Bayesian Networks (BNs) are graphical models which represent multivariate joint probability distributions which have been used successfully in several studies in many application areas. BN learning algorithms can be remarkably effective in many problems. The search space for a BN induction, however, has an exponential dimension. Therefore, finding the BN structure that better represents the dependencies among the variables is known to be a NP problem. This work proposes and discusses a hybrid Bayes/Genetic collaboration (VOGAC-MarkovPC) designed to induce Conditional Independence Bayesian Classifiers from data. The main contribution is the use of MarkovPC algorithm in order to reduce the computational complexity of a Genetic Algorithm (GA) designed to explore the Variable Orderings (VOs) in order to optimize the induced classifiers. Experiments performed in a number of datasets revealed that VOGAC-MarkovPC required less than 25% of the time demanded by VOGAC-PC on average. In addition, when concerning the classification accuracy, VOGAC-MarkovPC performed as well as VOGAC-PC did.
The contribution of snow meltwater to catchment streamflow can be quantified through hydrograph separation analyses for which stable water isotopes (18O, 2H) are used as environmental tracers. For this, the spatial and temporal variability of the isotopic composition of meltwater needs to be captured by the sampling method. This study compares an optimized snowmelt lysimeter system and an unheated precipitation collector with focus on their ability to capture snowmelt rates and the isotopic composition of snowmelt. The snowmelt lysimeter system consists of three individual unenclosed lysimeters at ground level with a surface of 0.14 m2 each. The unheated precipitation collector consists of a 30 cm-long, extended funnel with its orifice at 2.3 m above ground. Daily snowmelt samples were collected with both systems during two snowfall-snowmelt periods in 2016. The snowmelt lysimeter system provided more accurate measurements of natural melt rates and allowed for capturing the small-scale variability of snowmelt process at the plot scale, such as lateral meltwater flow from the surrounding snowpack. Because of the restricted volume of the extended funnel, daily melt rates from the unheated precipitation collector were up to 43% smaller compared to the snowmelt lysimeter system. Overall, both snowmelt collection methods captured the general temporal evolution of the isotopic signature in snowmelt.
In Chajda's paper (2014), to an arbitrary BCI-algebra the author assigned an ordered structure with one binary operation which possesses certain antitone mappings. In the present paper, we show that a similar construction can be done also for pseudo-BCI-algebras, but the resulting structure should have two binary operations and a set of couples of antitone mappings which are in a certain sense mutually inverse. The motivation for this approach is the well-known fact that every commutative BCK-algebra is in fact a join-semilattice and we try to obtain a similar result also for the non-commutative case and for pseudo-BCI-algebras which generalize BCK-algebras, see e.g. Imai and Iséki (1966) and Iséki (1966).
The paper outlines an epistemic logic based on the proof theory of substructural logics. The logic is a formal model of belief that i) is based on true assumptions (BTA belief) and ii) does not suffer from the usual omniscience properties., Článek nastiňuje epistemickou logiku založenou na důkazové teorii substrukturální logiky. Logika je formálním modelem víry, že i) je založena na pravdivých předpokladech (víra BTA) a ii) netrpí obvyklými vševědoucími vlastnostmi., and Igor Sedlár
This paper deals with a certain class of unbounded optimization problems. The optimization problems taken into account depend on a parameter. Firstly, there are established conditions which permit to guarantee the continuity with respect to the parameter of the minimum of the optimization problems under consideration, and the upper semicontinuity of the multifunction which applies each parameter into its set of minimizers. Besides, with the additional condition of uniqueness of the minimizer, its continuity is given. Some examples of nonconvex optimization problems that satisfy the conditions of the article are supplied. Secondly, the theory developed is applied to discounted Markov decision processes with unbounded cost functions and with possibly noncompact actions sets in order to obtain continuous optimal policies. This part of the paper is illustrated with two examples of the controlled Lindley's random walk. One of these examples has nonconstant action sets.
The hormone leptin, which is thought to be primarily produced by adipose tissue, is a polypeptide that was initially characterized by its ability to regulate food intake and energy metabolism. Leptin appears to signal the status of body energy stores to the brain, resulting in the regulation of food intake and whole-body energy expenditure. Subsequently, it was recognized as a cytokine with a wide range of peripheral actions and is involved in the regulation of a number of physiological systems including reproduction. In the fed state, leptin circulates in the plasma in proportion to body adiposity in all species studied to date. However other factors such as sex, age, body mass index (BMI), sex steroids and pregnancy may also affect leptin levels in plasma. In pregnant mice and humans, the placenta is also a major site of leptin expression. Leptin circulates in biological fluids both as free protein and in a form that is bound to the soluble isoform of its receptor or other binding proteins such as one of the immunoglobulin superfamily members Siglec-6 (OBBP1). Although the actions of leptin in the control of reproductive function are thought to be exerted mainly via the hypothalamicpituitary-gonadal axis, there have also been reports of local direct effects of leptin at the peripheral level, however, these data appear contradictory. Therefore, there is a need to summarize the current status of research outcomes and analyze the possible reasons for differing results and thus provide researchers with new insight in designing experiments to investigate leptin effect on reproduction. Most importantly, our recent experimental data suggesting that reproductive performance is improved by decreasing concentrations of peripheral leptin was unexpected and cannot be explained by hypotheses drawn from the experiments of excessive exogenous leptin administration to normal animals or ob/ob mice., M. Herrid, S. K. A. Palanisamy, U. A. Ciller, R. Fan, P. Moens, N. A. Smart, J. R. McFarlane., and Obsahuje bibliografii
Let $G=(V, E)$ be a simple graph. A subset $S\subseteq V$ is a dominating set of $G$, if for any vertex $u\in V-S$, there exists a vertex $v\in S$ such that $uv\in E$. The domination number, denoted by $\gamma (G)$, is the minimum cardinality of a dominating set. In this paper we will prove that if $G$ is a 5-regular graph, then $\gamma (G)\le {5\over 14}n$.
The basis number of a graph $G$ is defined by Schmeichel to be the least integer $h$ such that $G$ has an $h$-fold basis for its cycle space. MacLane showed that a graph is planar if and only if its basis number is $\le 2$. Schmeichel proved that the basis number of the complete graph $K_n$ is at most $3$. We generalize the result of Schmeichel by showing that the basis number of the $d$-th power of $K_n$ is at most $2d+1$.