Arte y Poder en la historia

Public power establishes, in a more or less transitory or sustained manner, the objective conditions for the development of art. Specifically, power allows the emergence of a type of specialization that drives the dynamic development of “professional” art, as a trade, to which the artist can dedicate, it ensures the conditions for financing, obtaining raw materials and importing innovations. In this way it allows art to evolve. Even though official art can be very conservative, it has the inclination or inertia to preserve. Let us talk then about the art that, since the down of history, is made at the request of power and for its own purposes, most art, because most of the artistic phenomena of our civilization originate from the demand of power: political, ecclesiastic o economic.El poder público establece, de manera más o menos transitoria o sostenida, las condiciones objetivas para el desarrollo del arte. El poder específicamente permite que se produzca el tipo de especialización que impulsa el desarrollo dinámico del arte “profesional”, como un oficio, al que el artista puede dedicarse, asegura las condiciones en las cuales se puede financiar, conseguir materias primas e importar innovaciones. De ese modo permite que el arte evolucione. Aunque también puede ser muy conservador el arte oficial, tiene esa inclinación o inercia, de conservar. Hablemos pues del arte que, desde los albores de la historia, se hace a solicitud del poder y para sus fines, casi todo el arte, porque la mayoría de los fenómenos artísticos de nuestra civilización se originan en esa demanda del poder: político, eclesiástico o económico

Aplicação de mapas de Kohonen à análise cinética da marcha humana

In recent years the use of artificial neural networks for classification and analysis of kinematic and kinetic characteristics of human locomotion has greatly increased. This happens in an attempt to overcome the limitations of traditional dynamic analysis and to find new clinical indicators for interpreting quick and objectively the large amount of information obtained in a gait lab. One of the most widely used neural networks for human gait analysis is the self-organizing or Kohonen map, based on unsupervised learning without prior definition of the formed natural groups. Among the advantages of using this type of neural network is the data dimensionality reduction, with minimal loss of information content, and the grouping of them in function of their similarities. Taking into account this, in this work an application case of a Kohonen map for clustering of locomotion kinetic characteristics in normal and Parkinson's disease individuals is presented. The results indicate that the groups identified by the map are consistent with the classification carried out by experts in function of traditional gait dynamic analysis, showing the potential of this technique for distinguishing between a population of individuals with normal gait and with gait disorders of different etiology.Nos últimos anos, tem aumentado significativamente o uso de redes neurais artificiais para a classificação e análise cinemática e cinética da marcha humana, em uma tentativa de superar as limitações da análise dinâmica tradicional e de encontrar novos indicadores clínicos para interpretar, de forma rápida e objetiva, a grande quantidade de informação obtida em laboratórios de marcha humana. Uma das redes neurais mais utilizadas para análise de marcha é o mapa de Kohonen ou mapa auto-organizado, baseado em aprendizado não supervisionado, sem uma definição prévia de grupos naturais que se formam. O uso deste tipo de rede neural tem mostrado benefícios significativos associados com a redução da dimensionalidade dos dados com mínima perda de conteúdo de informação e com o agrupamento de dados de acordo com suas semelhanças. Neste contexto, este trabalho apresenta um caso de aplicação de um mapa de Kohonen como classificador das características cinéticas da locomoção em indivíduos normais e com doença de Parkinson. Os resultados indicam que os grupos identificados no mapa são consistentes com a classificação feita por especialistas com base em análise dinâmica tradicional, que mostra o potencial desta técnica para diferenciar populações de indivíduos com marcha normal e de indivíduos com distúrbios da marcha de etiologia diferente.Fil: Rodrigo, Silvia Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Lescano Pastor, Claudia Noemí. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Rodrigo, Rodolfo Horacio. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Ingeniería Electromecánica; Argentin

Aplicação de mapas de Kohonen à análise cinética da marcha humana

In recent years the use of artificial neural networks for classification and analysis of kinematic and kinetic characteristics of human locomotion has greatly increased. This happens in an attempt to overcome the limitations of traditional dynamic analysis and to find new clinical indicators for interpreting quick and objectively the large amount of information obtained in a gait lab. One of the most widely used neural networks for human gait analysis is the self-organizing or Kohonen map, based on unsupervised learning without prior definition of the formed natural groups. Among the advantages of using this type of neural network is the data dimensionality reduction, with minimal loss of information content, and the grouping of them in function of their similarities. Taking into account this, in this work an application case of a Kohonen map for clustering of locomotion kinetic characteristics in normal and Parkinson's disease individuals is presented. The results indicate that the groups identified by the map are consistent with the classification carried out by experts in function of traditional gait dynamic analysis, showing the potential of this technique for distinguishing between a population of individuals with normal gait and with gait disorders of different etiology.Nos últimos anos, tem aumentado significativamente o uso de redes neurais artificiais para a classificação e análise cinemática e cinética da marcha humana, em uma tentativa de superar as limitações da análise dinâmica tradicional e de encontrar novos indicadores clínicos para interpretar, de forma rápida e objetiva, a grande quantidade de informação obtida em laboratórios de marcha humana. Uma das redes neurais mais utilizadas para análise de marcha é o mapa de Kohonen ou mapa auto-organizado, baseado em aprendizado não supervisionado, sem uma definição prévia de grupos naturais que se formam. O uso deste tipo de rede neural tem mostrado benefícios significativos associados com a redução da dimensionalidade dos dados com mínima perda de conteúdo de informação e com o agrupamento de dados de acordo com suas semelhanças. Neste contexto, este trabalho apresenta um caso de aplicação de um mapa de Kohonen como classificador das características cinéticas da locomoção em indivíduos normais e com doença de Parkinson. Os resultados indicam que os grupos identificados no mapa são consistentes com a classificação feita por especialistas com base em análise dinâmica tradicional, que mostra o potencial desta técnica para diferenciar populações de indivíduos com marcha normal e de indivíduos com distúrbios da marcha de etiologia diferente.Fil: Rodrigo, Silvia Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Lescano Pastor, Claudia Noemí. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Rodrigo, Rodolfo Horacio. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Ingeniería Electromecánica; Argentin

Taking advantage of the use of supervised learning methods for characterization of sperm population structure related with freezability in the Iberian red deer

P. 1661-1672Using Iberian red deer as a model, this study presents a supervised learning method, the Support Vector Machines (SVM), to characterize sperm population structure related with freezability. Male freezability was assessed by evaluating motility, membrane status and mitochondrial membrane potential of sperm after a freezing-thawing procedure. The SVM model was generated using sperm motility information captured by computer-assisted sperm analysis (CASA) from thawed semen, belonging to six stags with marked differences on their freezability. A total of 1369 sperm tracks were recorded for seven kinematic parameters and assigned to four motility patterns based on them: weak motile, progressive, transitional and hyperactivated-like. Then, these data were split in two sets: the training set, used to train the SVM model, and the testing set, used to examine how the SVM method and three other unsupervised methods, a non-hierarchical, a hierarchical and a multistep clustering procedures, performed the sperm classification into subpopulations. The SVM was revealed as the most accurate method in the characterization of sperm subpopulations, showing all the sperm subpopulations obtained in this way high significant correlations with those sperm parameters used to characterize freezability of males. Given its superiority, the SVM method was used to characterize the sperm motile subpopulations in Iberian red deer. Sperm motile data from frozen–thawed semen belonging to 25 stags were recorded and loaded into the SVM model. The sperm population structure revealed that those males showing poor freezability were characterized by high percentages of sperm with a weak motility pattern. In opposite, males showing good freezability were characterized by higher percentages of sperm with a progressive and hyperactivated-like motility pattern and lower percentages of sperm with a weak motile pattern. We also identified a sperm subpopulation with a transitional motility pattern. This subpopulation increased as the freezability of males improved, and may be used as indicative of overall sperm motility.S

Revealing giant exciton fine-structure splitting in 2D perovskites using van der Waals passivation

The study of two-dimensional (2D) van der Waals materials has been an active field of research in the development of new optoelectronics and photonic applications over the last decade. Organic-inorganic layered perovskites are currently some of the most promising 2D van der Waals materials, due to their exceptional optical brightness and enhanced excitonic effects. However, low crystal quality and spectral diffusion usually broaden the exciton linewidth, obscuring the fine structure of the exciton in conventional photoluminescence experiments. Here, we propose a mechanical approach for reducing the effect of spectral diffusion by means of hBN-capping on layered perovskites with different thicknesses, revealing the exciton fine structure. We used a stochastic model to link the reduction of the spectral linewidth with the population of active charge fluctuation centres present in the organic spacer taking part in the dynamical Stark shift. Active fluctuation centres are reduced by a factor of 3.7 to 7.1 when we include hBN-capping according to our direct spectral measurements. This rate is in good agreement with the analysis of the overlap between the squared perovskite lattice and the hexagonal hBN lattice. Van der Waals forces between both lattices cause the partial clamping of the perovskite organic spacer molecules, and hence, the amplitude of the dynamical Stark shift characteristic of the spectral diffusion effect is reduced. Our work provides an easy and low-cost solution to the problem of accessing important fine-structure excitonic state information, along with an explanation of the important carrier dynamics present in the organic spacer that affect the quality of the optical emission

Stereotactic ablative radiotherapy for acquired resistance to EGFR therapy in metastatic non-small cell lung cancer

The advent of targeted therapy has transformed the treatment paradigm and survival of patients with metastatic non-small cell lung cancer (NSCLC) with driver mutations. The development of acquired resistances during treatment with tyrosine kinase inhibitors (TKIs) impedes a prolonged survival in many patients. This fact is leading to the use of locally ablative therapies such as stereotactic ablative radiotherapy (SABR) to counter these resistances. SABR is a non-invasive treatment that can be delivered in multiple locations and has already proven effective in oligometastatic disease. Clinical evidence suggests that the combination of SABR with TKIs prolongs progression-free survival (PFS) in metastatic NSCLC patients with mutations in epidermal growth factor receptor (EGFR), with international guidelines recommending their use in unfavorable scenarios such as oligoprogressive disease. In this publication, we have reviewed the available evidence on EGFR-TKIs resistance mechanisms and the combination of SABR with TKI in metastatic NSCLC with EGFR mutations. We also describe the utility and clinical recommendations of this combination in oligometastatic and oligoprogressive disease

Multiparticle Biased DLA with surface diffusion: a comprehensive model of electrodeposition

We present a complete study of the Multiparticle Biased Diffusion-Limited Aggregation (MBDLA) model supplemented with surface difussion (SD), focusing on the relevance and effects of the latter transport mechanism. By comparing different algorithms, we show that MBDLA+SD is a very good qualitative model for electrodeposition in practically all the range of current intensities {\em provided} one introduces SD in the model in the proper fashion: We have found that the correct procedure involves simultaneous bulk diffusion and SD, introducing a time scale arising from the ratio of the rates of both processes. We discuss in detail the different morphologies obtained and compare them to the available experimental data with very satisfactory results. We also characterize the aggregates thus obtained by means of the dynamic scaling exponents of the interface height, allowing us to distinguish several regimes in the mentioned interface growth. Our asymptotic scaling exponents are again in good agreement with recent experiments. We conclude by discussing a global picture of the influence and consequences of SD in electrodeposition.Comment: 15 pages, 20 figures, accepted for publication in Physical Review

The relation between global migration and trade networks

In this paper we develop a methodology to analyze and compare multiple global networks, focusing our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a community of migrants significantly increases trade intensity, where to assure comparability across networks we apply a hypergeometric filter that lets us identify those links which intensity is significantly higher than expected. Next, proposing a new way to define country neighbors based on the most intense links in the trade network, we use spatial econometrics techniques to measure the effect of migration on international trade, while controlling for network interdependences. Overall, we find that migration significantly boosts trade across countries and we are able to identify product categories for which this effect is particularly strong

The Web Graph of a Tourism System

The website network of a tourism destination is examined. The main statistical characteristics of the underlying graph are calculated. The topology of the network is similar to the one characterizing similar systems. However, some differences are found, mainly due to the relatively poor connectivity among the vertices of the network