Propuesta de intervención basada en Mindfulness para personas diagnosticadas con trastornos específicos del aprendizaje Mindfulness-based intervention for specific learning disabilities

Propuesta de intervención basada en ejercicios de mindfulness para mejorar los niveles de bienestar del alumnado con Dificultades Específicas del Aprendizaje (DEA). Las personas con DEA presentan una serie de características socio-emocionales que afecta tanto a su calidad de vida como a su rendimiento escolar. La práctica regular y continua de ejercicios de atención plena o mindfulness ha sido probado que tiene múltiples beneficios sobre la salud mental y el bienestar general que experimentan las personas. En esta propuesta de intervención se enseña al alumnado diferentes ejercicios de mindfulness o atención plena con la intención de mejorar su calidad de vida.This a mindfulness-based intervention with the goal to improve student’s well-being with Specific Learning Disabilities (SLD). People with SLD usually have negative socioemotional consequences due to their diagnosis. The practice of mindfulness exercises has been suggested to provoque positive effects on student’s well-being. This intervention teaches students diferent mindfulness exercises that they can practice for a better wellbeing and improve of academic achievement

Alveolar Dynamics and Beyond – The Importance of Surfactant Protein C and Cholesterol in Lung Homeostasis and Fibrosis

Surfactant protein C (SP-C) is an important player in enhancing the interfacial adsorption of lung surfactant lipid films to the alveolar air-liquid interface. Doing so, surface tension drops down enough to stabilize alveoli and the lung, reducing the work of breathing. In addition, it has been shown that SP-C counteracts the deleterious effect of high amounts of cholesterol in the surfactant lipid films. On its side, cholesterol is a wellknown modulator of the biophysical properties of biological membranes and it has been proven that it activates the inflammasome pathways in the lung. Even though the molecular mechanism is not known, there are evidences suggesting that these two molecules may interplay with each other in order to keep the proper function of the lung. This review focuses in the role of SP-C and cholesterol in the development of lung fibrosis and the potential pathways in which impairment of both molecules leads to aberrant lung repair, and therefore impaired alveolar dynamics. From molecular to cellular mechanisms to evidences in animal models and human diseases. The evidences revised here highlight a potential SP-C/cholesterol axis as target for the treatment of lung fibrosis

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

GETSEL: Gallery Entropy for Template SElection on Large datasets

The ability of a biometric system to reliably recognize individuals, who were registered for authentication as well as security purposes, significantly depends on the kind and amount of variation that the exploited biometric trait may undergo from one acquisition to another. Those variations may be due both to factors related to acquisition devices, e.g. different resolutions, or to different environment settings, e.g., illumination, or to modification of the trait appearance, e.g., pose and expression of the face. One of the straightforward strategies to address issues related to changes in biometric features is to store more templates for the same person, in order to increase the chances to identify her. The problem arises to choose the templates to store in a way which actually achieves better performance, while avoiding flooding the system with an excessively huge gallery. This work proposes an approach for the selection of the best templates for face recognition, which is based on a notion of gallery entropy, and can be also used for large datasets. Though relying on a clustering process, its main achievement is to automatically derive the best number of clusters/prototypes per subject without requiring to fixing it in advance. Comparative tests with existing approaches show that it is a very promising solution

GETSEL: Gallery Entropy for Template SElection on Large datasets

The ability of a biometric system to reliably recognize individuals, who were registered for authentication as well as security purposes, significantly depends on the kind and amount of variation that the exploited biometric trait may undergo from one acquisition to another. Those variations may be due both to factors related to acquisition devices, e.g. different resolutions, or to different environment settings, e.g., illumination, or to modification of the trait appearance, e.g., pose and expression of the face. One of the straightforward strategies to address issues related to changes in biometric features is to store more templates for the same person, in order to increase the chances to identify her. The problem arises to choose the templates to store in a way which actually achieves better performance, while avoiding flooding the system with an excessively huge gallery. This work proposes an approach for the selection of the best templates for face recognition, which is based on a notion of gallery entropy, and can be also used for large datasets. Though relying on a clustering process, its main achievement is to automatically derive the best number of clusters/prototypes per subject without requiring to fixing it in advance. Comparative tests with existing approaches show that it is a very promising solution

Pertinencia del uso de las características espectrales del hábitat como predictor de la estructura en comunidades de aves de un humedal de Cuba

La teledetección es una herramienta emergente en ecología, pero de uso limitado en países neotropicales. En este estudio probamos la relación entre las variables de las comunidades de aves y variables espectrales en un humedal de Cuba. Determinamos la composición y estructura de la ornitofauna en tres localidades del Gran Humedal del Norte de Ciego de Ávila y su relación con las variables espectrales. Realizamos 78 transectos y determinamos la abundancia relativa, riqueza, el índice de Brillouin, de Simpson y la composición en gremios. Sobre una imagen satelital del Landsat 7 medimos los índices de humedad, verdor, diversidad de arbustos vivos, índice normalizado de diferencia de agua y ndvi. Realizamos análisis multivariados para estimar la similitud entre formaciones vegetales a partir de variables comunitarias y espectrales. Para probar si existía correlación entre las variables realizamos una prueba de Mantel y una correlación entre los valores del primer componente de los Análisis de Componentes Principales a partir de las variables comunitarias y espectrales. Contabilizamos 1,298 aves pertenecientes a 73 especies, 33 familias y14 órdenes. Cada formación vegetal tuvo una combinación propia de sus índices espectrales. La vegetación costera se diferenció del resto de las formaciones vegetales, y la demás vegetación tuvo superposición. No encontramos una relación significativa entre las variables comunitarias de las aves y espectrales. Esto puede deberse a una selección de índices poco informativos. Aun así, el método puede ser eficiente como complemento para el monitoreo de la biodiversidad y válido como recurso metodológico con fines de conservación