with augmented reality: voices from junior high school English teachers by Nafiseh Salehi

Get full text

Exploring the density and morphology of coconut structures at two locations: a time-based analysis using computer tomography by Shenghuang Lin, Chengxu Sun, Li’an Luo, Mengxing Huang, JeromeJeyakumar John Martin, Hongxing Cao, Jinyue Hu, Zhiming Bai, Zhanping He, Yu Zhang, Jing Chen

Get full text

Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale by Monica Casella, Nicola Milano, Pasquale Dolce, Davide Marocco

“…Various factors contribute to this issue, including participant non-response, dropout, or technical errors during data collection. Traditional methods like mean imputation or regression, commonly used to handle missing data, rely upon assumptions that may not hold on psychological data and can lead to distorted results.MethodsThis study aims to evaluate the effectiveness of transformer-based deep learning for missing data imputation, comparing ReMasker, a masking autoencoding transformer model, with conventional imputation techniques (mean and median imputation, Expectation–Maximization algorithm) and machine learning approaches (K-nearest neighbors, MissForest, and an Artificial Neural Network). …”
Get full text

Impute-VSS: A comprehensive web-based visualization and simulation suite for comparative data imputation and statistical evaluation by Vartul Shrivastava, Shekhar Shukla

“…In today's technological landscape, where data processing forms the backbone of modeling and predictive analytics, data imputation is crucial in filling missing values within datasets using statistical techniques. …”
Get full text

Spatio-Temporal Transformer Networks for Inland Ship Trajectory Prediction with Practical Deficient Automatic Identification System Data by Youan Xiao, Xin Luo, Tengfei Wang, Zijian Zhang

“…This study introduces a data processing technique to refine AIS data, encompassing segmentation, outlier elimination, missing point interpolation, and uniform interval resampling, aiming to enhance trajectory analysis reliability. …”
Get full text

Using the aeromagnetic data for mapping the basement depth and contact locations, at southern part of Tihamah region, western Yemen by Marwan A. Al-Badani, Yahia M. Al-Wathaf

“…The present study aims to produce an excellent picture for the basement depth and contact locations, deduced from the available aeromagnetic data. …”
Get full text

Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques by Juswin Sajan John, Boppuru Rudra Prathap, Gyanesh Gupta, Jaivanth Melanaturu

“…This study introduces a novel approach to effectively characterize mental stress through a multi-label, multi-class classification framework through natural language processing techniques. Building on existing literature, discussions with psychologists and other mental health practitioners, we developed a taxonomy of 27 distinctive markers spread across 4 label categories; aiming to create a preliminary screening tool leveraging textual data.The core objective is to identify the most suitable model for this complex task, encompassing comprehensive evaluation of various machine learning and deep learning algorithms. we experimented with support vector machines (SVM), random forest (RF) and long short-term memory (LSTM) algorithms incorporating various feature combinations involving Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA). …”
Get full text

Soil Organic Carbon Assessment Using Remote-Sensing Data and Machine Learning: A Systematic Literature Review by Arthur A. J. Lima, Júlio Castro Lopes, Rui Pedro Lopes, Tomás de Figueiredo, Eva Vidal-Vázquez, Zulimar Hernández

“…This Systematic Literature Review (SLR) aims to identify techniques and alternative ways to estimate SOC using Remote-Sensing (RS) spectral data and computer tools to process this database. …”
Get full text

Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence by Asma Aldrees, Stephen Ojo, James Wanliss, Muhammad Umer, Muhammad Attique Khan, Bayan Alabdullah, Shtwai Alsubai, Nisreen Innab

Get full text

Understanding the log file data from educational and psychological computer-based testing: A scoping review protocol. by Guanyu Chen, Yan Liu, Yue Mao

“…The debate on how to maximize insights from log file data has not yet reached a consensus. Therefore, we present this protocol for a scoping review that aims to characterize the application of log file data in current publications, including the data pre-processing techniques, analytical methodologies, and theoretical frameworks used by researchers. …”
Get full text

Networked Behaviors Associated With a Large-Scale Secure Messaging Network: Cross-Sectional Secondary Data Analysis by Laura Rosa Baratta, Linlin Xia, Daphne Lew, Elise Eiden, Y Jasmine Wu, Noshir Contractor, Bruce L Lambert, Sunny S Lou, Thomas Kannampallil

“…Social network analysis techniques were used to quantify the global (network)- and node (health care professional)-level properties of the network. …”
Get full text

Low-intensity behavioral activation smartphone app to support low mood: description, engagement and log data analysis by Paul Farrand, Patrick J. Raue, Earlise Ward, Sandra Healey, Jonathan Baker

Get full text

The Ponte Delle Chianche on the <i>Via Traiana</i> in Buonalbergo (Benevento, Italy): New Data for an Integrated Study by Ivan Ferrari

“…This article illustrates a systematic and updated study of the Ponte delle Chianche, a Roman bridge on the ancient Via Traiana built at the beginning of the second century AD and located near Buonalbergo (Benevento, Italy). The study aimed to retrieve all information contained in literary sources and to cross-reference them with new data from research conducted in recent years. …”
Get full text

New Approach in Fixed Resource Allocation and Target Setting Using Data Envelopment Analysis with Common Set of Weights by Marzieh Ghasemi, Mohammad Reza Mozaffari, Farhad Hosseinzadeh Lotfi, Mohsen Rostamy malkhalifeh, Mohammad Hasan Behzadi

“…One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). …”
Get full text

Comparing variable and feature selection strategies for prediction - protocol of a simulation study in low-dimensional transplantation data. by Linard Hoessly, Jaromil Frossard, Simon Schwab, Frédérique Chammartin, Alexander Leichtle, Peter Werner Schreiber, Dionysios Neofytos, Michael Koller, with the Swiss Transplant Cohort Study (STCS)

“…We describe the planned steps through the Aims, Data, Estimands, Methods, and Performance framework for simulation study design and reporting.…”
Get full text

Quantitative insights into the Winnipeg rental sector: A data-driven analytical approach using geographic and property metrics by Lahiru Wickramasinghe, Aditya Jain

Get full text

Early detection of esophageal cancer: Evaluating AI algorithms with multi-institutional narrowband and white-light imaging data. by Young Seo Baik, Hannah Lee, Young Jae Kim, Jun-Won Chung, Kwang Gi Kim

“…Esophageal cancer is one of the most common cancers worldwide, especially esophageal squamous cell carcinoma, which is often diagnosed at a late stage and has a poor prognosis. This study aimed to develop an algorithm to detect tumors in esophageal endoscopy images using innovative artificial intelligence (AI) techniques for early diagnosis and detection of esophageal cancer. …”
Get full text