University of Ljubljana

About: University of Ljubljana is a education organization based out in Ljubljana, Slovenia. It is known for research contribution in the topics: Population & Liquid crystal. The organization has 17210 authors who have published 47013 publications receiving 1082684 citations. The organization is also known as: Univerza v Ljubljani.

Woody biomass production lags stem-girth increase by over one month in coniferous forests

Abstract: Wood is the main terrestrial biotic reservoir for long-term carbon sequestration(1), and its formation in trees consumes around 15% of anthropogenic carbon dioxide emissions each year(2). However, the seasonal dynamics of woody biomass production cannot be quantified from eddy covariance or satellite observations. As such, our understanding of this key carbon cycle component, and its sensitivity to climate, remains limited. Here, we present high-resolution cellular based measurements of wood formation dynamics in three coniferous forest sites in northeastern France, performed over a period of 3 years. We show that stem woody biomass production lags behind stem-girth increase by over 1 month. We also analyse more general phenological observations of xylem tissue formation in Northern Hemisphere forests and find similar time lags in boreal, temperate, subalpine and Mediterranean forests. These time lags question the extension of the equivalence between stem size increase and woody biomass production to intra-annual time scales(3, 4, 5, 6). They also suggest that these two growth processes exhibit differential sensitivities to local environmental conditions. Indeed, in the well-watered French sites the seasonal dynamics of stem-girth increase matched the photoperiod cycle, whereas those of woody biomass production closely followed the seasonal course of temperature. We suggest that forecasted changes in the annual cycle of climatic factors(7) may shift the phase timing of stem size increase and woody biomass production in the future.

Quasilocal charges in integrable lattice systems

Abstract: We review recent progress in understanding the notion of locality in integrable quantum lattice systems. The central concept concerns the so-called quasilocal conserved quantities, which go beyond the standard perception of locality. Two systematic procedures to rigorously construct families of quasilocal conserved operators based on quantum transfer matrices are outlined, specializing on anisotropic Heisenberg XXZ spin-1/2 chain. Quasilocal conserved operators stem from two distinct classes of representations of the auxiliary space algebra, comprised of unitary (compact) representations, which can be naturally linked to the fusion algebra and quasiparticle content of the model, and non-unitary (non-compact) representations giving rise to charges, manifestly orthogonal to the unitary ones. Various condensed matter applications in which quasilocal conservation laws play an essential role are presented, with special emphasis on their implications for anomalous transport properties (finite Drude weight) and relaxation to non-thermal steady states in the quantum quench scenario.

Comparison of logistic regression and linear discriminant analysis : a simulation study

Abstract: Two of the most widely used statistical methods for analyzing categorical outcome variables are linear discrimina nt analysis and logistic regression. While both are appropriate for the deve lopment of linear classification models, linear discriminant analysis makes more assumptions about the underlying data. Hence, it is assumed tha t logistic regression is the more flexible and more robust method in case of violations of these assumptions. In this paper we consider the problem of choosing between the two methods, and set some guidelines for proper cho ice. The comparison between the methods is based on several measures of predictive accuracy. The performance of the methods is studied by simula tions. We start with an example where all the assumptions of the linear dis criminant analysis are satisfied and observe the impact of changes regardi ng the sample size, covariance matrix, Mahalanobis distance and directi on of distance between group means. Next, we compare the robustness of the methods towards categorisation and non-normality of explanatory var iables in a closely controlled way. We show that the results of LDA and LR are close whenever the normality assumptions are not too badl y violated, and set some guidelines for recognizing these situations. W e discuss the inappropriateness of LDA in all other cases.