MicroRNAs (miRNAs) function as master regulators of gene expression. Recent studies demonstrate that miRNA isoforms (isomiRs) play a unique role in cancer development. Here, we present QuagmiR, the first cloud-based tool to analyze isomiRs from next generation sequencing data. Using a novel and flexible searching algorithm designed for the detection and annotation of heterogeneous isomiRs, it permits extensive customization of the query process and reference databases to meet the user 's diverse research needs. Availability and implementation: QuagmiR is written in Python and can be obtained freely from GitHub (https://github.com/Gu-Lab-RBL-NCI/QuagmiR). QuagmiR can be run from the command line on local machines, as well as on high-performance servers. A web-accessible version of the tool has also been made available for use by academic researchers through the National Cancer Institute-funded Seven Bridges Cancer Genomics Cloud (https://cancergenomicscloud.org).

The main aim of this research is to examine the predictive power of personality traits, as defined by the Big five model of personality in expressing depression, anxiety, and stress with secondary school students of final years. The research was conducted on a sample of 977 secondary school students in the third and fourth grade from ten secondary schools in Niš. The gender structure of the sample was as follows: 397 boys and 607 girls. The following instruments were used in the research: Depression Anxiety Stress Scales (DASS-21; Lovibond and Lovibond, 1995), Big Five Inventory-BFI (John, Donahue and Kentle, 1991). The results showed that the regression model constructed by personal traits (Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to experience) explain 26% of the criterion variable of Anxiety. The largest individual contribution to

Original scientific paper https://doi.org/10.2298/TSCI180308167B This paper analyzes the impact of Trombe wall construction on heating and cooling demands of building with form (rectangular single-store building of about one hundred square meters area) which is common for individual residential buildings in the Republic of Serbia. Trombe wall, as a representative of a passive solar design, was installed on the south wall of the building. Model of the building was made in the Google SketchUp software, while the results of energy performance were obtained using EnergyPlus and jEplus. Parameters of thermal comfort and climatic data for the area of city of Belgrade, Republic of Serbia, were taken into account. Coverage of the south façade was varied, as well as the thickness of the thermal mass and orientation. Energy consumption of the object is discussed, based on obtained results of the analysis. According to comparative analysis of the above mentioned models it can be concluded that the application of the Trombe wall structure on south side may lead to savings of 33% on heating, but also the higher energy consumption for cooling. Total energy consumption on an annual basis is reduced by using this system.

Buildings are one of the biggest energy consumers in urban environments, so its efficient use represents a constant challenge. In public objects and households, a large part of the energy is used for heating and cooling. The orientation of the object, as well as the overall heat transfer coefficient (U-value) of transparent and non-transparent parts of the envelope, can have a significant impact on building energy needs. In this paper, analysis of the influence of different orientations, U-values of envelope elements, and size of windows on annual heating and cooling energy for an office building in city of Nis, Serbia, is presented. Model of the building was made in the Google SketchUp software, while the results of energy performance were obtained using EnergyPlus and jEplus, taking into account the parameters of thermal comfort and climatic data for the area of city of Nis. Obtained results showed that, for varied parameters, the maximum difference in annual heating energy is 15129.4 kWh, i. e per m 2 27.75 kWh/m 2 , while the maximum difference in annual cooling energy is 14356.1 kWh, i. e per m 2 26.33 kWh/m 2. Considering that differences in energy consumption are significant, analysis of these parameters in the early stage of design process can affect on increase of building energy efficiency.

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