He variables describing the dataset. iv) ACS Algorithm, further, would allow

He variables describing the dataset. iv) ACS Algorithm, further, would allow specialists to put semantic queries into a dataset, to discover the prototypical features of each variable in the dataset, when one or more variables are activated dynamically. ACS, then, could transform the dataset into a dynamical system for a data driven simulation environment, selecting the vulnerable and the protective variables determining IUGR.Supporting InformationS1 Dataset. Supplementary table of the data for all 14 variables for all 46 patients included in the analyses of this study. (DOC)Author ContributionsConceived and designed the experiments: MB MES. Performed the experiments: MB EG MES. Analyzed the data: MB EG LM MES. Contributed reagents/materials/analysis tools: MB EG MES. Wrote the paper: MB EG LM MES.
Innovation feeds social and economic progress and drives progress through enhanced efficiency [1?], costs [4?], and the quality of the products [7]. Innovation includes ideas, values, goods, services, technologies, processes, etc. that emerge and are disseminated both in markets, organizations and within social systems in general. Whether an innovation is effective or not depends on whether it can be assimilated by the socio-economic system it is designed for. This will be more or less complicated, depending on the setting in which it is disseminated. In markets, decisions to adopt the innovation and to commit the resources required to gain access to the product and use it for its intended purpose are normally taken by one and the same person. In organizations, on the other hand, the WP1066 supplier specialization of duties and distribution of authority and decision-making among various jobs mean that each stage in the innovation assimilation process may be carried out by different people, and this demands a greater level of coordination. The dissemination of innovation in social complex systems can therefore be described as a process of a succession of decisions regarding adoption forming groups of people, or markets, else it can be described as a process of internal diffusion throughout the implementation stage in organisations [8].PLOS ONE | DOI:10.1371/journal.pone.0126076 May 15,1 /The Role of the Organization Structure in the Diffusion of InnovationsCompeting Interests: The authors have declared that no competing interests exist.This paper examines the assimilation of innovation in social systems as a decentralized process. In such processes, early stage is key to the assimilation of innovation. At this early stage, either members unanimously accept the innovation or they continue with the status quo. When adoption and implementation are produced in separate stages a previous GSK-1605786 site consensus in favour of innovation will simplify the subsequent implementation stage since the people who will need to be involved at a later date are the same ones that previously came out in favour of adopting it. The use of Agent Based Models (ABM) as a methodological tool for the study of social phenomena provides useful insights about the fundamental causal mechanisms at work in social systems [9?1]. The large-scale macroscopic effects of simple forms of microscopic social interaction are very often surprising and generally hard to anticipate, such as the diffusion of information, emergence of norms, coordination of conventions, or participation in collective action. The traditional literature on the adoption and dissemination of innovation has been heavily influenced by the ep.He variables describing the dataset. iv) ACS Algorithm, further, would allow specialists to put semantic queries into a dataset, to discover the prototypical features of each variable in the dataset, when one or more variables are activated dynamically. ACS, then, could transform the dataset into a dynamical system for a data driven simulation environment, selecting the vulnerable and the protective variables determining IUGR.Supporting InformationS1 Dataset. Supplementary table of the data for all 14 variables for all 46 patients included in the analyses of this study. (DOC)Author ContributionsConceived and designed the experiments: MB MES. Performed the experiments: MB EG MES. Analyzed the data: MB EG LM MES. Contributed reagents/materials/analysis tools: MB EG MES. Wrote the paper: MB EG LM MES.
Innovation feeds social and economic progress and drives progress through enhanced efficiency [1?], costs [4?], and the quality of the products [7]. Innovation includes ideas, values, goods, services, technologies, processes, etc. that emerge and are disseminated both in markets, organizations and within social systems in general. Whether an innovation is effective or not depends on whether it can be assimilated by the socio-economic system it is designed for. This will be more or less complicated, depending on the setting in which it is disseminated. In markets, decisions to adopt the innovation and to commit the resources required to gain access to the product and use it for its intended purpose are normally taken by one and the same person. In organizations, on the other hand, the specialization of duties and distribution of authority and decision-making among various jobs mean that each stage in the innovation assimilation process may be carried out by different people, and this demands a greater level of coordination. The dissemination of innovation in social complex systems can therefore be described as a process of a succession of decisions regarding adoption forming groups of people, or markets, else it can be described as a process of internal diffusion throughout the implementation stage in organisations [8].PLOS ONE | DOI:10.1371/journal.pone.0126076 May 15,1 /The Role of the Organization Structure in the Diffusion of InnovationsCompeting Interests: The authors have declared that no competing interests exist.This paper examines the assimilation of innovation in social systems as a decentralized process. In such processes, early stage is key to the assimilation of innovation. At this early stage, either members unanimously accept the innovation or they continue with the status quo. When adoption and implementation are produced in separate stages a previous consensus in favour of innovation will simplify the subsequent implementation stage since the people who will need to be involved at a later date are the same ones that previously came out in favour of adopting it. The use of Agent Based Models (ABM) as a methodological tool for the study of social phenomena provides useful insights about the fundamental causal mechanisms at work in social systems [9?1]. The large-scale macroscopic effects of simple forms of microscopic social interaction are very often surprising and generally hard to anticipate, such as the diffusion of information, emergence of norms, coordination of conventions, or participation in collective action. The traditional literature on the adoption and dissemination of innovation has been heavily influenced by the ep.