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.

Adhesion of osteoblasts to a nanorough titanium implant surface

Abstract: This work considers the adhesion of cells to a nanorough titanium implant surface with sharp edges. The basic assumption was that the attraction between the negatively charged titanium surface and a negatively charged osteoblast is mediated by charged proteins with a distinctive quadrupolar internal charge distribution. Similarly, cation-mediated attraction between fibronectin molecules and the titanium surface is expected to be more efficient for a high surface charge density, resulting in facilitated integrin mediated osteoblast adhesion. We suggest that osteoblasts are most strongly bound along the sharp convex edges or spikes of nanorough titanium surfaces where the magnitude of the negative surface charge density is the highest. It is therefore plausible that nanorough regions of titanium surfaces with sharp edges and spikes promote the adhesion of osteoblasts.

Induced phytoextraction/soil washing of lead using biodegradable chelate and permeable barriers.

Abstract: Chelate-induced remediation has been proposed as an effective tool for the extraction of lead (Pb) from contaminated soils by plants. However, side-effects, mainly mobilization and leaching of Pb, raise environmental concerns. Biodegradable, synthetic organic chelate ethylenediaminedisuccinic acid (EDDS), and commonly used ethylenedimanetetraacetic acid (EDTA) were used for induced phytoextraction with a test plant Brassica rapa and in situ washing of soil contaminated with 1350 mg/kg of Pb. Horizontal permeable barriers were placed 20 cm deep in soil columns and tested for their ability to prevent leaching of Pb. The reactive materials in the barriers were nutrient enriched vermiculite, peat or agricultural hydrogel, and apatite. EDTA and EDDS addition increased Pb concentrations in the test plant by 158 and 89 times compared to the control, to 817 and 464 mg/kg, respectively. In EDTA treatments, approximately 25% or more of total initial soil Pb was leached in single cycle of chelate addition. In EDDS treatments, 20% of the initial Pb was leached from columns with no barrier, while barriers with vermiculite or hydrogel and apatite decreased leaching by more than 60 times, to 0.35%. 11.6% of total initial Pb was washed from the soil above the barrier with vermiculite and apatite, where almost all leached Pb was accumulated. Results indicate that use of biodegradable chelate EDDS and permeable barriers may lead to environmentally safe induced Pb phytoextraction and in situ washing of Pb.

Measurement of the inclusive isolated prompt photon cross section in pp collisions at √s=7TeV with the ATLAS detector

Abstract: A measurement of the cross section for the inclusive production of isolated prompt photons in pp collisions at a center-of-mass energy root s = 7 TeV is presented. The measurement covers the pseudorapidity ranges vertical bar eta(gamma)vertical bar < 1: 37 and 1: 52 <= vertical bar eta(gamma)vertical bar < 1: 81 in the transverse energy range 15 <= E-T(gamma) < 100 GeV. The results are based on an integrated luminosity of 880 nb(-1), collected with the ATLAS detector at the Large Hadron Collider. Photon candidates are identified by combining information from the calorimeters and from the inner tracker. Residual background in the selected sample is estimated from data based on the observed distribution of the transverse isolation energy in a narrow cone around the photon candidate. The results are compared to predictions from next-to-leading-order perturbative QCD calculations.

Weighted and Robust Incremental Method for Subspace Learning

Abstract: Visual learning is expected to be a continuous and robustprocess, which treats input images and pixels selectively.In this paper we present a method for subspace learning,which takes these considerations into account. Wepresent an incremental method, which sequentially updatesthe principal subspace considering weighted influence ofindividual images as well as individual pixels within an image.This approach is further extended to enable determinationof consistencies in the input data and imputation of thevalues in inconsistent pixels using the previously acquiredknowledge, resulting in a novel incremental, weighted androbust method for subspace learning.