904 resultados para flute players


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Poker is the gambling game that is currently gaining the most in popularity. However, there is little information on poker players' characteristics and risk factors. Furthermore, the first studies described poker players, often recruited in universities, as an homogeneous group who played in only one of the modes (land based or on the Internet). This study aims to identify, through latent class analyses, poker player subgroups. A convenience sample of 258 adult poker players was recruited across Quebec during special events or through advertising in various media. Participants filled out a series of questionnaires (Canadian Problem Gambling Index, Beck Depression, Beck Anxiety, erroneous belief and alcohol/drug consumption). The latent class analysis suggests that there are three classes of poker players. Class I (recreational poker players) includes those who have the lowest probability of engaging intensively in different game modes. Participants in class II (Internet poker players) all play poker on the Internet. This class includes the highest proportion of players who consider themselves experts or professionals. They make a living in part or in whole from poker. Class III (multiform players) includes participants with the broadest variety of poker patterns. This group is complex: these players are positioned halfway between professional and recreational players. Results indicate that poker players are not an homogeneous group identified simply on the basis of the form of poker played. The specific characteristics associated with each subgroup points to vulnerabilities that could potentially be targeted for preventive interventions.

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Soccer is a sport where everyone that is involved with it make all the efforts aiming for excellence. Not only the players need to show their skills on the pitch but also the coach, and the remaining staff, need to have their own tools so that they can perform at higher levels. Footdata is a project to build a new web application product for soccer (football), which integrates two fundamental components of this sport's world: the social and the professional. While the former is an enhanced social platform for soccer professionals and fans, the later can be considered as a Soccer Resource Planning, featuring a system for acquisition and processing information to meet all the soccer management needs. In this paper we focus only in a specific module of the professional component. We will describe the section of the web application that allows to analyse movements and tactics of the players using images directly taken from the pitch or from videos, we will show that it is possible to draw players and ball movements in a web application and detect if those movements occur during a game. © 2014 Springer International Publishing.

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Soccer is a sport where everyone that is involved with it make all the efforts aiming for excellence. Not only the players need to show their skills on the pitch but also the coach, and the remaining staff, need to have their own tools so that they can perform at higher levels. Footdata is a project to build a new web application product for soccer (football), which integrates two fundamental components of this sport’s world: the social and the professional. While the former is an enhanced social platform for soccer professionals and fans, the later can be considered as a Soccer Resource Planning, featuring a system for acquisition and processing information to meet all the soccer management needs. In this paper we focus only in a specific module of the professional component. We will describe the section of the web application that allows to analyse movements and tactics of the players using images directly taken from the pitch or from videos, we will show that it is possible to draw players and ball movements in a web application and detect if those movements occur during a game.

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The aims of this study were to 1) determine the relationship between performance on the court-based TIVRE-Basket® test and peak aerobic power determined from a criterion lab-based incremental treadmill test and 2) to examine the test-retest reliability of the TIVRE-Basket® test in elite male basketball players. To address aim 1, 36 elite male basketball players (age 25.2 + 4.7 years, weight 94.1 + 11.4 kg, height 195.83 + 9.6 cm) completed a graded treadmill exercise test and the TIVRE-Basket® within 72 hours. Mean distance recorded during the TIVRE-Basket® test was 4001.8 + 176.4m, and mean VO2 peak was 54.7 + 2.8 ml.kg.min-1, and the correlation between the two parameters was r=0.824 (P= <0.001). Linear regression analysis identified TIVRE-Basket® distance (m) as the only unique predictor of VO2 peak in a single variable plus constant model: VO2 peak = 2.595 + ((0.13* TIVRE-Basket® distance (m)). Performance on the TIVRE-Basket® test accounted for 67.8% of the variance in VO2 peak (t=8.466, P=<.001, 95% CI 0.01 - 0.016, SEE 1.61). To address aim 2, 20 male basketball players (age 26.7±4.2; height 1.94±0.92; weight 94.0±9.1) performed the TIVRE-Basket® test on two occasions. There was no significant difference in total distance covered between Trial 1 (4138.8 + 677.3m) and Trial 2 (4188.0 + 648.8m; t = 0.5798, P = 0.5688). Mean difference between trials was 49.2 + 399.5m, with an ICC of 0.85 suggesting a moderate level of reliability. Standardised TEM was 0.88%, representing a moderate degree of trial to trial error, and the CV was 6.3%. The TIVRE-Basket® test therefore represents a valid and moderately reliable court-based sport-specific test of aerobic power for use with individuals and teams of elite level male basketball players. Future research is required to ascertain its validity and reliability in other basketball populations e.g. across age groups, at different levels of competition, in females and in different forms of the game e.g. wheelchair basketball.

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This study provides an in depth insight into the current views and opinions of elite level rugby union players regarding the use of performance analysis as a tool for improving their own playing performance and in highlighting the strengths and weaknesses of upcoming opponents. A total of seventy-three elite level rugby union players from two clubs in Great Britain completed a semi-structured questionnaire. Additionally, four players completed a semi-structured interview and following inductive content analysis, four key themes emerged: (1) the use of video for player development, (2) preparing for a match, (3) using video for player reflection in addition to other psychological tools and (4) players suggestions for improvements to the clubs current performance analysis programme. The main finding of the study concludes that players viewed performance analysis as a beneficial and useful tool to support their development and preparation. As a result the study provides an insight into the use of performance analysis within professional rugby union, enabling rugby coaches and practitioners to gain an understanding and appreciation of the players views towards the clubs current provision. Additionally, the findings help build and strengthen the on-going knowledge coaches, analysts and researchers currently have regarding how players perceive performance analysis.

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Spinal cord regenerative ability is lost with development, but the mechanisms underlying this loss are still poorly understood. In chick embryos, effective regeneration does not occur after E13, when spinal cord injury induces extensive apoptotic response and tissue damage. As initial experiments showed that treatment with a calcium chelator after spinal cord injury reduced apoptosis and cavitation, we hypothesized that developmentally regulated mediators of calcium-dependent processes in secondary injury response may contribute to loss of regenerative ability. To this purpose we screened for such changes in chick spinal cords at stages of development permissive (E11) and non-permissive (E15) for regeneration. Among the developmentally regulated calcium-dependent proteins identified was PAD3, a member of the peptidylarginine deiminase (PAD) enzyme family that converts protein arginine residues to citrulline, a process known as deimination or citrullination. This post-translational modification has not been previously associated with response to injury. Following injury, PAD3 up-regulation was greater in spinal cords injured at E15 than at E11. Consistent with these differences in gene expression, deimination was more extensive at the non-regenerating stage, E15, both in the gray and white matter. As deimination paralleled the extent of apoptosis, we investigated the effect of blocking PAD activity on cell death and deiminated-histone 3, one of the PAD targets we identified by mass-spectrometry analysis of spinal cord deiminated proteins. Treatment with the PAD inhibitor, Cl-amidine, reduced the abundance of deiminated-histone 3, consistent with inhibition of PAD activity, and significantly reduced apoptosis and tissue loss following injury at E15. Altogether, our findings identify PADs and deimination as developmentally regulated modulators of secondary injury response, and suggest that PADs might be valuable therapeutic targets for spinal cord injury.

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Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

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Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

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Power systems have been through deep changes in recent years, namely with the operation of competitive electricity markets in the scope and the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new player type which allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles, (V2G) and consumers), to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

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The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

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Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.

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This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

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The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

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Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

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Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in very helpful sophisticated tools. This paper presents a new methodology for the management of coalitions in electricity markets. This approach is tested using the multi-agent market simulator MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), taking advantage of its ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market and internally, with their members in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. A case study using real data from the Iberian Electricity Market is performed to validate and illustrate the proposed approach.