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Productos Lácteos Aplicación de Altas Presiones
Téc. Magali Parzanese

Producto lácteos y tecnología de altas presiones

Actualmente se procesan mediante tecnologías de altas presiones leche y otros productos derivados, una vez que se encuentran envasados en su empaque final. El tratamiento de leche con tecnología de APH se realiza con el fin de disminuir la carga bacteriana e inhibir el desarrollo de microorganismos patógenos, sin afectar la cepa probiótica preseleccionada. Además permite el diseño de nuevos productos lácteos que se distinguen por presentar texturas y sabores innovadores, como por ejemplo yogures, quesos, salsas y rellenos.

Asimismo este tratamiento logra aumentar de 3 a 10 veces la vida útil de los productos presurizados.

Magnitudes de presión usadas en procesamiento de diferentes alimentos
Ventajas y desventajes de la aplicación de altas presiones en alimentos

Ver también:12345

Fuente:
alimentos argentinos

Criogenia Alisson Aguirre

Lenguajes de Programación ¿cuál es el mejor o el más fácil de aprender?

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Fuente: Codigo Facilito

Neighborhood Graphs with HITS and SALSA Seth J. Chandler



A particularly helpful search of a network such as the Internet or a citation network not only finds nodes that satisfy some criteria but also ranks those nodes for importance to create what amounts to a "reading list". Traditionally, this ranking was independent of the particular search performed. In part for reasons of speed, the nodes were ranked on the basis of their pre-computed importance within the entire network. More recently, however, relatively rapid algorithms have been developed to permit search-specific rankings. Thus, when these newer methodologies are used, if web pages or nodes in a citation network cover multiple topics and a particular document is important with respect to Topic A and far less important on Topic B, a search for documents based on the presence of Topic B will select this node but will not rank it highly. These newer methodologies essentially create a ranked and topic-specific "reading list" to explore the information revealed by the search. The key to these new methodologies is the creation of a "neighborhood graph", often containing far fewer nodes and edges than the full network to which various algorithms for computing node centrality can be rapidly applied.

This Demonstration shows how these new methods can create search-specific rankings of nodes selected by a search. It does so by the creation of a "neighborhood graph". You select from among six networks that are intended to resemble citation networks. Each node of the each network has an "attribute set" consisting of five Boolean values. You then filter the nodes (conduct a search) by choosing whether you want each member of the five attributes associated with the node to be True or False, or whether you don’t want to exclude any nodes based on the value of that attribute. These choices create a "result set" of nodes matching your selection. The Demonstration colors these nodes in red. These nodes are then augmented into a "base set" by adding a sample of the parents of each member of the result set and a sample of the children of each member of the result set. You specify the maximum cardinality of each selection of parents and the maximum cardinality of each selection of children. The base set thus establishes a partial "buffer" around the result set. The Demonstration colors these buffering nodes in green.

It is now time to determine how the nodes in the result set are to be ranked and the nodes are to be correlatively sized. Although you have the option of ranking the nodes based on their global importance in the entire network (using the traditional PageRanks method), in general, users will want to select a method for prioritizing the nodes in the result set based on the neighborhood graph. You can choose to prioritize the nodes in the neighborhood graph through the PageRanks method promoted by Google, the "HITS" (Hyperlink-Induced Topic Search) algorithm or the more recent "SALSA" (Stochastic Approach for Link Structure Analysis) algorithm. The latter two algorithms require you to specify whether you care about the nodes' importance as an "authority" relied on by other nodes or a "hub" that connects to an authoritative node.

Two additional controls let you customize the scale and the size of the vertices in the result set and permit you either to see the entire network or just the neighborhood graph.

Excel 2013 Tutorial - Parte I
Dostin Hurtado

Microsoft Excel es una aplicación distribuida por Microsoft Office para hojas de cálculo. Este programa es desarrollado y distribuido por Microsoft, y es utilizado normalmente en tareas financieras y contables.

Las características, especificaciones y límites de Excel han variado considerablemente de versión en versión, exhibiendo cambios en su interfaz operativa y capacidades desde el lanzamiento de su versión 12.0 mejor conocida como Excel 2007. Se puede destacar que mejoró su límite de columnas ampliando la cantidad máxima de columnas por hoja de cálculo de 256 a 16.384 columnas. De la misma forma fue ampliado el límite máximo de filas por hoja de cálculo de 65.536 a 1.048.576 filas3 por hoja. Otras características también fueron ampliadas, tales como el número máximo de hojas de cálculo que es posible crear por libro que pasó de 256 a 1.024 o la cantidad de memoria del PC que es posible emplear que creció de 1 GB a 2 GB soportando además la posibilidad de usar procesadores de varios núcleos.
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Fuente video: Dostin Hurtado