Swine health: history, challenges and prospects

En los sistemas de producción porcina, uno de los puntos críticos que deben ser atendidos con estricto rigor, es la salud de los cerdos. La salud, es un componente estructural del bienestar animal y refleja un estado óptimo de los animales, lo que repercute directamente en un mayor desempeño productivo y mejores condiciones de desarrollo. Uno de los eslabones más frágiles de la salud de los cerdos, es la presencia de enfermedades infecciosas más importantes, las cuales pueden representar pérdidas hasta del 100 % de la producción, por lo cual, debe ser un tema de atención constante, y continuamente vigilado por el Médico Veterinario Zootecnista y los productores, en perfecta coordinación con las autoridades sanitarias oficiales. En la actualidad, la implementación de mejores prácticas en la cadena productiva es de interés para productores y consumidores. El control de las enfermedades infecciosas debe ser un tema de colaboración entre los diferentes actores del entorno y ser considerado un bien público, ya que las repercusiones negativas, pueden ser desde el nivel local hasta mundial. En la presente revisión, se abordará la temática relacionada con las principales enfermedades infecciosas que ponen en riesgo la salud porcina, el impacto, las principales aportaciones realizadas por el Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP) en sus 35 años de vida, específicamente en el Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI), anteriormente conocido como el emblemático CENID-Microbiología o Palo Alto.In swine production systems, one of the critical points that must be strictly attended to is the health of the pigs. Health is a structural component of animal welfare and reflects an optimal state of the animals, which has a direct impact on a higher productive performance and better development conditions. Infectious diseases are one of the greatest threats to the health of pigs and can cause losses of up to 100 % of production; therefore, it requires constant attention and continuous monitoring by the veterinarian and producers, in perfect coordination with the official health authorities. Currently, the implementation of best practices in the production chain is of interest to both producers and consumers. The control of infectious diseases requires collaboration between the various actors in the environment and must be considered a public good, since their negative repercussions can range from the local to the global level. This review will address the main infectious diseases that endanger swine health, their impact, the main contributions made by the National Institute for Research in Forestry, Agriculture and Livestock (INIFAP) in its 35 years of life, mainly at the National Center for Disciplinary Research in Animal Health and Safety (CENID-SAI), formerly known as the emblematic CENID-Microbiología or Palo Alto

Modelamiento de series de caudal usando ANFIS

Este trabajo presenta ANFIS (Adaptative Network Based Fuzzy Inference System)como una técnica de modelamiento no lineal de series de tiempo, que en su formulación puede ser analizada como una generalización no lineal de los modelos autorregresivos, y a diferencia de otras metodologías permite incorporar conocimiento experto sobre la serie de tiempo

Sistemas adaptativos de inferência em nevro difusão com erros heterecedásticos para o modelado de séries financeiras

This paper proposes a new kind of non-linear hybrid model. In the proposed model, mean non-linearity is represented by using an adaptive neuro-fuzzy inference system (ANFIS) whereas variance is represented using a conditional self-regressive heteroscedastic component. The mathematical formula for this type of model is shown and a method to estimate it is proposed. In addition, a specification strategy is developed for the proposed model, based on a battery of statistical soft transaction regression (STR) tests and on verosimility radius testing. As a case study, the IBM stock closing price series dynamics were modeled, which is commonly used as a benchmark in the literature on time series. Results indicate that the model developed represents the dynamics of the studied series better than other models with similar characteristics.En este trabajo se propone una nueva clase de modelos híbridos no lineales. En el modelo propuesto, la no linealidad en la media se representa usando un sistema adaptativo neurodifuso de inferencia (ANFIS, por su sigla en inglés), mientras la varianza se representa usando una componente autorregresiva heterocedástica condicional. Se presenta la formulación matemática de este tipo de modelos y se propone un método para su estimación; adicionalmente, se desarrolla para el modelo propuesto una estrategia de especificación basada en una batería de pruebas estadísticas que incluyen pruebas para la especificación de los modelos de regresión con transición suave (STR, por su sigla en inglés) y la prueba del radio de verosimilitud. Como un caso de estudio, se modela la dinámica de la serie de los cambios en los precios de cierre de las acciones de IBM, la cual se usa comúnmente como referente en la literatura de series de tiempo. Los resultados indican que el modelo desarrollado representa mejor que otros modelos de características similares la dinámica de la serie estudiada.Neste trabalho propõem-se uma nova classe de modelos híbridos não lineais. No modelo proposto, a não linearidade em média representa-se utilizando um sistema adaptativo de nevro difusão de inferência (ANFIS, por sua sigla em inglês), enquanto a variação se representa usando um componente auto-regressivo heterecedástico condicional. Apresenta-se a formulação matemática deste tipo de modelos e propõem-se um método para sua estimação; adicionalmente, desenvolve-se para o modelo proposto uma estratégia de especificação baseada em uma bateria de provas estatísticas que incluem provas para a especificação dos modelos de regressão com transição suave (STR, por sua sigla em inglês), e a prova de rádio de verosimilitude. Como um caso de estudo, modela-se a dinâmica da série dos câmbios nos câmbios nos preços de feixe nas ações de IBM, a qual utiliza-se comummente como referente na literatura de séries de tempo. Os resultados indicam que o modelo desenvolvido representa melhor que outros modelos de características similares a dinâmica da série estudada

Sistemas adaptativos de inferência em nevro difusão com erros heterecedásticos para o modelado de séries financeiras

This paper proposes a new kind of non-linear hybrid model. In the proposed model, mean non-linearity is represented by using an adaptive neuro-fuzzy inference system (ANFIS) whereas variance is represented using a conditional self-regressive heteroscedastic component. The mathematical formula for this type of model is shown and a method to estimate it is proposed. In addition, a specification strategy is developed for the proposed model, based on a battery of statistical soft transaction regression (STR) tests and on verosimility radius testing. As a case study, the IBM stock closing price series dynamics were modeled, which is commonly used as a benchmark in the literature on time series. Results indicate that the model developed represents the dynamics of the studied series better than other models with similar characteristics.En este trabajo se propone una nueva clase de modelos híbridos no lineales. En el modelo propuesto, la no linealidad en la media se representa usando un sistema adaptativo neurodifuso de inferencia (ANFIS, por su sigla en inglés), mientras la varianza se representa usando una componente autorregresiva heterocedástica condicional. Se presenta la formulación matemática de este tipo de modelos y se propone un método para su estimación; adicionalmente, se desarrolla para el modelo propuesto una estrategia de especificación basada en una batería de pruebas estadísticas que incluyen pruebas para la especificación de los modelos de regresión con transición suave (STR, por su sigla en inglés) y la prueba del radio de verosimilitud. Como un caso de estudio, se modela la dinámica de la serie de los cambios en los precios de cierre de las acciones de IBM, la cual se usa comúnmente como referente en la literatura de series de tiempo. Los resultados indican que el modelo desarrollado representa mejor que otros modelos de características similares la dinámica de la serie estudiada.Neste trabalho propõem-se uma nova classe de modelos híbridos não lineais. No modelo proposto, a não linearidade em média representa-se utilizando um sistema adaptativo de nevro difusão de inferência (ANFIS, por sua sigla em inglês), enquanto a variação se representa usando um componente auto-regressivo heterecedástico condicional. Apresenta-se a formulação matemática deste tipo de modelos e propõem-se um método para sua estimação; adicionalmente, desenvolve-se para o modelo proposto uma estratégia de especificação baseada em uma bateria de provas estatísticas que incluem provas para a especificação dos modelos de regressão com transição suave (STR, por sua sigla em inglês), e a prova de rádio de verosimilitude. Como um caso de estudo, modela-se a dinâmica da série dos câmbios nos câmbios nos preços de feixe nas ações de IBM, a qual utiliza-se comummente como referente na literatura de séries de tempo. Os resultados indicam que o modelo desenvolvido representa melhor que outros modelos de características similares a dinâmica da série estudada

Modelos de predicción de caudales mensuales para el sector eléctrico colombiano.

Se hace una breve descripción de cinco metodologías para la predicción de caudales medios mensuales en Colombia: Redes Neuronales Artificiales, Redes Adaptativas Neuro-Difusas, Análisis Espectral Singular, Modelo Estructural y Modelo físico y la aplicación de estos modelos en diferentes estaciones de medición de caudal pertenecientes al sistema de Generación de Energía Eléctrica de Colombia

Territorialidades, espiritualidades y cuerpos : perspectivas críticas en estudios sociales

El proceso investigativo y crítico realizado por el GT CLACSO Territorialidades, espiritualidades y cuerpos durante 2019 y 2020 permitió ampliar las convergencias críticas en torno a las nuevas problemátizaciones referidas a las emergencias territoriales, las espiritualidades y los cuerpos. El grupo de investigación ha profundizado en los desplazamientos conceptuales y en el examen de las experimentaciones que se despliegan actualmente en el contexto latinoamericano y mundial, para hallar los entramados de los territorios que emergen, de las espiritualidades que nos conecten con los devenires de la biosfera y de zoé, de las nuevas sensibilidades y de las formas culturales que atraviesan la política de los cuerpos

Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study an international prospective cohort study

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care. We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4–7 days or ≥ 8 days of 1.25 (1.04–1.48), p = 0.015 and 1.31 (1.11–1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care