Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

A confiança interorganizacional nas compras

This research is part of the field of organizational studies, focusing on organizational purchase behavior and, specifically, trust interorganizational at the purchases. This topic is current and relevant by addressing the development of good relations between buyer-supplier that increases the exchange of information, increases the length of relationship, reduces the hierarchical controls and improves performance. Furthermore, although there is a vast literature on trust, the scientific work that deal specifically at the trust interorganizational still need further research to synthesize and validate the variables that generate this phenomenon. In this sense, this investigation is to explain the antecedents of trust interorganizational by the relationship between the variable operational performance, organizational characteristics, shared values and interpersonal relationships on purchases by manufacturing industries, in order to develop a robust literature, most consensual, that includes the current sociological and economic, considering the effect of interpersonal relationships in this phenomenon. This proposal is configured in a new vision of the antecedents of interorganizational trust, described as significant quantitative from models Morgan and Hunt (1994), Doney and Cannon (1997), Zhao and Cavusgil (2006) and Nyaga, Whipple, Lynch (2011), as well as qualitative analysis of Tacconi et al. (2011). With regard to methodological aspects, the study assumes the form of a descriptive, survey type, and causal trace theoretical and empirical. As for his nature, the investigation, explicative character, has developed a quantitative approach with the use of exploratory factor analysis and structural equation modeling SEM, with the use of IBM software SPSS Amos 18.0, using the method of maximum verisimilitude, and supported by technical bootstraping. The unit of analysis was the buyer-supplier relationship, in which the object under investigation was the supplier organization in view of the purchasing company. 237 valid questionnaires were collected among key informants, using a simple random sampling developed in manufacturing industries (SIC 10-33), located in the city of Natal and in the region of Natal. The first results of descriptive analysis demonstrate the phenomenon of interorganizational trust, in which purchasing firms believe, feel secure about the supplier. This demonstration showed high levels of intensity, predominantly among the vendors that supply the company with materials that are used directly in the production process. The exploratory and confirmatory factor analysis, performed on each variable alone, generated a set of observable and unobservable variables more consistent, giving rise to a model, that needed to be further specified. This again specify model consists of trajectories was positive, with a good fit, with a composite reliability and variance extracted satisfactory, and demonstrates convergent and discriminant validity, in which the factor loadings are significant and strong explanatory power. Given the findings that reinforce the model again specify data, suggesting a high probability that this model may be more suited for the study population, the results support the explanation that interorganizational trust depends on purchases directly from interpersonal relationships, sharing value and operating performance and indirectly of personal relationships, social networks, organizational characteristics, physical and relational aspect of performance. It is concluded that this trust can be explained by a set of interactions between these three determinants, where the focus is on interpersonal relationships, with the largest path coefficient for the factor under study

Simulação de fluxo de fluidos em meios porosos desordenados uma análise de efeito de escala na estimativa da permeabilidade e do coeficiente de arrasto

The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.

Efeito de diferentes divisões territoriais na flutuação aleatória de indicadores socioeconômicos relacionados à determinação social da saúde

This research aimed to analyse the effect of different territorial divisions in the random fluctuation of socio-economic indicators related to social determinants of health. This is an ecological study resulting from a combination of statistical methods including individuated and aggregate data analysis, using five databases derived from the database of the Brazilian demographic census 2010: overall results of the sample by weighting area. These data were grouped into the following levels: households; weighting areas; cities; Immediate Urban Associated Regions and Intermediate Urban Associated Regions. A theoretical model related to social determinants of health was used, with the dependent variable Household with death and as independent variables: Black race; Income; Childcare and school no attendance; Illiteracy; and Low schooling. The data was analysed in a model related to social determinants of health, using Poisson regression in individual basis, multilevel Poisson regression and multiple linear regression in light of the theoretical framework of the area. It was identified a greater proportion of households with deaths among those with at least one black resident, lower-income, illiterate, who do not attend or attended school or day-care and less educated. The analysis of the adjusted model showed that most adjusted prevalence ratio was related to Income, where there is a risk value of 1.33 for households with at least one resident with lower average personal income to R$ 655,00 (Brazilian current). The multilevel analysis demonstrated that there was a context effect when the variables were subjected to the effects of areas, insofar as the random effects were significant for all models and with different prevalence rates being higher in the areas with smaller dimensions - Weighting areas with coefficient of 0.035 and Cities with coefficient of 0.024. The ecological analyses have shown that the variable Income and Low schooling presented explanatory potential for the outcome on all models, having income greater power to determine the household deaths, especially in models related to Immediate Urban Associated Regions with a standardized coefficient of -0.616 and regions intermediate urban associated regions with a standardized coefficient of -0.618. It was concluded that there was a context effect on the random fluctuation of the socioeconomic indicators related to social determinants of health. This effect was explained by the characteristics of territorial divisions and individuals who live or work there. Context effects were better identified in the areas with smaller dimensions, which are more favourable to explain phenomena related to social determinants of health, especially in studies of societies marked by social inequalities. The composition effects were better identified in the Regions of Urban Articulation, shaped through mechanisms similar to the phenomenon under study.

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

A confiança interorganizacional nas compras

This research is part of the field of organizational studies, focusing on organizational purchase behavior and, specifically, trust interorganizational at the purchases. This topic is current and relevant by addressing the development of good relations between buyer-supplier that increases the exchange of information, increases the length of relationship, reduces the hierarchical controls and improves performance. Furthermore, although there is a vast literature on trust, the scientific work that deal specifically at the trust interorganizational still need further research to synthesize and validate the variables that generate this phenomenon. In this sense, this investigation is to explain the antecedents of trust interorganizational by the relationship between the variable operational performance, organizational characteristics, shared values and interpersonal relationships on purchases by manufacturing industries, in order to develop a robust literature, most consensual, that includes the current sociological and economic, considering the effect of interpersonal relationships in this phenomenon. This proposal is configured in a new vision of the antecedents of interorganizational trust, described as significant quantitative from models Morgan and Hunt (1994), Doney and Cannon (1997), Zhao and Cavusgil (2006) and Nyaga, Whipple, Lynch (2011), as well as qualitative analysis of Tacconi et al. (2011). With regard to methodological aspects, the study assumes the form of a descriptive, survey type, and causal trace theoretical and empirical. As for his nature, the investigation, explicative character, has developed a quantitative approach with the use of exploratory factor analysis and structural equation modeling SEM, with the use of IBM software SPSS Amos 18.0, using the method of maximum verisimilitude, and supported by technical bootstraping. The unit of analysis was the buyer-supplier relationship, in which the object under investigation was the supplier organization in view of the purchasing company. 237 valid questionnaires were collected among key informants, using a simple random sampling developed in manufacturing industries (SIC 10-33), located in the city of Natal and in the region of Natal. The first results of descriptive analysis demonstrate the phenomenon of interorganizational trust, in which purchasing firms believe, feel secure about the supplier. This demonstration showed high levels of intensity, predominantly among the vendors that supply the company with materials that are used directly in the production process. The exploratory and confirmatory factor analysis, performed on each variable alone, generated a set of observable and unobservable variables more consistent, giving rise to a model, that needed to be further specified. This again specify model consists of trajectories was positive, with a good fit, with a composite reliability and variance extracted satisfactory, and demonstrates convergent and discriminant validity, in which the factor loadings are significant and strong explanatory power. Given the findings that reinforce the model again specify data, suggesting a high probability that this model may be more suited for the study population, the results support the explanation that interorganizational trust depends on purchases directly from interpersonal relationships, sharing value and operating performance and indirectly of personal relationships, social networks, organizational characteristics, physical and relational aspect of performance. It is concluded that this trust can be explained by a set of interactions between these three determinants, where the focus is on interpersonal relationships, with the largest path coefficient for the factor under study

Simulação de fluxo de fluidos em meios porosos desordenados uma análise de efeito de escala na estimativa da permeabilidade e do coeficiente de arrasto

The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.