943 resultados para Adaptive change


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BACKGROUND Many patients presenting to the emergency department (ED) for assessment of possible acute coronary syndrome (ACS) have low cardiac troponin concentrations that change very little on repeat blood draw. It is unclear if a lack of change in cardiac troponin concentration can be used to identify acutely presenting patients at low risk of ACS. METHODS We used the hs-cTnI assay from Abbott Diagnostics, which can detect cTnI in the blood of nearly all people. We identified a population of ED patients being assessed for ACS with repeat cTnI measurement who ultimately were proven to have no acute cardiac disease at the time of presentation. We used data from the repeat sampling to calculate total within-person CV (CV(T)) and, knowing the assay analytical CV (CV(A)), we could calculate within-person biological variation (CV(i)), reference change values (RCVs), and absolute RCV delta cTnI concentrations. RESULTS We had data sets on 283 patients. Men and women had similar CV(i) values of approximately 14%, which was similar at all concentrations <40 ng/L. The biological variation was not dependent on the time interval between sample collections (t = 1.5-17 h). The absolute delta critical reference change value was similar no matter what the initial cTnI concentration was. More than 90% of subjects had a critical reference change value <5 ng/L, and 97% had values of <10 ng/L. CONCLUSIONS With this hs-cTnI assay, delta cTnI seems to be a useful tool for rapidly identifying ED patients at low risk for possible ACS.

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Climate change is one of the most important issues confronting the sustainable supply of seafood, with projections suggesting major effects on wild and farmed fisheries worldwide. While climate change has been a consideration for Australian fisheries and aquaculture management, emphasis in both research and adaptation effort has been at the production end of supply chains—impacts further along the chain have been overlooked to date. A holistic biophysical and socio-economic system view of seafood industries, as represented by end-to-end supply chains, may lead to an additional set of options in the face of climate change, thus maximizing opportunities for improved fishery profitability, while also reducing the potential for maladaptation. In this paper, we explore Australian seafood industry stakeholder perspectives on potential options for adaptation along seafood supply chains based on future potential scenarios. Stakeholders, representing wild capture and aquaculture industries, provided a range of actions targeting different stages of the supply chain. Overall, proposed strategies were predominantly related to the production end of the supply chain, suggesting that greater attention in developing adaptation options is needed at post-production stages. However, there are chain-wide adaptation strategies that can present win–win scenarios, where commercial objectives beyond adaptation can also be addressed alongside direct or indirect impacts of climate. Likewise, certain adaptation strategies in place at one stage of the chain may have varying implications on other stages of the chain. These findings represent an important step in understanding the role of supply chains in effective adaptation of fisheries and aquaculture industries to climate change.

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Background The evidence base for the impact of social determinants of health has been strengthened considerably in the last decade. Increasingly, the public health field is using this as a foundation for arguments and actions to change government policies. The Health in All Policies (HiAP) approach, alongside recommendations from the 2010 Marmot Review into health inequalities in the UK (which we refer to as the ‘Fairness Agenda’), go beyond advocating for the redesign of individual policies, to shaping the government structures and processes that facilitate the implementation of these policies. In doing so, public health is drawing on recent trends in public policy towards ‘joined up government’, where greater integration is sought between government departments, agencies and actors outside of government. Methods In this paper we provide a meta-synthesis of the empirical public policy research into joined up government, drawing out characteristics associated with successful joined up initiatives. We use this thematic synthesis as a basis for comparing and contrasting emerging public health interventions concerned with joined-up action across government. Results We find that HiAP and the Fairness Agenda exhibit some of the characteristics associated with successful joined up initiatives, however they also utilise ‘change instruments’ that have been found to be ineffective. Moreover, we find that – like many joined up initiatives – there is room for improvement in the alignment between the goals of the interventions and their design. Conclusion Drawing on public policy studies, we recommend a number of strategies to increase the efficacy of current interventions. More broadly, we argue that up-stream interventions need to be ‘fit-for-purpose’, and cannot be easily replicated from one context to the next.

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Spatially explicit information on local perceptions of ecosystem services is needed to inform land use planning within rapidly changing landscapes. In this paper we spatially modelled local people's use and perceptions of benefits from forest ecosystem services in Borneo, from interviews of 1837 people in 185 villages. Questions related to provisioning, cultural/spiritual, regulating and supporting ecosystem services derived from forest, and attitudes towards forest conversion. We used boosted regression trees (BRTs) to combine interview data with social and environmental predictors to understand spatial variation of perceptions across Borneo. Our results show that people use a variety of products from intact and highly degraded forests. Perceptions of benefits from forests were strongest: in human-altered forest landscapes for cultural and spiritual benefits; in human-altered and intact forests landscapes for health benefits; intact forest for direct health benefits, such as medicinal plants; and in regions with little forest and extensive plantations, for environmental benefits, such as climatic impacts from deforestation. Forest clearing for small scale agriculture was predicted to be widely supported yet less so for large-scale agriculture. Understanding perceptions of rural communities in dynamic, multi-use landscapes is important where people are often directly affected by the decline in ecosystem services.

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Background Multiple health behavior change can ameliorate adverse effects of cancer. Purpose The purpose of this study was to determine the effects of a multiple health behavior change intervention (CanChange) for colorectal cancer survivors on psychosocial outcomes and quality of life. Methods A total of 410 colorectal cancer survivors were randomized to a 6-month telephone-based health coaching intervention (11 sessions using acceptance and commitment therapy strategies focusing on physical activity, weight management, diet, alcohol, and smoking) or usual care. Posttraumatic growth, spirituality, acceptance, mindfulness, distress, and quality of life were assessed at baseline, 6 and 12 months. Results Significant intervention effects were observed for posttraumatic growth at 6 (7.5, p < 0.001) and 12 months (4.1, p = 0.033), spirituality at 6 months (1.8, p = 0.011), acceptance at 6 months (0.2, p = 0.005), and quality of life at 6 (0.8, p = 0.049) and 12 months (0.9, p = 0.037). Conclusions The intervention improved psychosocial outcomes and quality of life (physical well-being) at 6 months with most effects still present at 12 months. (Trial Registration Number: ACTRN12608000399392).

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Parent-centred interventions for childhood obesity aim to improve parents' skills and confidence in managing children's dietary and activity patterns, and in promoting a healthy lifestyle in their family. However, few studies assess changes in parenting over the course of treatment. This study describes the evaluation of a lifestyle-specific parenting program (Group Lifestyle Triple P) on multiple child and parent outcomes. One-hundred-and-one families with overweight and obese 4- to 11-year-old children participated in an intervention or waitlist control condition. The 12-week intervention was associated with significant reductions in child BMI z score and weight-related problem behaviour. At the end of the intervention, parents reported increased confidence in managing children's weight-related behaviour, and less frequent use of inconsistent or coercive parenting practices. All short-term intervention effects were maintained at one-year follow-up assessment, with additional improvements in child body size. The results support the efficacy of Group Lifestyle Triple P and suggest that parenting influences treatment outcomes. Further research is needed to evaluate the long-term effectiveness of the intervention and to elucidate the mechanisms of change. © 2010 Elsevier Ltd.

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"This chapter reviews the capacity of the discipline field to account for the velocity and quality of digitally-driven transformations, while making a case for a "middle range" approach that steers between unbridled optimism ("all-change") and determined scepticism ("Continuity") about the potential of such change. The chapter focuses on online screen distribution as a case study, considering the evidence for, and significance of, change in industry structure and the main payers, how content is produced and by whom, the nature of content, and the degree to which online screen distribution has reached thresholds of mainstream popularity."

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Public private partnerships (PPPs) have been adopted widely to provide public facilities and services. According to the PPP agreement, PPP projects would be transferred to the public sector. However, problems related to the subsequent management of ongoing PPP projects have not been studied thoroughly. Residual value risk (RVR) can occur if the public sector cannot obtain the project in the desired conditions as required in the agreement when a project is being transferred. RVR has been identified as an important risk in PPPs and has greatly influenced the outputs of the projects. In order to further observe the change of residual value (RV) during the process of PPP projects and to reveal the internal mechanism for reducing the RVR, a comparative case study of two PPP projects in mainland China and Hong Kong was conducted. Based on the case study, different factors leading to RVR and a series of key risk indicators (KRIs) were identified. The comparison demonstrates that RVR is an important risk that could influence the success of PPP projects. The cumulative effects during the concession period can play significant roles in the occurrence of RVR. Additionally, the cumulative effects in different cases can make the RVR different because of different stakeholders’ efforts on the projects and ways to treat RVR. Finally, alternatives for the public sector to treat RVR were proposed. The findings of this research can reduce RVR and improve the performance of PPP projects.

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Forests play a critical role in addressing climate change concerns in the broader context of global change and sustainable development. Forests are linked to climate change in three ways. i) Forests are a source of greenhouse gas (GHG) emissions: ii) Forests offer mitigation opportunities to stabilise GHG concentrations: iii) Forests are impacted by climate change. This paper reviews studies related to climate change and forests in India: first, the studies estimating carbon inventory for the Indian land use change and forestry sector (LUCF), then the different models and mitigation potential estimates for the LUCF sector in India. Finally it reviews the studies on the impact of climate change on forest ecosystems in India, identifying the implications for net primary productivity and bio-diversity. The paper highlights data, modelling and research gaps relevant to the GHG inventory, mitigation potential and vulnerability and impact assessments for the forest sector in India.

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Forty-three children with recurrent abdominal pain who had received treatment from a paediatric gastroenterology clinic were reassessed 6 and 12 months after initial presentation. Measures of children's pain included a pain diary (PD) which measured pain intensity, a parent observation record (POR) which assessed pain behaviour and a structured interview to assess the degree to which pain interferes with the child's activities. Pretreatment measures of the child's history of pain, coping strategies in dealing with pain, and their mother's caregiving strategies were examined as predictors of two indices of clinical improvement: the extent of change in pain on the child's pain diary from pre-test to 6 months follow-up, and the degree of interference to the child's activities. All children had shown significant improvement in the level of pain at follow up, with 74.4% being pain free at 12 month follow-up on the PD and 83.7% being pain free on the POR. The amount of change they showed varied, with some showing residual impairment even though they were significantly improved. Regression analyses showed that children with greatest reductions on the child's pain diary at the 6 month follow-up were those with a stress-related mode of onset, whose mothers used more adaptive caregiving strategies, and who received cognitive behavioural family intervention. There was also a non significant trend for younger children to fare better. These data suggest the importance of early diagnosis and routinely assessing parental caregiving behaviour and beliefs about the origins of pain in planning treatment for children with RAP.

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In this paper, we first recast the generalized symmetric eigenvalue problem, where the underlying matrix pencil consists of symmetric positive definite matrices, into an unconstrained minimization problem by constructing an appropriate cost function, We then extend it to the case of multiple eigenvectors using an inflation technique, Based on this asymptotic formulation, we derive a quasi-Newton-based adaptive algorithm for estimating the required generalized eigenvectors in the data case. The resulting algorithm is modular and parallel, and it is globally convergent with probability one, We also analyze the effect of inexact inflation on the convergence of this algorithm and that of inexact knowledge of one of the matrices (in the pencil) on the resulting eigenstructure. Simulation results demonstrate that the performance of this algorithm is almost identical to that of the rank-one updating algorithm of Karasalo. Further, the performance of the proposed algorithm has been found to remain stable even over 1 million updates without suffering from any error accumulation problems.

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The accelerated rate of increase in atmospheric CO2 concentration in recent years has revived the idea of stabilizing the global climate through geoengineering schemes. Majority of the proposed geoengineering schemes will attempt to reduce the amount of solar radiation absorbed by our planet. Climate modelling studies of these so called 'sunshade geoengineering schemes' show that global warming from increasing concentrations of CO2 can be mitigated by intentionally manipulating the amount of sunlight absorbed by the climate system. These studies also suggest that the residual changes could be large on regional scales, so that climate change may not be mitigated on a local basis. More recent modelling studies have shown that these schemes could lead to a slow-down in the global hydrological cycle. Other problems such as changes in the terrestrial carbon cycle and ocean acidification remain unsolved by sunshade geoengineering schemes. In this article, I review the proposed geoengineering schemes, results from climate models and discuss why geoengineering is not the best option to deal with climate change.

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This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the simulation studies. For the simulation study, a linearized helicopter model at different straight and level flight conditions is considered. A neural network with a linear filter architecture trained using backpropagation through time is used to approximate the control law. The controller network parameters are adapted using updated rules Lyapunov synthesis. The off-line trained (for finite time interval) network provides the necessary stability and tracking performance. The on-line learning is used to adapt the network under varying flight conditions. The on-line learning ability is demonstrated through parameter uncertainties. The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).

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Let E be an elliptic curve defined over Q and let K/Q be a finite Galois extension with Galois group G. The equivariant Birch-Swinnerton-Dyer conjecture for h(1)(E x(Q) K)(1) viewed as amotive over Q with coefficients in Q[G] relates the twisted L-values associated with E with the arithmetic invariants of the same. In this paper I prescribe an approach to verify this conjecture for a given data. Using this approach, we verify the conjecture for an elliptic curve of conductor 11 and an S-3-extension of Q.

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Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.