Results 91 to 100 of about 83,751 (262)

Based a machine learning approach to investigate the factors influencing nirmatrelvir/ritonavir exposure in human plasma: a multicenter, observational study

Frontiers in Cellular and Infection Microbiology
ObjectivesNirmatrelvir/ritonavir (N/R) is an effective antiviral for treating COVID-19. However, evidence supporting therapeutic drug monitoring (TDM) for N/R remains limited, potentially increasing the risk of adverse reactions and compromising efficacy.
Yue Zhang, Yue Zhang, Xiner Yang, Xiner Yang, Liang Sun, Liang Sun, Runcong Zhang, Runcong Zhang, Weibin Fan, Weibin Fan, Nengming Lin, Nengming Lin, Nengming Lin, Bin Lin, Bin Lin, Bin Lin   +15 more
doaj   +1 more source

Plasma EV Proteomics Identifies ECM Remodeling and Inflammatory Proteins LUM and C7 as Candidate Biomarkers in FSHD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit, Chiranth K. Nagaraj, Jackson S. Newell, Kim Truc Nguyen, Xilal Y. Rima, Jacob Doon‐Ralls, Eduardo Reátegui, Jeffrey M. Statland, Rabi Tawil, Kevin M. Flanigan, Scott Q. Harper, Nizar Y. Saad   +11 more
wiley   +1 more source

A Deep Learning Model Using Transformer Network and Expert Optimizer for an Hour Ahead Wind Power Forecasting

IEEE Access
The renewable energy platform cannot operate without an accurate wind power forecast. The power system can better manage its supply and guarantee grid reliability with an accurate wind power forecast. Accurate forecasting is difficult to achieve, though,
Anushalini Thiyagarajan, B. Sri Revathi, Vishnu Suresh   +2 more
doaj   +1 more source

A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi, Giorgio Ricciardiello Mejia, Andre Metzger, Kang Hyun Ryu, Salonee Marwaha, Eva Grzegorczyk, Li Zhou, Eliana Jacobs, Boris Gilyadov, Claudia Kunney, Liqhwa Ncube, Ankit Parekh, Emmanuel Mignot, Fanny M. Elahi, Joseph Winer, Kathleen Poston, Andreas Brink‐Kjaer, Emmanuel H. During   +17 more
wiley   +1 more source

APPLICATION OF RANKING BASED ATTRIBUTE SELECTION FILTERS TO PERFORM AUTOMATED EVALUATION OF DESCRIPTIVE ANSWERS THROUGH SEQUENTIAL MINIMAL OPTIMIZATION MODELS [PDF]

ICTACT Journal on Soft Computing, 2014
In this paper, we study the performance of various models for automated evaluation of descriptive answers by using rank based feature selection filters for dimensionality reduction.
C. Sunil Kumar, R.J. Rama Sree
doaj  

Differential Item Functioning on the Patient Health Questionnaire 8 by Disease Subtype, Language, Sex, and Age Among People With Systemic Sclerosis: A Scleroderma Patient‐Centered Intervention Network Cohort Study

Arthritis Care &Research, EarlyView.
Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu, Marie‐Eve Carrier, Marie‐Claude Geoffroy, Meira Golberg, Linda Kwakkenbos, Susan J. Bartlett, Catherine Fortuné, Amy Gietzen, Karen Gottesman, Geneviève Guillot, Laura K. Hummers, Amanda Lawrie‐Jones, Vanessa L. Malcarne, Michelle Richard, Maureen Sauvé, Luc Mouthon, Andrea Benedetti, Brett D. Thombs, on behalf of the SPIN Investigators, Claire E. Adams, Marie Hudson, Maureen D. Mayes, James Stempel, Robyn K. Wojeck, Christian Agard, Laurent Alric, Marc André, Floryan Beaslay, Elana J. Bernstein, Sabine Berthier, Lyne Bissonnette, Sophie Blaise, Eva Bories, Alessandra Bruns, Carlotta Cacciatore, Patricia Carreira, Marion Casadevall, Benjamin Chaigne, Lorinda Chung, Benjamin Crichi, Thylbert Deltombe, Christopher P. Denton, Tannvir Desroche, Robyn Domsic, James V. Dunne, Bertrand Dunogue, Regina Fare, Dominique Farge‐Bancel, Paul R. Fortin, Tracy Frech, Loraine Gauzère, Anne Gerber, Jessica K. Gordon, Brigitte Granel‐Rey, Aurélien Guffroy, Geneviève Gyger, Eric Hachulla, Daphna Harel, Monique Hinchcliff, Sabrina Hoa, Michael Hugues, Alena Ikic, Sindhu R. Johnson, Nader Khalidi, Kimberly S. Lakin, Marc Lambert, Maggie Larche, David Launay, Yvonne C. Lee, Paul Legendre, Catarina Leite, Hélène Maillard, Nancy Maltez, Joanne Manning, Isabelle Marie, Maria Martin Lopez, Thierry Martin, Ariel Masetto, Arsène Mekinian, Sheila Melchor Díaz, Morgane Mourguet, Christelle Nguyen, Karen Nielsen, Mandana Nikpour, Louis Olagne, Vincent Poindron, Janet Pope, Susanna Proudman, Grégory Pugnet, Loïc Raffray, François Rannou, Alexis Régent, Frederic Renou, Sébastien Rivière, David Robinson, Esther Rodríguez Almazar, Tatiana Sofia Rodríguez‐Reyna, Sophie Roux, Perrine Smets, Vincent Sobanski, Robert F. Spiera, Virginia Steen, Evelyn Sutton, Carter Thorne, Damien Vagner, John Varga, Pearce Wilcox, Vanessa Cook, Cassidy Dal Santo, Monica D'Onofrio, Elsa‐Lynn Nassar   +110 more
wiley   +1 more source

An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions

Scientific Reports
This study introduces a novel hybrid model for accurate CO2 emissions prediction, supporting sustainable decision-making. The model integrates the Gaussian mutation and shrink mechanism-based moth flame optimization (GMSMFO) algorithm with an extreme ...
Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa   +1 more
doaj   +1 more source

root mean square error of cross validation

Citation: 'root mean square error of cross validation' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.10109 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual ...
openaire   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Carboxylic‐Acid Functionalized Multiwalled Carbon Nanotube‐Alkane‐Based Resistive Temperature Sensor for Cold Chain Applications

Advanced Engineering Materials, EarlyView.
This study presents a reversible temperature sensor with high switching ratio, ∼103. The device is fabricated using PET‐ITO and carbon nanotube dispersions in alkane. Considering its application in cold chain logistics, a proof‐of‐concept with LED is showcased. Thus, a temperature drop below the threshold temperature (crystallization temperature of the
Sunil Kumar Behera, Philippe Marrec, A. Jorge Parola, Madalena Dionísio, Hugo Águas, Andreia F. M. Santos, Hamed Pourkheirollah, Donald Lupo, César A. T. Laia   +8 more
wiley   +1 more source