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.

Rab35 Controls Actin Bundling by Recruiting Fascin as an Effector Protein

Abstract: Actin filaments are key components of the eukaryotic cytoskeleton that provide mechanical structure and generate forces during cell shape changes, growth, and migration. Actin filaments are dynamically assembled into higher-order structures at specified locations to regulate diverse functions. The Rab family of small guanosine triphosphatases is evolutionarily conserved and mediates intracellular vesicle trafficking. We found that Rab35 regulates the assembly of actin filaments during bristle development in Drosophila and filopodia formation in cultured cells. These effects were mediated by the actin-bundling protein fascin, which directly associated with active Rab35. Targeting Rab35 to the outer mitochondrial membrane triggered actin recruitment, demonstrating a role for an intracellular trafficking protein in localized actin assembly.

Decision trees for hierarchical multilabel classification: a case study in functional genomics

Abstract: Hierarchical multilabel classification (HMC) is a variant of classification where instances may belong to multiple classes organized in a hierarchy. The task is relevant for several application domains. This paper presents an empirical study of decision tree approaches to HMC in the area of functional genomics. We compare learning a single HMC tree (which makes predictions for all classes together) to learning a set of regular classification trees (one for each class). Interestingly, on all 12 datasets we use, the HMC tree wins on all fronts: it is faster to learn and to apply, easier to interpret, and has similar or better predictive performance than the set of regular trees. It turns out that HMC tree learning is more robust to overfitting than regular tree learning.

Antennas for the detection of radio emission pulses from cosmic-ray induced air showers at the Pierre Auger Observatory

Abstract: The Pierre Auger Observatory is exploring the potential of the radio detection technique to study extensive air showers induced by ultra-high energy cosmic rays. The Auger Engineering Radio Array (AERA) addresses both technological and scientific aspects of the radio technique. A first phase of AERA has been operating since September 2010 with detector stations observing radio signals at frequencies between 30 and 80 MHz. In this paper we present comparative studies to identify and optimize the antenna design for the final configuration of AERA consisting of 160 individual radio detector stations. The transient nature of the air shower signal requires a detailed description of the antenna sensor. As the ultra-wideband reception of pulses is not widely discussed in antenna literature, we review the relevant antenna characteristics and enhance theoretical considerations towards the impulse response of antennas including polarization effects and multiple signal reflections. On the basis of the vector effective length we study the transient response characteristics of three candidate antennas in the time domain. Observing the variation of the continuous galactic background intensity we rank the antennas with respect to the noise level added to the galactic signal.