Towards a Smart(er) Social Science Using High-Dimensional Continuous-Time Trajectories from the Open Dynamic Interaction Networks (ODIN) Platform

2019 ◽  
Author(s):  
Bilal Khan ◽  
Kirk Dombrowski ◽  
Alekhya Bellam ◽  
Gisela Font Sayeras ◽  
Kin Pi ◽  
...  
Keyword(s):  
Social Science ◽  
Continuous Time ◽  
Dynamic Interaction ◽  
Interaction Networks ◽  
High Dimensional

scholarly journals Dynamic interaction networks in a hierarchically organized tissue

2010 ◽  
Vol 6 (1) ◽  
pp. 417 ◽  
Author(s):  
Daniel C Kirouac ◽  
Caryn Ito ◽  
Elizabeth Csaszar ◽  
Aline Roch ◽  
Mei Yu ◽  
...  
Keyword(s):  
Dynamic Interaction ◽  
Interaction Networks

scholarly journals Fra køn til diversitet – intersektionalitet i en dansk/nordisk kontekst

2006 ◽  
Author(s):  
Ann-Dorte Christensen ◽  
Birte Siim
Keyword(s):  
Social Science ◽  
Critical Reflection ◽  
Black Feminism ◽  
Dynamic Interaction ◽  
Gender Research ◽  
The Us ◽  
Methodological Approaches ◽  
New Perspective

Intersectionality is a travelling concept rooted in Black Feminism that has recently been adopted by Nordic gender research. The concept has been transformed on its way from the US to the Danish/Nordic context. The purpose with this article is to contribute to a critical reflection of the concept and discuss its potentials from a Danish/Nordic context. Adopting a social science optic we first discuss some tensions between the original American understanding of the concept and the special – predominantly poststructural and postcolonial  conceptualisation given in the Danish/ Nordic context. Secondly we present two analytical frames able to analyse the dynamic interaction between different forms of power and between structures, institutions and identities. We argue that  intersectionality is not a coherent theory but a new perspective able to contain different and competing theoretical and methodological approaches.

scholarly journals Umibato: estimation of time-varying microbial interaction using continuous-time regression hidden Markov model

2021 ◽  
Author(s):  
Shion Hosoda ◽  
Tsukasa Fukunaga ◽  
Michiaki Hamada
Keyword(s):  
Gut Microbiota ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Continuous Time ◽  
Hidden Markov ◽  
Hidden Variables ◽  
Microbial Interactions ◽  
Interaction Networks ◽  
Time Varying ◽  
Microbial Interaction

AbstractMotivationAccumulating evidence has highlighted the importance of microbial interaction networks. Methods have been developed for estimating microbial interaction networks, of which the generalized Lotka-Volterra equation (gLVE)-based method can estimate a directed interaction network. The previous gLVE-based method for estimating microbial interaction networks did not consider time-varying interactions.ResultsIn this study, we developed unsupervised learning based microbial interaction inference method using Bayesian estimation (Umibato), a method for estimating time-varying microbial interactions. The Umibato algorithm comprises Gaussian process regression (GPR) and a new Bayesian probabilistic model, the continuous-time regression hidden Markov model (CTRHMM). Growth rates are estimated by GPR, and interaction networks are estimated by CTRHMM. CTRHMM can estimate time-varying interaction networks using interaction states, which are defined as hidden variables. Umibato outperformed the existing methods on synthetic datasets. In addition, it yielded reasonable estimations in experiments on a mouse gut microbiota dataset, thus providing novel insights into the relationship between consumed diets and the gut microbiota.AvailabilityThe C++ and python source codes of the Umibato software are available at http://github.com/shion-h/[email protected], [email protected]

Transcriptional Complexity from Dynamic Interaction Networks In Vivo

2004 ◽  
Vol 5 (7) ◽  
pp. 559-566 ◽  
Author(s):  
Miroslav Dundr ◽  
Tom Misteli
Keyword(s):  
Dynamic Interaction ◽  
Interaction Networks

scholarly journals STABILIZATION POLICY AS BIFURCATION SELECTION: WOULD STABILIZATION POLICY WORK IF THE ECONOMY REALLY WERE UNSTABLE?

2002 ◽  
Vol 6 (5) ◽  
pp. 713-747 ◽  
Author(s):  
William A. Barnett ◽  
Yijun He
Keyword(s):  
Parameter Space ◽  
Continuous Time ◽  
Operating Regime ◽  
Point Of View ◽  
High Dimensional ◽  
Stabilization Policy ◽  
Macroeconometric Model ◽  
Stable Operating ◽  
Policy Work ◽  
Selection Of

Taken literally, the concept of “stabilization policy” implicitly assumes that the macroeconomy is unstable without imposition of a policy. Hence, selection of a “stabilization policy” can be viewed as selection of a policy to bifurcate the system from an unstable to a stable operating regime. The literature on dynamics of high-dimensional systems suggests that successful bifurcation selection is challenging. As an experiment to investigate this point of view, we use the continuous-time UK dynamic macroeconometric model. Under assumptions designed to be most favorable to stabilization policy, we find that policies that would produce successful bifurcation are very complicated. We also find that less complicated policies based upon reasonable economic intuition can be counterproductive, since such policies can contract the size of the stable subset of the parameter space. In fact, an economy that is dynamically stable without policy, but subject to stochastic shocks, could be bifurcated to instability with imposition of a poorly designed “stabilization” policy.

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