Localization length of the 1+11+1 continuum directed random polymer

In this paper, we study the localization length of the $1+1$ continuum directed polymer, defined as the distance between the endpoints of two paths sampled independently from the quenched polymer measure. We show that the localization length converges in distribution in the thermodynamic limit, and derive an explicit density formula of the limiting distribution. As a consequence, we prove the $\tfrac32$-power law decay of the density, confirming the physics prediction of Hwa-Fisher \cite{fisher}. Our proof uses the recent result of Das-Zhu \cite{daszhu}.Comment: v2, 18 pages, minor revision, final versio

Death pathways activated in the neurotrophic factor-deprived neurons

Programed cell death (PCD) is a fundamental biological process that is as essential for the development and tissue homeostasis as cell proliferation, differentiation and adaptation. The main mode of PCD - apoptosis - occurs via specifi c pathways, such as mitochondrial or death receptor pathway. In the developing nervous system, programed death broadly occurs, mainly triggered by the defi ciency of different survival-promoting neurotrophic factors, but the respective death pathways are poorly studied. In one of the best-characterized models, sympathetic neurons deprived of nerve growth factor (NGF) die via the classical mitochondrial apoptotic pathway. The main aim of this study was to describe the death programs activated in these and other neuronal populations by using neuronal cultures deprived of other neurotrophic factors. First, this study showed that the cultured sympathetic neurons deprived of glial cell line-derived neurotrophic factor (GDNF) die via a novel non-classical death pathway, in which mitochondria and death receptors are not involved. Indeed, cytochrome c was not released into the cytosol, Bax, caspase-9, and caspase-3 were not involved, and Bcl-xL overexpression did not prevent the death. This pathway involved activation of mixed lineage kinases and c-jun, and crucially requires caspase-2 and -7. Second, it was shown that deprivation of neurotrophin-3 (NT-3) from cultured sensory neurons of the dorsal root ganglia kills them via a dependence receptor pathway, including cleavage of the NT- 3 receptor TrkC and liberation of a pro-apoptotic dependence domain. Indeed, death of NT-3-deprived neurons was blocked by a dominant-negative construct interfering with TrkC cleavage. Also, the uncleavable mutant of TrkC, replacing the siRNA-silenced endogeneous TrkC, was not able to trigger death upon NT-3 removal. Such a pathway was not activated in another subpopulation of sensory neurons deprived of NGF. Third, it was shown that cultured midbrain dopaminergic neurons deprived of GDNF or brainderived neurotrophic factor (BDNF) kills them by still a different pathway, in which death receptors and caspases, but not mitochondria, are activated. Indeed, cytochrome c was not released into the cytosol, Bax was not activated, and Bcl-xL did not block the death, but caspases were necessary for the death of these neurons. Blocking the components of the death receptor pathway - caspase-8, FADD, or Fas - blocked the death, whereas activation of Fas accelerated it. The activity of Fas in the dopaminergic neurons could be controlled by the apoptosis inhibitory molecule FAIML. For these studies we developed a novel assay to study apoptosis in the transfected dopaminergic neurons. Thus, a novel death pathway, characteristic for the dopaminergic neurons was described. The study suggests death receptors as possible targets for the treatment of Parkinson s disease, which is caused by the degeneration of dopaminergic neurons.Ei saatavill

BIOMECHANICAL CHARACTERISTICS OF KINEMATICS IN LONG JUMPERS

The maximum speed attained by the athlete in broad jump competition is an important objective for the approach phase of the jump. Although the technique of male broad jump athletes has been studied, very little research has focussed on the performance of female high performance broad jump athletes. The purpose of this study was to analyze the characteristics of movement kinematics in three males and three females broad jumpers. A comparison of performance between the males and females was made so as to provide the information for coaches and athletes to improve performance

A Novel MADM Approach Based on Fuzzy Cross Entropy with Interval-Valued Intuitionistic Fuzzy Sets

The paper presents a novel multiple attribute decision-making (MADM) approach for the problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy sets (IVIFS). First, the fuzzy cross entropy and discrimination degree of IVIFS are defied. Subsequently, based on the discrimination degree of IVIFS, a nonlinear programming model to minimize the total deviation of discrimination degrees between alternatives and the positive ideal solution PIS as well as the negative ideal solution (NIS) is constructed to obtain the attribute weights and, then, the weighted discrimination degree. Finally, all the alternatives are ranked according to the relative closeness coefficients using the extended TOPSIS method, and the most desirable alternative is chosen. The proposed approach extends the research method of MADM based on the IVIF cross entropy. Finally, we illustrate the feasibility and validity of the proposed method by two examples

The Supplying Chain Scheduling with the Cost Constraint and Subcontracting

We propose an analytical scheduling model with subcontracting. Each job can be processed either on a single machine at a manufacturer or outsourced to a subcontractor, possibly at a higher cost. For a given set of jobs, the decisions the manufacturer needs to make include the selection of a subset of jobs to be outsourced and the schedule of all the jobs. The objective functions are to minimize the commonly used scheduling measures, subject to a constraint on the total production and subcontracting cost. We show the NP-hardiness for the problems with different objective functions and develop dynamic programming algorithms for solving them

Condition trend prediction of aero-generator based on particle swarm optimization and fuzzy integral

In order to improve and enhance the prediction accuracy and efficiency of aero-generator running trend, grasp its running condition, and avoid accidents happening, in this paper, auto-regressive and moving average model (ARMA) and least squares support vector machine (LSSVM) which are used to predict its running trend have been optimized using particle swarm optimization (PSO) based on using features found in real aero-generator life test, which lasts a long period of time on specialized test platform and collects mass data that reflects aero-generator characteristics, to build new models of PSO-ARMA and PSO-LSSVM. And we use fuzzy integral methodology to carry out decision fusion of the predicted results of these two new models. The research shows that the prediction accuracy of PSO-ARMA and PSO-LSSVM has been much improved on that of ARMA and LSSVM, and the results of decision fusion based on fuzzy integral methodology show further substantial improvement in accuracy than each particle swarm optimized model. Conclusion can be drawn that the optimized model and the decision fusion method presented in this paper are available in aero-generator condition trend prediction and have great value of engineering application