Jožef Stefan Institute

About: Jožef Stefan Institute is a facility organization based out in Ljubljana, Slovenia. It is known for research contribution in the topics: Liquid crystal & Dielectric. The organization has 3828 authors who have published 12614 publications receiving 291025 citations.

How Bad Metals Turn Good: Spectroscopic Signatures of Resilient Quasiparticles

Abstract: We investigate transport in strongly correlated metals. Within dynamical mean-field theory, we calculate the resistivity, thermopower, optical conductivity and thermodynamic properties of a hole-doped Mott insulator. Two well-separated temperature scales are identified: ${T}_{\mathrm{FL}}$ below which Landau Fermi liquid behavior applies, and ${T}_{\mathrm{MIR}}$ above which the resistivity exceeds the Mott-Ioffe-Regel value and bad-metal behavior is found. We show that quasiparticle excitations remain well defined above ${T}_{\mathrm{FL}}$ and dominate transport throughout the intermediate regime ${T}_{\mathrm{FL}}\ensuremath{\lesssim}T\ensuremath{\lesssim}{T}_{\mathrm{MIR}}$. The lifetime of these resilient quasiparticles is longer for electronlike excitations and this pronounced particle-hole asymmetry has important consequences for the thermopower. The crossover into the bad-metal regime corresponds to the disappearance of these excitations and has clear signatures in optical spectroscopy.

On Estimating Probabilities in Tree Pruning

Abstract: In this paper we introduce a new method for decision tree pruning, based on the minimisation of the expected classification error method by Niblett and Bratko. The original Niblett-Bratko pruning algorithm uses Laplace probability estimates. Here we introduce a new, more general Bayesian approach to estimating probabilities which we call m-probability-estimation. By varying a parameter m in this method, tree pruning can be adjusted to particular properties of the learning domain, such as level of noise. The resulting pruning method improves on the original Niblett-Bratko pruning in the following respects: apriori probabilities can be incorporated into error estimation, several trees pruned to various degrees can be generated, and the degree of pruning is not affected by the number of classes. These improvements are supported by experimental findings. m-probability-estimation also enables the combination of learning data obtained from various sources.

The Role of Interferons in Inflammation and Inflammasome Activation.

Abstract: Inflammation is an essential physiological process which enables survival during infection and maintains tissue homeostasis. Interferons and pro- and anti- inflammatory cytokines are crutial for appropriate response to pathogens, damaged cells or irritants in inflamamtory response. The inflammasom is multiprotein complex which initiates cleavage of pro-inflammatory cytokines IL-1β and IL-18 into active forms. In addition, inflammasomes initiate pyroptotic cell death. In the present review I summarize and analyze recent findings regarding the crosstalk of interferons and inflammasomes.

EFFTRAN : A Monte Carlo efficiency transfer code for gamma-ray spectrometry

Abstract: An implementation of the efficiency transfer method for cylindrical samples in gamma-ray spectrometry is presented, based on a Monte Carlo integration of the interaction probabilities of gamma rays over the detector and sample volumes. This approach makes it possible for the computer code to be relatively straightforward to write and the speed of the calculation to be adequate for routine on-line analysis of gamma-ray spectra. Virtual components of the detector system are introduced to prevent any erroneous or double counting of gamma-ray paths, which simplifies the tracking algorithm.