7,030 results match your criteria latent structure


Triadic family structures and their day-to-day dynamics from an adolescent perspective: A multilevel latent profile analysis.

Fam Process 2021 Sep 16. Epub 2021 Sep 16.

Human Development and Family Studies, The Pennsylvania State University, University Park, Pennsylvania, USA.

Relationship structure (patterns of relative closeness among multiple family members) and dynamics (changes in relationship structures overtime) are two main aspects of family system functioning, yet empirical tests of these concepts lag behind theory. Recent growth in advanced methods for complex data structures makes it possible to empirically capture structures and dynamics within multiple family relationships overtime. To answer how relationship structure may fluctuate from day to day, this study used multilevel latent profile analysis (MLPA) as an innovative and feasible method to capture mother-father-adolescent (MFA) relationship structures and dynamics on a daily basis. Read More

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September 2021

Identifying the dynamic gene regulatory network during latent HIV-1 reactivation using high-dimensional ordinary differential equations.

Int J Comput Biol Drug Des 2018 28;11(1-2):135-153. Epub 2018 Mar 28.

Department of Biostatistics, The University of Texas School of Public Health, 1200 Pressler Street, Houston, TX, USA, 77030, USA.

Reactivation of latently infected cells has emerged as an important strategy for eradication of HIV. However, genetic mechanisms of regulation after reactivation remain unclear. We describe a five-step pipeline to study the dynamics of the gene regulatory network following a viral reactivation using high-dimensional ordinary differential equations. Read More

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Contrast Phase Classification with a Generative Adversarial Network.

Proc SPIE Int Soc Opt Eng 2020 Feb 10;11313. Epub 2020 Mar 10.

Department of Eletrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA 37212.

Dynamic contrast enhanced computed tomography (CT) is an imaging technique that provides critical information on the relationship of vascular structure and dynamics in the context of underlying anatomy. A key challenge for image processing with contrast enhanced CT is that phase discrepancies are latent in different tissues due to contrast protocols, vascular dynamics, and metabolism variance. Previous studies with deep learning frameworks have been proposed for classifying contrast enhancement with networks inspired by computer vision. Read More

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February 2020

A psychometric validation of the motives for physical activity measure for youth with intellectual disabilities (MPAM-ID).

Disabil Rehabil 2021 Sep 16:1-10. Epub 2021 Sep 16.

Institute for Positive Psychology and Education, Australian Catholic University, Sydney, Australia.

Purpose: To validate a version of the Motives for Physical Activity Measure (MPAM) adapted for youth with intellectual disabilities (ID).

Materials And Methods: A sample of 359 youth with mild to moderate ID from Australia and Canada respectively completed English and French versions of the MPAM-ID.

Results: Exploratory structural equation models supported the validity and reliability of the five-factor structure of the MPAM-ID, as well as the weak, latent variance-covariance, and latent mean invariance across linguistic versions. Read More

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September 2021

UHPLC-MS-MS analysis of oxylipins metabolomics components of follicular fluid in infertile individuals with diminished ovarian reserve.

Reprod Biol Endocrinol 2021 Sep 14;19(1):143. Epub 2021 Sep 14.

Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, 201204, China.

Background: Diminished ovarian reserve (DOR) refers to a decrease in the number and quality of oocytes in the ovary, which results in a lack of sex hormones and a decline of fertility in women. DOR can potentially progress to premature ovarian failure (POF), which has a negative impact on women's quality of life and is a major cause of female infertility. Oxidative stress is a major contributor to fertility decrease in DOR patients, affecting the follicular microenvironment, oocyte maturation, fertilization, and embryo development. Read More

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September 2021

Inosine Substitutions in RNA Activate Latent G-Quadruplexes.

J Am Chem Soc 2021 Sep 14. Epub 2021 Sep 14.

Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland.

It is well-accepted that gene expression is heavily influenced by RNA structure. For instance, stem-loops and G-quadruplexes (rG4s) are dynamic motifs in mRNAs that influence gene expression. Adenosine-to-inosine (A-to-I) editing is a common chemical modification of RNA which introduces a nucleobase that is -structural with guanine, thereby changing RNA base-pairing properties. Read More

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September 2021

Joint analysis of longitudinal measurements and spatially clustered competing risks HIV/AIDS data.

Authors:
Somayeh Momenyan

Stat Med 2021 Sep 13. Epub 2021 Sep 13.

Department of Biostatistics, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

The joint modeling of repeated measurements and time-to-event provides a general framework to describe better the link between the progression of disease through longitudinal measurements and time-to-event outcome. In the survival data, a sample of individuals is frequently grouped into clusters. In some applications, these clusters could be arranged spatially, for example, based on geographical regions. Read More

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September 2021

Adapting and Testing the Self-Efficacy in Environmental Risk Reduction Instrument Among Spanish-Speaking Populations.

J Nurs Meas 2021 Sep 13. Epub 2021 Sep 13.

Washington State University Elson S. Floyd College of Medicine, Spokane, Washington, DC.

Purpose: The purpose of this study was to adapt and test the Self-Efficacy in Environmental Risk Reduction instrument in a Spanish-speaking population.

Methods: Harkness' model of cross-cultural survey design was used to adapt the instrument. We sampled 95 adult, Spanish speakers from a federally qualified health clinic. Read More

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September 2021

Open set recognition algorithm based on Conditional Gaussian Encoder.

Math Biosci Eng 2021 Aug;18(5):6620-6637

School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China.

For the existing Closed Set Recognition (CSR) methods mistakenly identify unknown jamming signals as a known class, a Conditional Gaussian Encoder (CG-Encoder) for 1-dimensional signal Open Set Recognition (OSR) is designed. The network retains the original form of the signal as much as possible and deep neural network is used to extract useful information. CG-Encoder adopts residual network structure and a new Kullback-Leibler (KL) divergence is defined. Read More

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Human inference in changing environments with temporal structure.

Psychol Rev 2021 Sep 13. Epub 2021 Sep 13.

Laboratoire de Physique.

To make informed decisions in natural environments that change over time, humans must update their beliefs as new observations are gathered. Studies exploring human inference as a dynamical process that unfolds in time have focused on situations in which the statistics of observations are history-independent. Yet, temporal structure is everywhere in nature and yields history-dependent observations. Read More

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September 2021

Latent Factor Structure of Outcome Measures Used in the HABIT® Mild Cognitive Impairment Intervention Programs.

J Alzheimers Dis 2021 Sep 8. Epub 2021 Sep 8.

Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA.

Background: In Alzheimer's disease and related disorders (ADRD) research, common outcome measures include cognitive and functional impairment, as well as persons with mild cognitive impairment (pwMCI) and care partner self-reported mood and quality of life. Studies commonly analyze these measures separately, which potentially leads to issues of multiple comparisons and/or multicollinearity among measures while ignoring the latent constructs they may be measuring.

Objective: This study sought to examine the latent factor structure of a battery of 12-13 measures of domains mentioned above, used in a multicomponent behavioral intervention (The HABIT® program) for pwMCI and their partners. Read More

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September 2021

Psychosocial determinants of healthcare personnel's willingness to carry real-time locating system tags during daily inpatient care in hospital managing COVID-19 patients: insights from a mixed-methods analysis.

JAMIA Open 2021 Jul 5;4(3):ooaa072. Epub 2021 Feb 5.

Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore.

Objective: Real-time locating systems (RTLS) enable contact tracing and hand hygiene reminders, to improve hospital safety. Successful implementation requires healthcare personnel (HCP) to carry RTLS tags continuously. We assessed for determinants of HCP's willingness to use RTLS tags during routine inpatient care, and evaluated concerns using mixed-methods analysis. Read More

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Multilevel Approach for the Treatment of Giardiasis by Targeting Arginine Deiminase.

Int J Mol Sci 2021 Aug 31;22(17). Epub 2021 Aug 31.

Laboratorio de Biomoléculas y Salud Infantil, Instituto Nacional de Pediatría, Ciudad de Mexico 04530, Mexico.

Giardiasis represents a latent problem in public health due to the exceptionally pathogenic strategies of the parasite for evading the human immune system. Strains resistant to first-line drugs are also a challenge. Therefore, new antigiardial therapies are urgently needed. Read More

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[Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after "the Thanks to You Challenge" during the COVID-19 Pandemic].

J Korean Acad Nurs 2021 Aug;51(4):442-453

College of Nursing Science, Kyung Hee University, Seoul, Korea.

Purpose: This study was conducted to assess public awareness and policy challenges faced by practicing nurses.

Methods: After collecting nurse-related news articles published before and after 'the Thanks to You Challenge' campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles. Read More

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Shaping Dynamics With Multiple Populations in Low-Rank Recurrent Networks.

Neural Comput 2021 May;33(6):1572-1615

Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure. PSL University, 75005 Paris, France

An emerging paradigm proposes that neural computations can be understood at the level of dynamic systems that govern low-dimensional trajectories of collective neural activity. How the connectivity structure of a network determines the emergent dynamical system, however, remains to be clarified. Here we consider a novel class of models, gaussian-mixture, low-rank recurrent networks in which the rank of the connectivity matrix and the number of statistically defined populations are independent hyperparameters. Read More

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Confirmatory factor analysis of the Patient Health Questionnaire-9: A study amongst tuberculosis patients in the Free State province.

Authors:
Gladys Kigozi

S Afr J Infect Dis 2020 21;35(1):242. Epub 2020 Dec 21.

Department Center for Health Systems Research & Development, Faculty Humanities, Free State University, Bloemfontein, South Africa.

Background: There is growing evidence that depression is frequently comorbid with tuberculosis (TB) and is often associated with a decreased quality of life and poor treatment outcomes. The Patient Health Questionnaire (PHQ-9) is widely used to screen for depression in clinical settings in low-and middle-income countries. This study examined the construct validity and reliability of an interviewer-administered PHQ-9 in a sample of new TB patients in the Free State province of South Africa. Read More

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December 2020

Latent group detection in functional partially linear regression models.

Biometrics 2021 Sep 5. Epub 2021 Sep 5.

Department of Statistics, The George Washington University, Washington, DC, USA.

In this paper, we propose a functional partially linear regression model with latent group structures to accommodate the heterogeneous relationship between a scalar response and functional covariates. The proposed model is motivated by a salinity tolerance study of barley families, whose main objective is to detect salinity tolerant barley plants. Our model is flexible, allowing for heterogeneous functional coefficients while being efficient by pooling information within a group for estimation. Read More

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September 2021

Unsupervised Subspace Learning With Flexible Neighboring.

IEEE Trans Neural Netw Learn Syst 2021 Sep 3;PP. Epub 2021 Sep 3.

Graph-based subspace learning has been widely used in various applications as the rapid growth of data dimension, while the graph is constructed by affinity matrix of input data. However, it is difficult for these subspace learning methods to preserve the intrinsic local structure of data with the high-dimensional noise. To address this problem, we proposed a novel unsupervised dimensionality reduction approach named unsupervised subspace learning with flexible neighboring (USFN). Read More

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September 2021

Parametric UMAP Embeddings for Representation and Semisupervised Learning.

Neural Comput 2021 Aug 30:1-27. Epub 2021 Aug 30.

University of California San Diego, La Jolla, CA 92093, U.S.A.

UMAP is a nonparametric graph-based dimensionality reduction algorithm using applied Riemannian geometry and algebraic topology to find low-dimensional embeddings of structured data. The UMAP algorithm consists of two steps: (1) computing a graphical representation of a data set (fuzzy simplicial complex) and (2) through stochastic gradient descent, optimizing a low-dimensional embedding of the graph. Here, we extend the second step of UMAP to a parametric optimization over neural network weights, learning a parametric relationship between data and embedding. Read More

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Measuring Risk Tolerance across Domains: Scale Development and Validation.

J Pers Assess 2021 Sep 1:1-12. Epub 2021 Sep 1.

Research School of Psychology, Australian National University, Canberra, ACT, Australia.

Risk attitudes are of interest to researchers in many fields as they play a crucial role in our day-to-day decision-making. In this paper we develop a measure of risk attitudes-the Multi-Domain Risk Tolerance (MDRT) scale-that addresses some key shortcomings of popular self-report scales, such as the Domain-Specific Risk-Taking (DOSPERT) scale. We do this by clearly aligning the risk in the items with the particular domain of risk, reducing item ambiguity, and reducing the impact of prior knowledge. Read More

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September 2021

Capturing discrete latent structures: choose LDs over PCs.

Biostatistics 2021 Sep 1. Epub 2021 Sep 1.

Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA and Data Science and Statistical Computing, Genentech, Inc. South San Francisco, CA 94080, USA.

High-dimensional biological data collection across heterogeneous groups of samples has become increasingly common, creating high demand for dimensionality reduction techniques that capture underlying structure of the data. Discovering low-dimensional embeddings that describe the separation of any underlying discrete latent structure in data is an important motivation for applying these techniques since these latent classes can represent important sources of unwanted variability, such as batch effects, or interesting sources of signal such as unknown cell types. The features that define this discrete latent structure are often hard to identify in high-dimensional data. Read More

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September 2021

Grip strength from midlife as an indicator of later-life brain health and cognition: evidence from a British birth cohort.

BMC Geriatr 2021 08 31;21(1):475. Epub 2021 Aug 31.

MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom.

Background: Grip strength is an indicator of physical function with potential predictive value for health in ageing populations. We assessed whether trends in grip strength from midlife predicted later-life brain health and cognition.

Methods: 446 participants in an ongoing British birth cohort study, the National Survey of Health and Development (NSHD), had their maximum grip strength measured at ages 53, 60-64, and 69, and subsequently underwent neuroimaging as part of a neuroscience sub-study, referred to as "Insight 46", at age 69-71. Read More

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Comparative analysis of therapeutic effects between medium cut-off and high flux dialyzers using metabolomics and proteomics: exploratory, prospective study in hemodialysis.

Sci Rep 2021 Aug 30;11(1):17335. Epub 2021 Aug 30.

Department of Internal Medicine, Pusan National University Hospital, Busan, Korea.

In this single-center prospective study of 20 patients receiving maintenance hemodialysis (HD), we compared the therapeutic effects of medium cut-off (MCO) and high flux (HF) dialyzers using metabolomics and proteomics. A consecutive dialyzer membrane was used for 15-week study periods: 1st HF dialyzer, MCO dialyzer, 2nd HF dialyzer, for 5 weeks respectively. H-nuclear magnetic resonance was used to identify the metabolites and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis was used to identify proteins. Read More

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Data pre-processing using Neural Processes for Modelling Personalised Vital-Sign Time-Series Data.

IEEE J Biomed Health Inform 2021 Aug 30;PP. Epub 2021 Aug 30.

Clinical time-series data retrieved from electronic medical records are widely used to build predictive models of adverse events to support resource management. Such data is often sparse and irregularly-sampled, which makes it challenging to use many common machine learning methods. Missing values may be interpolated by carrying the last value forward, based on pre-specified physiological normality ranges, or through linear regression. Read More

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Psychometric Evaluation of the Health State Description Questionnaire in Chile: A Proposal for a Latent Variable Approach for Valuating Health States.

Value Health Reg Issues 2021 Aug 25;26:142-149. Epub 2021 Aug 25.

Centre of Global Mental Health, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, England, UK.

Background: A few instruments that identify and valuate health states are based on the International Classification of Functioning, Disability and Health States of the World Health Organization. One of them is the Health State Description (HSD) questionnaire first used in the World Health Survey (WHS) initiative (HSD-WHS), whose psychometric properties have not been evaluated in Chile. Additionally, the use of latent variables for the valuation process of health states has been scarcely investigated in the context of population health metrics. Read More

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Methodological and Conceptual Progresses in Studies on the Latent Tracks in PADC.

Polymers (Basel) 2021 Aug 10;13(16). Epub 2021 Aug 10.

Institut Pluridisiplinaire Hubert Curien, UMR 7178, CNRS, The University of Strasbourg, 67081 Strasbourg, France.

Modified structure along latent tracks and track formation process have been investigated in poly (allyl diglycol carbonate), PADC, which is well recognized as a sensitive etched track detector. This knowledge is essential to develop novel detectors with improved track registration property. The track structures of protons and heavy ions (He, C, Ne, Ar, Fe, Kr and Xe) have been examined by means of FT-IR spectrometry, covering the stopping power region between 1. Read More

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Latent Network Construction for Univariate Time Series Based on Variational Auto-Encode.

Entropy (Basel) 2021 Aug 18;23(8). Epub 2021 Aug 18.

School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang 330013, China.

Time series analysis has been an important branch of information processing, and the conversion of time series into complex networks provides a new means to understand and analyze time series. In this work, using Variational Auto-Encode (VAE), we explored the construction of latent networks for univariate time series. We first trained the VAE to obtain the space of latent probability distributions of the time series and then decomposed the multivariate Gaussian distribution into multiple univariate Gaussian distributions. Read More

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Computational Drug Repurposing for Antituberculosis Therapy: Discovery of Multi-Strain Inhibitors.

Antibiotics (Basel) 2021 Aug 19;10(8). Epub 2021 Aug 19.

Postgraduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa 58051-900, Brazil.

Tuberculosis remains the most afflicting infectious disease known by humankind, with one quarter of the population estimated to have it in the latent state. Discovering antituberculosis drugs is a challenging, complex, expensive, and time-consuming task. To overcome the substantial costs and accelerate drug discovery and development, drug repurposing has emerged as an attractive alternative to find new applications for "old" drugs and where computational approaches play an essential role by filtering the chemical space. Read More

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Multilabel Feature Selection With Constrained Latent Structure Shared Term.

IEEE Trans Neural Netw Learn Syst 2021 Aug 26;PP. Epub 2021 Aug 26.

High-dimensional multilabel data have increasingly emerged in many application areas, suffering from two noteworthy issues: instances with high-dimensional features and large-scale labels. Multilabel feature selection methods are widely studied to address the issues. Previous multilabel feature selection methods focus on exploring label correlations to guide the feature selection process, ignoring the impact of latent feature structure on label correlations. Read More

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