Artes marciales japonesas: prácticas corporales representativas de su identidad cultural

La implantación y difusión de las artes marciales japonesas en Occidente supuso la importación de prácticas socioculturales privadas de las premisas de su contexto de origen. ¿Cómo afrontar estas prácticas que son ajenas a nuestra identidad cultural? Una interpretación estricta exige entenderlas como prácticas corporales con una idiosincrasia cultural, caracterizadas por incorporar una experiencia vivencial en la que el cuerpo ocupa un lugar preeminente. Su enseñanza y aprendizaje se establecen a través de un sistema triangular integrado por una esencia espiritual, una forma técnica y una estructura física (sin-gi-tai), que se inserta en un proceso singular (shu-ha-ri)

The anatomy of urban social networks and its implications in the searchability problem

The appearance of large geolocated communication datasets has recently increased our understanding of how social networks relate to their physical space. However, many recurrently reported properties, such as the spatial clustering of network communities, have not yet been systematically tested at different scales. In this work we analyze the social network structure of over 25 million phone users from three countries at three different scales: country, provinces and cities. We consistently find that this last urban scenario presents significant differences to common knowledge about social networks. First, the emergence of a giant component in the network seems to be controlled by whether or not the network spans over the entire urban border, almost independently of the population or geographic extension of the city. Second, urban communities are much less geographically clustered than expected. These two findings shed new light on the widely-studied searchability in self-organized networks. By exhaustive simulation of decentralized search strategies we conclude that urban networks are searchable not through geographical proximity as their country-wide counterparts, but through an homophily-driven community structure

Outcomes and endpoints of relevance in gynecologic cancer clinical trials.

Drug development is paramount to improve outcomes in patients with gynecologic cancers. A randomized clinical trial should measure whether a clinically relevant improvement is detected with the new intervention compared with the standard of care, using reproductible and appropriate endpoints. Clinically meaningful improvements in overall survival and/or quality of life (QoL) are the gold standards to measure benefit of new therapeutic strategies. Alternative endpoints, such as progression-free survival, provide an earlier measure of the effect of the new therapeutic drug, and are not confounded by the effect of subsequent lines of therapy. Yet, its surrogacy with improved overall survival or QoL is unclear in gynecologic malignancies. Of relevance to studies assessing maintenance strategies are other time-to-event endpoints, such as progression-free survival two and time to second subsequent treatment, which provide valuable information on the disease control in the longer term. Translational and biomarker studies are increasingly being incorporated into gynecologic oncology clinical trials, as they may allow understanding of the biology of the disease, resistance mechanisms, and enable a better selection of patients who might benefit from the new therapeutic strategy. Globally, the endpoint selection of a clinical trial will differ according to the type of study, population, disease setting, and type of therapeutic strategy. This review provides an overview of primary and secondary endpoint selection of relevance for gynecologic oncology clinical trials

Computational dosimetry of a simulated combined standard X-rays and BNCT treatment

There has been increasing interest in combining Boron Neutron Capture Therapy (BNCT) with standard radiotherapy, either concomitantly or as a BNCT treatment of a recurrent tumor that was previously irradiated with a medical electron linear accelerator (LINAC). In this work we report the simulated dosimetry of treatments combining X-rays and BNCT.Fil: Casal, M. R.. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "dr.angel Roffo". Departamento de Radioterapia y Cancer Experimental; Argentina. Comisión Nacional de Energía Atómica; ArgentinaFil: Herrera, Maria Silvia. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia Física (Centro Atómico Constituyentes). Proyecto Tandar; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: González, Sara Josefina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia Física (Centro Atómico Constituyentes). Proyecto Tandar; ArgentinaFil: Minsky, Daniel Mauricio. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia Física (Centro Atómico Constituyentes). Proyecto Tandar; Argentin

The Alpheus species from the Canary Islands with a first record of Alpheus sulcatus Kingsley, 1878 (Crustacea, Decapoda, Caridea, Alpheidae)

Updated information on geographical distribution and ecology of the Canary Islands' Alpheus species is presented as well as the first record of the pantropical species Alpheus sulcatus Kingsley, 1878.Se proporciona información actualizada sobre la distribución geográfica y la ecología de los Alpheus de Canarias, incluyendo la primera cita para estas islas de la especie pantropical Alpheus sulcatus Kingsley, 1878.Instituto Español de Oceanografí

Phase mapping of aging process in InN nanostructures: oxygen incorporation and the role of the zincblende phase

Uncapped InN nanostructures undergo a deleterious natural aging process at ambient conditions by oxygen incorporation. The phases involved in this process and their localization is mapped by Transmission Electron Microscopy (TEM) related techniques. The parent wurtzite InN (InN-w) phase disappears from the surface and gradually forms a highly textured cubic layer that completely wraps up a InN-w nucleus which still remains from original single-crystalline quantum dots. The good reticular relationships between the different crystals generate low misfit strains and explain the apparent easiness for phase transformations at room temperature and pressure conditions, but also disable the classical methods to identify phases and grains from TEM images. The application of the geometrical phase algorithm in order to form numerical moire mappings, and RGB multilayered image reconstructions allows to discern among the different phases and grains formed inside these nanostructures. Samples aged for shorter times reveal the presence of metastable InN:O zincblende (zb) volumes, which acts as the intermediate phase between the initial InN-w and the most stable cubic In2O3 end phase. These cubic phases are highly twinned with a proportion of 50:50 between both orientations. We suggest that the existence of the intermediate InN:O-zb phase should be seriously considered to understand the reason of the widely scattered reported fundamental properties of thought to be InN-w, as its bandgap or superconductivity.Comment: 18 pages 7 figure

Enhancing Big Data Feature Selection Using a Hybrid Correlation-Based Feature Selection

This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based feature selection (CFS), best first search (BFS), and dominance-based rough set approach (DRSA) methods. This study aims to enhance the classifier’s performance in decision analysis by eliminating uncorrelated and inconsistent data values. The proposed method, named CFS-DRSA, comprises several phases executed in sequence, with the main phases incorporating two crucial feature extraction tasks. Data reduction is first, which implements a CFS method with a BFS algorithm. Secondly, a data selection process applies a DRSA to generate the optimized dataset. Therefore, this study aims to solve the computational time complexity and increase the classification accuracy. Several datasets with various characteristics and volumes were used in the experimental process to evaluate the proposed method’s credibility. The method’s performance was validated using standard evaluation measures and benchmarked with other established methods such as deep learning (DL). Overall, the proposed work proved that it could assist the classifier in returning a significant result, with an accuracy rate of 82.1% for the neural network (NN) classifier, compared to the support vector machine (SVM), which returned 66.5% and 49.96% for DL. The one-way analysis of variance (ANOVA) statistical result indicates that the proposed method is an alternative extraction tool for those with difficulties acquiring expensive big data analysis tools and those who are new to the data analysis field.Ministry of Higher Education under the Fundamental Research Grant Scheme (FRGS/1/2018/ICT04/UTM/01/1)Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-20H04, Malaysia Research University Network (MRUN) Vot 4L876SPEV project, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic (ID: 2102–2021), “Smart Solutions in Ubiquitous Computing Environments

Using clustering methods to deal with high number of alternatives on Group Decision Making

Novel Group Decision Making methods and Web 2.0 have augmented the quantity of data that experts have to discuss about. Nevertheless, experts are only capable of dealing with a reduced set of information. In this paper, a novel method for dealing with decision environments that include a large set of alternatives is presented. By the use of clustering methods, the available alternatives are combined into clusters according to their similarity. Afterwards, one Group Decision Making process is employed for choosing a cluster and another one for selecting the final alternative.The authors would like to thank the FEDER financial support for the Project TIN2016-75850-P by the Spanish Ministry of Science, Innovation and Universities