Miracle-dz/UniFAR-FTUs huggingface dataset:
The usual suspects : fingerprinting microbial communities involved in decay of treated southern yellow pine

Current standards for soil-block testing have long been based on the effectiveness of preservative systems against only a small number of wood decay fungi and even fewer bacteria. Culture-independent molecular methods offer simple, reproducible means to obtain a more holistic view of the microbial communities that colonize wood throughout the decay process. By using a culture-independent PCR-based method called terminal restriction fragment length polymorphism (T-RFLP) analysis, we were able to detect shifts of fungal and bacterial communities in wood treated with sub-lethal concentrations of ACQ-C and CTN. T-RFLP takes into account all species of a taxonomic group and creates a community profile or “fingerprint,” where each peak in the profile represents a unique species. Both compounds appeared to change the patterns of bacterial succession completely, so that beginning and ending communities were significantly different in regard to species composition. Fungal species community structure was initially changed, but became more similar to untreated controls over time, presumably as the preservatives were depleted from samples. Subsequent depletion analysis found >60% depletion of preservatives from treated field stakes after 15 months exposure. Further modification to this process will eventually enable us to accurately identify fungal and bacterial species making up the microbial communities found in treated and decaying wood and offer new insights into the decay process.
The complete chloroplast genome of Tanacetum coccineum

Abstract Tanacetum coccineum, a perennial plant of the Tanacetum genus, cultivated as a natural pesticide or ornamental plant widely distributed in many countries. In this research, the complete chloroplast genome sequence of T. coccineum was determined to comprise a 150,143 bp double-stranded circular DNA, including a pair of 24,416 bp inverted repeat regions (IRs), small single copy (SSC) region of 18,389 bp and large single copy (LCS) region of 82,922 bp. An overall GC content was 37.49%, and the corresponding values in IRs, SSC, and LSC regions are 43.16%, 30.88%, and 35.61%, respectively. A total of 129 genes include 84 protein-coding genes, 37 tRNA, and eight rRNA. Four rRNA genes and seven tRNA genes were duplicated in IRs. A phylogenetic tree reconstructed by 38 Composite family chloroplast genomes sequence reveals that T. coccineum is mostly related to Ismelia carinata.
Genome-wide analysis of drug resistant Mycobacterium tuberculosis isolates causing pulmonary and extrapulmonary tuberculosis in Russia

Mycobacterium tuberculosis is a highly studied pathogen due to public health importance. Despite progress in M.tuberculosis genome diversity analysis there remain insufficient data on genome analysis of M.tuberculosis strains associated with pulmonary vs. extrapulmonary TB (PTB or XPTB respectively) tissue localization. Here we conduct comparative analysis of whole-genome sequence (WGS) for clinical M.tuberculosis strains collected from patients with PTB (n=72) and XPTB (n=73) localization. We further analyze the incidence of point mutations widely used for drug resistance detection in laboratory practice. M.tuberculosis isolates were collected from patients with varying clinical status from 2007 to 2014 in Russia. Bacterial DNA was extracted and sequenced using MiSeq platform (Illumina). WGS data allowed identifying M.tuberculosis substrains associated with distinctions in the occurrence in PTB v s. XPTB cases. There occurred little statistically significant specific DNA variants or genotypes diagnostic of tissue distribution, however phylogenetic analyses did reveal M.tuberculosis genetic substrains associated with TB localization. XPTB was associated with Beijing CAO, A and 4.8 groups, while PTB localization was associated with group LAM (4.3). Further, XPTB strain in some cases showed elevated drug resistance patterns relative to PTB isolates. HIV is significantly associated with the development of XPTB in the Beijing B0/W148 group and among unclustered Beijing isolates. This research analysis pinpointed genomic markers identified in XPTB and PTB with detailed characterization of drug-resistance markers of Russian M.tuberculosis isolates. We suggest that further comprehensive analysis of bacterial and human biological signatures might allow for better understanding consistent pattern of XPTB development. Summary This paper gives genome-wide characteristics of Mycobacterium tuberculosis strains collected from pulmonary and extrapulmonary tuberculosis patients: - M.tuberculosis genetic strains associated with TB tissue localization, - influence of HIV co-infection on TB dissemination; - mutations associated with M.tuberculosis drug resistance.
Esophageal foreign body removal using endoscopy in cat

A 10-months-old cross long hair cat named Casper with clinical symptom of vomiting mixed with slimy cat feed was referred to Veterinary Teaching Hospital, Faculty of Veterinary Medicine, Bogor Agricultural University to endoscopy examination and therapy. The owner believed that Casper ate a 5 cm long sewing needle a few days earlier. The history and physical examination were examined at DNA Clinic with symptoms of lack of appetite and becoming quieter and calmer. Radiogram showed the needle was in thorax area with a vertical needle penetrating the esophageal wall. Removal of the needle and observation of the esophagus area were done using endoscopy under general anesthesia. Using endoscopy, it was known that the needle was swallowed along with the sewing thread with position of all needles penetrating the esophagus wall and leaving a small amount of thread on the lumen. The needle was pulled back to the esophageal lumen by pulling the remaining thread and then both needle and the thread were pulled back out using an alligator grasping forceps that used through working channel. Therapy given after endoscopy was antibiotics and anti-emetics.
A Novel Adaptive Attention Model for Image Captioning

Image captioning is an extremely challenging work, which involves both computer vision and natural language processing. However, in recent years, with the introduction and improvement of various new technologies, it has made a great advancement. In this paper, a novel attention-based image caption model is proposed. We use Resnet harnessed by outstanding performance in convolutional neural network, as the encoder. For the decoding, LSTM network equipping with fitness of dealing with problems highly related to time series, is adopted. At each time step, the attention mechanism guides the language model to synthesize context vectors adaptively. The experimental results show that the model has good performance in various quantitative metrics as well as in human evaluation.
Découverte et caractérisation des petites protéines sécrétées chez les rouilles foliaires du peuplier (melampsora spp.)

Poplar leaf rusts belonging to the genus Melampsora are considered as the world‟s most important disease of poplars. During infection, Melampsora species secrete a diverse set of effector proteins that aim to reprogram the host into a susceptible state. However, recognition of particular effector proteins by the plant immune system, so-called avirulence proteins, leads to induction of the hypersensitve response, a form of programmed cell death. Based on prevalent models of plant–pathogen coevolution, some of these effectors, notably those with avirulence functions, are predicted to exhibit molecular signatures of accelerated evolution. In this thesis, features described above were used to identify the pathogenicity determinants of poplar leaf rusts with the specific aim of identifying candidate effector proteins. The first part of this thesis includes the development of a multifaceted approach to take advantage of available EST libraries, and included computational prediction of secreted proteins, intraand interspecific comparative genomics, and testing for the presence of positive selection. Accelerated evolution was found to act more importantly on secreted proteins, and most of those proteins under positive selection were shown to harbour a high number of Cys residues and to share no homology in international databases. The second part of this thesis presents the results of a collaborative effort to characterize the entire secretome of M. larici-populina using expert annotation, screening for positive selection, and transcript profiling approaches. A significant part of the secretome was found to be under positive selection, and commonalities described before were observed again (Cys-rich proteins with no homology in international databases). Most of those with transcript evidence were found to be specifically expressed in planta, and positively selected sites were concentrated in the Cterminal region, consistent with an effector function. As a first step toward a functional characterization, immunolocalization of selected candidates has revealed specific labeling of some proteins in the haustoria periphery.
A computational investigation of the interaction of the collagen molecule with hydroxyapatite

This thesis presents the results of computer simulation studies of the interaction of the predominant molecules in the collagen protein with the hydroxyapatite mineral. Using a combination of computational techniques, quantum-mechanical methods based on the density functional theory (DFT) and molecular dynamics simulations based on interatomic potentials, we have investigated the interface between the collagen protein and the apatite mineral. First we have employed electronic structure techniques (DFT) to study a range of different binding modes of the amino acids glycine, proline and hydroxyproline, which are major constituents of the collagen I protein, at two important hydroxyapatite surfaces, (0001) and (0110) . We have performed full geometry optimizations of the hydroxyapatite surface with adsorbed amino acid molecules to obtain the optimum substrate/adsorbate structures and interaction energies. We have also used DFT to investigate the binding of a series of representative peptides containing hydrophobic side groups (proline), uncharged polar side groups (glycine and hydroxyproline), and charged polar side groups (lysine and hydroxylysine) to the hydroxyapatite (0001) and (0110) surfaces. This selection of adsorbates has given us the opportunity to study separately the interactions of the carboxylic acid and amine functional groups, as well as the effect of hydroxylation and the charges of the side group, on the strength of interaction with the surfaces. We have also investigated the same systems in an aqueous environment using classical molecular dynamics simulation, where we have calculated the energies and geometries of adsorption of the peptide at the surfaces of hydroxyapatite in competition with pre-adsorbed water. Finally, we have studied the onset of nucleation of the hydroxyapatite mineral at an entire collagen molecule in aqueous solution.
Who Gets Duped? The Impact of Economics and Finance Education on Skepticism in an Investment Task

Many financial scandals appear to depend on a lack of skepticism on the part of their victims. For example, sophisticated investors trusted Bernie Madoff, despite early warning signs of implausible returns. Our study investigates how education and personality explain skeptical behavior in financial decision making. In a simple survey, economics and finance students are asked to make an investment recommendation from among four different hypothetical funds, including one based on Madoff’s fund. We find that perceptions of the suspiciousness and ethicality of the Madoff fund affect a participant’s recommendation. In turn, these perceptions are affected by education and personality, with more education leading to higher suspicions.
Nanoparticle catalysts

In this review, the importance of nanoparticles (NPs), with emphasis on their general and specific properties, especially the high surface-to-volume ratio (A/V), in many technological and industrial applications is studied. Some physical and chemical preparation methods for growing several metallic and binary alloy NP catalysts are reviewed. The growth and mechanism of catalytic reactions for synthesis of 1D nanostructures such as ZnO nanowires and multiwall carbon nanotubes (MWCNTs) are discussed. Gas-phase production with emphasis on dependence of catalytic activity and selectivity on size, shape and structure of NPs is also investigated. Application of NP catalysts in several technological processes including H2 production and storage as well as antibacterial effect, gas sensors and fuel cells is discussed. The mechanism of H2 production from catalytic photoelectrochemical and photocatalytic degradation reactions of some organic dyes is discussed. Finally, the future outlook of NP catalysts in various disciplines is presented.
Automatic Helmet Detection System on Motorcyclists Using YOLOv3

: Safety, it is the most important thing to keep in mind when travelling. But it is often neglected by most people, especially by motorcyclists who are often caught riding without a helmet. The objective of this project is to help better enforce traffic rules with motorcyclists by automating the process, as it is quite tedious for traffic police to catch every offender by themselves. In the proposed approach we implement a methodology for automatic helmet detection for motorcyclists riding without a helmet, using a video of traffic on public roads as input. The first step is to detect and classify the different vehicles on the road applying a vehicle classifier for each frame using OpenCV and Python, after which we extract the image of the motorcycle and apply YOLOV3 algorithm, a deep learning algorithm on the extracted image to check if the rider is wearing a helmet or not. If the output is negative, i.e. not wearing a helmet the licence plate is then noted down by the respective officials.
Social Media Analytics for Stance Mining A Multi-Modal Approach with Weak Supervision

People express their opinions on blogs and other social media platforms. As per a recent estimate, interactions on Twitter alone result in over 500 million tweets perday. The magnitude of this data enables new applications of opinion mining that have previously remained challenging e.g., finding users’ stance (as in pro or con) on topics of interest. However, one of the major barriers to utilizing this amount of data is the cost of hand-labeling examples for machine learning. This barrier is even more apparent in stance mining, as opinions can change overtime and can be about any issues. To reduce the need for hand-labeled data by taking the complex interactions of social media users and their social influence into account, this dissertationdevelops semi-supervised methods for stance mining.Most existing studies on stance mining take a simplistic view that assumes a sentence (like a Tweet) holds a perspective that is independent of the context and the author’s network position. This approach to stance learning leaves three crucial unresolved challenges. First, how do we train stance-learning models on new topics with minimal labeling effort? Discussion topics change fast and new issues emerge, making it difficult to reuse prior labeled data. However, artifacts of social networks like hashtags can give noisy signal about the stance of users. To extract the signal from noise, I develop methods to find useful hashtags by exploiting how users in the pro-group and the anti-group use popular hashtags. Second, how can we use multiple interaction modalities for stance mining? Users opinions are evident in different types of interactions, e.g. tweeting, retweeting or liking. I develop a semisupervised method based on co-training that jointly trains multiple stance classifiers using different interaction modalities resulting in a better stance prediction model. Third, how to leverage users networks for stance prediction? The current approachesto stance learning ignore important network factors such as the interactions of social media users (e.g., a persons preference can also be known from his friends preferences). I use the network alignment as one of the training signals to train the stance classifiers. My thesis brings a new direction to the stance learning problem that is grounded in social theory, is more amenable to analyzing activities on social media, and allows effective learning from multiple types of interactions without requiring large amounts of labeled data. By labeling only a few hashtags used in Twitter conversations on a few controversial topics, my approach allows for predicting both the stance of users (as in whether they are pro or con a topic) by over 80% accuracy andthe stance in conversations (as in whether they favor or deny others posts) by over 70% accuracy.
Diversity and structure preferences for ant-hemipteran mutualisms in cocoa trees (Theobroma cacao L., Sterculiaceae)

The aim of this study is to evaluate the diversity and specificity of ant-hemipteran mutualisms according to the different structures observed on cocoa trees. The experiment was carried out in two cocoa planting systems: cabruca and derruba total at Ilhéus, Brazil. We made observations and collected monthly over one year the mutualistic ants and hemipterans that occurred on Theobroma cacao L. trees. Observations were performed on cacao trees at three distinct sites of the plant: flowers, pods and leaf flush. We observed 932 ant-hemipteran associations, comprising 203 different mutualistic interactions. The assemblage was composed of 26 hemipteran species and 54 ant species. No differences were observed in the ant community, however, we found differences in the hemipteran community according to the different structure evaluated. We recorded a total of 404 trophobiosis events on pods, 394 on leaf flushes and 134 on flowers. Our results point out the diversity of ant-hemipteran trophobioses in the cocoa agrosystems resembles the diversity found in tropical forests and demonstrate that the location of interactions may result in ecological restrictions for some organisms involved in these trophobioses in cacao agrosystems.
IMPROVEMENT OF PROJECT PERFORMANCE THROUGH PLANNING, TEAM CAPABILITY, PROCUREMENT OF MATERIALS, AND WORK SCOPE CASE STUDY IN THE MRO PROJECT

The project must be successful so that the goals expected by both the customer and the project implementer. This research was conducted at one company in Indonesia which is engaged in the electricity sector, especially in the field of Maintenance, Repair & Overhaul (MRO) of power plants. In its implementation there are Maintenance, Repair & Overhaul projects that are overtime, over budget and get complaints, so this research aims to determine the effect of project planning on team capabilities, material procurement and project scope, and to determine the effect of team capabilities, material procurement and scope of work on project performance. The data of this study were collected through a questionnaire of 50 project employee respondents with 21 questions. Data analysis in this study used a partial least squares (PLS) approach. This study concludes that project planning has a positive and significant impact on team capability, material procurement and scope of work. The study also concluded that team capability, material procurement, scope of work had a positive and significant impact on project performance. With these results it can be concluded that project performance can go well, good planning must be carried out, the team has the capability, appropriate material procurement and clear scope of work.
A Study of Hematological Changes in Neonatal Sepsis

Background: Neonatal sepsis is one of the major causes of morbidity and mortality in the newborn. Early diagnosis and treatment are crucial in the management of neonatal sepsis. Blood culture, the gold standard, takes long time and lack sensitivity. Hematological sepsis score is a simple score obtained by combining routinely available tests and is rapid, non-expensive and has shown good correlation with blood culture. With this background the study was carried out to evaluate hematological changes in neonatal sepsis and to analyse the diagnostic utility of hematological scoring system (HSS) and its correlation with C- reactive protein and blood culture in neonatal sepsis. Methods: The study included 200 neonates admitted to Neonatal Intensive Care Unit with clinical suspicion of neonatal sepsis. CBC, Peripheral blood smear, CRP and Blood culture were obtained from all the neonate. Hematological sepsis score was calculated, and its sensitivity and specificity were obtain using blood culture as gold standard. Result: We screened 200 neonates with suspected neonatal sepsis. Blood culture was positive in 101 (50.5%) and HSS score >2 was found in 80 (40%) neonates. CRP and HSS had sensitivity of 84.15% and 72.27% and specificity of 68.68% and 92.92% respectively. Conclusion: Our study shows that HSS had fairly good sensitivity and specificity for neonatal sepsis screening and HHS can be utilized for neonatal sepsis screening.
Formal methods of parallel software design automation

ISSN 1025-6415. Допов. Нац. акад. наук Укр. 2020. No 6: 15—20 Ц и т у в а н н я: Doroshenko A.Yu. , Yatsenko O.A. Formal methods of parallel software design automation. Допов. Нац. акад. наук Укр. 2020. No 6. С. 15—20. https://doi.org/10.15407/dopovidi2020.06. 15 Current and emerging scientific and industrial applications require a significant com puting power provided by parallel platforms such as multicore, clusters, cloud compu ting, and GPGPU (General-Purpose Computing on Graphics Processing Units). Modern software development tools for such platforms are quite complex and require the use of new programming models, as well as knowledge of software and hardware details. One of the promising areas in the modern parallel programming is the development of abstract models and formal methods of design, analysis, and implementation of algorithms and programs. Such models and methods are constructed, particularly, in the framework of the algebraic programming and algorithmics. Algebraic programming is based on the term rewriting theory [1] and describes the processes of program design, algebraic transfor mations, proving mathematical theorems and the development of intelligent agents. The algorithmics is the direction of computer science being developed within the Ukrainian algebraic-cybernetic school [2, 3]. It is based on the Glushkov system of algorithmic algebras (SAA) focused on solving the problems of formalization and design of sequential and parallel algorithms. The objects of research in algorithmics are models of algorithms and programs represented in the form of high-level specifications — schemes. This paper proposes formal methods and software tools for designing parallel programs based on the algebra of algorithms. The aphttps://doi.org/10.15407/dopovidi2020.06. 015 UDC 004.4’24
Mise au point d'un procédé d'ozonation catalytique pour le traitement des effluents aqueux : application à l'industrie papetière

Les travaux presentes dans ce memoire concernent la mise en oeuvre d'un procede d'ozonation catalytique pour le traitement des eaux residuaires industrielles. La reaction d'ozonation catalytique est pealablement etudiee en reacteur agite, avec un catalyseur en poudre. L'etude porte sur la destruction d'un compose modele refractaire a l'ozonation, l'acide hexanoique. Cette reaction est alors mise en oeuvre en reacteur colonne a lit fixe, fonctionnant a co-courant ascendant de gaz et de liquide. L'etude du transfert et de la decomposition de l'ozone en phase aqueuse est suivie de la determination des parametres hydrodynamiques essentiels a l'obtention de resultats optimaux lors de la reaction de mineralisation de l'acide hexanoique. Le vieillissement et la voie de synthese du catalyseur sont egalement consideres. L'ozonation catalytique est finalement utilisee pour le traitement d'effluents papetiers.