Historical background of the factors of attribution of civil liability, starting with Napoleon's Civil Code of 1804 and its reception in the Colombian Civil Code of 1873. The special case of the objective regime for hazardous activities

Gaius' inclusion of the figure of quasi-crime had a great impact on the subsequent conception of the glosadors and the natural law regarding civil liability; the difficulties in differentiating this figure from crime contributed to the subjective conception of responsibility, embodied in Napoleon's Civil Code. French doctrine and jurisprudence created an objective liability factor based on the risk of the fact of things. This did not happen in the same way in Colombia; Don Andrés Bello's code was not a copy of the French Code, its author took into account other sources and did not incorporate into the code a general rule of responsibility for the fact of things. In light of the historical account of the receipt of the factors for attribution of civil liability, it is impossible in Colombia to support the theory of risk in article 2356 CC col

Desenvolvimento de um aplicativo para a predição de ingredientes e receitas de cozinha por meio de TensorFlow e máquinas de suporte vetorial

This article is derived from a research project in which an application for the prediction of ingredients and recipes by TensorFlow and support- vector machines was developed. A scheme with general architecture was developed, then a neural network was implemented, and then, the support-vector machine was run. After that, they were integrated via an application that allows the user to select ingredients’ images for their prediction and the prediction of kitchens recipe in a didactic manner. It was concluded that the system has an average precision value of 75.8% and 71% for 17 ingredients categories and recipes classifier. In addition, sensitivity testing was performed on the application resulting on statistically equivalent results.Este artículo es derivado de un proyecto de investigación en el cual se realizó el desarrollo de una aplicación para la predicción de ingredientes y recetas por medio de TensorFlow y máquinas de soporte vectorial. Se realizó un esquema de la arquitectura general, luego se desarrolló una red neuronal y después se efectuó la ejecución de la máquina de soporte vectorial. Finalmente, se realizó la integración en una aplicación que permite al usuario seleccionar imágenes de los ingredientes para su predicción y de la receta de cocina para desayunos de manera didáctica. Se concluyó que el sistema tiene un promedio de precisión del 75,8 % para las 17 categorías de ingredientes y de 71 % para el clasificador de recetas. Adicionalmente, se realizó un análisis de esta estabilidad y se observó que todos los resultados eran iguales en términos estadísticos.Este artigo é derivado de um projeto de pesquisa no qual se realizou o desenvolvimento de um aplicativo para a predição de ingredientes e receitas por meio de TensorFlow e máquinas de suporte vetorial. Realizou-se um esquema da arquitetura geral, desenvolveu-se uma rede neuronal e depois efetuou-se a execução da máquina de suporte vetorial. Finalmente, realizou-se a integração num aplicativo que permite ao usuário selecionar imagens dos ingredientes para sua predição e da receita de cozinha para cafés da manhã de maneira didática. Concluiu-se que o sistema tem uma média de precisão de 75,8 % para as 17 categorias de ingredientes e de 71 % para o classificador de receitas. Adicionalmente, realizou-se uma análise dessa estabilidade e observou-se que todos os resultados eram iguais em termos estatísticos.&nbsp

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Desarrollo de una aplicación para la predicción de ingredientes y recetas de cocina por medio de TensorFlow y máquinas de soporte vectorial

This article is derived from a research project in which an application for the prediction of ingredients and recipes by TensorFlow and suppor-t-vector machines was developed. A scheme with general architecture was developed, then a neural network was implemented, and then, the support-vector machine was run. After that, they were integrated via an application that allows the user to select ingredients’ images for their prediction and the prediction of kitchens recipe in a didactic manner. It was concluded that the system has an average precision value of 75.8% and 71% for 17 ingredients categories and recipes classifier. In addition, sensitivity testing was performed on the application resulting on statis-tically equivalent resultsEste artigo é derivado de um projeto de pesquisa no qual se realizou o desenvolvimento de um aplicativo para a predição de ingredientes e recei-tas por meio de TensorFlow e máquinas de suporte vetorial. Realizou-se um esquema da arquitetura geral, desenvolveu-se uma rede neuronal e depois efetuou-se a execução da máquina de suporte vetorial. Finalmente, realizou-se a integração num aplicativo que permite ao usuário selecionar imagens dos ingredientes para sua predição e da receita de cozinha para cafés da manhã de maneira didática. Concluiu-se que o sistema tem uma média de precisão de 75,8 % para as 17 categorias de ingredientes e de 71 % para o classificador de receitas. Adicionalmente, realizou-se uma análise dessa estabilidade e observou-se que todos os resultados eram iguais em termos estatísticos.Este artículo es derivado de un proyecto de investigación en el cual se realizó el desarrollo de una aplicación para la predicción de ingredientes y recetas por medio de TensorFlow y máquinas de soporte vectorial. Se realizó un esquema de la arquitectura general, luego se desarrolló una red neuronal y después se efectuó la ejecución de la máquina de soporte vectorial. Finalmente, se realizó la integración en una aplicación que permite al usuario seleccionar imágenes de los ingredientes para su predicción y de la receta de cocina para desayunos de manera didáctica. Se concluyó que el sistema tiene un promedio de precisión del 75,8 % para las 17 categorías de ingredientes y de 71 % para el clasificador de recetas. Adicionalmente, se realizó un análisis de esta estabilidad y se observó que todos los resultados eran iguales en términos estadísticos

Drug-induced anaphilaxis in Latin America

LIBRA Fdn, Buenos Aires, DF, ArgentinaCtr Med Docente La Trinidad, Caracas, VenezuelaHosp San Bernardo, Salta, ArgentinaUniv Fed Sao Paulo, Sao Paulo, BrazilFdn Valle del Lili, Cali, ColombiaUniv Autonoma Nuevo Leon, Hosp Dr Jose Eleuterio Gonzalez, Monterrey, MexicoCatholic Univ Cordoba, Cordoba, ArgentinaConsultorios San Juan, San Juan, ArgentinaHosp San Angel, Mexico City, DF, MexicoUniv Antiquia, Medellin, ColombiaUniv Nacl La Plata, La Plata, Buenos Aires, ArgentinaNuevo Hosp San Roque, Cordoba, ArgentinaRespiralab Hosp Kennedy, Guayaquil, EcuadorClin Las Condes, Santiago, ChileUniv Nacl Rosario, RA-2000 Rosario, Santa Fe, ArgentinaUniv Fed Sao Paulo, Sao Paulo, BrazilWeb of Scienc

XV International Congress of Control Electronics and Telecommunications: "The role of technology in times of pandemic and post-pandemic: innovation and development for strategic social and productive sectors"

La anterior selección, motivados por la aseveración de Manuel Castells -hace casi 20 años ya- que la innovación y la difusión de la tecnología parecía ser la herramienta apropiada para el desarrollo en la era de la información. Este 2020, sin embargo, ante la situación disruptiva que aquejó y aqueja a la sociedad red como una estructura social emergente de la Era de la Información basada en redes de producción, energizadas por el poder y la experiencia; falló y debe reencontrar su rumbo. Es así que los problemas acuciantes, ahora, fueron: la atención sanitaria y la superación de la epidemia de Sars Cov 2; tomó forma la, hasta entonces, visión irrealista de Castells que … no podemos avanzar con nuestros modelos de desarrollo actual, destruyendo nuestro entorno y excluyendo a la mayor parte de la humanidad de los beneficios de la revolución tecnológica más extraordinaria de la historia, sin sufrir una devastadora reacción por parte de la sociedad y la naturaleza. Fue así que el Cuarto Mundo, específicamente, donde la suficiencia de recurso humano, de capital, trabajo, información y mercado -vinculados todos a través de la tecnología- supuso que atendería eficazmente a través de la población que podía por su capacidad hacer uso racional y profesional del conocimiento, las necesidades de la mayoritaria población vulnerable y vulnerada. Por lo anterior, poner en el centro a las personas, en entornos de tarea y trabajo globales hiperconectados combinando espacios físicos, corrientes de información con canales de conexión expeditos, y formando profesionales del conocimiento que asuman y afronten los retos derivados de la transformación digital de empresas, universidades, y organizaciones, pero en condiciones de equidad y sujetos de prosperidad, será el desafío en los escenarios presentes y futuros inmediatos.The previous selection, motivated by the assertion of Manuel Castells -almost 20 years ago- that innovation and diffusion of technology seemed to be the appropriate tool for development in the information age. This 2020, however, in the face of the disruptive situation that afflicted and continues to afflict the network society as an emerging social structure of the Information Age based on production networks, energized by power and experience; He failed and must find his way again. Thus, the pressing problems now were: health care and overcoming the Sars Cov 2 epidemic; Castells' until then unrealistic vision took shape that... we cannot advance with our current development models, destroying our environment and excluding the majority of humanity from the benefits of the most extraordinary technological revolution in history, without suffering a devastating reaction from society and nature. It was thus that the Fourth World, specifically, where the sufficiency of human resources, capital, work, information and market - all linked through technology - meant that it would serve effectively through the population that could, due to its capacity, make rational use. and knowledge professional, the needs of the majority vulnerable and vulnerable population. Therefore, putting people at the center, in hyperconnected global task and work environments, combining physical spaces, information flows with expedited connection channels, and training knowledge professionals who assume and face the challenges derived from the digital transformation of companies, universities, and organizations, but in conditions of equality and subject to prosperity, will be the challenge in the present and immediate future scenarios.Bogot