24 resultados para Distributed model predictive control


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The dual-effects model of social control not only assumes that social control leads to better health practices but also arouses psychological distress. However, findings are inconsistent. The present study advances the current literature by examining social control from a dyadic perspective in the context of smoking. In addition, the study examines whether control, continuous smoking abstinence, and affect are differentially related for men and women. Before and three weeks after a self-set quit attempt, we examined 106 smokers (77 men, mean age: 40.67, average number of cigarettes smoked per day: 16.59 [SD=8.52, range=1-40] at baseline and 5.27 [SD=6.97, range=0-40] at follow-up) and their nonsmoking heterosexual partners, assessing received and provided control, continuous abstinence, and affect. With regard to smoker's affective reactions, partner's provided control was related to an increase in positive and to a decrease in negative affect, but only for female smokers. Moreover, the greater the discrepancy between smoker received and partner's provided control was the more positive affect increased and the more negative affect decreased, but again only for female smokers. These findings demonstrate that female smokers' well-being was raised over time if they were not aware of the control attempts of their nonsmoking partners, indicating positive effects of invisible social control. This study's results emphasize the importance of applying a dyadic perspective and taking gender differences in the dual-effects model of social control into account.

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BACKGROUND: Clinical disorders often share common symptoms and aetiological factors. Bifactor models acknowledge the role of an underlying general distress component and more specific sub-domains of psychopathology which specify the unique components of disorders over and above a general factor. METHODS: A bifactor model jointly calibrated data on subjective distress from The Mood and Feelings Questionnaire and the Revised Children's Manifest Anxiety Scale. The bifactor model encompassed a general distress factor, and specific factors for (a) hopelessness-suicidal ideation, (b) generalised worrying and (c) restlessness-fatigue at age 14 which were related to lifetime clinical diagnoses established by interviews at ages 14 (concurrent validity) and current diagnoses at 17 years (predictive validity) in a British population sample of 1159 adolescents. RESULTS: Diagnostic interviews confirmed the validity of a symptom-level bifactor model. The underlying general distress factor was a powerful but non-specific predictor of affective, anxiety and behaviour disorders. The specific factors for hopelessness-suicidal ideation and generalised worrying contributed to predictive specificity. Hopelessness-suicidal ideation predicted concurrent and future affective disorder; generalised worrying predicted concurrent and future anxiety, specifically concurrent generalised anxiety disorders. Generalised worrying was negatively associated with behaviour disorders. LIMITATIONS: The analyses of gender differences and the prediction of specific disorders was limited due to a low frequency of disorders other than depression. CONCLUSIONS: The bifactor model was able to differentiate concurrent and predict future clinical diagnoses. This can inform the development of targeted as well as non-specific interventions for prevention and treatment of different disorders.

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Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

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In the present article, we argue that it may be fruitful to incorporate the ideas of the strength model of self-control into the core assumptions of the well-established attentional control theory (ACT). In ACT, it is assumed that anxiety automatically leads to attention disruption and increased distractibility, which may impair subsequent cognitive or perceptual-motor performance, but only if individuals do not have the ability to counteract this attention disruption. However, ACT does not clarify which process determines whether one can volitionally regulate attention despite experiencing high levels of anxiety. In terms of the strength model of self-control, attention regulation can be viewed as a self-control act depending on the momentary availability of self-control strength. We review literature that has revealed that self-control strength moderates the anxiety-performance relationship, discuss how to integrate these two theoretical models, and offer practical recommendations of how to counteract negative anxiety effects.

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Neuroenhancement (NE), the use of substances as a means to enhance performance, has garnered considerable scientific attention of late. While ethical and epidemiological publications on the topic accumulate, there is a lack of theory-driven psychological research that aims at understanding psychological drivers of NE. In this perspective article we argue that self-control strength offers a promising theory-based approach to further understand and investigate NE behavior. Using the strength model of self-control, we derive two theory-driven perspectives on NE-self-control research. First, we propose that individual differences in state/trait self-control strength differentially affect NE behavior based on one’s individual experience of NE use. Building upon this, we outline promising research questions that (will) further elucidate our understanding of NE based on the strength model’s propositions. Second, we discuss evidence indicating that popular NE substances (like Methylphenidate) may counteract imminent losses of self-control strength. We outline how further research on NE’s effects on the ego-depletion effect may further broaden our understanding of the strength model of self-control.

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The strength model of self-control assumes that all acts of self-control (e.g., emotion regulation, persistence) are empowered by a single global metaphorical strength that has limited capacity. This strength can become temporarily depleted after a primary self-control act, which, in turn, can impair performance in subsequent acts of self-control. Recently, the assumptions of the strength model of self-control also have been adopted and tested in the field of sport and exercise psychology. The present review paper aims to give an overview of recent developments in self-control research based on the strength model of self-control. Furthermore, recent research on interventions on how to improve and revitalize self-control strength will be presented. Finally, the strength model of self-control has been criticized lately, as well as expanded in scope, so the present paper will also discuss alternative explanations of why previous acts of self-control can lead to impaired performance in sport and exercise.

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Analogue model experiments using both brittle and viscous materials were performed to investigate the development and interaction of strike-slip faults in zones of distributed shear deformation. At low strain, bulk dextral shear deformation of an initial rectangular model is dominantly accommodated by left-stepping, en echelon strike-slip faults (Riedel shears, R) that form in response to the regional (bulk) stress field. Push-up zones form in the area of interaction between adjacent left-stepping Riedel shears. In cross sections, faults bounding push-up zones have an arcuate shape or merge at depth. Adjacent left-stepping R shears merge by sideways propagation or link by short synthetic shears that strike subparallel to the bulk shear direction. Coalescence of en echelon R shears results in major, through-going faults zones (master faults). Several parallel master faults develop due to the distributed nature of deformation. Spacing between master faults is related to the thickness of the brittle layers overlying the basal viscous layer. Master faults control to a large extent the subsequent fault pattern. With increasing strain, relatively short antithetic and synthetic faults develop mostly between old, but still active master faults. The orientation and evolution of the new faults indicate local modifications of the stress field. In experiments lacking lateral borders, closely spaced parallel antithetic faults (cross faults) define blocks that undergo clockwise rotation about a vertical axis with continuing deformation. Fault development and fault interaction at different stages of shear strain in our models show similarities with natural examples that have undergone distributed shear.

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1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.