Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific.
Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific.
El método de tránsito es un método efectivo para identificar planetas extrasolares, que se basa en la disminución poco profunda que provoca un planeta en el brillo aparente de su estrella anfitriona. Sin embargo, los eventos de tránsito están muy cerca del límite de la sensibilidad de detección de los telescopios y se necesitan al menos tres (3) eventos de tránsito producidos por el mismo planeta para confirmar el descubrimiento de éste, lo que hace que se requieran observaciones por tiempos prolongados de una estrella para detectar planetas extrasolares que puedan estar orbitandola, lo que resulta en grandes cantidades de datos que deben ser analizados. En este trabajo se desarrolló una nueva tuberia de software (pipeline) para la detección autónoma de rastros de tránsitos planetarios analizando características extraídas de curvas de luz estelares utilizando un clasificador de lógica difusa, evadiendo la tarea de buscar tránsitos en cada sección de las curvas de luz. Para el desarrollo de esta tuberia de software se implementó la metodologia llamada: Knowledge Discovery in Databases (KDD) la cual presenta una forma de extraer conocimiento de grandes conjuntos de datos.
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