80 resultados para Chern-Simons Theories


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The topics of succession and post-disturbance ecosystem recovery have a long and convoluted history. There is extensive redundancy within this body of theory, which has resulted in confusion, and the links among theories have not been adequately drawn. This review aims to distil the unique ideas from the array of theory related to ecosystem change in response to disturbance. This will help to reduce redundancy, and improve communication and understanding between researchers. We first outline the broad range of concepts that have developed over the past century to describe community change in response to disturbance. The body of work spans overlapping succession concepts presented by Clements in 1916, Egler in 1954, and Connell and Slatyer in 1977. Other theories describing community change include state and transition models, biological legacy theory, and the application of functional traits to predict responses to disturbance. Second, we identify areas of overlap of these theories, in addition to highlighting the conceptual and taxonomic limitations of each. In aligning each of these theories with one another, the limited scope and relative inflexibility of some theories becomes apparent, and redundancy becomes explicit. We identify a set of unique concepts to describe the range of mechanisms driving ecosystem responses to disturbance. We present a schematic model of our proposed synthesis which brings together the range of unique mechanisms that were identified in our review. The model describes five main mechanisms of transition away from a post-disturbance community: (i) pulse events with rapid state shifts; (ii) stochastic community drift; (iii) facilitation; (iv) competition; and (v) the influence of the initial composition of a post-disturbance community. In addition, stabilising processes such as biological legacies, inhibition or continuing disturbance may prevent a transition between community types. Integrating these six mechanisms with the functional trait approach is likely to improve the predictive capacity of disturbance theory. Finally, we complement our discussion of theory with a case study which emphasises that many post-disturbance theories apply simultaneously to the same ecosystem. Using the well-studied mountain ash (Eucalyptus regnans) forests of south-eastern Australia, we illustrate phenomena that align with six of the theories described in our model of rationalised disturbance theory. We encourage further work to improve our schematic model, increase coverage of disturbance-related theory, and to show how the model may link to, or integrate with, other domains of ecological theory.

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This article explores how theories of radicalisation have placed an emphasis on the development of an indicators-based approach to identify individuals who might engage in politically motivated violence. We trace how policing agencies have juxtaposed the search for indicators as a defence against criticisms of racial profiling. However, through an analysis of Canadian counter-terrorism training programmes, we demonstrate that the search for radicalisation indicators reaffirms pre-emptive and discriminatory security practices. We insist that despite efforts to theorise radicalisation outside of the practices of the “war on terror”, current trends risk rationalising prejudicial policing that affirms social exclusion and injustice.

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Conspiracy Theory (CT) endorsers believe in an omnipresent, malevolent, and highly coordinated group that wields secret influence for personal gain, and credit this group with the responsibility for many noteworthy events. Two explanations for the emergence of CTs are that they result from social marginalisation and a lack of agency, or that they are due to a need-to-explain-the-unexplained. Furthermore, representativeness heuristics may form reasoning biases that make such beliefs more likely. Two related studies (N = 107; N = 120) examined the relationships between these social marginalisation, intolerance of uncertainty, heuristics and CT belief using a correlational design. Overall, intolerance of uncertainty did not link strongly to CT belief, but worldview variables did - particularly a sense of the world as (socially) threatening, non-random, and with no fixed morality. The use of both representative heuristics that were examined was heightened in those participants more likely to endorse CTs. These factors seem to contribute to the likelihood of whether the individual will endorse CTs generally, relating similarly to common CTs, CTs generally historically accepted as "true", and to the endorsement of fictional CTs that the individual would find novel. Implications are discussed.

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We examined a model, informed by self-regulation theories from the health psychology literature, which included goal adjustment capacities, appraisals of challenge and threat, coping, and well-being. Two-hundred and twelve athletes from the United Kingdom (n 147)= or Australia (n = 65), who played team (n = 135) or individual sports (n = 77), and competed at international (n = 7), national (n = 11), county (n = 67), club (n = 84), or beginner (n = 43) levels participated in this study. Participants completed measures of goal adjustment capacities and stress appraisals two days before competing. Athletes also completed coping and well-being questionnaires within three hours of their competition ending.The way an athlete responded to an unattainable goal was associated with his or her well-being in the period leading up to and including the competition. Goal reengagement positively predicted well-being, whereas goal disengagement negatively predicted well-being. Further, goal reengagement was positively associated with challenge appraisals, which in turn was linked to task-oriented coping, and task-oriented coping positively associated with well-being.When highly-valued goals become unattainable, consultants and coaches could encourage athletes to generate alternative approaches to achieve the same goal or help them develop a completely new goal in order to promote well-being among athletes.

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Big data is one of the hottest research topics in science and technology communities, and it possesses a great potential in every sector for our society, such as climate, economy, health, social science, and so on. Big data is currently treated as data sets with sizes beyond the ability of commonly used software tools to capture, curate, and manage. We have tasted the power of big data in various applications, such as finance, business, health, and so on. However, big data is still in her infancy stage, which is evidenced by its vague definition, limited application, unsolved security and privacy barriers for pervasive implementation, and so forth. It is certain that we will face many unprecedented problems and challenges along the way of this unfolding revolutionary chapter of human history.