Napping is a multivariate sensory method in which participants physically place stimuli on a large sheet of paper and orient them so that the distance between pairs represents a measure of dissimilarity. The two-dimensional nature of the task may be a limitation to the ability of this and similar methodologies to recover information about complex stimuli. In the first investigation, eight simulated three-dimensional stimuli were created with two different levels for each attribute. Simulated napping experiments had groups of participants attend to two of the dimensions with different probabilities. Multiple factor analysis (an analytical multivariate statistical procedure that can be thought of as a principle components analysis on the individuals) and MDS-INDSCAL (a variation on multidimensional scaling that finds a common configuration through reducing a stress measure associated with lack of fit) recovered full dimensionality from these data, although MFA had trouble when attention was the most unbalanced. In the second experiment, a human napping experiment was designed using custom three-dimensional stimuli: shapes with two levels each of size, color, and shape attributes. This experiment confirmed the results of Experiment 1, as both MDS-INDSCAL and MFA analyses again recovered the full dimensionality of the stimuli.
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http://dx.doi.org/10.3758/s13414-011-0091-0 | DOI Listing |
J Hum Nutr Diet
February 2025
School of Life Sciences, Pontifical Catholic University of Campinas, Campinas, São Paulo, Brazil.
Introduction: Food addiction (FA) has been associated with emotional dysregulation, impulsivity and reduced quality of life, but its interrelationships remain underexplored. This cross-sectional descriptive study aimed to examine these connections using network analysis.
Methods: Data were collected from 1777 university students in Brazil and Canada through an online survey.
Environ Mol Mutagen
December 2024
Research and Development, Preclinical Safety, Sanofi, Industriepark Hoechst, Frankfurt am Main, Germany.
Genotoxicity is a critical determinant for assessing the safety of pharmaceutical drugs, their metabolites, and impurities. Among genotoxicity tests, mechanistic assays such as the MultiFlow® DNA damage assay (MFA) allows the investigations on mode of action (MoA) of DNA damage through four mechanistic markers recorded at two time points. Previous studies have shown that machine learning (ML) can enhance precision on classifying the MoA of genotoxicants.
View Article and Find Full Text PDFPLoS One
December 2024
IFB AdiposityDiseases, Leipzig University Medical Center, Leipzig, Germany.
Background: Maternal-foetal attachment (MFA) seems essential for adapting to motherhood and the healthy development of the child, with direct implications for clinical practice. It is often assessed using the Maternal Antenatal Attachment Scale (MAAS), which covers two dimensions: quality and intensity of attachment. However, studies including the MAAS presented missing or inadequate psychometric properties.
View Article and Find Full Text PDFResidential and non-residential buildings are a major contributor to human well-being. At the same time, buildings cause 30% of final energy use, 18% of greenhouse gas emissions (GHGE), and about 65% of material accumulation globally. With electrification and higher energy efficiency of buildings, material-related emissions gain relevance.
View Article and Find Full Text PDFMaterial flow analysis (MFA) is used to quantify and understand the life cycles of materials from production to end of use, which enables environmental, social, and economic impacts and interventions. MFA is challenging as available data are often limited and uncertain, leading to an under-determined system with an infinite number of possible stocks and flows values. Bayesian statistics is an effective way to address these challenges by principally incorporating domain knowledge, quantifying uncertainty in the data, and providing probabilities associated with model solutions.
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