The spatial distribution of the young objects of varioue age groups -
HII regions and open clusters - in the Saglttarius-Carina arm (SC arm) at 1 « 280°- 25° ie Inyestlgated. Both transverse and longitudinal age gradients have been found in the arm, Two giant star formation complexes with the size of about 1 kpc at 1 = 285°-300° at 1 = 340°-20° are existed, Each of them contains several giant HII regions, a number of glant moleoular clouds (GMCa) and some extremely young clusters, Between these complexes we have found an elder one of the same aime.This complex contains 24 (3-6)»10^7 years old clusters and a small number of faint HII regions. Assuming that it is a remnant of a
giant star formation complex the upper limit of lifetimes for such complexes and GMCs is (3-6)•10^7 years,
The estimations of spiral pattem parameters are made.The value of the pitch-angle is 21°+3°. The value of spiral pattem velocity, -26.8+2.2 km/s«kpc, leads us to conclusion that the Sun is near the oorrotation radius of the Galaxy. The star formation efficiency in
these complexes is discussed.
The imbalance of an edge e = {u, v} in a graph is defined as i(e) = |d(u)−d(v)|, where d(·) is the vertex degree. The irregularity I(G) of G is then defined as the sum of imbalances over all edges of G. This concept was introduced by Albertson who proved that I(G)\leqslant 4n^{3}/27 (where n = |V(G)|) and obtained stronger bounds for bipartite and triangle-free graphs. Since then a number of additional bounds were given by various authors. In this paper we prove a new upper bound, which improves a bound found by Zhou and Luo in 2008. Our bound involves the Laplacian spectral radius λ., Felix Goldberg., and Obsahuje seznam literatury
We outline a solution method for mixed finite element discretizations based on dissecting the problem into three separate steps. The first handles the inhomogeneous constraint, the second solves the flux variable from the homogeneous problem, whereas the third step, adjoint to the first, finally gives the Lagrangian multiplier. We concentrate on aspects involved in the first and third step mainly, and advertise a multi-level method that allows for a stable computation of the intermediate and final quantities in optimal computational complexity.
Over the past 40 years, much has been published on the ultrastructure and cellular development of embryonic structures in a wide range of cestodes. However, the literature contains many discrepancies in both terminology and interpretations because of the facts that these organisms are phylogenetically diverse within their respective orders and families, the habitats that affect embryonic envelope structure are diverse, and the work has been done in various laboratories around the world. This review and synthesis was initiated by a working group of biologists from around the world convened at the Fifth International Workshop on Cestode Systematics and Phylogeny in České Budĕjovice, at the Institute of Parasitology of the Biology Centre, Academy of Sciences of the Czech Republic. It brings together the data from published work and establishes a uniform terminology and interpretation based on the data as they are presented. A consensus was reached for standardised definitions of the oncosphere, hexacanth, coracidium, embryonic envelopes, outer envelope, inner envelope, embryophore, vitelline capsule, shell, and outer coat. All of these are defined as components of the embryo or its vitellocyte-derived or uterine-derived coatings.
Different methods for Blind Source Separation (BSS) have been recently proposed. Most of these methods are suitable for separating either a mixture of sub-Gaussian source or a mixture of super-Gaussian sources. In this paper, a unified statistical approach for separating the mixture of sub-Gaussian and super-Gaussian source is proposed. Source separation techniques use an objective function to be optimized. The optimization process requires probability density function to be expressed in the terms of the random variable. Two different density models have been used for representing sub-Gaussian and super-Gaussian sources. Optimization of the objective function yields different nonlinear functions. Kurtosis has been ušed as measure of Gaussianity of a source. Depending upon the sign of kurtosis one of the nonlinearities is ušed in the proposed algorithm. Simulations with artificiaily generated as well as audio signals demonstrate effectiveness of the proposed approach.
A short approach to the Kurzweil-Henstock integral is outlined, based on approximating a real function on a compact interval by suitable step-functions, and using filterbase convergence to define the integral. The properties of the integral are then easy to establish.
The contribution focuses on the design of a control algorithm aimed at the operative control of runoff water from a reservoir during flood situations. Management is based on the stochastically specified forecast of water inflow into the reservoir. From a mathematical perspective, the solved task presents the control of a dynamic system whose predicted hydrological input (water inflow) is characterised by significant uncertainty. The algorithm uses a combination of simulation model data, in which the position of the bottom outlets is sought via nonlinear optimisation methods, and artificial intelligence methods (adaptation and fuzzy model). The task is written in the technical computing language MATLAB using the Fuzzy Logic Toolbox.
In this paper, we consider a distributed stochastic computation of AXB=C with local set constraints over an multi-agent system, where each agent over the network only knows a few rows or columns of matrixes. Through formulating an equivalent distributed optimization problem for seeking least-squares solutions of AXB=C, we propose a distributed stochastic mirror-descent algorithm for solving the equivalent distributed problem. Then, we provide the sublinear convergence of the proposed algorithm. Moreover, a numerical example is also given to illustrate the effectiveness of the proposed algorithm.
Maintaining liquid asset portfolios involves a high carry cost and is mandatory by law for most financial institutions. Taking this into account a financial institution's aim is to manage a liquid asset portfolio in an "optimal" way, such that it keeps the minimum required liquid assets to comply with regulations. In this paper we propose a multi-stage dynamic stochastic programming model for liquid asset portfolio management. The model allows for portfolio rebalancing decisions over a multi-period horizon, as well as for flexible risk management decisions, such as reinvesting coupons, at intermediate time steps. We show how our problem closely relates to insurance products with guarantees and utilize this in the formulation. We will discuss our formulation and implementation of a multi-stage stochastic programming model that minimizes the down-side risk of these portfolios. The model is back-tested on real market data over a period of two years