“…Numerous methods to identify network hubs exist, but in the last years there was a great interest in using and apply the Auto-Contractive map (AutoCM). AutoCM system is a fourth-generation unsupervised artificial neural network (ANN) that can outperform numerous unsupervised algorithms ( Buscema and Sacco, 2016 ). The system uses the minimum spanning tree (MST) theory to underline the natural connections between variables ( Buscema and Grossi, 2008 ; Buscema et al, 2008 ).…”
Section: Microbial Network: New Insights Into Bacterial Ecologymentioning
confidence: 99%
“…This approach allows to both highlight the relevant nodes of the system and show the network of the main relations among variables. Nodes, also defined as “hubs,” are defined as variables with the highest number of relations in the map ( Buscema and Grossi, 2008 ; Buscema et al, 2008 ; Buscema and Sacco, 2016 ).…”
Section: Microbial Network: New Insights Into Bacterial Ecologymentioning
The human milk is fundamental for a correct development of newborns, as it is a source not only of vitamins and nutrients, but also of commensal bacteria. The microbiota associated to the human breast milk contributes to create the “initial” intestinal microbiota of infants, having also a pivotal role in modulating and influencing the newborns’ immune system. Indeed, the transient gut microbiota is responsible for the initial change from an intrauterine Th2 prevailing response to a Th1/Th2 balanced one. Bacteria located in both colostrum and mature milk can stimulate the anti-inflammatory response, by stimulating the production of specific cytokines, reducing the risk of developing a broad range of inflammatory diseases and preventing the expression of immune-mediated pathologies, such as asthma and atopic dermatitis. The aim of the present Mini Review is to elucidate the specific immunologic role of the human milk-associated microbiota and its impact on the newborn’s health and life, highlighting the importance to properly study the biological interactions in a bacterial population and between the microbiota and the host. The Auto Contractive Map, for instance, is a promising analytical methodology based on artificial neural network that can elucidate the specific role of bacteria contained in the breast milk in modulating the infants’ immunological response.
“…Numerous methods to identify network hubs exist, but in the last years there was a great interest in using and apply the Auto-Contractive map (AutoCM). AutoCM system is a fourth-generation unsupervised artificial neural network (ANN) that can outperform numerous unsupervised algorithms ( Buscema and Sacco, 2016 ). The system uses the minimum spanning tree (MST) theory to underline the natural connections between variables ( Buscema and Grossi, 2008 ; Buscema et al, 2008 ).…”
Section: Microbial Network: New Insights Into Bacterial Ecologymentioning
confidence: 99%
“…This approach allows to both highlight the relevant nodes of the system and show the network of the main relations among variables. Nodes, also defined as “hubs,” are defined as variables with the highest number of relations in the map ( Buscema and Grossi, 2008 ; Buscema et al, 2008 ; Buscema and Sacco, 2016 ).…”
Section: Microbial Network: New Insights Into Bacterial Ecologymentioning
The human milk is fundamental for a correct development of newborns, as it is a source not only of vitamins and nutrients, but also of commensal bacteria. The microbiota associated to the human breast milk contributes to create the “initial” intestinal microbiota of infants, having also a pivotal role in modulating and influencing the newborns’ immune system. Indeed, the transient gut microbiota is responsible for the initial change from an intrauterine Th2 prevailing response to a Th1/Th2 balanced one. Bacteria located in both colostrum and mature milk can stimulate the anti-inflammatory response, by stimulating the production of specific cytokines, reducing the risk of developing a broad range of inflammatory diseases and preventing the expression of immune-mediated pathologies, such as asthma and atopic dermatitis. The aim of the present Mini Review is to elucidate the specific immunologic role of the human milk-associated microbiota and its impact on the newborn’s health and life, highlighting the importance to properly study the biological interactions in a bacterial population and between the microbiota and the host. The Auto Contractive Map, for instance, is a promising analytical methodology based on artificial neural network that can elucidate the specific role of bacteria contained in the breast milk in modulating the infants’ immunological response.
“…14b a, b, c show the graph of the attractors according to the Markov Chain inferred from . The Non-Linear Minimum Spanning Tree (NL-MST) that represents the minimum-energy tree configuration that connects all the points of the distribution, pruning away all the edges that are not indispensable to maintain the connectedness among points by means of the most relevant interactions [ 20 ]. Fig.…”
The first case of COVID-19 in USA was reported on January 20, 2020. The number of COVID-19 confirmed cases and death has increased since the first reported case and the outbreak has appeared in all states. This paper analyzes disease outbreak using Topological Weighted Centroid (TWC), which is a data driven intelligent geographical dynamical system that models disease spread in space and time. In this analysis the COVID-19 cases in USA on March 26, 2020 as provided by Johns Hopkins University is used. The COVID-19 outbreak is mapped by the TWC method. We were able to predict and capture some features of the pandemic spread using the early data. Although we have used the geographical distance from the latitude and longitude coordinates, our results indicate that one of the main paths of diseases spread are arguably airline routes. In this analysis, we used a large set of data. A modified version of TWC, is named TWC-Windowing to elaborate the effect of data from all places.
“…In this section, we show that AutoCM performs better than several well-known alternatives in terms of the informational content of the MST that it generates to organize the structure of the relationship among the descriptor variables, as compared to the MSTs generated by alternative techniques. This approach to the comparative evaluation of alternative computational techniques has been developed in Buscema and Sacco (2016) and is based on the notion of MST fitness. In particular, by main MST fitness, we mean the amount of meaningful associations among the descriptor variables that is coded by the MST generated by the corresponding algorithm and by recursive (or global) fitness the amount of meaningful associations among the more strongly associated descriptor variables as obtained through a suitable selective recursion of the corresponding MSTs.…”
This article examines the implicit space grammar of the cultural vibrancy of the region of Halland in Southwest Sweden. By using a new computational approach, we implement for the first time a methodology that allows us, on the one side, to extrapolate the complex dynamic evolution of the region’s cultural geography and, on the other side, to diagnose the structural causes of its eventual decay. The results provide a basis for a more systematic approach to evidence-based policy design at the regional scale, and for a more participatory, bottom-up public decision-making in the cultural and other policy spheres.
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