Ecocantando: actividades lúdico-musicales para fortalecer la conciencia ambiental

En la actualidad, la contaminación de nuestro medio ambiente está acabando con la vida de muchas especies. Es contradictorio pensar que cada día los avances científicos y tecnológicos producto de la inteligencia humana,exploran y conquistan los más inimaginables campos del saber y sin embargo es el mismo hombre el responsable de la destrucción de nuestro planeta. La escuela es, por excelencia, la institución depositaria del saber humano. En ella los niños y las niñas, desde los primeros años de su vida, adquieren y desarrollan un conjunto de competencias que los convertirán en hombres y mujeres responsables de las grandes decisiones que transformarán el mundo. El ambiente escolar es propicio para despertar en los estudiantes la necesidad de velar por una convivencia pacífica y armónica con el medio ambiente. Las propuestas curriculares que abordan esta problemática deben constituirse en temas transversales que, desde las diversas áreas o asignaturas, estén orientados a propiciar en los estudiantes esa conciencia ambientalista que nos asegure personas responsables y conscientes de la vital necesidad que tiene el cuidado del planeta Tierra. Este programa emplea actividades musicales y lúdicas para abordar aspectos básicos que están relacionados con el medio ambiente, presentado de manera creativa y original las estrategias seleccionadas y cuyo único propósito es asumir una actitud favorable hacia la preservación y cuidado de todas las maravillas que el planeta tiene como son la fauna, flora, clima, atmósfera, ríos,mares, bosques y nosotros mismos

One-pot near-ambient temperature syntheses of aryl(difluoroenol) derivatives from trifluoroethanol

Difluoroalkenylzinc reagents prepared from 1-(2’-methoxy-ethoxymethoxy)-2,2,2-trifluoroethane and 1-(N,N-diethylcarbamoyloxy)-2,2,2-trifluoroethane at ice bath temperatures, underwent Negishi coupling with a range of aryl halides in a convenient one pot procedure. While significant differences between the enol acetal and carbamate reagents were revealed, the Negishi protocol compared very favourably with alternative coupling procedures in terms of overall yields from trifluoroethanol

Accuracy and interpretability trade-offs in machine learning applied to safer gambling

Responsible gambling is an area of research and industry which seeks to understand the pathways to harm from gambling and implement programmes to reduce or prevent harm that gambling might cause. There is a growing body of research that has used gambling behavioural data to model and predict harmful gambling, and the industry is showing increasing interest in technologies that can help gambling operators to better predict harm and prevent it through appropriate interventions. However, industry surveys and feedback clearly indicate that in order to enable wider adoption of such data-driven methods, industry and policy makers require a greater understanding of how machine learning methods make these predictions. In this paper, we make use of the TREPAN algorithm for extracting decision trees from Neural Networks and Random Forests. We present the first comparative evaluation of predictive performance and tree properties for extracted trees, which is also the first comparative evaluation of knowledge extraction for safer gambling. Results indicate that TREPAN extracts better performing trees than direct learning of decision trees from the data. Overall, trees extracted with TREPAN from different models offer a good compromise between prediction accuracy and interpretability. TREPAN can produce decision trees with extended tests rules of different forms, so that interpretability depends on multiple factors. We present detailed results and a discussion of the trade-offs with regard to performance and interpretability and use in the gambling industry

The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks

Responsible gambling is a field of study that involves supporting gamblers so as to reduce the harm that their gambling activity might cause. Recently in the literature, machine learning algorithms have been introduced as a way to predict potentially harmful gambling based on patterns of gambling behavior, such as trends in amounts wagered and the time spent gambling. In this paper, neural network models are analyzed to help predict the outcome of a partial proxy for harmful gambling behavior: when a gambler “self-excludes”, requesting a gambling operator to prevent them from accessing gambling opportunities. Drawing on survey and interview insights from industry and public officials as to the importance of interpretability, a variant of the knowledge extraction algorithm TREPAN is proposed which can produce compact, human-readable logic rules efficiently, given a neural network trained on gambling data. To the best of our knowledge, this paper reports the first industrial-strength application of knowledge extraction from neural networks, which otherwise are black-boxes unable to provide the explanatory insights which are crucially required in this area of application. We show that through knowledge extraction one can explore and validate the kinds of behavioral and demographic profiles that best predict self-exclusion, while developing a machine learning approach with greater potential for adoption by industry and treatment providers. Experimental results reported in this paper indicate that the rules extracted can achieve high fidelity to the trained neural network while maintaining competitive accuracy and providing useful insight to domain experts in responsible gambling

Clinical Characteristics of Idiopathic Granulomatous Mastitis in a Hispanic Border Population: A Case Series and Literature Review

Idiopathic granulomatous mastitis (IGM) is an autoimmune condition of the breast that is commonly encountered in women of non-white ethnicity such as Southeast Asians, Middle Easterners, and Hispanics. This condition often presents as a painful breast mass, and many patients undergo invasive diagnostic procedures or surgical excision, which can lead to disfiguring scars. Early recognition and prompt treatment with immunosuppressive medications can prevent invasive workups and management. Although previously thought to require an exclusively surgical approach, it now prompts interdisciplinary management. In this context, we present a case series of patients with IGM in a Hispanic population of South Texas

Digital Peer-Supported Self-Management Intervention Codesigned by People With Long COVID: Mixed Methods Proof-of-Concept Study.

BACKGROUND: There are around 1.3 million people in the United Kingdom with the devastating psychological, physical, and cognitive consequences of long COVID (LC). UK guidelines recommend that LC symptoms be managed pragmatically with holistic support for patients' biopsychosocial needs, including psychological, emotional, and physical health. Self-management strategies, such as pacing, prioritization, and goal setting, are vital for the self-management of many LC symptoms. OBJECTIVE: This paper describes the codevelopment and initial testing of a digital intervention combining peer support with positive psychology approaches for self-managing the physical, emotional, psychological, and cognitive challenges associated with LC. The objectives of this study were to (1) codesign an intervention with and for people with LC; (2) test the intervention and study methods; (3) measure changes in participant well-being, self-efficacy, fatigue, and loneliness; and (4) understand the types of self-management goals and strategies used by people with LC. METHODS: The study used a pre-post, mixed methods, pragmatic, uncontrolled design. Digital intervention content was codeveloped with a lived-experience group to meet the needs uncovered during the intervention development and logic mapping phase. The resulting 8-week digital intervention, Hope Programme for Long COVID, was attended by 47 participants, who completed pre- and postprogram measures of well-being, self-efficacy, fatigue, and loneliness. Goal-setting data were extracted from the digital platform at the end of the intervention. RESULTS: The recruitment rate (n=47, 83.9%) and follow-up rate (n=28, 59.6%) were encouraging. Positive mental well-being (mean difference 6.5, P<.001) and self-efficacy (mean difference 1.1, P=.009) improved from baseline to postcourse. All goals set by participants mapped onto the 5 goal-oriented domains in the taxonomy of everyday self-management strategies (TEDSS). The most frequent type of goals was related to activity strategies, followed by health behavior and internal strategies. CONCLUSIONS: The bespoke self-management intervention, Hope Programme for Long COVID, was well attended, and follow-up was encouraging. The sample characteristics largely mirrored those of the wider UK population with LC. Although not powered to detect statistically significant changes, the preliminary data show improvements in self-efficacy and positive mental well-being. Our next trial (ISRCTN: 11868601) will use a nonrandomized waitlist control design to further examine intervention efficacy

Love, rights and solidarity: studying children's participation using Honneth's theory of recognition

Recent attempts to theorize children’s participation have drawn on a wide range of ideas, concepts and models from political and social theory. The aim of this article is to explore the specific usefulness of Honneth’s theory of a ‘struggle for recognition’ in thinking about this area of practice. The article identifies what is distinctive about Honneth’s theory of recognition, and how it differs from other theories of recognition. It then considers the relevance of Honneth’s conceptual framework to the social position of children, including those who may be involved in a variety of ‘participatory’ activities. It looks at how useful Honneth’s ideas are in direct engagement with young people’s praxis, drawing on ethnographic research with members of a children and young people’s forum. The article concludes by reflecting on the implications of this theoretical approach and the further questions which it opens up for theories of participation and of adult–child relations more generally

A Merger Scenario for the Dynamics of Abell 665

We present new redshift measurements for 55 galaxies in the vicinity of the rich galaxy cluster Abell 665. When combined with results from the literature, we have good velocity measurements for a sample of 77 confirmed cluster members from which we derive the cluster's redshift z=0.1829 +/- 0.0005 and line-of-sight velocity dispersion of 1390 +/- 120 km/s. Our analysis of the kinematical and spatial data for the subset of galaxies located within the central 750 kpc reveals only subtle evidence for substructure and non-Gaussianity in the velocity distribution. We find that the brightest cluster member is not moving significantly relative to the other galaxies near the center of the cluster. On the other hand, our deep ROSAT high resolution image of A665 shows strong evidence for isophotal twisting and centroid variation, thereby confirming previous suggestions of significant substructure in the hot X-ray--emitting intracluster gas. In light of this evident substructure, we have compared the optical velocity data with N-body simulations of head-on cluster mergers. We find that a merger of two similar mass subclusters (mass ratios of 1:1 or 1:2) seen close to the time of core-crossing produces velocity distributions that are consistent with that observed.Comment: 30 pages and 7 figures. Accepted by the Astrophysical Journal Full resoultion figures 1 and 3 available in postscript at http://www.physics.rutgers.edu/~percy/A665paper.htm

Short-wave infrared barriode detectors using InGaAsSb absorption material lattice matched to GaSb

Short-wave infrared barriode detectors were grown by molecular beam epitaxy. An absorption layer composition of In0.28Ga0.72As0.25Sb0.75 allowed for lattice matching to GaSb and cut-off wavelengths of 2.9 μm at 250 K and 3.0 μm at room temperature. Arrhenius plots of the dark current density showed diffusion limited dark currents approaching those expected for optimized HgCdTe-based detectors. Specific detectivity figures of around 7×1010 Jones and 1×1010 Jones were calculated, for 240 K and room temperature, respectively. Significantly, these devices could support focal plane arrays working at higher operating temperatures