La exposición artística como mediación pedagógica y social para el reconocimiento de la diversidad cultural

RESUMEN: Este informe de investigación responde a la pregunta ¿De qué manera la exposición como mediación pedagógica y social desde el área de educación artística, contribuye al reconocimiento de la diversidad cultural y así mejorar las relaciones interpersonales de los estudiantes? Esta es una investigación desde el paradigma cualitativo y con un enfoque de teorías críticas. Los instrumentos de recolección de datos fueron el diario de campo, la encuesta, reflexiones escritas de los estudiantes y un diario de visitas de la exposición. Realicé esta investigación en la Institución Educativa Lusitania Paz de Colombia con los estudiantes del grado noveno. Las tres fases: Deconstrucción, Reconstrucción y Transformación de la práctica pedagógica en la Investigación-acción educativa son las mismas que utilizo para la presentación de este informe. A través de este trabajo investigativo encuentro no solo transformación de mi práctica pedagógica, si no también de mi sensibilidad como maestro que avanza en la enseñanza con un acercamiento más visible hacia el componente humano de mis estudiantes y del contexto; encuentro que los contenidos de la educación artística me sirven como medio para acercarme a explorar y visibilizar con los estudiantes sus realidades y percepciones del mundo, de “los otros” y de lo que tienen en común, promoviendo quizás un enfoque intercultural en la educación artística.ABSTRACT: This research answer the question: How does artistic exhibition as a pedagogical and social mediation from the area of arts education contributes to the recognition of cultural diversity and thus improve the interpersonal relationships of students? The research is under a qualitative paradigm with a focus on critical theories. The data collection instruments were the field diary, the survey, the written reflections of students and a diary of the visits to the artistic exhibition. I carried out this research in the Lusitania Paz de Colombia Educational Institution with ninth-grade learners. The three phases: Deconstruction, Reconstruction and Transformation of the pedagogical practice in the Educational Action Research are the same ones that I use for the presentation of this report. Through this research I find, not only transformation of my pedagogical practice, but also my sensitivity as a teacher that advances in teaching with a more visible approach towards the human component of my students and the context; I find that the contents of artistic education serve as a means to approach me to explore and make visible to students their realities and perceptions of the world of ""others"" and what they have in common, perhaps promoting an intercultural approach in artistic education

Protein Stability Perturbation Contributes to the Loss of Function in Haploinsufficient Genes

Missense variants are among the most studied genome modifications as disease biomarkers. It has been shown that the \u201cperturbation\u201d of the protein stability upon a missense variant (in terms of absolute \u394\u394G value, i.e., |\u394\u394G|) has a significant, but not predictive, correlation with the pathogenicity of that variant. However, here we show that this correlation becomes significantly amplified in haploinsufficient genes. Moreover, the enrichment of pathogenic variants increases at the increasing protein stability perturbation value. These findings suggest that protein stability perturbation might be considered as a potential cofactor in diseases associated with haploinsufficient genes reporting missense variants

The KM3NeT data acquisition system - Status and evolution

In this contribution, we present the data acquisition system system of the KM3NeT neutrino telescopes, ARCA and ORCA, already operating while under construction at the bottom of the Mediterranean Sea. The DAQ system implements a modular and scalable hardware-triggerless streaming readout of the optical modules in the telescopes. Handling a raw incoming throughput up to hundreds of Gbps, it is integrated with the online alert system of the KM3NeT Multimessenger program. The system will evolve according to a new design, currently under validation, which will grant the extension of the telescope to the aimed cubic kilometer scale

Tuber mesentericum and Tuber aestivum Truffles: New Insights Based on Morphological and Phylogenetic Analyses

Tuber aestivum, one of the most sought out and marketed truffle species in the world, is morphologically similar to Tuber mesentericum, which is only locally appreciated in south Italy and north-east France. Because T. aestivum and T. mesentericum have very similar ascocarp features, and collection may occur in similar environments and periods, these two species are frequently mistaken for one another. In this study, 43 T. aestivum and T. mesentericum ascocarps were collected in Italy for morphological and molecular characterization. The morphological and aromatic characteristics of the fresh ascocarps were compared with their spore morphology. Afterwards, we amplified and sequenced the elongation factor 1-α (EF1α) locus and built maximum likelihood trees to assess phylogenetic similarities between the two species. Tuber aestivum and T. mesentericum sequences cluster into different clades, with T. mesentericum sequences divided into three different sub-clades. According to their morphological features, three samples (T7, T8 and T12) were classified as T. mesentericum. However, when fresh, these ascocarps lacked the typical phenolic aromatic note. These specimens fall into the sub-clade III of the T. mesentericum phylogeny, which has the lowest genetic distance from the T. aestivum clade

INFN Cloud Users and Projects Support, Training and Communication

Having a long tradition in state-of-the-art distributed IT technologies, in the last couple of years INFN made available to its users “INFN Cloud”: a cloud infrastructure and related services portfolio dedicated to the scientific communities supported by INFN. Given the distributed nature of the infrastructure as well as the considerable number of technical solutions provided to the INFN users, it is important to have a reliable user support service aimed to properly interact both with INFN Cloud users and administrators. As an added value, proper training activities have been defined and differentiated to different types of users and the training courses are integrated with a rich set of user guides and technical documentation. In this article, an overview of the INFN Cloud, its evolution to DataCloud project, and the support and training activities will be provided and presented

Social cognition in people with schizophrenia: A cluster-analytic approach

Background The study aimed to subtype patients with schizophrenia on the basis of social cognition (SC), and to identify cut-offs that best discriminate among subtypes in 809 out-patients recruited in the context of the Italian Network for Research on Psychoses. Method A two-step cluster analysis of The Awareness of Social Inference Test (TASIT), the Facial Emotion Identification Test and Mayer-Salovey-Caruso Emotional Intelligence Test scores was performed. Classification and regression tree analysis was used to identify the cut-offs of variables that best discriminated among clusters. Results We identified three clusters, characterized by unimpaired (42%), impaired (50.4%) and very impaired (7.5%) SC. Three theory-of-mind domains were more important for the cluster definition as compared with emotion perception and emotional intelligence. Patients more able to understand simple sarcasm (14 for TASIT-SS) were very likely to belong to the unimpaired SC cluster. Compared with patients in the impaired SC cluster, those in the very impaired SC cluster performed significantly worse in lie scenes (TASIT-LI <10), but not in simple sarcasm. Moreover, functioning, neurocognition, disorganization and SC had a linear relationship across the three clusters, while positive symptoms were significantly lower in patients with unimpaired SC as compared with patients with impaired and very impaired SC. On the other hand, negative symptoms were highest in patients with impaired levels of SC. Conclusions If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Towards a Muon Collider

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.Comment: 118 pages, 103 figure