Validation of the Spanish version of the Childhood Executive Functioning Inventory (CHEXI) in 4-5 year-old children

Background: The Childhood Executive Functioning Inventory (CHEXI) was designed to identify EF deficits in daily life contexts. The aim of the present study was to validate the Spanish version of the CHEXI in 4-5-year-old children. Method: Parents’ ratings of the CHEXI and laboratory tests of EF were investigated in two large samples of 445 children aged 4 years (196 girls, 249 boys) and 459 children aged 5 years (208 girls, 251 boys). CHEXI ratings were collected again after one-year. Results: The two-factor structure of the CHEXI (i.e., Working Memory and Inhibition) was replicated, showing high internal consistency and temporal stability. The 4-year-olds were reported to have higher EF deficits than 5-year-olds have. Boys were rated as having higher EF deficits than girls were. However, gender differences were not significant contrasting performance on EF tasks. Finally, associations between CHEXI ratings and EF tests were weak, suggesting that EF tests and EF ratings capture different aspects of EF. Conclusions: The Spanish CHEXI provides a suitable instrument to assess EF in 4-5-year-old children. Contexto: El Childhood Executive Functioning Inventory (CHEXI) se diseñó para detectar déficit de Funciones Ejecutivas (FE) en contextos de la vida diaria. El propósito del presente estudio era validar la versión española del CHEXI para niños de 4 y 5 años. Método: Se obtuvieron las valoraciones de los padres y las puntuaciones en test de laboratorio en una muestra de 445 niños de 4 años (196 niñas, 249niños) y otra de 459 niños de 5 años (208 niñas, 251 niños). Un año más tarde se volvieron a recoger las valoraciones de los padres en CHEXI. Resultados: Se replicó la estructura de dos factores de CHEXI (Memoria de Trabajo e Inhibición), obteniendo una alta consistencia interna y estabilidad temporal. Los niños de 4 años eran valorados con mayor déficit en FE que los niños de 5 años. Los niños alcanzaban puntuaciones más elevadas de déficit de FE. Sin embargo, no aparecieron diferencias significativas de género en las pruebas conductuales. Finalmente, se encontró una baja asociación entre las valoraciones de CHEXI y las puntuaciones de las pruebas conductuales. Este resultado sugiere que los inventarios y las medidas conductuales evalúan diferentes aspectos de las FE. Conclusiones: La versión española de CHEXI ofrece un instrumento válido para evaluar las FE en niños de 4 y 5 años.

A New Method for Estimating Starspot Lifetimes Based on Autocorrelation Functions

We present a method that utilizes autocorrelation functions from long-term precision broadband differential light curves to estimate the average lifetimes of starspot groups for two large samples of Kepler stars: stars with and without previously known rotation periods. Our method is calibrated by comparing the strengths of the first few normalized autocorrelation peaks using ensembles of models that have various starspot lifetimes. We find that we must mix models of short and long lifetimes together (in heuristically determined ratios) to align the models with the Kepler data. Our fundamental result is that short starspot-group lifetimes (one to four rotations) are implied when the first normalized peak is weaker than about 0.4, long lifetimes (15 or greater) are implied when it is greater than about 0.7, and in between are the intermediate cases. Rotational lifetimes can be converted to physical lifetimes if the rotation period is known. Stars with shorter rotation periods tend to have longer rotational (but not physical) spot lifetimes, and cooler stars tend to have longer physical spot lifetimes than warmer stars with the same rotation period. The distributions of the physical lifetimes are log-normal for both samples and generally longer in the first sample. The shorter lifetimes in the stars without known periods probably explain why their periods are difficult to measure. Some stars exhibit longer than average physical starspot lifetimes; their percentage drops with increasing temperature from nearly half at 3000 K to nearly zero for hotter than 6000 K.

CP violation in charm

The existence of CP violation in the decays of strange and beauty mesons is very well established experimentally. On the contrary, CP violation in the decays of charmed particles has been elusive for a long time and has been observed for the first time in 2019 by the LHCb experiment. Since then several studies have been performed in the charm sector. During the LHC Run 1 and Run 2, the LHCb collaboration has collected large samples containing charm hadron decays, on a scale never seen before. Collected data enabled physicists to obtain several new results, most of which surpassed previous results and became new world’s best measurements. Presently the LHCb spectrometer is being upgraded to enhance readout system, improve subdetector components and increase integrated luminosity to 50 fb−1 by the end of Run 4.

Direct comparison of the effects of liraglutide and dulaglutide on the dynamics of scales and markers of hepatic fibrosis

Objective. Comparison of the effects of liraglutide and dulaglutide on the dynamics of scales and markers of hepatic fibrosis.Materials and methods. 35 patients with NAFLD were included in the study and received liraglutide 1.8 mg or dulaglutide 1.5 mg once daily for 6 months.Results. Body weight and glycated hemoglobin (HbA1C) decreased significantly and comparable after 6 months of treatment in both groups. Serum aspartate aminotransferase (AST) levels decreased only in the dulaglutide group. The decrease in the AST level in the dulaglutide group was from 31.9 ± 26.8 to 30.8 ± 10.6 U / L (p = 0.04). The dynamics of the risk of fibrosis reached statistical significance only when assessed on the FIB-4 scale in the liraglutide group when comparing the baseline values and values after 6 months of treatment — 1.18 ± 0.51 and 0.97 ± 0.40, respectively (p = 0.022). In the dulaglutide group, there was also an insignificant positive dynamics of 1.31 ± 0.53 and 1.11 ± 0.23 (p = 0.865), which can be explained by the minimal severity of changes at baseline.Conclusions. The study demonstrated comparable effects of liraglutide and dulaglutide on metabolic parameters and, at the same time, the advantage of liraglutide in influencing the dynamics of the risk of fibrosis, assessed on the FIB-4 scale. To unequivocally confirm the benefits of liraglutide in the treatment of patients with NAFLD, randomized prospective comparative studies of various aGPP1 on large samples of patients with different stages of NAFLD are needed.

An Exponential Endogenous Switching Regression with Correlated Random Coefficients

This paper presents a method for estimating the average treatment effects (ATE) of an exponential endogenous switching model where the coefficients of covariates in the structural equation are random and correlated with the binary treatment variable. The estimating equations are derived under some mild identifying assumptions. We find that the ATE is identified, although each coefficient in the structural model may not be. Tests assessing the endogeneity of treatment and for model selection are provided. Monte Carlo simulations show that, in large samples, the proposed estimator has a smaller bias and a larger variance than the methods that do not take the random coefficients into account. This is applied to health insurance data of Oregon.

Happiness Measurability and Interpersonal Comparability

Simple ways to improve the accuracy and interpersonal and intertemporal comparability of happiness measurement include using happiness instead of life satisfaction (or other concepts), pinning down the dividing line of the zero amount of net happiness, using an interpersonally valid unit based on the just perceivable increment of happiness, and the complementary use of this method for small samples and the traditional methods for large samples.

Bayesian Fitting of Multi-Gaussian Expansion Models to Galaxy Images

Fitting parameterized models to images of galaxies has become the standard for measuring galaxy morphology. This forward-modeling technique allows one to account for the point-spread function to effectively study semi-resolved galaxies. However, using a specific parameterization for a galaxy’s surface brightness profile can bias measurements if it is not an accurate representation. Furthermore, it can be difficult to assess systematic errors in parameterized profiles. To overcome these issues we employ the Multi-Gaussian expansion (MGE) method of representing a galaxy’s profile together with a Bayesian framework for fitting images. MGE flexibly represents a galaxy’s profile using a series of Gaussians. We introduce a novel Bayesian inference approach that uses pre-rendered Gaussian components, which greatly speeds up computation time and makes it feasible to run the fitting code on large samples of galaxies. We demonstrate our method with a series of validation tests. By injecting galaxies, with properties similar to those observed at z ∼ 1.5, into deep Hubble Space Telescope observations we show that it can accurately recover total fluxes and effective radii of realistic galaxies. Additionally we use degraded images of local galaxies to show that our method can recover realistic galaxy surface brightness and color profiles. Our implementation is available in an open source python package imcascade, which contains all methods needed for the preparation of images, fitting, and analysis of results.

Moves to age-restricted housing and functional health trajectories among independent living older adults

Where independent living older adults live has been found to have strong links with disability. For example, older adults living in age-restricted housing contexts (e.g., retirement communities) have been found to have worse functional health compared to those living in non-age-restricted settings. Theories and empirical research demonstrate positive and negative aspects of living in age-restricted housing. Recent availability of population-level longitudinal data with sufficiently large samples has made examination of this heterogeneity possible. In this study we examine whether a move to age-restricted housing is associated with functional health trajectories and whether age at time of move moderates this link. We examine these questions using nine waves of longitudinal data from a representative sample of 8,687 U.S. adults age 65 and older from the National Health and Aging Trends Study. Spline-like growth curve models were estimated to determine the intercept, slope prior to move to age-restricted housing, and slope after the move. We also tested whether these processes are conditional on age at time of move. Results indicate that regardless of age all respondents experienced a decline in functional health following a move to age-restricted housing. However, there is variation in the steepness of this decline by age at time of the move. People who move to age-restricted housing earlier experience a less steep decline in functional health post-move compared to those who move later. Findings suggest moving to age-restricted housing earlier may enable older adults to utilize resources often available in these settings to prevent steep health declines.

Imbalanced Fault Identification via Embedding-augmented Gaussian Prototype Network with Meta-Learning Perspective

In practical engineering, the number of acquired fault samples from different categories might be in great difference due to the little probability of key equipment happening to malfunctioned. When training the imbalanced data, more methods focus on balancing the number of samples between different categories which may be time-consuming and easy to over-fit. To address this problem, we proposed Embedding-augmented Gaussian Prototype Network (EGPN) which applied a new training mechanism from the perspective of meta-learning. We only train the categories with large samples and the remaining categories only appeared in the testing process to calculate untrained prototypes. EGPN includes a feature embedding augmented module, weighted prototype module and metric module. Firstly, ordinary convolution and dilated convolution are mixed to capture different frequency bands simultaneously, and residual-attention module is added to highlight key features and suppress unimportant features. Different prototypes are calculated by weighting to the embedding vectors through Gaussian covariance matrix. Finally, the classification is taken according to the modified distance. The experiments in two datasets indicating that the proposed method can effectively recognize the untrained categories with only a few samples using as the prototypes, which can tackle the problem of identifying imbalanced fault data efficiently.