Redundancy in nonlinear systems: A set covering approach.

In this thesis we present Boneh\u27s Set Covering (SC) approach to the redundancy detection problem, and we show that his approach is also applicable to the related problem of finding a Prime Representation (PR), an Irreducible Infeasible System (IIS) or a Minimal Infeasible System (MIS). In order to generate the SC matrix E, we need a probabilistic method for sampling points in Rn. Consequently we can assign a detection probability to each row of E, and we show that if a row of E has a zero detection probability, then it must correspond to what we call a local quasi-minimizer We show that convex systems have no such local quasi-minimizers.Dept. of Economics, Mathematics, and Statistics. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1999 .F46. Source: Masters Abstracts International, Volume: 39-02, page: 0516. Adviser: Richard J. Caron. Thesis (M.Sc.)--University of Windsor (Canada), 1999

A design of resonant inelastic X-ray scattering (RIXS) spectrometer for spatial- and time-resolved spectroscopy.

The optical design of a Hettrick-Underwood-style soft X-ray spectrometer with Wolter type 1 mirrors is presented. The spectrometer with a nominal length of 3.1 m can achieve a high resolving power (resolving power higher than 10000) in the soft X-ray regime when a small source beam (<3 µm in the grating dispersion direction) and small pixel detector (5 µm effective pixel size) are used. Adding Wolter mirrors to the spectrometer before its dispersive elements can realize the spatial imaging capability, which finds applications in the spectroscopic studies of spatially dependent electronic structures in tandem catalysts, heterostructures, etc. In the pump-probe experiments where the pump beam perturbs the materials followed by the time-delayed probe beam to reveal the transient evolution of electronic structures, the imaging capability of the Wolter mirrors can offer the pixel-equivalent femtosecond time delay between the pump and probe beams when their wavefronts are not collinear. In combination with some special sample handing systems, such as liquid jets and droplets, the imaging capability can also be used to study the time-dependent electronic structure of chemical transformation spanning multiple time domains from microseconds to nanoseconds. The proposed Wolter mirrors can also be adopted to the existing soft X-ray spectrometers that use the Hettrick-Underwood optical scheme, expanding their capabilities in materials research

A Monte Carlo Study of Erraticity Behavior in Nucleus-Nucleus Collisions at High Energies

It is demonstrated using Monte Carlo simulation that in different nucleus$-$nucleus collision samples, the increase of the fluctuation of event factorial moments with decreasing phase space scale, called erraticity, is still dominated by the statistical fluctuations. This result does not depend on the Monte Carlo models. Nor does it depend on the concrete conditions, e.g. the collision energy, the mass of colliding nuclei, the cut of phase space, etc.. This means that the erraticity method is sensitive to the appearance of novel physics in the central collisions of heavy nuclei.Comment: 9 pages, 4 figures (in eps form

Hardware/software partitioning algorithm based on the combination of genetic algorithm and tabu search

To solve the hardware/software (HW/SW) partitioning problem of a single Central Processing Unit (CPU) system, a hybrid algorithm of Genetic Algorithm (GA) and Tabu Search(TS) is studied. Firstly, the concept hardware orientation is proposed and then used in creating the initial colony of GA and the mutation, which reduces the randomicity of initial colony and the blindness of search. Secondly, GA is run, the crossover and mutation probability become smaller in the process of GA, thus they not only ensure a big search space in the early stages, but also save the good solution for later browsing. Finally, the result of GA is used as initial solution of TS, and tabu length adaptive method is put forward in the process of TS, which can improve the convergence speed. From experimental statistics, the efficiency of proposed algorithm outperforms comparison algorithm by up to 25% in a large-scale problem, what is more, it can obtain a better solution. In conclusion, under specific conditions, the proposed algorithm has higher efficiency and can get better solutions

Automatic Deduction Path Learning via Reinforcement Learning with Environmental Correction

Automatic bill payment is an important part of business operations in fintech companies. The practice of deduction was mainly based on the total amount or heuristic search by dividing the bill into smaller parts to deduct as much as possible. This article proposes an end-to-end approach of automatically learning the optimal deduction paths (deduction amount in order), which reduces the cost of manual path design and maximizes the amount of successful deduction. Specifically, in view of the large search space of the paths and the extreme sparsity of historical successful deduction records, we propose a deep hierarchical reinforcement learning approach which abstracts the action into a two-level hierarchical space: an upper agent that determines the number of steps of deductions each day and a lower agent that decides the amount of deduction at each step. In such a way, the action space is structured via prior knowledge and the exploration space is reduced. Moreover, the inherited information incompleteness of the business makes the environment just partially observable. To be precise, the deducted amounts indicate merely the lower bounds of the available account balance. To this end, we formulate the problem as a partially observable Markov decision problem (POMDP) and employ an environment correction algorithm based on the characteristics of the business. In the world's largest electronic payment business, we have verified the effectiveness of this scheme offline and deployed it online to serve millions of users

Exponential Cluster Synchronization of Neural Networks with Proportional Delays

Exponential cluster synchronization of neural networks with proportional delays is studied in this paper. Unlike previous constant delay or bounded time delay, we consider the time-varying proportional delay is unbounded, less conservative, and more widely applied. Furthermore, we designed a novel adaptive controller based on Lyapunov function and inequality technique to achieve exponential cluster synchronization for neural networks and by using a unique way of equivalent system we proved the main conclusions. Finally, an example is given to illustrate the effectiveness of our proposed method

Prostaglandin E(2 )receptor subtype 2 (EP2) regulates microglial activation and associated neurotoxicity induced by aggregated α-synuclein

BACKGROUND: The pathogenesis of idiopathic Parkinson's disease (PD) remains elusive, although evidence has suggested that neuroinflammation characterized by activation of resident microglia in the brain may contribute significantly to neurodegeneration in PD. It has been demonstrated that aggregated α-synuclein potently activates microglia and causes neurotoxicity. However, the mechanisms by which aggregated α-synuclein activates microglia are not understood fully. METHODS: We investigated the role of prostaglandin E(2 )receptor subtype 2 (EP2) in α-synuclein aggregation-induced microglial activation using ex vivo, in vivo and in vitro experimental systems. RESULTS: Results demonstrated that ablation of EP2(EP2(-/-)) significantly enhanced microglia-mediated ex vivo clearance of α-synuclein aggregates (from mesocortex of Lewy body disease patients) while significantly attenuating neurotoxicity and extent of α-synuclein aggregation in mice treated with a parkinsonian toxicant 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. Furthermore, we report that reduced neurotoxicity by EP2(-/- )microglia could be attributed to suppressed translocation of a critical cytoplasmic subunit (p47-phox) of NADPH oxidase (PHOX) to the membranous compartment after exposure to aggregated α-synuclein. CONCLUSION: Thus, it appears that microglial EP2 plays a critical role in α-synuclein-mediated neurotoxicity