Especificação do tipo intervalar parametrizado em CASL

The interval datatype applications in several areas is important to construct a interval type reusable, i.e., a interval constructor can be applied to any datatype and get intervals this datatype. Since the interval is, of certain form, a set of elements limited for two bounds, left and right, with a order notions, then it s reasonable that interval constructor enclose datatypes with partial order. On the order hand, what we want is work with interval of any datatype like this we work with this datatype then. it s important to guarantee the properties of the datatype when maps to interval of this datatype. Thus, the interval constructor get a theory to parametrized interval type, i.e., a interval with generics parameters (for example rational, real, complex). Sometimes, the interval application in some algebras doesn t guarantee the mainutenance of their properties, for example, when we use interval of real, that satisfies the field properties, it doesn t guarantee the distributivity propertie. A form to surpass this problem Santiago introduced the local equality theory that weakened the notion of strong equality, and thus, allowing some properties are local keeped, what can be discard before. The interval arithmetic generalization aim to apply the interval constructor on ordered algebras weakened for local equality with the purpose of the keep their properties. How the intervals are important in applications with continuous data, it s interesting specify that theory using a specification language that supply a system development using intervals of form disciplined, trustworth and safe. Currently, the algebraic specification language, based in math models, have been use to that intention often. We choose CASL (Common Algebraic Specification Language) among others languages because CASL has several characteristics excellent to parametrized interval type, such as, provide parcialiy and parametrization

New Approach on Robust Delay-Dependent H∞ Control for Uncertain T-S Fuzzy Systems With Interval Time-Varying Delay

This paper investigates the robust H∞ control for Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delay. By employing a new and tighter integral inequality and constructing an appropriate type of Lyapunov functional, delay-dependent stability criteria are derived for the control problem. Because neither any model transformation nor free weighting matrices are employed in our theoretical derivation, the developed stability criteria significantly improve and simplify the existing stability conditions. Also, the maximum allowable upper delay bound and controller feedback gains can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples are given to demonstrate the effectiveness of the proposed methods.

Deletion mapping suggests that the 1p22 melanoma susceptibility gene is a tumor suppressor localized to a 9-Mb interval

Loss of the short arm of chromosome 1 is frequently observed in many tumor types, including melanoma. We recently localized a third melanoma susceptibility locus to chromosome band 1p22. Critical recombinants in linked families localized the gene to a 15-Mb region between D1S430 and D1S2664. To map the locus more finely we have performed studies to assess allelic loss across the region in a panel of melanomas from 1p22-linked families, sporadic melanomas, and melanoma cell lines. Eighty percent of familial melanomas exhibited loss of heterozygosity (LOH) within the region, with a smallest region of overlapping deletions (SRO) of 9 Mb between D1S207 and D1S435. This high frequency of LOH makes it very likely that the susceptibility locus is a tumor suppressor. In sporadic tumors, four SROs were defined. SRO1 and SRO2 map within the critical recombinant and familial tumor region, indicating that one or the other is likely to harbor the susceptibility gene. However, SRO3 may also be significant because it overlaps with the markers with the highest 2-point LOD score (D1S2776), part of the linkage recombinant region, and the critical region defined in mesothelioma. The candidate genes PRKCL2 and GTF2B, within SRO2, and TGFBR3, CDC7, and EVI5, in a broad region encompassing SRO3, were screened in 1p22-linked melanoma kindreds, but no coding mutations were detected. Allelic loss in melanoma cell lines was significantly less frequent than in fresh tumors, indicating that this gene may not be involved late in progression, such as in overriding cellular senescence, necessary for the propagation of melanoma cells in culture.

‘Expected satiety’ changes hunger and fullness in the inter-meal interval

Previously, we have shown that foods differ markedly in the satiety that they are expected to confer (compared calorie-for-calorie). In the present study we tested the hypothesis that ‘expected satiety’ plays a causal role in the satiety that is experienced after a food has been consumed. Before lunch, participants (N = 32) were shown the ingredients of a fruit smoothie. Half were shown a small portion of fruit and half were shown a large portion. Participants then assessed the expected satiety of the smoothie and provided appetite ratings, before, and for three hours after its consumption. As anticipated, expected satiety was significantly higher in the ‘large portion’ condition. Moreover, and consistent with our hypothesis, participants reported significantly less hunger and significantly greater fullness in the large portion condition. Importantly, this effect endured throughout the test period (for three hours). Together, these findings confirm previous reports indicating that beliefs and expectations can have marked effects on satiety and they show that this effect can persist well into the inter-meal interval. Potential explanations are discussed, including the prospect that satiety is moderated by memories of expected satiety that are encoded around the time that a meal is consumed.

Influence of high-intensity interval training on adaptations in well-trained cyclists

The purpose of the present study was to examine the influence of 3 different high-intensity interval training regimens on the first and second ventilatory thresholds (VT1 and VT2), anaerobic capacity (ANC), and plasma volume (PV) in well-trained endurance cyclists. Before and after 2 and 4 weeks of training, 38 well-trained cyclists (VO2peak = 64.5 +/- 5.2 ml[middle dot]kg-1[middle dot]min-1) performed (a) a progressive cycle test to measure VO2peak, peak power output (PPO), VT1, and VT2; (b) a time to exhaustion test (Tmax) at their VO2peak power output (Pmax); and (c) a 40-km time-trial (TT40). Subjects were assigned to 1 of 4 training groups (group 1: n = 8, 8 3 60% Tmax at Pmax, 1:2 work-recovery ratio; group 2: n = 9, 8 x 60% Tmax at Pmax, recovery at 65% maximum heart rate; group 3: n = 10, 12 x 30 seconds at 175% PPO, 4.5-minute recovery; control group: n = 11). The TT40 performance, VO2peak, VT1,VT2, and ANC were all significantly increased in groups 1, 2, and 3 (p < 0.05) but not in the control group. However, PV did not change in response to the 4-week training program. Changes in TT40 performance were modestly related to the changes in VO2peak, VT1, VT2, and ANC (r = 0.41, 0.34, 0.42, and 0.40, respectively; all p < 0.05). In conclusion, the improvements in TT40 performance were related to significant increases in VO2peak, VT1,VT2, and ANC but were not accompanied by significant changes in PV. Thus, peripheral adaptations rather than central adaptations are likely responsible for the improved performances witnessed in well-trained endurance athletes following various forms of high-intensity interval training programs.

Interval training program optimization in highly trained endurance cyclists

PURPOSE: The purpose of this study was to examine the influence of three different high-intensity interval training (HIT) regimens on endurance performance in highly trained endurance athletes. METHODS: Before, and after 2 and 4 wk of training, 38 cyclists and triathletes (mean +/- SD; age = 25 +/- 6 yr; mass = 75 +/- 7 kg; VO(2peak) = 64.5 +/- 5.2 mL x kg(-1) min(-1)) performed: 1) a progressive cycle test to measure peak oxygen consumption (VO(2peak)) and peak aerobic power output (PPO), 2) a time to exhaustion test (T(max)) at their VO(2peak) power output (P(max)), as well as 3) a 40-km time-trial (TT(40)). Subjects were matched and assigned to one of four training groups (G(2), N = 8, 8 x 60% T(max) at P(max), 1:2 work:recovery ratio; G(2), N = 9, 8 x 60% T(max) at P(max), recovery at 65% HR(max); G(3), N = 10, 12 x 30 s at 175% PPO, 4.5-min recovery; G(CON), N = 11). In addition to G(1), G(2), and G(3) performing HIT twice per week, all athletes maintained their regular low-intensity training throughout the experimental period. RESULTS: All HIT groups improved TT(40) performance (+4.4 to +5.8%) and PPO (+3.0 to +6.2%) significantly more than G(CON) (-0.9 to +1.1%; P < 0.05). Furthermore, G(1) (+5.4%) and G(2) (+8.1%) improved their VO(2peak) significantly more than G(CON) (+1.0%; P < 0.05). CONCLUSION: The present study has shown that when HIT incorporates P(max) as the interval intensity and 60% of T(max) as the interval duration, already highly trained cyclists can significantly improve their 40-km time trial performance. Moreover, the present data confirm prior research, in that repeated supramaximal HIT can significantly improve 40-km time trial performance.

The role of intensity of interval training on fat oxidation and eating behaviour in overweight/obese men

The increasing prevalence of obesity in society has been associated with a number of atherogenic risk factors such as insulin resistance. Aerobic training is often recommended as a strategy to induce weight loss, with a greater impact of high-intensity levels on cardiovascular function and insulin sensitivity, and a greater impact of moderate-intensity levels on fat oxidation. Anaerobic high-intensity (supramaximal) interval training has been advocated to improve cardiovascular function, insulin sensitivity and fat oxidation. However, obese individuals tend to have a lower tolerance of high-intensity exercise due to discomfort. Furthermore, some obese individuals may compensate for the increased energy expenditure by eating more and/or becoming less active. Recently, both moderate- and high-intensity aerobic interval training have been advocated as alternative approaches. However, it is still uncertain as to which approach is more effective in terms of increasing fat oxidation given the issues with levels of fitness and motivation, and compensatory behaviours. Accordingly, the objectives of this thesis were to compare the influence of moderate- and high-intensity interval training on fat oxidation and eating behaviour in overweight/obese men. Two exercise interventions were undertaken by 10-12 overweight/obese men to compare their responses to study variables, including fat oxidation and eating behaviour during moderate- and high-intensity interval training (MIIT and HIIT). The acute training intervention was a methodological study designed to examine the validity of using exercise intensity from the graded exercise test (GXT) - which measured the intensity that elicits maximal fat oxidation (FATmax) - to prescribe interval training during 30-min MIIT. The 30-min MIIT session involved 5-min repetitions of workloads 20% below and 20% above the FATmax. The acute intervention was extended to involve HIIT in a cross-over design to compare the influence of MIIT and HIIT on eating behaviour using subjective appetite sensation and food preference through the liking and wanting test. The HIIT consisted of 15-sec interval training at 85 %VO2peak interspersed by 15-sec unloaded recovery, with a total mechanical work equal to MIIT. The medium term training intervention was a cross-over 4-week (12 sessions) MIIT and HIIT exercise training with a 6-week detraining washout period. The MIIT sessions consisted of 5-min cycling stages at ±20% of mechanical work at 45 %VO2peak, and the HIIT sessions consisted of repetitive 30-sec work at 90 %VO2peak and 30-sec interval rests, during identical exercise sessions of between 30 and 45 mins. Assessments included a constant-load test (45 %VO2peak for 45 mins) followed by 60-min recovery at baseline and the end of 4-week training, to determine fat oxidation rate. Participants’ responses to exercise were measured using blood lactate (BLa), heart rate (HR) and rating of perceived exertion (RPE) and were measured during the constant-load test and in the first intervention training session of every week during training. Eating behaviour responses were assessed by measuring subjective appetite sensations, liking and wanting and ad libitum energy intake. Results of the acute intervention showed that FATmax is a valid method to estimate VO2 and BLa, but is not valid to estimate HR and RPE in the MIIT session. While the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax (0.16 ±0.09 and 0.14 ±0.08 g/min, respectively), fat oxidation was significantly higher at minute 25 of MIIT (P≤0.01). In addition, there was no significant difference between MIIT and HIIT in the rate of appetite sensations after exercise, but there was a tendency towards a lower rate of hunger after HIIT. Different intensities of interval exercise also did not affect explicit liking or implicit wanting. Results of the medium-term intervention indicated that current interval training levels did not affect body composition, fasting insulin and fasting glucose. Maximal aerobic capacity significantly increased (P≤0.01) (2.8 and 7.0% after MIIT and HIIT respectively) during GXT, and fat oxidation significantly increased (P≤0.01) (96 and 43% after MIIT and HIIT respectively) during the acute constant-load exercise test. RPE significantly decreased after HIIT greater than MIIT (P≤0.05), and the decrease in BLa was greater during the constant-load test after HIIT than MIIT, but this difference did not reach statistical significance (P=0.09). In addition, following constant-load exercise, exercise-induced hunger and desire to eat decreased after HIIT greater than MIIT but were not significant (p value for desire to eat was 0.07). Exercise-induced liking of high-fat sweet (HFSW) and high-fat non-sweet (HFNS) foods increased after MIIT and decreased after HIIT (p value for HFNS was 0.09). The intervention explained 12.4% of the change in fat intake (p = 0.07). This research is significant in that it confirmed two points in the acute study. While the rate of fat oxidation increased during MIIT, the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax. In addition, manipulating the intensity of acute interval exercise did not affect appetite sensations and liking and wanting. In the medium-term intervention, constant-load exercise-induced fat oxidation significantly increased after interval training, independent of exercise intensity. In addition, desire to eat, explicit liking for HFNS and fat intake collectively confirmed that MIIT is accompanied by a greater compensation of eating behaviour than HIIT. Findings from this research will assist in developing exercise strategies to provide obese men with various training options. In addition, the finding that overweight/obese men expressed a lower RPE and decreased BLa after HIIT compared with MIIT is contrary to the view that obese individuals may not tolerate high-intensity interval training. Therefore, high-intensity interval training can be advocated among the obese adult male population. Future studies may extend this work by using a longer-term intervention.

Effect of aerobic interval training and caffeine on blood platelet function

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.

Effect of interval training intensity on fat oxidation, blood lactate and the rate of perceived exertion in obese men

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.

Event interval analysis: Why do processes take time?

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.

Facial emotion modulates the neural mechanisms responsible for short interval time perception

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.

Acute interval exercise intensity does not affect appetite and nutrient preferences in overweight and obese males

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.

Metabolic and hormonal responses to isoenergetic high-intensity interval exercise and continuous moderate-intensity exercise

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.

Interval training intensity affects energy intake compensation in obese men

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.