Miracle-dz/UniFAR-FTUs huggingface dataset:
MAD2B-mediated cell cycle reentry of podocytes is involved in the pathogenesis of FSGS

Rationale: Focal segmental glomerulosclerosis (FSGS) is characterized by the dysfunction of “post-mitotic” podocytes. The reentry of podocytes in the cell cycle will ultimately result in cell death. Mitotic arrest deficient 2-like protein 2 (MAD2B), an inhibitor of anaphase-promoting complex (APC)/cyclosome, precisely controls the metaphase to anaphase transition and ordered cell cycle progression. However, the role of MAD2B in FSGS podocyte injury remains unknown. Methods: To explore MAD2B function in podocyte cell cycle reentry, we used conditional mutant mice lacking MAD2B selectively in podocytes in ADR-induced FSGS murine model. Additionally, KU-55933, a specific inhibitor of ataxia-telangiectasia mutated (ATM) was utilized in vivo and in vitro to explore the role of ATM in regulating MAD2B. Results: The expression of MAD2B in podocytes was dramatically increased in patients with FSGS and ADR-treated mice along with podocyte cell cycle reentry. Podocyte-specific knockout of MAD2B effectively attenuated proteinuria, podocyte injury, and prevented the aberrant cell cycle reentry. By bioinformatics analysis we revealed that ATM kinase is a key upstream regulator of MAD2B. Furthermore, inhibition of ATM kinase abolished MAD2B-driven cell cycle reentry and alleviated podocyte impairment in FSGS murine model. In vitro studies by site-directed mutagenesis and immunoprecipitation we revealed ATM phosphorylated MAD2B and consequently hampered the ubiquitination of MAD2B in a phosphorylation-dependent manner. Conclusions: ATM kinase-MAD2B axis importantly contributes to the cell cycle reentry of podocytes, which is a novel pathogenic mechanism of FSGS, and may shed light on the development of its therapeutic approaches.
Chemical composition and biological activities of essential oil from turmeric (Curcuma longa L.) rhizomes grown in Amazonian Ecuador

La curcuma ( Curcuma longa L.) es una planta perenne herbacea y con rizomas ampliamente cultivada en las regiones tropicales y subtropicales del mundo. Se han reportado multiples actividades farmacologicas del aceite esencial de los rizomas. En este trabajo se estudio la composicion quimica, asi como las actividades antioxidante y antimicrobiana del aceite esencial de los rizomas cultivados en el Ecuador amazonico. El aceite esencial se obtuvo por destilacion por arrastre con vapor. Los analisis se hicieron por cromatografia de gases con detectores de llama de hidrogeno y selectivo de masas. Se identificaron 88 compuestos en el aceite esencial. Los compuestos oxigenados fueron la clase quimica mas representativa con 63,6 %. Entre ellos, la ar -turmerona (45,5 %) y α-turmerona (13,4 %) fueron los mas abundantes. Los hidrocarburos sesquiterpenicos fueron la segunda mayor clase (18,0 %) con el α-zingibereno (5,3 %) como predominante. Otro constituyente mayoritario fue el hidrocarburo monoterpenico α-felandreno (6,3 %). La capacidad antioxidante fue evaluada en el aceite esencial mediante los metodos del 1,1-difenil-2-picril-hidrazilo (DPPH) y el poder antioxidante reductor del ferrico (FRAP). El aceite esencial mostro una baja actividad antioxidante por ambos metodos, mientras que tuvo actividad antibacteriana, contra bacterias gram positiva ( Bacillus subtilis and Staphylococcus aureus ) y Pennicilium citrinum . No se encontro actividad antimicrobiana frente a Escherichia coli , Salmonella Enteritidis y Aspergillus niger .
THE K-THEORY OF THE 
${\mathit{C}}^{\star }$
 -ALGEBRAS OF 2-RANK GRAPHS ASSOCIATED TO COMPLETE BIPARTITE GRAPHS

Abstract Using a result of Vdovina, we may associate to each complete connected bipartite graph $\kappa $ a two-dimensional square complex, which we call a tile complex, whose link at each vertex is $\kappa $ . We regard the tile complex in two different ways, each having a different structure as a $2$ -rank graph. To each $2$ -rank graph is associated a universal $C^{\star }$ -algebra, for which we compute the K-theory, thus providing a new infinite collection of $2$ -rank graph algebras with explicit K-groups. We determine the homology of the tile complexes and give generalisations of the procedures to complexes and systems consisting of polygons with a higher number of sides.
Anticancer Activity of Biogenic Selenium Nanoparticles: Apoptotic and Immunogenic Cell Death Markers in Colon Cancer Cells

Simple Summary Colorectal cancer remains a major health problem worldwide, with high prevalence and mortality rates. Innovative approaches and advanced therapeutic anticancer strategies need to be developed. In this frame, the aim of the present study was to assess the potential of biogenic selenium nanoparticles, produced by a probiotic microorganism, to induce apoptotic and immunogenic cell death in colon cancer cell lines. The findings of the present study confirmed that treatment of colon cancer cell lines with selenium nanoparticles induced pro-apoptotic and immunogenic cell death markers (indicating immunogenic cell death) and highlighted their potential to provide an efficient strategy for destroying tumour cells not only directly by apoptotic cell death, but also indirectly through enhanced immunogenicity. Abstract Colorectal cancer is a health problem with high mortality rates and prevalence. Thus, innovative treatment approaches need to be developed. Biogenic nanoparticles are nanomaterials that can be synthesised in biological systems and, compared to chemically synthesised nanoparticles, have better bioavailability while being more cost-effective, eco-friendlier, and less toxic. In our previous studies, the probiotic strain Lactobacillus casei ATCC 393 was used to synthesise selenium nanoparticles (SeNps), which were shown to inhibit colon cancer cell growth in vitro and in vivo. Herein, we have further investigated SeNps’ pro-apoptotic activity and their ability to induce immunogenic cell death (ICD) in colon cancer cells. The SeNps’ effect on Caco-2 cells growth was examined along with their potential to induce caspase activation. Moreover, the expression of typical pro-apoptotic and ICD markers were examined in SeNps-treated HT29 and CT26 cells by flow cytometry, Western blot, ELISA and fluorescence microscopy. Elevated caspase-3 activation and surface phosphatyldoserine, that subsided upon co-incubation with a pan-caspase inhibitor, were detected in SeNps-treated cells. Furthermore, nanoparticles induced modulation of the expression of various apoptosis-related proteins. We also report the detection of biomarkers involved in ICD, namely the translocation of calreticulin and ERp57, the release of HMGB1 and ATP, and the secretion of pro-inflammatory cytokines from SeNps-treated cells. Moreover, RAW246.7 macrophages exhibited a higher rate of phagocytosis against treated CT26 when compared to control cells. Taken together, our findings indicate that treatment with SeNps might be an efficient strategy to destroy tumour cells by inducing apoptotic cell death and triggering immune responses.
Genetic diversity and functional connectivity of a critically endangered salamander

Habitat loss and fragmentation are among the greatest threats to biodiversity since unsuitable habitat can be a significant barrier to gene flow, disrupting the connectivity of populations. In this scenario, landscape genetic approaches have been applied as invaluable tools to demonstrate how contemporary habitat alterations affect gene flow. In this study, we used nine microsatellite genotypes to determine the landscape features driving genetic diversity, structure, and functional connectivity among eleven sampling sites of a micro‐endemic, and critically endangered salamander (Pseudoeurycea robertsi) in the Nevado de Toluca Volcano. We also modelled the ecological niche of P. robertsi to assess the most important habitat features associated with its probability of presence and analyzed the corridor network to identify important core areas and corridors to keep the network connected, as well as points where the network connection is lost or tightened. Moreover, we performed a redundancy analysis to assess the effect of genetic distance and habitat resistances on gene flow. We found the highest levels of genetic diversity and connectivity at the northwestern part of the Volcano. Meson Viejo sampling site was of especial importance to overall network connectivity. We found low levels of migration rates and low levels of genetic structure. The most important habitat feature associated with probability of presence of Pseudoeurycea robertsi was the Abies forest, and two models were significant under the RDA analysis: Abies forest and Abies forest+Grasslands. We recommend prioritizing the areas of the northwestern and central parts of the volcano in conservation programs.
RESEARCH REGARDING THE IMPLEMENTATION, DEVELOPMENT AND IMPACT OF AGRITOURISM ON ROMANIA'S RURAL AREAS BETWEEN 1990 AND 2015

Based on more than 25 years of research in the field of agritourism, the current work represents a pertinent, realistic and critical analysis of the main factors favourable to the implementation and development of agritourism and rural tourism in Romania. Firstly, we examined the main natural and anthropic tourist resources which constitute the country’s tourist treasures, and we concluded that Romania has rich, varied and attractive tourist resources that have not been fully exploited and promoted so far. Secondly, we carried out an evaluation of Romania’s implicit agritourist and tourist potential, as a future tourist destination, based on all its tourist resources and on 12 evaluation criteria. The results have shown that quality-wise, the value is high to very high, leading to the idea that Romania may satisfy to a large extent the potential clients’ numerous expectations and requirements. Lastly, we carried out a SWOT analysis regarding the level of implementation, development and impact of agritourism on the Romanian rural areas during the researched period. The aforementioned SWOT analysis led to a very clear and precise conclusion. Agritourism activity, in the areas where it was implemented and developed, had a very strong and favourable impact not only on the economic and tourist framework of localities, but also on their social, cultural, spiritual and even ecological framework.
Enzymatic Activity and Physicochemical Properties of Soil Profiles of Luvisols

Most studies on soil enzymes are focused on the upper horizons of the soil profile, even though they transform the soil organic matter at every depth of the soil profile. The aim of this work was to investigate the distribution of β-glucosidase (GLU), nitrate reductase (NR), urease (UR), phosphatase (PHA), dehydrogenase (DHA) and catalase (CAT) activity through 14 trunked soil profiles of the Luvisols formed from a glacial till. The content of microbial biomass carbon (MBC) as well as physicochemical properties such as organic carbon (CORG), total nitrogen (NTOT), available P, K and Mg, soil density and porosity, pH in KCl and fractional composition were also studied. In general, enzymatic activity was highest in the top 30 cm layer of the profiles and decreased progressively towards the deeper horizons. The exceptions were the NR activity, which was active only in the Ap horizon and whose activity decreased sharply to nearly zero in the Bt horizon and parent rock, and the PHA activity, which was highly active even in the parent rock depth. The decreased availability of carbon and nutrients was the main driver of decreases in microbial abundance and enzymatic activity with depth. The enzymatic activity, when expressed on a CORG and MBC basis, behaves differently compared to the activity expressed on a soil mass basis. The activity decreased (NR), increased (PHA, UR), showed no clear pattern (GLU) or the changes were not significant (DHA, CAT). The content of CORG, NTOT, K and PAVAIL generally decreased with depth, while for Mg, there was no clear direction in the profile distribution. Future studies to characterize the substrate distribution within the soil profile and enzyme stability will provide further insight into the controls on nutrient cycling and related enzymes throughout the soil profiles.
A first principles study of the phonon anharmonicity, electronic structure and optical characteristics of LaAlO3

The way elementary excitations work together with their couplings and interact as condensed matter systems is very important when designing optimum energy-conversion devices. We investigated the electronic structure of LaAlO3, and we show that the bandgap insulator of LaAlO3 obtained theoretically by the hybrid functional HSE06 is an indirect 5.649eV that show a very good agreement with experimental data. The lattice constant is obtained exactly as experiment. In thermos-electric materials, the concept of conversion-efficiency (heat to electricity) is improved instantly by suppressing the phonon quasi-particles propagations that are responsible for draft macroscopic thermal transport. The material presented here for thermo-electric conversion-efficiency of cubic perovskite LaAlO3, show that it has an ultralow thermal-conductivity, while the formalism to its strong phonon scattering interactions resides mostly unclear. From the bases of Ab-initio simulations, the 4-dimensional phonon-dispersion surfaces of the cubic perovskite LaAlO3, have been mapped and we found that the origins of the ionic potential an-harmonicity being responsible for the unique behaviour and properties of LaAlO3. It is investigated that these phonon scattering arise solely from the LaAlO3 unstable electronic-structure, with its orbital interactions resulting to lattice instability similar to the ferroelectric instabilities. Our results show a microscopic insight bonding electronic-structure and phonon an-harmonicity in LaAlO3, and provides some new picture the way interactions happen between phonon–electron and phonon–phonon this lead to understand the concept of ultralow thermal-conductivity. Ab-initio calculations was performed on cubic perovskite LaAlO3 to obtain the phonon density of states (DOS) from 50 K to 5000 K, we find that the anharmonic behaviour starts around temperature limits of 500 K. The computed optical spectra were obtained using both the Beth Slapter Equation BSE and compared with the perturbed method using HSE06, optical spectra show that the inter-band transition occur precisely from the O-valence bands to the La-conduction bands throughout the low energy area. The energy-loss spectrum, optical conductivity and reflectivity and the refractive index are computed from first principles by using HSE06 hybrid functional. The optical band gap of material shows about 6.21 eV, which agrees with some cited experimental measurements.
Building an Italian Written-Spoken Parallel Corpus: a Pilot Study

This paper presents a pilot study towards the creation of a monolingual written– spoken parallel corpus in Italian, featuring two main novelties in the general landscape of spoken corpora: the alignment with the written counterpart of the same content and the spoken variety dealt with, represented by transcriptions of radio news broadcasting.
A 1.52-GHz Super-Harmonic Injection-Locked Ring Oscillator in 130nm CMOS

Injection-locked oscillators (ILOs) are one of many topologies used in forwarded-clock wireline applications. In this paper, a super-harmonic injection-locked ring oscillator (ILRO) is proposed. The proposed ILRO has been designed and simulated using a 130-nm CMOS technology. The circuit is injected with a 7.6-GHz clock signal and generates 10 output clocks of 1.52 GHz each. The proposed design occupies an area of approx. 0.001 , has a phase noise of -148.1 dBc/Hz at 1MHz offset frequency and consumes 9.97 mW from a 1.2-V supply achieving a figure of merit (FoM) of 201.8 dBc/Hz.
Review Article: Atomic layer deposition for oxide semiconductor thin film transistors: Advances in research and development

This article is a review of recent research and development advances in oxide thin film transistors (TFTs) fabricated by atomic layer deposition (ALD) processes. The ALD process is remarkable as it offers accurate control of film thickness and composition as well as the ability to achieve excellent uniformity over large areas at relatively low temperatures. Firstly, an introduction to n-type oxide TFTs is provided with a focus on the development of active-layer material combinations from binary oxide active layers, like zinc oxide and indium oxide, to ternary and quaternary oxide active layers formed by doping with elements such as gallium or tin to achieve high mobility and high device stability for TFTs. Secondly, ALD p-type channel oxide TFTs are also introduced, which are required for the realization of many types of low-power circuits, such as complementary metal oxide semiconductor devices.
Machine Reading Comprehension: Matching and Orders

In this paper, we study the machine reading comprehension of temporal order in text. Given a document of instruction sequences, a model aims to find out the most coherent sequences of activities matching the document among all answer candidates. To tackle the task, we proposeOrdMatch model, which is able to match each activity in a sequence to the corresponding instruction in the document and regularizes the partial order of activities to match the order of instructions. We evaluate the task using the RecipeQA dataset, which includes step-by-step instructions of cooking recipes. Our model outperforms the state-of-the-art models with a wide margin. The experimental results demonstrate the effectiveness of our novel ordering regularizer. Our code will be made available at \hrefhttps://github.com/Aolius/OrdMatch https://github.com/Aolius/OrdMatch.
Multistage Real-Time Fire Detection Using Convolutional Neural Networks and Long Short-Term Memory Networks

Fire is one of the most commonly occurring disasters and is the main cause of catastrophic personal injury and devastating property damage. An early detection system is necessary to prevent fires from spreading out of control. In this paper, we propose a multistage fire detection method using convolutional neural networks (CNNs) and long short-term memory (LSTM) networks. In the first stage, fire candidates are detected by using their salient features, such as their color, flickering frequency, and brightness. In the second stage, a pretrained CNN model is used to extract the 2D features of flames that are the input for the LSTM network. In the last stage, a softmax classifier is utilized to determine whether the flames represent a true fire or a nonfire moving object. The experimental results show that our proposed method can achieve competitive performance compared with other state-of-the-art methods and is suitable for real-world applications.
Selection of software testing method by using ARAS method

DARJAN M. KARABAŠEVIĆ, University Business Academy in Novi Sad, Review paper Faculty of Applied Management, UDC: 004.4 Economics and Finance, Belgrade DOI: 10.5937/tehnika1805724K MLAĐAN V. MAKSIMOVIĆ, University Business Academy in Novi Sad Faculty of Applied Management, Economics and Finance, Belgrade DRAGIŠA M. STANUJKIĆ, University of Belgrade, Technical Faculty in Bor, Bor GORAN B. JOCIĆ, University Business Academy in Novi Sad, Faculty of Applied Management, Economics and Finance, Belgrade DUŠAN P. RAJČEVIĆ, University Business Academy in Novi Sad, Faculty of Applied Management, Economics and Finance, Belgrade
Learning and Reasoning on Graph for Recommendation

Recommendation methods construct predictive models to estimate the likelihood of a user-item interaction. Previous models largely follow a general supervised learning paradigm - treating each interaction as a separate data instance and building a supervised learning model upon the information isolated island. Such paradigm, however, overlook relations among data instances, hence easily resulting in suboptimal performance especially for sparse scenarios. Moreover, due to the black-box nature, most models hardly exhibit the reasons behind a prediction, making the recommendation process opaque to understand. In this tutorial, we revisit the recommendation problem from the perspective of graph learning and reasoning. Common data sources for recommendation can be organized into graphs, such as bipartite user-item interaction graphs, social networks, item knowledge graphs (heterogeneous graphs), among others. Such a graph-based organization connects the isolated data instances and exhibits relationships among instances as high-order connectivities, thereby encoding meaningful patterns for collaborative filtering, content-based filtering, social influence modeling, and knowledgeaware reasoning. Inspired by this, prior studies have incorporated graph analysis (e.g., random walk) and graph learning (e.g., network embedding) into recommender models and achieved great success. Together with the recent success of graph neural networks (GNNs), graph-based models have exhibited the potential to be the technologies for next-generation recommender systems. This tutorial provides a review on graph-based learning methods for recommendation, with special focus on recent developments of GNNs. By introducing this emerging and promising topic in this tutorial, we expect the audience to get deep understanding and accurate insight on the spaces, stimulate more ideas and discussions, and promote developments of technologies.
Label-Free Detection of Human Serum Using Surface-Enhanced Raman Spectroscopy Based on Highly Branched Gold Nanoparticle Substrates for Discrimination of Non-Small Cell Lung Cancer

Surface-enhanced Raman spectroscopy (SERS) is a good candidate for the development of fast and easy-to-use diagnostic tools, possibly used on serum in screening tests. In this study, a potential label-free serum test based on SERS spectroscopy was developed to analyze human serum for the diagnosis of the non-small cell lung cancer (NSCLC). We firstly synthesized novel highly branched gold nanoparticles (HGNPs) at high yield through a one-step reduction of HAuCl4 with dopamine hydrochloride at 60°C. Then, HGNP substrates with good reproducibility, uniformity, and high SERS effect were fabricated by the electrostatically assisted (3-aminopropyl) triethoxysilane-(APTES-) functionalized silicon wafer surface-sedimentary self-assembly method. Using as-prepared HGNP substrates as a high-performance sensing platform, SERS spectral data of serum obtained from healthy subjects, lung adenocarcinoma patients, lung squamous carcinoma patients, and large cell lung cancer patients were collected. The difference spectra among different types of NSCLC were compared, and analysis result revealed their intrinsic difference in types and contents of nucleic acids, proteins, carbohydrates, amino acids, and lipids. SERS spectra were analyzed by principal component analysis (PCA), which was able to distinguish different types of NSCLC. Considering its time efficiency, being label-free, and sensitivity, SERS based on HGNP substrates is very promising for mass screening NSCLC and plays an important role in the detection and prevention of other diseases.
RA-GAT: Repulsion and Attraction Graph Attention for Trajectory Prediction

Precise trajectory prediction in complex driving scenarios is crucial for autonomous vehicles. To achieve so, the autonomous vehicle has to effectively model the interactions between surrounding vehicles and consider the environmental information at the same time. This research proposes a unified prediction framework that simultaneously models the vehicle-vehicle interaction and the vehicle-environment relation. With a heuristic scene representation in graph structure in which vehicles and spaces are modeled as nodes, a dual graph attention module is adopted to model repulsion and attraction respectively from surrounding vehicles and the non-vehicle spaces. Deterministic trajectories are predicted using the updated repulsion- and attraction-aware scene encodings. Experiments are conducted on the NGSIM dataset to show the effectiveness of the proposed framework. Maneuver-based statistics are collected to analyze the prediction ability of the proposed model facing different maneuver trajectories.