986 resultados para interval-valued similarity


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Purpose: Hyperactive platelets contribute to the thrombotic response in humans, and exercise transiently increases platelet function. Caffeine is routinely used by athletes as an ergogenic aid, but the combined effect of exercise and caffeine on platelet function has not been investigated. Methods: Twelve healthy males were randomly assigned to one of four groups and undertook four experimental trials of a high-intensity aerobic interval training (AIT) bout or rest with ingestion of caffeine (3 mg·kg-1) or placebo. AIT was 8 × 5 min at approximately 75% peak power output (approximately 80% V?O2peak) and 1-min recovery (approximately 40% peak power output, approximately 50% V?O2peak) intervals. Blood/urine was collected before, 60, and 90 min after capsule ingestion and analyzed for platelet aggregation/activation. Results: AIT increased platelet reactivity to adenosine diphosphate (placebo 30.3%, caffeine 13.4%, P < 0.05) and collagen (placebo 10.8%, caffeine 5.1%, P < 0.05) compared with rest. Exercise placebo increased adenosine diphosphate-induced aggregation 90 min postingestion compared with baseline (40.5%, P < 0.05), but the increase when exercise was combined with caffeine was small (6.6%). During the resting caffeine protocol, collagen-induced aggregation was reduced (-4.3%, P < 0.05). AIT increased expression of platelet activation marker PAC-1 with exercise placebo (P < 0.05) but not when combined with caffeine. Conclusion: A single bout of AIT increases platelet function, but caffeine ingestion (3 mg·kg) does not exacerbate platelet function at rest or in response to AIT. Our results provide new information showing caffeine at a dose that can elicit ergogenic effects on performance has no detrimental effect on platelet function and may have the potential to attenuate increases in platelet activation and aggregation when undertaking strenuous exercise.

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Purpose The objectives of this study were to examine the effect of 4-week moderate- and high-intensity interval training (MIIT and HIIT) on fat oxidation and the responses of blood lactate (BLa) and rating of perceived exertion (RPE). Methods Ten overweight/obese men (age = 29 ±3.7 years, BMI = 30.7 ±3.4 kg/m2) participated in a cross-over study of 4-week MIIT and HIIT training. The MIIT training sessions consisted of 5-min cycling stages at mechanical workloads 20% above and 20% below 45%VO2peak. The HIIT sessions consisted of intervals of 30-s work at 90%VO2peak and 30-s rest. Pre- and post-training assessments included VO2max using a graded exercise test (GXT) and fat oxidation using a 45-min constant-load test at 45%VO2max. BLa and RPE were also measured during the constant-load exercise test. Results There were no significant changes in body composition with either intervention. There were significant increases in fat oxidation after MIIT and HIIT (p ≤ 0.01), with no effect of intensity. BLa during the constant-load exercise test significantly decreased after MIIT and HIIT (p ≤ 0.01), and the difference between MIIT and HIIT was not significant (p = 0.09). RPE significantly decreased after HIIT greater than MIIT (p ≤ 0.05). Conclusion Interval training can increase fat oxidation with no effect of exercise intensity, but BLa and RPE decreased after HIIT to greater extent than MIIT.

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Similarity solutions are carried out for flow of power law non-Newtonian fluid film on unsteady stretching surface subjected to constant heat flux. Free convection heat transfer induces thermal boundary layer within a semi-infinite layer of Boussinesq fluid. The nonlinear coupled partial differential equations (PDE) governing the flow and the boundary conditions are converted to a system of ordinary differential equations (ODE) using two-parameter groups. This technique reduces the number of independent variables by two, and finally the obtained ordinary differential equations are solved numerically for the temperature and velocity using the shooting method. The thermal and velocity boundary layers are studied by the means of Prandtl number and non-Newtonian power index plotted in curves.

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In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

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Through the application of process mining, valuable evidence-based insights can be obtained about business processes in organisations. As a result the field has seen an increased uptake in recent years as evidenced by success stories and increased tool support. However, despite this impact, current performance analysis capabilities remain somewhat limited in the context of information-poor event logs. For example, natural daily and weekly patterns are not considered. In this paper a new framework for analysing event logs is defined which is based on the concept of event gap. The framework allows for a systematic approach to sophisticated performance-related analysis of event logs containing varying degrees of information. The paper formalises a range of event gap types and then presents an implementation as well as an evaluation of the proposed approach.

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Emotionally arousing events can distort our sense of time. We used mixed block/event-related fMRI design to establish the neural basis for this effect. Nineteen participants were asked to judge whether angry, happy and neutral facial expressions that varied in duration (from 400 to 1,600 ms) were closer in duration to either a short or long duration they learnt previously. Time was overestimated for both angry and happy expressions compared to neutral expressions. For faces presented for 700 ms, facial emotion modulated activity in regions of the timing network Wiener et al. (NeuroImage 49(2):1728–1740, 2010) namely the right supplementary motor area (SMA) and the junction of the right inferior frontal gyrus and anterior insula (IFG/AI). Reaction times were slowest when faces were displayed for 700 ms indicating increased decision making difficulty. Taken together with existing electrophysiological evidence Ng et al. (Neuroscience, doi: 10.3389/fnint.2011.00077, 2011), the effects are consistent with the idea that facial emotion moderates temporal decision making and that the right SMA and right IFG/AI are key neural structures responsible for this effect.

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This study investigated the influence of two different intensities of acute interval exercise on food preferences and appetite sensations in overweight and obese men. Twelve overweight/obese males (age=29.0±4.1 years; BMI =29.1±2.4 kg/m2) completed three exercise sessions: an initial graded exercise test, and two interval cycling sessions: moderate-(MIIT) and high-intensity (HIIT) interval exercise sessions on separate days in a counterbalanced order. The MIIT session involved cycling for 5-minute repetitions of alternate workloads 20% below and 20% above maximal fat oxidation. The HIIT session consisted of cycling for alternate bouts of 15 seconds at 85% VO2max and 15 seconds unloaded recovery. Appetite sensations and food preferences were measured immediately before and after the exercise sessions using the Visual Analogue Scale and the Liking & Wanting experimental procedure. Results indicated that liking significantly increased and wanting significantly decreased in all food categories after both MIIT and HIIT. There were no differences between MIIT and HIIT on the effect on appetite sensations and Liking & Wanting. In conclusion, manipulating the intensity of acute interval exercise did not affect appetite and nutrient preferences.

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This study investigated the effects of high-intensity interval training (HIIT) vs. work-matched moderate-intensity continuous exercise (MOD) on metabolism and counterregulatory stress hormones. In a randomized and counterbalanced order, 10 well-trained male cyclists and triathletes completed a HIIT session [81.6 ± 3.7% maximum oxygen consumption (V̇o2 max); 72.0 ± 3.2% peak power output; 792 ± 95 kJ] and a MOD session (66.7 ± 3.5% V̇o2 max; 48.5 ± 3.1% peak power output; 797 ± 95 kJ). Blood samples were collected before, immediately after, and 1 and 2 h postexercise. Carbohydrate oxidation was higher (P = 0.037; 20%), whereas fat oxidation was lower (P = 0.037; −47%) during HIIT vs. MOD. Immediately after exercise, plasma glucose (P = 0.024; 20%) and lactate (P < 0.01; 5.4×) were higher in HIIT vs. MOD, whereas total serum free fatty acid concentration was not significantly different (P = 0.33). Targeted gas chromatography-mass spectromtery metabolomics analysis identified and quantified 49 metabolites in plasma, among which 11 changed after both HIIT and MOD, 13 changed only after HIIT, and 5 changed only after MOD. Notable changes included substantial increases in tricarboxylic acid intermediates and monounsaturated fatty acids after HIIT and marked decreases in amino acids during recovery from both trials. Plasma adrenocorticotrophic hormone (P = 0.019), cortisol (P < 0.01), and growth hormone (P < 0.01) were all higher immediately after HIIT. Plasma norepinephrine (P = 0.11) and interleukin-6 (P = 0.20) immediately after exercise were not significantly different between trials. Plasma insulin decreased during recovery from both HIIT and MOD (P < 0.01). These data indicate distinct differences in specific metabolites and counterregulatory hormones following HIIT vs. MOD and highlight the value of targeted metabolomic analysis to provide more detailed insights into the metabolic demands of exercise.

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Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

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The function of a protein can be partially determined by the information contained in its amino acid sequence. It can be assumed that proteins with similar amino acid sequences normally have closer functions. Hence analysing the similarity of proteins has become one of the most important areas of protein study. In this work, a layered comparison method is used to analyze the similarity of proteins. It is based on the empirical mode decomposition (EMD) method, and protein sequences are characterized by the intrinsic mode functions (IMFs). The similarity of proteins is studied with a new cross-correlation formula. It seems that the EMD method can be used to detect the functional relationship of two proteins. This kind of similarity method is a complement of traditional sequence similarity approaches which focus on the alignment of amino acids

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Advances in neural network language models have demonstrated that these models can effectively learn representations of words meaning. In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text. This model is employed for the task of measuring semantic similarity between medical concepts, a task that is central to a number of techniques in medical informatics and information retrieval. The model is built with two medical corpora (journal abstracts and patient records) and empirically validated on two ground-truth datasets of human-judged concept pairs assessed by medical professionals. Empirically, our approach correlates closely with expert human assessors ($\approx$ 0.9) and outperforms a number of state-of-the-art benchmarks for medical semantic similarity. The demonstrated superiority of this model for providing an effective semantic similarity measure is promising in that this may translate into effectiveness gains for techniques in medical information retrieval and medical informatics (e.g., query expansion and literature-based discovery).

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Automated digital recordings are useful for large-scale temporal and spatial environmental monitoring. An important research effort has been the automated classification of calling bird species. In this paper we examine a related task, retrieval of birdcalls from a database of audio recordings, similar to a user supplied query call. Such a retrieval task can sometimes be more useful than an automated classifier. We compare three approaches to similarity-based birdcall retrieval using spectral ridge features and two kinds of gradient features, structure tensor and the histogram of oriented gradients. The retrieval accuracy of our spectral ridge method is 94% compared to 82% for the structure tensor method and 90% for the histogram of gradients method. Additionally, this approach potentially offers a more compact representation and is more computationally efficient.

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Abstract PURPOSE: Compensatory responses may attenuate the effectiveness of exercise training in weight management. The aim of this study was to compare the effect of moderate- and high-intensity interval training on eating behavior compensation. METHODS: Using a crossover design, 10 overweight and obese men participated in 4-week moderate (MIIT) and high (HIIT) intensity interval training. MIIT consisted of 5-min cycling stages at ± 20% of mechanical work at 45%VO(2)peak, and HIIT consisted of alternate 30-s work at 90%VO(2)peak and 30-s rests, for 30 to 45 min. Assessments included a constant-load exercise test at 45%VO(2)peak for 45 min followed by 60-min recovery. Appetite sensations were measured during the exercise test using a Visual Analog Scale. Food preferences (liking and wanting) were assessed using a computer-based paradigm, and this paradigm uses 20 photographic food stimuli varying along two dimensions, fat (high or low) and taste (sweet or nonsweet). An ad libitum test meal was provided after the constant-load exercise test. RESULTS: Exercise-induced hunger and desire to eat decreased after HIIT, and the difference between MIIT and HIIT in desire to eat approached significance (p = .07). Exercise-induced liking for high-fat nonsweet food tended to increase after MIIT and decreased after HIIT (p = .09). Fat intake decreased by 16% after HIIT, and increased by 38% after MIIT, with the difference between MIIT and HIIT approaching significance (p = .07). CONCLUSIONS: This study provides evidence that energy intake compensation differs between MIIT and HIIT.