939 resultados para TOT (time of task)


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The evolution of surface water waves in finite depth under wind forcing is reduced to an antidissipative Korteweg-de Vries-Burgers equation. We exhibit its solitary wave solution. Antidissipation accelerates and increases the amplitude of the solitary wave and leads to blow-up and breaking. Blow-up occurs in finite time for infinitely large asymptotic space so it is a nonlinear, dispersive, and antidissipative equivalent of the linear instability which occurs for infinite time. Due to antidissipation two given arbitrary and adjacent planes of constant phases of the solitary wave acquire different velocities and accelerations inducing breaking. Soliton breaking occurs in finite space in a time prior to the blow-up. We show that the theoretical growth in amplitude and the time of breaking are both testable in an existing experimental facility.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Resistive-type of superconducting fault current limiters (RSFCL) have been developed for medium voltage class aiming to operate at 1 MVA power capacity and short time recovery (< 2 s). A RSFCL in form of superconducting modular device was designed and constructed using 50 m-length of YBCO coated conductor tapes for operation under 1 kV / 1 kA and acting time of 0.1 s. In order to increase the acting time the RSFCL was combined with an air-core reactor in parallel to increase the fault limiting time up to 1 s. The tests determined the electrical and thermal characteristics of the combined resistive/ inductive protection unit. The combined fault current limiter reached a limiting current of 583 A, corresponding to a limiting factor of 3.3 times within an acting time of up to 1 s.

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The aim of this study was to compare time-motion indicators during judo matches performed by athletes from different age groups. The following age groups were analysed: Pre-Juvenile (13-14 years, n=522), Juvenile (15-16 years, n 353); Junior (19 years, n = 349) and Senior (>20 years, n = 587). The time-motion indicators included: Total Combat Time, Standing Combat Time, Displacement Without Contact, Gripping Time, Groundwork Combat Time and Pause Time. Analysis of variance (ANOVA) one-way and the Tukey test, as well as the Kruskal-Wallis test and Mann-Whitney (for non-parametric data), were conducted, using P < 0.05 as significance level. The results showed that all analysed groups obtained a median of 7 (first quantile - 3, third quantile - 12) sequences of combat/pause cycles. In total time of combat, the result was: for Total Combat Time, Standing Combat Time and Gripping Time: Pre-Juvenile and Senior were significantly longer than Juvenile and Junior. Considering Displacement Without Contact, Junior was significantly longer than all other age groups. For Groundwork Combat Time, Senior was significantly longer than all other age groups and Pre-Juvenile was longer than Junior. These results can be used to improve the physiological performance in intermittent practices, as well as technicaltactical training during judo sessions.

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The symptoms of lumbar disc herniation, such as low back pain and sciatica, have been associated with local release of cytokines following the inflammatory process induced by the contact of the nucleus pulposus (NP) with the spinal nerve. Using an animal experimental model of intervertebral disc herniation and behavioral tests to evaluate mechanical (electronic von Frey test) and thermal (Hargreaves Plantar test) hyperalgesia in the hind paw of rats submitted to the surgical model, this study aimed to detect in normal intervertebral disc the cytokines known to be involved in the mechanisms of inflammatory hyperalgesia, to observe if previous exposure of the intervertebral disc tissue to specific antibodies could affect the pain behavior (mechanical and thermal hyperalgesia) induced by the NP, and to observe the influence of the time of contact of the NP with the fifth lumbar dorsal root ganglion (L5-DRG) in the mechanical and thermal hyperalgesia. The cytokines present at highest concentrations in the rat NP were TNF-alpha, IL-1 beta and CINC-1. Rats submitted to the disc herniation experimental model, in which a NP from the sacrococcygeal region is deposited over the right L5-DRG, showed increased mechanical and thermal hyperalgesia that lasted at least 7 weeks. When the autologous NP was treated with antibodies against the three cytokines found at highest concentrations in the NP (TNF-alpha, IL-1 beta and CINC-1), there was decrease in both mechanical and thermal hyperalgesia in different time points, suggesting that each cytokine may be important for the hyperalgesia in different steps of the inflammatory process. The surgical remotion of the NP from herniated rats 1 week after the implantation reduced the hyperalgesia to the level similar to the control group. This reduction in the hyperalgesia was also observed in the group that had the NP removed 3 weeks after the implantation, although the intensity of the hyperalgesia did not decreased totally. The removal of the NP after 5 weeks did not changed the hyperalgesia observed in the hind paw, which suggests that the longer the contact of the NP with the DRG, the greater is the possibility of development of chronic pain. Together our results indicate that specific cytokines released during the inflammatory process induced by the herniated intervertebral disc play fundamental role in the development of the two modalities of hyperalgesia (mechanical and thermal) and that the maintenance of this inflammation may be the most important point for the chronification of the pain.

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Electrothermomechanical MEMS are essentially microactuators that operate based on the thermoelastic effect induced by the Joule heating of the structure. They can be easily fabricated and require relatively low excitation voltages. However, the actuation time of an electrothermomechanical microdevice is higher than the actuation times related to electrostatic and piezoelectric actuation principles. Thus, in this research, we propose an optimization framework based on the topology optimization method applied to transient problems, to design electrothermomechanical microactuators for response time reduction. The objective is to maximize the integral of the output displacement of the actuator, which is a function of time. The finite element equations that govern the time response of the actuators are provided. Furthermore, the Solid Isotropic Material with Penalization model and Sequential Linear Programming are employed. Finally, a smoothing filter is implemented to control the solution. Results aiming at two distinct applications suggest the proposed approach can provide more than 50% faster actuators. (C) 2012 Elsevier B.V. All rights reserved.

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Two hundred eighty-eight 32-wk-old Hisex White laying hens were used in this research during a 10 weeks period, arranged in a 2 x 5 completely randomized factorial design, with three replicates of eight birds per treatment. Two groups: fish oil (OP) and Marine Algae (AM) with five DHA levels (120, 180, 240, 300 and 360 mg/100 g diet) were assigned including two control groups birds fed corn and soybean basal diet (CON) and a diet supplemented with AM (AM420) to study the effect of time 0, 2, 4, 6 and 8 weeks (wk) on the efficiency of egg yolk fatty acid enrichment. The means varied (p<0.01) of 17.63% (OP360) to 22.08% (AM420) is the total Polyunsaturated Fatty Acids (PUFAs) and 45.8 mg/g (OP360), 40.37 mg/g (OP360, 4 wk) to 65.82 mg/g (AM420) and 68.79 mg/g/yolk (AM120, 8 wk) for n-6 PUFAs. On the influence of sources and levels in the times, the means of n-3 PUFAs increased by 5.58 mg/g (AM120, 2 wk) to 14.16 mg/g (OP360, 6 wk) when compared to average of 3.34 mg PUFAs Ω/g/yolk (CON). Usually, the means DHA also increased from 22.34 (CON) to 176.53 mg (μ, OP360), 187.91 mg (OP360, 8 wk) and 192.96 mg (OP360, 6 wk) and 134.18 mg (μ, OP360), 135.79 mg (AM420, 6 wk), 149.75 mg DHA (AM420, 8 wk) per yolk. The opposite was observed for the means AA, so the effect of the sources, levels and times, decreased (P <0.01) of 99.83 mg (CON) to 31.99 mg (OP360, 4 wk), 40.43 mg (μ, OP360) to 61.21 mg (AM420) and 71.51 mg AA / yolk (μ, AM420). Variations of the average weight of 15.75g (OP360) to 17.08g (AM420) yolks of eggs de 32.55% (AM420) to 34.08% (OP360) of total lipids and 5.28 g (AM240) to 5.84 g (AM120) of fat in the yolk were not affected (p>0.05) by treatments, sources, levels and times studied. Starting of 2 week, the hens increased the level of n-3 PUFAs in the egg yolks, being expressively increased (p<0.01) until 4 weeks, which after the increased levels of n-3 PUFAs tended to if stabilize around of time of 8 experimental weeks, when it was more effective saturation of the tissues and yolk.

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Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and flexible method- ology for automatically learning ontology from textual data, lightening the human workload required for conceptualizing domain-specific knowledge and populating an extracted schema with real data, speeding up the whole ontology production process. Here computational linguistics plays a fundamental role, from automati- cally identifying facts from natural language and extracting frame of relations among recognized entities, to producing linked data with which extending existing knowledge bases or creating new ones. In the state of the art, automatic ontology learning systems are mainly based on plain-pipelined linguistics classifiers performing tasks such as Named Entity recognition, Entity resolution, Taxonomy and Relation extraction [11]. These approaches present some weaknesses, specially in capturing struc- tures through which the meaning of complex concepts is expressed [24]. Humans, in fact, tend to organize knowledge in well-defined patterns, which include participant entities and meaningful relations linking entities with each other. In literature, these structures have been called Semantic Frames by Fill- 6 Introduction more [20], or more recently as Knowledge Patterns [23]. Some NLP studies has recently shown the possibility of performing more accurate deep parsing with the ability of logically understanding the structure of discourse [7]. In this work, some of these technologies have been investigated and em- ployed to produce accurate ontology schemas. The long-term goal is to collect large amounts of semantically structured information from the web of crowds, through an automated process, in order to identify and investigate the cognitive patterns used by human to organize their knowledge.

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The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

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The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

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Delayed occlusion time in parent artery occlusion of brain-supplying vessels might carry risk for thromboembolic complications. Vascular plug devices are successfully used in cardiopulmonary and peripheral interventions to occlude high-flow lesions and have been adapted for use in neurointerventions. The purpose of the present study was to experimentally evaluate the immediate occlusion time of the AMPLATZER vascular plug (AVP) II-a second-generation cylindrical, self-expandable, resheathable nitinol wire mesh consisting of three lobes-in the carotid artery.