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.

Quantitative Detection of the nosZ Gene, Encoding Nitrous Oxide Reductase, and Comparison of the Abundances of 16S rRNA, narG, nirK, and nosZ Genes in Soils

Abstract: Nitrous oxide (N2O) is an important greenhouse gas in the troposphere controlling ozone concentration in the stratosphere through nitric oxide production. In order to quantify bacteria capable of N2O reduction, we developed a SYBR green quantitative real-time PCR assay targeting the nosZ gene encoding the catalytic subunit of the nitrous oxide reductase. Two independent sets of nosZ primers flanking the nosZ fragment previously used in diversity studies were designed and tested (K. Kloos, A. Mergel, C. Rosch, and H. Bothe, Aust. J. Plant Physiol. 28:991-998, 2001). The utility of these real-time PCR assays was demonstrated by quantifying the nosZ gene present in six different soils. Detection limits were between 10(1) and 10(2) target molecules per reaction for all assays. Sequence analysis of 128 cloned quantitative PCR products confirmed the specificity of the designed primers. The abundance of nosZ genes ranged from 10(5) to 10(7) target copies g(-1) of dry soil, whereas genes for 16S rRNA were found at 10(8) to 10(9) target copies g(-1) of dry soil. The abundance of narG and nirK genes was within the upper and lower limits of the 16S rRNA and nosZ gene copy numbers. The two sets of nosZ primers gave similar gene copy numbers for all tested soils. The maximum abundance of nosZ and nirK relative to 16S rRNA was 5 to 6%, confirming the low proportion of denitrifiers to total bacteria in soils.

Stereo matching by training a convolutional neural network to compare image patches

Abstract: We present a method for extracting depth information from a rectified image pair. Our approach focuses on the first stage of many stereo algorithms: the matching cost computation. We approach the problem by learning a similarity measure on small image patches using a convolutional neural network. Training is carried out in a supervised manner by constructing a binary classification data set with examples of similar and dissimilar pairs of patches. We examine two network architectures for this task: one tuned for speed, the other for accuracy. The output of the convolutional neural network is used to initialize the stereo matching cost. A series of post-processing steps follow: cross-based cost aggregation, semiglobal matching, a left-right consistency check, subpixel enhancement, a median filter, and a bilateral filter. We evaluate our method on the KITTI 2012, KITTI 2015, and Middlebury stereo data sets and show that it outperforms other approaches on all three data sets.

A Computational Guide to Physics of Eclipsing Binaries. I. Demonstrations and Perspectives

Abstract: PHOEBE (PHysics Of Eclipsing BinariEs) is a modeling package for eclipsing binary stars, built on top of the widely used WD program of Wilson & Devinney. This introductory paper gives an overview of the most important scientific extensions (incorporating observational spectra of eclipsing binaries into the solution-seeking process, extracting individual temperatures from observed color indices, main-sequence constraining, and proper treatment of the reddening), numerical innovations (suggested improvements to WD's differential corrections method, the new Nelder & Mead downhill simplex method), and technical aspects (back-end scripter structure, graphical user interface). While PHOEBE retains 100% WD compatibility, its add-ons are a powerful way to enhance WD by encompassing even more physics and solution reliability. The operability of all these extensions is demonstrated on a synthetic main-sequence test binary; applications to real data will be published in follow-up papers. PHOEBE is released under the GNU General Public License, which guarantees it to be free and open to anyone interested in joining in on future development.

Impacts of the COVID-19 Pandemic on Life of Higher Education Students: A Global Perspective

Abstract: The paper presents the most comprehensive and large-scale study to date on how students perceive the impacts of the first wave of COVID-19 crisis in early 2020 on various aspects of their lives on a global level. With a sample of 30,383 students from 62 countries, the study reveals that amid the worldwide lockdown and transition to online learning students were most satisfied with the support provided by teaching staff and their universities’ public relations. Still, deficient computer skills and the perception of a higher workload prevented them from perceiving their own improved performance in the new teaching environment. Students were mainly concerned about issues to do with their future professional career and studies, and experienced boredom, anxiety, and frustration. The pandemic has led to the adoption of particular hygienic behaviours (e.g., wearing masks, washing hands) and discouraged certain daily practices (e.g., leaving home, shaking hands). Students were also more satisfied with the role played by hospitals and universities during the epidemic compared to the governments and banks. The findings also show that students with certain socio-demographic characteristics (male, part-time, first-level, applied sciences, a lower living standard, from Africa or Asia) were significantly less satisfied with their academic work/life during the crisis, whereas female, full-time, first-level students and students faced with financial problems were generally affected more by the pandemic in terms of their emotional life and personal circumstances. Key factors influencing students’ satisfaction with the role of their university are also identified. Policymakers and higher education institutions around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.