942 resultados para Optimal performance


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We analyze the optimal technology policy to solve a free-riding problem between the members of a RJV. We assume that when intervening the Government suffers an additional adverse selection problem because it is not able to distinguish the value of the potential innovation. Although subsidies and monitoring may be equivalent policy tools to solve firms' free-riding problem, they imply different social losses if the Government is not able to perfectly distinguish the value of the potential innovation. The supremacy of monitoring tools over subsidies is proved to depend on which type of information the Government is able to obtain about firms' R&D performance.

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We study the optimal public intervention in setting minimum standards of formation for specialized medical care. The abilities the physicians obtain by means of their training allow them to improve their performance as providers of cure and earn some monopoly rents.. Our aim is to characterize the most efficient regulation in this field taking into account different regulatory frameworks. We find that the existing situation in some countries, in which the amount of specialization is controlled, and the costs of this process of specialization are publicly financed, can be supported as the best possible intervention.

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The PulseCath iVAC 3L? left ventricular assist device is an option to treat transitory left heart failure or dysfunction post-cardiac surgery. Assisted blood flow should reach up to 3 l/min. In the present in vitro model exact pump flow, depending on various frequencies and afterload was examined. Optimal flow was achieved with inflation/deflation frequencies of about 70-80/min. The maximal flow rate was achieved at about 2.5 l/min with a minimal afterload of 22 mmHg. Handling of the device was easy due to the connection to a standard intra-aortic balloon pump console. With increasing afterload (up to a simulated mean systemic pressure of 66 mmHg) flow rate and cardiac support are in some extent limited.

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The Agglomeration Bonus (AB) is a mechanism to induce adjacent landowners to spatially coordinate their land use for the delivery of ecosystem services from farmland. This paper uses laboratory experiments to explore the performance of the AB in achieving the socially optimal land management configuration in a local network environment where the information available to subjects varies. The AB poses a coordination problem between two Nash equilibria: a Pareto dominant and a risk dominant equilibrium. The experiments indicate that if subjects are informed about both their direct and indirect neighbors’ actions, they are more likely to coordinate on the Pareto dominant equilibrium relative to the case where subjects have information about their direct neighbors’ action only. However, the extra information can only delay – and not prevent – the transition to the socially inferior risk dominant Nash equilibrium. In the long run, the AB mechanism may only be partially effective in enhancing delivery of ecosystem services on farming landscapes featuring local networks.

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We compared the diagnostic performance characteristics of newly developed method, the rapid dipstick test, which provides colorimetric determination by developing antibody to the lactate dehydrogenase enzyme of parasites, with conventional standard thick-blood film examination. For the rapid test, OptiMAL commercial kits were used. The results were also evaluated with clinical findings from patients. The parasites were determined by microscopic examination of thick-blood films from 81 patients with vivax malaria from southeastern Anatolia, Turkey. The OptiMAL test results were found to be negative in five patients who were diagnosed clinically and through thick-film testing as having vivax malaria. There was no false positivity observed with the OptiMAL test. We concluded that this rapid malaria test has a lower level of sensitivity than the classical thick-blood-film test for malaria, but that these methods have equal specificity.

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AbstractPerforming publicly has become increasingly important in a variety of professions. This condition is associated with performance anxiety in almost all performers. Whereas some performers successfully cope with this anxiety, for others it represents a major problem and even threatens their career. Musicians and especially music students were shown to be particularly affected by performance anxiety.Therefore, the goal of this PhD thesis was to gain a better understanding of performance anxiety in university music students. More precisely, the first part of this thesis aimed at increasing knowledge on the occurrence, the experience, and the management of performance anxiety (Article 1). The second part aimed at investigating the hypothesis that there is an underlying hyperventilation problem in musicians with a high level of anxiety before a performance. This hypothesis was addressed in two ways: firstly, by investigating the association between the negative affective dimension of music performance anxiety (MPA) and self-perceived physiological symptoms that are known to co-occur with hyperventilation (Article 2) and secondly, by analyzing this association on the physiological level before a private (audience-free) and a public performance (Article 3). Article 4 places some key variables of Article 3 in a larger context by jointly analyzing the phases before, during, and after performing.The main results of the self-report data show (a) that stage fright is experienced as a problem by one-third of the surveyed students, (b) that the students express a considerable need for more help to better cope with it, and (c) that there is a positive association between negative feelings of MPA and the self-reported hyperventilation complaints before performing. This latter finding was confirmed on the physiological level in a tendency of particularly high performance-anxious musicians to hyperventilate. Furthermore, the psycho-physiological activation increased from a private to a public performance, and was higher during the performances than before or after them. The physiological activation was mainly independent of the MPA score. Finally, there was a low response coherence between the actual physiological activation and the self-reports on the instantaneous anxiety, tension, and perceived physiological activation.Given the high proportion of music students who consider stage fright as a problem and given the need for more help to better cope with it, a better understanding of this phenomenon and its inclusion in the educational process is fundamental to prevent future occupational problems. On the physiological level, breathing exercises might be a good means to decrease - but also to increase - the arousal associated with a public performance in order to meet an optimal level of arousal needed for a good performance.

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In this paper a novel methodology aimed at minimizing the probability of network failure and the failure impact (in terms of QoS degradation) while optimizing the resource consumption is introduced. A detailed study of MPLS recovery techniques and their GMPLS extensions are also presented. In this scenario, some features for reducing the failure impact and offering minimum failure probabilities at the same time are also analyzed. Novel two-step routing algorithms using this methodology are proposed. Results show that these methods offer high protection levels with optimal resource consumption

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In this article we compare regression models obtained to predict PhD students’ academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student’s research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. Academic performance was measured by the weighted number of publications. Two web questionnaires were designed, one for PhD students and one for their supervisors and other research group members. Most of the variables were easily comparable across universities due to the careful translation procedure and pre-tests. When direct comparison was notpossible we created comparable indicators. We used a regression model in which the country was introduced as a dummy coded variable including all possible interaction effects. The optimal transformations of the main and interaction variables are discussed. Some differences between Slovenian and Girona universities emerge. Some variables like supervisor’s performance and motivation for autonomy prior to starting the PhD have the same positive effect on the PhD student’s performance in both countries. On the other hand, variables like too close supervision by the supervisor and having children have a negative influence in both countries. However, we find differences between countries when we observe the motivation for research prior to starting the PhD which increases performance in Slovenia but not in Girona. As regards network variables, frequency of supervisor advice increases performance in Slovenia and decreases it in Girona. The negative effect in Girona could be explained by the fact that additional contacts of the PhD student with his/her supervisor might indicate a higher workload in addition to or instead of a better advice about the dissertation. The number of external student’s advice relationships and social support mean contact intensity are not significant in Girona, but they have a negative effect in Slovenia. We might explain the negative effect of external advice relationships in Slovenia by saying that a lot of external advice may actually result from a lack of the more relevant internal advice

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BACKGROUND: Surgeons' personalities have been described as different from those of the general population, but this was based on small descriptive studies limited by the choice of evaluation instrument. Furthermore, although the importance of the human factor in team performance has been recognized, the effect of personality traits on technical performance is unknown. This study aimed to compare surgical residents' personality traits with those of the general population and to evaluate whether an association exists between their personality traits and technical performance using a virtual reality (VR) laparoscopy simulator. METHODS: In this study, 95 participants (54 residents with basic, 29 with intermediate laparoscopic experience, and 12 students) underwent personality assessment using the NEO-Five Factor Inventory and performed five VR tasks of the Lap Mentor? basic tasks module. The residents' personality traits were compared with those of the general population, and the association between VR performance and personality traits was investigated. RESULTS: Surgical residents showed personality traits different from those of the general population, demonstrating lower neuroticism, higher extraversion and conscientiousness, and male residents showed greater openness. In the multivariable analysis, adjusted for gender and surgical experience, none of the personality traits was found to be an independent predictor of technical performance. CONCLUSIONS: Surgical residents present distinct personality traits that differ from those of the general population. These traits were not found to be associated with technical performance in a virtual environment. The traits may, however, play an important role in team performance, which in turn is highly relevant for optimal surgical performance.

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A new graph-based construction of generalized low density codes (GLD-Tanner) with binary BCH constituents is described. The proposed family of GLD codes is optimal on block erasure channels and quasi-optimal on block fading channels. Optimality is considered in the outage probability sense. Aclassical GLD code for ergodic channels (e.g., the AWGN channel,the i.i.d. Rayleigh fading channel, and the i.i.d. binary erasure channel) is built by connecting bitnodes and subcode nodes via a unique random edge permutation. In the proposed construction of full-diversity GLD codes (referred to as root GLD), bitnodes are divided into 4 classes, subcodes are divided into 2 classes, and finally both sides of the Tanner graph are linked via 4 random edge permutations. The study focuses on non-ergodic channels with two states and can be easily extended to channels with 3 states or more.

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The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

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The achievable region approach seeks solutions to stochastic optimisation problems by: (i) characterising the space of all possible performances(the achievable region) of the system of interest, and (ii) optimisingthe overall system-wide performance objective over this space. This isradically different from conventional formulations based on dynamicprogramming. The approach is explained with reference to a simpletwo-class queueing system. Powerful new methodologies due to the authorsand co-workers are deployed to analyse a general multiclass queueingsystem with parallel servers and then to develop an approach to optimalload distribution across a network of interconnected stations. Finally,the approach is used for the first time to analyse a class of intensitycontrol problems.

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Most research on single machine scheduling has assumedthe linearity of job holding costs, which is arguablynot appropriate in some applications. This motivates ourstudy of a model for scheduling $n$ classes of stochasticjobs on a single machine, with the objective of minimizingthe total expected holding cost (discounted or undiscounted). We allow general holding cost rates that are separable,nondecreasing and convex on the number of jobs in eachclass. We formulate the problem as a linear program overa certain greedoid polytope, and establish that it issolved optimally by a dynamic (priority) index rule,whichextends the classical Smith's rule (1956) for the linearcase. Unlike Smith's indices, defined for each class, ournew indices are defined for each extended class, consistingof a class and a number of jobs in that class, and yieldan optimal dynamic index rule: work at each time on a jobwhose current extended class has larger index. We furthershow that the indices possess a decomposition property,as they are computed separately for each class, andinterpret them in economic terms as marginal expected cost rate reductions per unit of expected processing time.We establish the results by deploying a methodology recentlyintroduced by us [J. Niño-Mora (1999). "Restless bandits,partial conservation laws, and indexability. "Forthcomingin Advances in Applied Probability Vol. 33 No. 1, 2001],based on the satisfaction by performance measures of partialconservation laws (PCL) (which extend the generalizedconservation laws of Bertsimas and Niño-Mora (1996)):PCL provide a polyhedral framework for establishing theoptimality of index policies with special structure inscheduling problems under admissible objectives, which weapply to the model of concern.

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We address the problem of scheduling a multiclass $M/M/m$ queue with Bernoulli feedback on $m$ parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov's optimal solution to the single-server case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (approximate optimality) for Klimov's rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as long as they stay within system capacity;and (ii) the number of servers. It follows that its relativesuboptimality gap vanishes in a heavy-traffic limit, as external arrival rates approach system capacity (heavy-traffic optimality). We obtain simpler expressions for the special no-feedback case, where the heuristic reduces to the classical $c \mu$ rule. Our analysis is based on comparing the expected cost of Klimov's ruleto the value of a strong linear programming (LP) relaxation of the system's region of achievable performance of mean queue lengths. In order to obtain this relaxation, we derive and exploit a new set ofwork decomposition laws for the parallel-server system. We further report on the results of a computational study on the quality of the $c \mu$ rule for parallel scheduling.

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This paper resolves three empirical puzzles in outsourcing by formalizing the adaptationcost of long-term performance contracts. Side-trading with a new partner alongside a long-term contract (to exploit an adaptation-requiring investment) is usually less effective than switching to the new partner when the contract expires. So long-term contracts that prevent holdup of specific investments may induce holdup of adaptation investments. Contract length therefore trades of specific and adaptation investments. Length should increase with the importance and specificity of self-investments, and decrease with the importance of adaptation investments for which side-trading is ineffective. My general model also shows how optimal length falls with cross-investments and wasteful investments.