Results 101 to 110 of about 33,003,501 (342)

A Novel Approach to Improve the Estimation of a Diet Adherence Considering Seasonality and Short Term Variability – The NU-AGE Mediterranean Diet Experience

open access: yesFrontiers in Physiology, 2019
In this work we present a novel statistical approach to improve the assessment of the adherence to a 1-year nutritional intervention within the framework of the NU-AGE project. This was measured with a single adherence score based on 7-days food records,
Enrico Giampieri   +16 more
doaj   +1 more source

A hierarchical model of metacognition. [PDF]

open access: yes, 2020
I present a novel method of conceptualizing metacognition in a computational hierarchy. Metacognition is commonlydescribed as cognition acting on itself, and correlates with enhanced performance in memory, reasoning, emotional reg-ulation, and motor skills.
Conway-Smith, Brendan, West, Robert
openaire   +1 more source

Hierarchical Geodesic Models in Diffeomorphisms

open access: yesInternational Journal of Computer Vision, 2015
Hierarchical linear models (HLMs) are a standard approach for analyzing data where individuals are measured repeatedly over time. However, such models are only applicable to longitudinal studies of Euclidean data. This paper develops the theory of hierarchical geodesic models (HGMs), which generalize HLMs to the manifold setting.
Nikhil Singh 0002   +3 more
openaire   +3 more sources

Hierarchical location-allocation models for congested systems [PDF]

open access: yes
In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher ...
Daniel Serra, Vladimir Marianov
core  

UiO‐66 metal–organic frameworks in biomedicine: From structural tunability to bioimaging, photodiagnostics, and photodynamic cancer therapy

open access: yesFEBS Open Bio, EarlyView.
UiO‐66(Zr) metal–organic frameworks are chemically stable, biocompatible, and highly tunable nanomaterials. Their modular structure enables controlled drug delivery, multimodal bioimaging, and light‐activated photodynamic therapy, supporting integrated diagnostic and therapeutic (theranostic) applications in cancer and biomedical research.
Veronika Huntošová   +2 more
wiley   +1 more source

A Hierarchical Model of Binocular Rivalry [PDF]

open access: yesNeural Computation, 1998
Binocular rivalry is the alternating percept that can result when the two eyes see different scenes. Recent psychophysical evidence supports the notion that some aspects of binocular rivalry bear functional similarities to other bistable percepts. We build a model based on the hypothesis (Logothetis & Schall, 1989; Leopold & Logothetis, 1996 ...
openaire   +3 more sources

Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA

open access: yesFEBS Open Bio, EarlyView.
Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley   +1 more source

Kernel-Based Learning of Hierarchical Multilabel Classification Models

open access: yes, 2006
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time.
Szedmak, S.   +3 more
core   +1 more source

SOMTreeNet: A Hybrid Topological Neural Model Combining Self-Organizing Maps and BIRCH for Structured Learning

open access: yesMathematics
This study introduces SOMTreeNet, a novel hybrid neural model that integrates Self-Organizing Maps (SOMs) with BIRCH-inspired clustering features to address structured learning in a scalable and interpretable manner.
Yunus Doğan
doaj   +1 more source

Comparing MCMC and INLA for disease mapping with Bayesian hierarchical models

open access: yesArchives of Public Health, 2015
Bayesian hierarchical models with random effects are one of the most widely used methods in modern disease mapping, as a superior alternative to standardized ratios.
T. De Smedt   +3 more
semanticscholar   +1 more source

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