University of Warsaw

About: University of Warsaw is a education organization based out in Warsaw, Poland. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 20832 authors who have published 56617 publications receiving 1185084 citations. The organization is also known as: Uniwersytet Warszawski & Warsaw University.

Abundance and systematics of nuclear superdeformed states; relation to the pseudospin and pseudo-SU(3) symmetries.

Abstract: Results of a multidimensional (${\ensuremath{\beta}}_{2}$, \ensuremath{\gamma}, ${\ensuremath{\beta}}_{4}$, \ensuremath{\omega}, Z, and N) search for nuclear superdeformed configurations are presented. Calculations based on a realistic deformed average field give a relatively strong dependence of the ``super'' elongation on the particle number. This dependence is shown to be a cyclic function of the particle number. It originates from the pseudospin and pseudo-SU(3) symmetries which are obeyed approximately in a realistic average field.

Is quasar optical variability a damped random walk

Abstract: The damped random walk (DRW) model is increasingly used to model the variability in quasar optical light curves, but it is still uncertain whether the DRW model provides an adequate description of quasar optical variability across all time scales. Using a sample of OGLE quasar light curves, we consider four modifications to the DRW model by introducing additional parameters into the covariance function to search for deviations from the DRW model on both short and long time scales. We find good agreement with the DRW model on time scales that are well sampled by the data (from a month to a few years), possibly with some intrinsic scatter in the additional parameters, but this conclusion depends on the statistical test employed and is sensitive to whether the estimates of the photometric errors are correct to within ∼10%. On very short time scales (below a few months), we see some evidence of the existence of a cutoff below which the correlation is stronger than the DRW model, echoing the recent finding of Mushotzky et al. (2011) using quasar light curves from Kepler. On very long time scales (> a few years), the light curves do not constrain models well, but are consistent with the DRW model. Subject headings: galaxies: active — galaxies: statistics — methods: data analysis — methods: numerical — methods: statistical

Solving Connectivity Problems Parameterized by Treewidth in Single Exponential Time

Abstract: For the vast majority of local problems on graphs of small tree width (where by local we mean that a solution can be verified by checking separately the neighbourhood of each vertex), standard dynamic programming techniques give c^tw |V|^O(1) time algorithms, where tw is the tree width of the input graph G = (V, E) and c is a constant. On the other hand, for problems with a global requirement (usually connectivity) the best -- known algorithms were naive dynamic programming schemes running in at least tw^tw time. We breach this gap by introducing a technique we named Cut&Count that allows to produce c^tw |V|^O(1) time Monte Carlo algorithms for most connectivity-type problems, including Hamiltonian Path, Steiner Tree, Feedback Vertex Set and Connected Dominating Set. These results have numerous consequences in various fields, like parameterized complexity, exact and approximate algorithms on planar and H-minor-free graphs and exact algorithms on graphs of bounded degree. The constant c in our algorithms is in all cases small, and in several cases we are able to show that improving those constants would cause the Strong Exponential Time Hypothesis to fail. In contrast to the problems aiming to minimize the number of connected components that we solve using Cut&Count as mentioned above, we show that, assuming the Exponential Time Hypothesis, the aforementioned gap cannot be breached for some problems that aim to maximize the number of connected components like Cycle Packing.

Influence of environmental abiotic factors on the content of saponins in plants

Abstract: Saponins are a large group of secondary metabolites occurring in significant amounts in many plant species. However, the saponin content of plants is variable and it can be influenced by the surrounding environment. The local geoclimate, seasonal changes, external conditions such as light, temperature, humidity and soil fertility, as well as cultivation techniques, affect both the quantitative amount and qualitative composition of saponins. Such variation substantially impacts on the quality and properties of wild and cultivated plants exploited for pharmaceutical, nutritional and industrial applications. This review summarizes the available data on the effects of abiotic environmental factors on saponin level in plants, especially those of considerable economic importance, highlighting current problems such as the reduction in natural plant resources, over-exploitation and destruction of wild habitats, climate shifts as well as the consequences of the growing demand for plant-derived medicinal and industrial products. The need for a theoretical basis for a reasonable harvest, attempts at the domestication of wild plant species and the development of new agricultural technologies allowing high production under optimized conditions are also discussed.