Abstract:
In this paper the approach to solving several combinatorial optimization problems using the local search and the genetic algorithm techniques is proposed. Initially this approach was developed in purpose to overcome some difficulties inhibiting the application of above mentioned techniques to the problems of the Questionnaire Theory. But when the algorithms were developed it became clear that them could be successfully applied also to the Minimum Set Cover, the 0-1-Knapsack and probably to other combinatorial optimization problems.

Abstract:
In this article we consider the inversion problem for polynomially computable discrete functions. These functions describe behavior of many discrete systems and are used in model checking, hardware verification, cryptanalysis, computer biology and other domains. Quite often it is necessary to invert these functions, i.e. to find an unknown preimage if an image and algorithm of function computation are given. In general case this problem is computationally intractable. However, many of it's special cases are very important in practical applications. Thus development of algorithms that are applicable to these special cases is of importance. The practical applicability of such algorithms can be validated by their ability to solve the problems that are considered to be computationally hard (for example cryptanalysis problems). In this article we propose the technology of solving the inversion problem for polynomially computable discrete functions. This technology was implemented in distributed computing environments (parallel clusters and Grid-systems). It is based on reducing the inversion problem for the considered function to some SAT problem. We describe a general approach to coarse-grained parallelization for obtained SAT problems. Efficiency of each parallelization scheme is determined by the means of a special predictive function. The proposed technology was validated by successful solving of cryptanalysis problems for some keystream generators. The main practical result of this work is a complete cryptanalysis of keystream generator A5/1 which was performed in a Grid system specially built for this task.

Abstract:
Species of Euphorbia with a widespread distribution often show variability. In Somalia such variation is found in populations of E. cuneata Vahl and the complexes surrounding E. nubica N. E. Br., E. nigrispina Pax and E. xylacantha Pax. Possible undescribed taxa are also found in forms of more restricted species within Somalia, such as E. multiclava Bally& S. Carter and the more recently described E. umbonata S. Carter and E. atrox S. Carter. Espècies d'Euphorbio d'àmplia distribució mostren sovint variabilitat. A Somàlia, aquesta variació es presenta en poblacions d'E. cuneata Vahl i en els complexos que envolten E. nubica N. E. Br., E. nigrispina Pax i E. xylacantha Pax. Formes de possibles tàxons encara no descrits es troben dins les espècies d'àrea més restringida a Somàlia, com és el cas d'E. multiclava Bally & S. Carter i de les més recentment descrites E. umbonata S. Carter i E. atrox S. Carter.

Abstract:
We consider zeta functions: $Z(f ;P ;s)=\sum_{\m \in \N^{n}} f(m_1,..., m_n) P(m_1,..., m_n)^{-s/d}$ where $P \in \R [X_1,..., X_n]$ has degree $d$ and $f$ is a function arithmetic in origin, e.g. a multiplicative function. In this paper, I study the meromorphic continuation of such series beyond an a priori domain of absolute convergence when $f$ and $P$ satisfy properties one typically meets in applications. As a result, I prove an explicit asymptotic for a general class of lattice point problems subject to arithmetic constraints.

Abstract:
Objective The lack of the disease biomarker to support objective laboratory tests still constitutes a bottleneck in the clinical diagnosis and evaluation of major depressive disorder (MDD) and its subtypes. We used metabonomic techniques to screen the diagnostic biomarker panels from the plasma of MDD patients with and without early life stress (ELS) experience. Methods Plasma samples were collected from 25 healthy adults and 46 patients with MDD, including 23 patients with ELS and 23 patients without ELS. Furthermore, gas chromatography/mass spectrometry (GC/MS) coupled with multivariate statistical analysis was used to identify the differences in global plasma metabolites among the 3 groups. Results The distinctive metabolic profiles exist either between healthy subjects and MDD patients or between the MDD patients with ELS experience (ELS/MDD patients) and the MDD patients without it (non-ELS/MDD patients), and some diagnostic panels of feature metabolites' combination have higher predictive potential than the diagnostic panels of differential metabolites. Conclusions These findings in this study have high potential of being used as novel laboratory diagnostic tool for MDD patients and it with ELS or not in clinical application.

Abstract:
This article analyzes the relationship between the automatic segmentation of Chinese words and natural language processing and that between the automatic segmentation of Chinese words and information retrieval. Then based on the analysis, it introduces principles that the automatic segmentation of Chinese words abides by. Finally it discusses some related problems faced by the application of it in information retrieval.

Abstract:
In this article we apply and discuss El-Desouky technique to derive a generalization of the problem of selecting k balls from an n-line with no two adjacent balls being s-separation. We solve the problem in which the separation of the adjacent elements is not having odd and even separation. Also we enumerate the number of ways of selecting k objects from n-line objects with no two adjacent being of separations m, m + 1, …, pm, where p is positive integer. Moreover we discuss some applications on these problems.

Abstract:
This is a survey of some problems in geometric group theory which I find interesting. The problems are from different areas of group theory. Each section is devoted to problems in one area. It contains an introduction where I give some necessary definitions and motivations, problems and some discussions of them. For each problem, I try to mention the author. If the author is not given, the problem, to the best of my knowledge, was formulated by me first.

Abstract:
The data source was a Canadian longitudinal study called the National Population Health Survey (NPHS). A simulation model representing the course of depressive episodes was used to reshape estimates deriving from binary and ordinal logistic models (fit to the NPHS data) into equations more capable of informing clinical and public health decisions. Discrete event simulation was used for this purpose. Whereas the intention was to clarify a complex epidemiology, the models themselves needed to become excessively complex in order to provide an accurate description of the data.Simulation methods are useful in circumstances where a representation of a real-world system has practical value. In this particular scenario, the usefulness of simulation was limited both by problems with the data source and by inherent complexity of the underlying epidemiology.Major Depressive Disorder (MDD) is a mood disorder that is characterized by one or more major depressive episodes (MDE). Clinical practice guidelines for MDD have historically regarded the diagnosis as a de facto indication of treatment need (e.g.[1]). However, in community studies application of diagnostic criteria for MDD has been shown to identify some short lived episodes that may not be associated with a need for treatment [2]. This has led to more recent recommendations acknowledging the apparent heterogeneity of this condition. For example, in the strategy of "watchful waiting" treatment may be delayed for several weeks while there is ongoing monitoring in order to determine whether an episode will resolve without active treatment [3]. For mild episodes, guided self-management has also been proposed as a reasonable intervention [3,4].It would be helpful to make use of epidemiologic data in order to quantify the probability of various outcomes and ultimately to use this information as a means of supporting clinical decisions. Recently, the predictD study has reported predictive algorithms for the risk of MDE in genera