995 resultados para randomized algorithms
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Background. People with intellectual disabilities (ID) experience similar or even higher rates of mental health problems than the general population and there is a need to develop appropriate treatments. Cognitive behaviour therapy (CBT) is effective for a wide range of disorders in the general population. However, there is some evidence that people with ID may lack the cognitive skills needed to take part in CBT. Aims. To test if people with ID can learn skills required for CBT, specifically the ability to distinguish between thoughts, feelings, and behaviours and to link thoughts and feelings (cognitive mediation). Method. A randomized independent groups design was used to examine the effect of training in CBT on two tasks measuring CBT skills. Thirty-four adults with ID were randomly allocated to the experimental condition ðN ¼ 18Þ or to the control condition ðN ¼ 16Þ. CBT skills were assessed blind at baseline and after the intervention. Results. The training led to significant improvements in participants’ ability to link thoughts and feelings, and this skill was generalized to new material. There was no effect of training on participants’ ability to distinguish amongst thoughts, feelings, and behaviours. People with ID can, therefore, learn some skills required for CBT. This implies that preparatory training for CBT might be useful for people with ID. The results might be applicable to other groups who find aspects of CBT difficult.
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Background and Objectives Low self-esteem (LSE) is associated with psychiatric disorder, and is distressing and debilitating in its own right. Hence, it is frequent target for treatment in cognitive behavioural interventions, yet it has rarely been the primary focus for intervention. This paper reports on a preliminary randomized controlled trial of cognitive behaviour therapy (CBT) for LSE using Fennell’s (1997) cognitive conceptualisation and transdiagnostic treatment approach ( [Fennell, 1997] and [Fennell, 1999]). Methods Twenty-two participants were randomly allocated to either immediate treatment (IT) (n = 11) or to a waitlist condition (WL) (n = 11). Treatment consisted of 10 sessions of individual CBT accompanied by workbooks. Participants allocated to the WL condition received the CBT intervention once the waitlist period was completed and all participants were followed up 11 weeks after completing CBT. Results The IT group showed significantly better functioning than the WL group on measures of LSE, overall functioning and depression and had fewer psychiatric diagnoses at the end of treatment. The WL group showed the same pattern of response to CBT as the group who had received CBT immediately. All treatment gains were maintained at follow-up assessment. Limitations The sample size is small and consists mainly of women with a high level of educational attainment and the follow-up period was relatively short. Conclusions These preliminary findings suggest that a focused, brief CBT intervention can be effective in treating LSE and associated symptoms and diagnoses in a clinically representative group of individuals with a range of different and co-morbid disorders.
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Data assimilation algorithms are a crucial part of operational systems in numerical weather prediction, hydrology and climate science, but are also important for dynamical reconstruction in medical applications and quality control for manufacturing processes. Usually, a variety of diverse measurement data are employed to determine the state of the atmosphere or to a wider system including land and oceans. Modern data assimilation systems use more and more remote sensing data, in particular radiances measured by satellites, radar data and integrated water vapor measurements via GPS/GNSS signals. The inversion of some of these measurements are ill-posed in the classical sense, i.e. the inverse of the operator H which maps the state onto the data is unbounded. In this case, the use of such data can lead to significant instabilities of data assimilation algorithms. The goal of this work is to provide a rigorous mathematical analysis of the instability of well-known data assimilation methods. Here, we will restrict our attention to particular linear systems, in which the instability can be explicitly analyzed. We investigate the three-dimensional variational assimilation and four-dimensional variational assimilation. A theory for the instability is developed using the classical theory of ill-posed problems in a Banach space framework. Further, we demonstrate by numerical examples that instabilities can and will occur, including an example from dynamic magnetic tomography.
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In order to assist in comparing the computational techniques used in different models, the authors propose a standardized set of one-dimensional numerical experiments that could be completed for each model. The results of these experiments, with a simplified form of the computational representation for advection, diffusion, pressure gradient term, Coriolis term, and filter used in the models, should be reported in the peer-reviewed literature. Specific recommendations are described in this paper.
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We discuss the modeling of dielectric responses for an electromagnetically excited network of capacitors and resistors using a systems identification framework. Standard models that assume integral order dynamics are augmented to incorporate fractional order dynamics. This enables us to relate more faithfully the modeled responses to those reported in the Dielectrics literature.
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With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment.
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The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.
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Dietary nitrate, from beetroot, has been reported to lower blood pressure (BP) by the sequential reduction of nitrate to nitrite and further to NO in the circulation. However, the impact of beetroot on microvascular vasodilation and arterial stiffness is unknown. In addition, beetroot is consumed by only 4.5% of the UK population, whereas bread is a staple component of the diet. Thus, we investigated the acute effects of beetroot bread (BB) on microvascular vasodilation, arterial stiffness, and BP in healthy participants. Twenty-three healthy men received 200 g bread containing 100 g beetroot (1.1 mmol nitrate) or 200 g control white bread (CB; 0 g beetroot, 0.01 mmol nitrate) in an acute, randomized, open-label, controlled crossover trial. The primary outcome was postprandial microvascular vasodilation measured by laser Doppler iontophoresis and the secondary outcomes were arterial stiffness measured by Pulse Wave Analysis and Velocity and ambulatory BP measured at regular intervals for a total period of 6 h. Plasma nitrate and nitrite were measured at regular intervals for a total period of 7 h. The incremental area under the curve (0-6 h after ingestion of bread) for endothelium-independent vasodilation was greater (P = 0.017) and lower for diastolic BP (DBP; P = 0.032) but not systolic (P = 0.99) BP after BB compared with CB. These effects occurred in conjunction with increases in plasma and urinary nitrate (P < 0.0001) and nitrite (P < 0.001). BB acutely increased endothelium-independent vasodilation and decreased DBP. Therefore, enriching bread with beetroot may be a suitable vehicle to increase intakes of cardioprotective beetroot in the diet and may provide new therapeutic perspectives in the management of hypertension.
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We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.
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Objective: Obsessive-compulsive disorder (OCD) in young people can be effectively treated with Cognitive Behavior Therapy (CBT). Practice guidelines in the United Kingdom recommend that CBT be delivered with parental or family involvement; however, there is no evidence from randomized trials that this enhances effectiveness. The aim of this trial was to assess if CBT with high parental involvement was more effective than CBT with low parental involvement (individual CBT) in reducing symptoms of OCD. Method: Fifty young people ages 12–17 years with OCD were randomly allocated to individual CBT or parent-enhanced CBT. In parent-enhanced CBT parents attended all treatment sessions; in individual CBT, parents attended only Sessions 1, 7, and the final session. Participants received up to 14 sessions of CBT. Data were analyzed using intent-to-treat and per-protocol methods. The primary outcome measure was the Children’s Yale-Brown Obsessive Compulsion Scale (Scahill et al., 1997). Results: Both forms of CBT significantly reduced symptoms of OCD and anxiety. Change in OCD symptoms was maintained at 6 months. Per-protocol analysis suggested that parent-enhanced CBT may be associated with significantly larger reductions in anxiety symptoms. Conclusions: High and low parental involvement in CBT for OCD in young people were both effective, and there was no evidence that 1 method of delivery was superior on the primary outcome measure. However, this study was small. Future trials should be adequately powered and examine interactions with the age of the young person and comorbid anxiety disorders.
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Background Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. Methods/Design Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). Discussion MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.
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We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.
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BACKGROUND: Observed associations between increased fruit and vegetable (F&V) consumption, particularly those F&Vs that are rich in flavonoids, and vascular health improvements require confirmation in adequately powered randomized controlled trials. OBJECTIVE: This study was designed to measure the dose-response relation between high-flavonoid (HF), low-flavonoid (LF), and habitual F&V intakes and vascular function and other cardiovascular disease (CVD) risk indicators. DESIGN: A single-blind, dose-dependent, parallel randomized controlled dietary intervention study was conducted. Male and female low-F&V consumers who had a ≥1.5-fold increased risk of CVD (n = 174) were randomly assigned to receive an HF F&V, an LF F&V, or a habitual diet, with HF and LF F&V amounts sequentially increasing by 2, 4, and 6 (+2, +4, and +6) portions/d every 6 wk over habitual intakes. Microvascular reactivity (laser Doppler imaging with iontophoresis), arterial stiffness [pulse wave velocity, pulse wave analysis (PWA)], 24-h ambulatory blood pressure, and biomarkers of nitric oxide (NO), vascular function, and inflammation were determined at baseline and at 6, 12, and 18 wk. RESULTS: In men, the HF F&V diet increased endothelium-dependent microvascular reactivity (P = 0.017) with +2 portions/d (at 6 wk) and reduced C-reactive protein (P = 0.001), E-selectin (P = 0.0005), and vascular cell adhesion molecule (P = 0.0468) with +4 portions/d (at 12 wk). HF F&Vs increased plasma NO (P = 0.0243) with +4 portions/d (at 12 wk) in the group as a whole. An increase in F&Vs, regardless of flavonoid content in the groups as a whole, mitigated increases in vascular stiffness measured by PWA (P = 0.0065) and reductions in NO (P = 0.0299) in the control group. CONCLUSION: These data support recommendations to increase F&V intake to ≥6 portions daily, with additional benefit from F&Vs that are rich in flavonoids, particularly in men with an increased risk of CVD. This trial was registered at www.controlled-trials.com as ISRCTN47748735.