The impact of cultural dissonance and acculturation orientations on immigrant students' academic performance

Indexación: Scopus; Scielo; Redalyc.Prior research has documented meaningful differences between school performance of immigrant and native students. Multicultural education has been associated with academic failure of foreign students. e aim of this study was to examine the impact of a set of psychosocial variables on the perceived academic achievement of first generation immigrant adolescents from public secondary schools in Northern Spain. Results showed that 46% of the variability in foreign students’ perceived academic performance was explained by home-school cultural dissonance. We also explored the impact of acculturation orientation to separation, perception of discrimination from teachers, school adjustment, and psychological well-being in academic performance. Any multicultural education context should take into account psychosocial adjustment, given its influence on academic performance of all studentsSe han hallado diferencias significativas entre el rendimiento académico de los inmigrantes y el de los estudiantes nativos. Sin embargo, hay una escasa evidencia acerca de los aspectos psicosociales de este fenómeno. El objetivo de este estudio fue examinar el impacto de un conjunto de variables psicosociales: disonancia cultural y orientaciones de aculturación en el rendimiento académico percibido de adolescentes inmigrantes de primera generación de centros de Educación Secundaria en el Norte de España. Los resultados mostraron que alrededor del 46% de la variabilidad en el rendimiento era explicada por la disonancia cultural entre escuela y hogar. Cualquier contexto de educación multicultural ha de tomar en consideración el ajuste psicosocial, dada su influencia en el rendimiento académico de los estudiantes.http://www.redalyc.org/jatsRepo/647/64753989003/index.htm

Hydrogeological vulnerability assessment in urban systems, Spain

Resumo alargado da comunicação oral apresentada na 6th International Conference on Environmental Science and Development.The main objective of this research is the study of vulnerability to pollution in an unconfined karstic aquifer system. Aquifer vulnerability assessment to define critical zones of contamination is a core issue an effective monitoring network for groundwater management. Vulnerability integration is addressed for risk valuation and risk–benefit considerations, focusing the requirements of the European Community’s Water and Groundwater Directives. The development of an integrated vulnerability assessment methodology can be useful for the effective management and protection of this valuable freshwater source. The research insights suggest that an effective governance is mandatory as the future highway, the prison and the airport are overlaying the aquifer’s most vulnerable areas

Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation

The counterfactual distribution models the effect of the treatment in the untreated group. While most of the work focuses on the expected values of the treatment effect, one may be interested in the whole counterfactual distribution or other quantities associated to it. Building on the framework of Bayesian conditional mean embeddings, we propose a Bayesian approach for modeling the counterfactual distribution, which leads to quantifying the epistemic uncertainty about the distribution. The framework naturally extends to the setting where one observes multiple treatment effects (e.g. an intermediate effect after an interim period, and an ultimate treatment effect which is of main interest) and allows for additionally modelling uncertainty about the relationship of these effects. For such goal, we present three novel Bayesian methods to estimate the expectation of the ultimate treatment effect, when only noisy samples of the dependence between intermediate and ultimate effects are provided. These methods differ on the source of uncertainty considered and allow for combining two sources of data. Moreover, we generalize these ideas to the off-policy evaluation framework, which can be seen as an extension of the counterfactual estimation problem. We empirically explore the calibration of the algorithms in two different experimental settings which require data fusion, and illustrate the value of considering the uncertainty stemming from the two sources of data

Counterfactual Density Estimation using Kernel Stein Discrepancies

Causal effects are usually studied in terms of the means of counterfactual distributions, which may be insufficient in many scenarios. Given a class of densities known up to normalizing constants, we propose to model counterfactual distributions by minimizing kernel Stein discrepancies in a doubly robust manner. This enables the estimation of counterfactuals over large classes of distributions while exploiting the desired double robustness. We present a theoretical analysis of the proposed estimator, providing sufficient conditions for consistency and asymptotic normality, as well as an examination of its empirical performance

Microarray analysis of autoimmune diseases by machine learning procedures

—Microarray-based global gene expression profiling, with the use of sophisticated statistical algorithms is providing new insights into the pathogenesis of autoimmune diseases. We have applied a novel statistical technique for gene selection based on machine learning approaches to analyze microarray expression data gathered from patients with systemic lupus erythematosus (SLE) and primary antiphospholipid syndrome (PAPS), two autoimmune diseases of unknown genetic origin that share many common features. The methodology included a combination of three data discretization policies, a consensus gene selection method, and a multivariate correlation measurement. A set of 150 genes was found to discriminate SLE and PAPS patients from healthy individuals. Statistical validations demonstrate the relevance of this gene set from an univariate and multivariate perspective. Moreover, functional characterization of these genes identified an interferon-regulated gene signature, consistent with previous reports. It also revealed the existence of other regulatory pathways, including those regulated by PTEN, TNF, and BCL-2, which are altered in SLE and PAPS. Remarkably, a significant number of these genes carry E2F binding motifs in their promoters, projecting a role for E2F in the regulation of autoimmunity

The 2HWC HAWC Observatory Gamma Ray Catalog

We present the first catalog of TeV gamma-ray sources realized with the recently completed High Altitude Water Cherenkov Observatory (HAWC). It is the most sensitive wide field-of-view TeV telescope currently in operation, with a 1-year survey sensitivity of ~5-10% of the flux of the Crab Nebula. With an instantaneous field of view >1.5 sr and >90% duty cycle, it continuously surveys and monitors the sky for gamma ray energies between hundreds GeV and tens of TeV. HAWC is located in Mexico at a latitude of 19 degree North and was completed in March 2015. Here, we present the 2HWC catalog, which is the result of the first source search realized with the complete HAWC detector. Realized with 507 days of data and represents the most sensitive TeV survey to date for such a large fraction of the sky. A total of 39 sources were detected, with an expected contamination of 0.5 due to background fluctuation. Out of these sources, 16 are more than one degree away from any previously reported TeV source. The source list, including the position measurement, spectrum measurement, and uncertainties, is reported. Seven of the detected sources may be associated with pulsar wind nebulae, two with supernova remnants, two with blazars, and the remaining 23 have no firm identification yet.Comment: Submitted 2017/02/09 to the Astrophysical Journa

An Efficient Doubly-Robust Test for the Kernel Treatment Effect

The average treatment effect, which is the difference in expectation of the counterfactuals, is probably the most popular target effect in causal inference with binary treatments. However, treatments may have effects beyond the mean, for instance decreasing or increasing the variance. We propose a new kernel-based test for distributional effects of the treatment. It is, to the best of our knowledge, the first kernel-based, doubly-robust test with provably valid type-I error. Furthermore, our proposed algorithm is efficient, avoiding the use of permutations

The Sensitivity of HAWC to High-Mass Dark Matter Annihilations

The High Altitude Water Cherenkov (HAWC) observatory is a wide field-of-view detector sensitive to gamma rays of 100 GeV to a few hundred TeV. Located in central Mexico at 19 degrees North latitude and 4100 m above sea level, HAWC will observe gamma rays and cosmic rays with an array of water Cherenkov detectors. The full HAWC array is scheduled to be operational in Spring 2015. In this paper, we study the HAWC sensitivity to the gamma-ray signatures of high-mass (multi- TeV) dark matter annihilation. The HAWC observatory will be sensitive to diverse searches for dark matter annihilation, including annihilation from extended dark matter sources, the diffuse gamma-ray emission from dark matter annihilation, and gamma-ray emission from non-luminous dark matter subhalos. Here we consider the HAWC sensitivity to a subset of these sources, including dwarf galaxies, the M31 galaxy, the Virgo cluster, and the Galactic center. We simulate the HAWC response to gamma rays from these sources in several well-motivated dark matter annihilation channels. If no gamma-ray excess is observed, we show the limits HAWC can place on the dark matter cross-section from these sources. In particular, in the case of dark matter annihilation into gauge bosons, HAWC will be able to detect a narrow range of dark matter masses to cross-sections below thermal. HAWC should also be sensitive to non-thermal cross-sections for masses up to nearly 1000 TeV. The constraints placed by HAWC on the dark matter cross-section from known sources should be competitive with current limits in the mass range where HAWC has similar sensitivity. HAWC can additionally explore higher dark matter masses than are currently constrained.Comment: 15 pages, 4 figures, version to be published in PR