Results 41 to 50 of about 197,762 (310)

The Association Between Utility of Learning Resources, Class Attendance, Statistical Self-Efficacy, Mathematics Competence and Statistics Anxiety Among Undergraduate Students

open access: yesJournal of Statistics and Data Science Education
Statistics anxiety is recognized as a major challenge facing students at all academic levels. It particularly affects their performance in statistics and research methods courses.
Fareena Maryam Alladin   +2 more
doaj   +1 more source

Mathematical Statistics with Mathematica®

open access: yes, 2002
Imagine computer software that can find expectations of arbitrary random variables, calculate variances, invert characteristic functions, solve transformations of random variables, calculate probabilities, derive order statistics, find Fisher's Information and Cramér-Rao Lower Bounds, derive symbolic (exact) maximum likelihood estimators,perform ...
C Rose, Murray Smith
openaire   +2 more sources

Protocol for quantifying miRNA trafficking across the endosomal membrane

open access: yesFEBS Open Bio, EarlyView.
An in vitro protocol measures miRNA uptake into endosomes isolated from mammalian cell extracts, which are free of subcellular contaminants. Performed at 37 °C in the presence of ATP, it ensures the import of single‐stranded miRNA into the endosomal lumen.
Syamantak Ghosh   +2 more
wiley   +1 more source

The Method Based on Series Solution for Identifying an Unknown Source Coefficient on the Temperature Field in the Quasiperiodic Media

open access: yesInternational Journal of Differential Equations, 2021
In this paper, we consider the reconstruction of heat field in one-dimensional quasiperiodic media with an unknown source from the interior measurement.
Bingxian Wang   +3 more
doaj   +1 more source

Digital Cognitive Testing in Mitochondrial Disease: Validity and Challenges for Clinical Trial Use

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Primary mitochondrial disease is a group of genetic disorders caused by pathogenic variants in nuclear or mitochondrial DNA, often resulting in progressive neurodegeneration and cognitive decline. Current management is primarily supportive, though recent research offers hope for disease‐modifying treatments in the future.
Oksana Pogoryelova   +9 more
wiley   +1 more source

Department of Applied Mathematics and Statistics newsletter, September 5, 2023

open access: yes, 2023
Newsletter of the Department of Applied Mathematics and Statistics at Colorado School of ...

core  

Research on Ethanol Coupling to Prepare C4 Olefins Based on BP Neural Network and Cluster Analysis

open access: yesJournal of Chemistry, 2022
Ethanol, as a clean energy source, is an ideal raw material for the preparation of C4 olefins, but there are few studies on the preparation of C4 olefins by the coupling of ethanol.
Sheng-Mei Zhang   +4 more
doaj   +1 more source

Blood RNA Biomarker Signatures for Early Diagnosis and Prognosis in Ischemic and Hemorrhagic Stroke: The IBIS‐CT1 Study

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau   +11 more
wiley   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif   +17 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +2 more
wiley   +1 more source

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