Machine Learning-Based VO₂ Estimation Using a Wearable Multiwavelength Photoplethysmography Device by Chin-To Hsiao, Carl Tong, Gerard L. Coté

“…This study presents a novel wrist-worn multiwavelength photoplethysmography (PPG) device and machine learning algorithm designed to estimate VO₂ continuously. …”
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Colorimetric Biosensors: Advancements in Nanomaterials and Cutting-Edge Detection Strategies by Yubeen Lee, Izzati Haizan, Sang Baek Sim, Jin-Ha Choi

“…In order to enhance the color change reactions in colorimetric techniques, functional nanomaterials are often integrated due to their desirable intrinsic properties. …”
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Modeling functional connectivity with learning and memory in a mouse model of Alzheimer's disease by Lindsay Fadel, Elizabeth Hipskind, Steen E. Pedersen, Jonathan Romero, Caitlyn Ortiz, Caitlyn Ortiz, Eric Shin, Md Abul Hassan Samee, Robia G. Pautler, Robia G. Pautler, Robia G. Pautler

“…IntroductionFunctional connectivity (FC) is a metric of how different brain regions interact with each other. …”
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Design and Development of a Bespoke Rotary Friction Welding Machine in Exploration of Joining Dissimilar Materials for Nuclear Applications by Michail Dellepiane, Laurie Da Silva, Athanasios Toumpis

“…However, access to expensive and complex industrial-grade friction welding machines is not always possible. This study explores the design process and functionality of a laboratory-scale friction welding setup following the fundamentals of large-scale machinery. …”
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A Distributional Robust Distribution Network Reconfiguration Method Based on Compressed Switch Candidate Set by Haocheng DU, Shilong LI, Yuntao JU, Jinqi ZHANG

“…The first stage took the minimization of active network loss of the system as the objective function and used the optimal matching loop flow method to compress the switch candidate set; the second stage took the minimization of the sum of the power purchase cost and the switch action cost as the objective function, constructed the chance constraints on the capacity limits of the power point, and adopted a Wasserstein ball-based distributional robust method to deal with the uncertainty of distributed generation. …”
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Clinical Characterization of Patients with Syncope of Unclear Cause Using Unsupervised Machine-Learning Tools: A Pilot Study by María-José Muñoz-Martínez, Manuel Casal-Guisande, María Torres-Durán, Bernardo Sopeña, Alberto Fernández-Villar

“…The number of clusters was determined through cost function analysis and silhouette index, and visual validation was performed using UMAP. …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…This research aims to compare the key machine learning approaches, Namely Support Vector Machines (SVM), Random Forest (RF) and Decision Trees (DT), in their ability to classify Intrusion Detection Systems (IDS) via routing networks over distributed computing systems. …”
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Application of microscopic smartphone attachment for remote preoperative lab testing by Kefan Song, Kefan Song, Alexander T. Adams, Alexander T. Adams

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Immunologic aspects of West syndrome and evidence of plasma inhibitory effects on T cell function by Terezinha C.B. Montelli, Angela M.V.C. Soares, Maria Terezinha S. Peraçoli

“…Thus, WS was studied at different points of the natural evolutive history of the disease. …”
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Determination of the Most Suitable Cut-Off Point of the Cervical Foraminal Cross-Sectional Area at the C5/6 Level to Predict Cervical Foraminal Bony Stenosis by Joohyun Lee, Jee Young Lee, Keum Nae Kang, Jae Ni Jang, Sukhee Park, Young Uk Kim

“…<b>Background</b>: Cervical foraminal bony stenosis (CFBS) is a common degenerative spinal condition that causes radicular pain and functional impairment in the upper extremities. Accurate and objective diagnosis of CFBS remains challenging due to the absence of standardized morphometric criteria. …”
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Variational Quantum Circuit-Based Quantum Machine Learning Approach for Predicting Corrosion Inhibition Efficiency of Expired Pharmaceuticals by Muhamad Akrom, Muhammad Reesa Rosyid, Lubna Mawaddah, Akbar Priyo Santosa

“…This study examines the potential of quantum machine learning (QML) to predict the corrosion inhibition capacity of expired pharmaceutical compounds. …”
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Documenting the Production Process of Faba bean (Vicia faba L.) in Gorgan, Ali Abadkatol and Aqqola Regions by Mohammad Reza Mansouri Vajari, Ebrahim Zeinali, Afshin Soltani, Benjamin Torabi, Alireza Nehbandani

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A technique of building a value function at the stage of conceptual design of microprocessor systems by B. N. Chugaev, M. A. Shaposhnikova

“…In general, when n properties are taken into account for each of the compared systems, then the solution of the task of choosing “the best” system depends on choosing a function-criterion. Such function is called a value function in the article. …”
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Mapping changes of grassland to arable land using automatic machine learning of stacked ensembles and H2O library by Jiří Šandera, Přemysl Štych

“…The importance of several biological predictors has been tested (FAPAR, FCOVER, LAI, NDVI, etc.) with the help of a heatmap that is part of AutoML function of H2O library.…”
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Increased epicardial tissue and reduced TAPSE and MAPSE scores in borderline personality disorders. Early indicators for cardiovascular risk? by Charlotte F. M. Schaefer, Britta Stapel, Nicole Scharn, Sebastian Bertele, Alexander Glahn, Kai G. Kahl, Phileas J. Proskynitopoulos, Mechthild Westhoff-Bleck

“…BPD patients were more frequently smokers and reported lower levels of physical exercise compared to controls.ConclusionThe present study demonstrates morphological and functional differences in a matched sample of female patients with BPD and healthy controls, pointing to an increased risk for the development of cardiovascular disorders. …”
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Selective Separation of Scandium in Acidic Water Using Carboxyl Functionalized Covalent Phosphonitrile Polymers by Yu BAI, Ayinuer WUSHUER, Lei OUYANG, Lijin HUANG, Qin SHUAI

“…BACKGROUNDScandium (Sc) is widely used due to its excellent properties such as high melting point, high boiling point, low density, and good stability. …”
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Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy’s impact on ART adherence by Abraham Keffale Mengistu, Kelemua Aschale Yeneakale, Nebebe Demis Baykemagn, Zelalem Yitayal Melese, Andualem Enyew Gedefaw

“…Using observational data from 4152 HIV patients in Ethiopia (2005–2024), we applied causal inference methods, including Adjusted Logistic Regression, Propensity Score Matching, and Causal Forest Double Machine Learning (DML), to estimate TPT’s effect on ART adherence. …”
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Transfer learning-based techniques for efficient 3D-reconstruction of functionally graded materials by Pouria Hamidpour, Alireza Araee, Majid Baniassadi

“…In the next step, transfer learning is applied using convolutional occupancy networks to reconstruct the 3D microstructure from the 2D image depth layers, with the model trained on point clouds obtained from 2D images. To validate the method, the reconstructed microstructures are compared to actual material images at the same depth using various metrics, including lineal path, two-point correlation, and quality of connection functions. …”
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Analysis on Full Automatic Operation Scenes and Related Functional Requirements of Urban Railway Transport by Pengzhe WEN, Daoliang XU, Shijie GAO, Xiangtao LI

“…Taking the automatic car wash scene and the large passenger flow operation scene as examples for analysis, the functional requirements of communication, signal, vehicle, integrated supervisory and control, platform edge door, car washing machine and other key equipments and interface relationship between various equipment of different operation scenes were pointed out. …”
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Inspired by nature, refined by numbers: formal–functional bioinspiration and intelligent computation in vehicle design by Pooya Sareh

“…For centuries, naturalist philosophers and scientists have studied the form and function of living organisms, striving to propose theories that describe the interplay between these two essential components of biological entities. …”
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