Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of co-expression gene networks controlling rice blast disease during an incompatible reaction

Rice blast disease is a major threat to rice production worldwide; the causative pathogenic fungus Magnaporthe oryzae induces rice (Oryza sativa) plants to undergo molecular changes that help them to circumvent this fungal attack. Transcriptome studies have demonstrated that many genes are involved in the defense response of rice to M. oryzae, but most of these studies focused on the screening of differentially expressed genes and the studies did not investigate the interactions among genes. We examined the interaction of rice and M. oryzae in a network context. Two near-isogenic lines were profiled at different time-points. Using transcriptome data obtained from an RNASeq analysis, a network based on the relationships among genes was developed through weighted gene co-expression network analysis. The analysis of degree centrality identified numerous hub genes and potential key regulators that control the rice response, providing new insights into the molecular network underlying the resistance of rice to M. oryzae infection. Additionally, a protein-protein interaction network was derived to identify complexes that might physically interact. For example, complexes of OsbHLH148/OsJAZ, OsMYB4 and some components of the phenylpropanoid pathway, as well as MYB/bHLH
#gainingweightiscool: the use of transformation photos on Instagram among female weightlifters in recovery from eating disorders

ABSTRACT In this article, we explore transformation photos on Instagram as ‘digital artefacts’ that can inform understandings of eating disorder recovery in the context of sport, exercise and health. Transformation photos are two images (from different time points) set alongside one another to represent the changing of bodies in look, shape or size. These images are prevalent within eating disorder recovery and fitness spaces on Instagram and typically display an individual’s recovery journey through a before (thin) and after (more muscular) image comparison. By triangulating interview, photo elicitation and netnography data from research on female weightlifting as a tool for recovery from eating disorders, we explore transformation photos in relation to three intersecting themes; 1) new modes of ‘becoming’, 2) representation and ‘mediated memories’, and finally, 3) survivorship and identity. Our findings demonstrate that transformation photos are integral to the process and practice of recovery for women who use weightlifting as a tool for recovery from eating disorders. Moreover, we suggest that by engaging with a popular mimetic device (transformation photos), we were able to ‘meet participants where they are’ and offer a novel qualitative approach to understanding how digitally mediated lives are lived.
14 Retrotransposon Reverse Transcription

During the past decade, it has become evident that genes encoding putative reverse transcriptases (RTs) are widespread genomic residents. Potential RT-coding domains have been identified in genes inhabiting a variety of genomic niches within animal, plant, protozoan, fungal, and even eubacterial cells. The existence of extensive sequence data has led to a number of studies of the evolutionary relationships among RT-encoding elements and speculations about the origin of this enzyme in a pre-DNA world, preceding the prokaryotic/eukaryotic divergence (Temin 1985; Darnell and Doolittle 1986; Wintersberger and Wintersberger 1987; Varmus 1989). This chapter concentrates on the available evidence for the existence of RTs encoded by three broad groups of transposable elements as well as evidence suggesting that these elements transpose through an RNA-mediated mechanism. These three groups of elements, collectively called “retrotransposons,” differ from the much more extensively studied retroviruses in a number of ways, most conspicuously by their apparent inability to be transferred horizontally. Given the impossibility of discussing all of the large number of sequenced transposons thought to encode RT, this chapter concentrates on those systems that have proved to be most amenable to experimental dissection of the detailed mechanisms involved in transposon reverse transcription. Recent comprehensive reviews of these genomic elements can be found elsewhere (Boeke 1988; Berg and Howe 1989; Echalier 1989; Boeke and Sandmeyer 1991), and more specialized reviews are referenced in the text under specific topics. A list of structural features of the elements discussed in this chapter is presented in Table 1. The wide.
Factors Affecting Sustainable Purchase Intentions of SNS Emojis: Modeling the Impact of Self-Presentation

To promote more sustainable consumption of Social Networking Service (SNS) emojis, it is necessary to understand the relationships between social psychological antecedents and SNS users’ intention to purchase emojis. This study aimed to investigate motivational factors affecting users’ intentions to purchase SNS emojis. We examined SNS users of Kakao Talk, the most widely used instant messaging service in South Korea, and investigated the relationships among five latent constructs: Self-presentation, symbolic values, playfulness, purchase intentions, and need for uniqueness. The results of this study indicate that self-presentation does not directly affect the intention to purchase emojis (β = 0.10, p > 0.05). Rather, self-presentation positively influences purchase intention through the mediating path of SNS users’ perceived symbolic value (β = 0.60, p < 0.001) and playfulness (β = 0.35, p < 0.001) to purchase intention (β = 0.29, p < 0.001; β = 0.37, p < 0.001). Further, symbolic value affects playfulness (β = 0.56, p < 0.001), which in turn leads to consumers’ intentions to purchase emojis. This study highlights that SNS users’ need for uniqueness functions as a moderator in the relationship between self-presentation and their intentions to purchase emojis.
Caractérisation des phages et des mécanismes anti-phages chez Lactococcus lactis

Lactococcus lactis is a lactic acid bacterium widely used for production of diverse cheeses. Nonetheless, this bacterium is susceptible to bacteriophages that are sporadically causing fermentation problems. The phages of L. lactis are among the most studied. However, many notions remain vague about their evolution and biology, and this is especially notable in response to anti-phage systems. Three different aspects of L. lactis phage biology were studied in this thesis: their genetic diversity, their evolution and the anti-phage mechanisms. The genome of the phage P335 was sequenced and analyzed revealing the heterogeneity of the groups bearing the same name and it was also possible to point out the emergence of sub-groups within this group. A module of moron genes possessing homology with prophages from other taxons was identified in the phage P335 illustrating the genomic plasticity of these phages. The second objective of this project was to demonstrate the genetic plasticity of the group P335 and their evolution when challenged with Abi phage resistance mechanisms. Phage mutants were isolated and characterized. One of the phage mutants had exchanged as much as 79% of its genome to acquire resistance to both AbiK and AbiT. The phage mutants have exchange genetic module from at least two different prophages within their host genome. Finally, AbiT mode of action was studied. Many phage mutants resistant to AbiT were isolated and characterized. Three AbiT targets/activators were identified. Two are early genes of unknown function. The third target is a late gene found in the morphogenesis module and is coding for the major capsid protein. Lactococcus lactis and their bacteriophages are an important model for the understanding of lactic acid bacteria phage/host interaction. This project increases our knowledge on the evolution of P335 phages and their genetic diversity. The amazing genetic plasticity of these phages allows their populations to rapidly evolve when confronted to a selective force such as anti-phage systems. Moreover, the mode of action of AbiT is more complex that initially estimated since it targets three phage components in different functional modules.
On the Problem of Management of Physical Education of Younger Schoolchildren Using Modular Substitutions of Structural Bases of The Educational Subject

The work aims to improve the quality of education of primary school students in physical education by introducing a scientifically-based exemplary program into the practice of educational organizations developed following the basic provisions of the modular approach and the principles of managing the educational process. Analysis and synthesis of literature data on modern trends in the development of the education system, the experience of educational organizations, and the development of the fundamentals of a physical education subject are used as the main research methods. The result of the work is the substantiation of conceptual approaches and methodological provisions on the formation of the structure and content of an exemplary Modular educational program in physical education, criteria, recommendations for the meaningful filling of its training modules, the technology of their substitution in the educational process.
Synthesis, characterisation and decomposition properties of manganese-based borohydrides for hydrogen storage

In this work, a series of Mn-based borohydrides were synthesized by mechanochemical milling of ABH\(_4\)-MnCl\(_2\) (where A=Li, Na, K) under argon. Samples prepared by milling xLiBH\(_4\)-MnCl\(_2\) (where x = 2 or 3) resulted in the formation of Mn(BH\(_4\))\(_2\) and LiCl in a stoichiometric ratio. Thermal decomposition of Mn(BH\(_4\))\(_2\) was observed between 105 and 180°C with the concurrent evolution of hydrogen and diborane. Analysis of the decomposition products suggested the presence of amorphous B, Mn and LiCl. When NaBH\(_4\) was used as a reagent, Mn(BH\(_4\))\(_2\) was also observed, however instead of NaCl, a solid solution of NaCl\(_x\)(BH\(_4\))\(_1\)\(_-\)\(_x\) and Na\(_6\)MnCl\(_8\) were formed. Mn(BH\(_4\))\(_2\) decomposed between 110 and 170°C for xNaBH\(_4\)-MnCl\(_2\) with the concurrent evolution of hydrogen and diborane. Analysis of the decomposed samples showed that amorphous B and Mn formed (110 to 170°C) and NaCl\(_x\)(BH\(_4\))\(_1\)\(_-\)\(_x\) reacted with Na\(6\)MnCl\(_8\) to produce NaCl (250 to 475°C). When KBH\(_4\) was used as a reagent, Mn(BH\(_4\))\(_2\) was not observed. Rather, K\(_2\)Mn(BH\(_4\))\(_4\), KMnCl\(_3\) and unreacted KBH\(_4\) were observed. The mass losses for the milled sample were observed between 100 to 160°C with a release of hydrogen and trace diborane, forming KBH\(_4\), B, and Mn, and between 165 to 260°C with only hydrogen release, giving KCl, B and Mn.
A Contrast Enhancement Model for X-Ray Mammograms Using Modified Local s-Curve Transformation Based on Multi-Objective Optimization

The biased X-ray field and the subtle difference in X-ray attenuation between normal and abnormal breast tissues prevent the biomedical sensors to generate mammograms with good quality. These are the common imperfections in the acquisition systems (sensor) of Mammography which contribute towards the degradation of mammogram image quality. This paper aims to develop a contrast enhancement model for mammograms so that the human or machine vision can distinguish easily among the variants of breast lesions and predict their severity. The proposed mammogram enhancement model exploits locally the proprieties of the sigmoidal function based on multi-objective Genetic Algorithm for improving the contrast of lesions along with a simultaneous increment in various Image Quality Assessment (IQA) parameters like: <inline-formula> <tex-math notation="LaTeX">$\textit {EME}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\textit {EC}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\textit {AMBEn}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\textit {FSIM}$ </tex-math></inline-formula>. Herein, the multi-objective optimization problem is transformed into a single-objective optimization to find a unique solution for mammogram enhancement. An increase in these IQA metrics is indicative of better contrast, edge content, and conservation of brightness and other diagnostics information. Simulations of the proposed enhancement model are carried out on mammograms from the mini-MIAS database for benchmarking and validation of results.
Uranium Dispersion and Dosimetry (UDAD) Code

The Uranium Dispersion and Dosimetry (UDAD) Code provides estimates of potential radiation exposure to individuals and to the general population in the vicinity of a uranium processing facility. The UDAD Code incorporates the radiation dose from the airborne release of radioactive materials, and includes dosimetry of inhalation, ingestion, and external exposures. The removal of raioactive particles from a contaminated area by wind action is estimated, atmospheric concentrations of radioactivity from specific sources are calculated, and source depletion as a result of deposition, fallout, and ingrowth of radon daughters are included in a sector-averaged Gaussian plume dispersion model. The average air concentration at any given receptor location is assumed to be constant during each annual release period, but to increase from year to year because of resuspension. Surface contamination and deposition velocity are estimated. Calculation of the inhalation dose and dose rate to an individual is based on the ICRP Task Group Lung Model. Estimates of the dose to the bronchial epithelium of the lung from inhalation of radon and its short-lived daughters are calculated based on a dose conversion factor from the BEIR report. External radiation exposure includes radiation from airborne radionuclides and exposure to radiation from contaminated ground. Terrestrialmore » food pathways include vegetation, meat, milk, poultry, and eggs. Internal dosimetry is based on ICRP recommendations. In addition, individual dose commitments, population dose commitments, and environmental dose commitments are computed. This code also may be applied to dispersion of any other pollutant. (ERB)« less
Denitrification in Membrane Bioreactors

I ACKNOWLEDGMENTS III TABLE OF CONTENTS IV LIST OF TABLES VI LIST OF FIGURES VII CHAPTER 1INTRODUCTION 1 PROBLEM STATEMENT 1 ALTERNATIVES 1 APPROACH 1 CHAPTER 2LITERATURE REVIEW 3 NITRATE POLLUTION 3 TREATMENT TECHNOLOGIES 3 ION EXCHANGE (IX) 3 BIOLOGICAL DENITRIFICATION 4 COMBINED ION-EXCHANGE (IX) AND BIOLOGICAL DENITRIFICATION 5 REVERSE OSMOSIS AND ELECTRODIALYSIS 5 MEMBRANE BIOREACTORS 5 DENITRIFICATION IN FILTER MEMBRANE BIOREACTORS 7 DENITRIFICATION IN CONTACTOR MEMBRANE BIOREACTORS 8 CHAPTER 3 MATERIALS AND METHODS 10 POLLUTED GROUNDWATER 10 BIOREACTOR FEED . 10 LOW FLUX FILTER MEMBRANE BIOREACTOR (LLF) 10 DIAFILTER MEMBRANE BIOREACTOR (DF) 14 ION-EXCHANGE BIOREACTOR (IE) 14 START-UP CULTURE 14 ANALYTICAL PROCEDURES 15 SAMPLE STORAGE 16 CHAPTER 4 RESULTS 17 LOW FLUX FILTER MEMBRANE BIOREACTOR (LFF) 17 DIAFILTER MEMBRANE BIOREACTOR 20 ION EXCHANGE MEMBRANE BIOREACTOR 24 CHAPTER 5 DISCUSSION 28 LOW FLUX FILTER MBR 28 MEMBRANE FLUX 28 DENITRIFICATION RATE AND LOADING CAPACITY 28 SECONDARY POLLUTION 29 DIAFILTER-MBR 29 DENITRIFICATION RATE AND SECONDARY POLLUTION 29 POLLUTION WITH NITRITE 31 MICROBIAL CONTAMINATION OF THE TREATED WATER 31 C/N REQUIREMENT . 31 ION EXCHANGE-MBR 31
Biological Control of Manganese in Water Supplies in the Presence of Humic Acids

OF DISSERTATION BIOLOGICAL CONTROL OF MANGANESE IN WATER SUPPLIES IN THE PRESENCE OF HUMIC ACIDS The main objective of this study was to improve our understanding of biological filtration (biofilm type) treatment for manganese (Mn) removal in drinking water. Biological filtration treatment involves biofilms of Mn(II)-oxidizing microorganisms attached to solid filter material that remove and immobilize dissolved Mn(II) in raw water by conversion to black MnO2(s) precipitates. Mn-biological filtration is an emerging green technology that can serve as an alternative to conventional physicochemical treatments, but its full potential is hindered by various factors. These include lack of understanding the (1) optimal removal conditions for Mn, (2) mechanisms for biofilter Mn releases, and (3) effects of recalcitrant natural organic matter (NOM) on biofiltration. Confounding these issues is the unknown identity of the diverse microbial communities which occupy the biofilms attached to the filter media. To investigate these issues, biological Mn removal was studied in laboratory bench scale reactors using a new Mn(II)-oxidizing bacterium isolate, Pseudomonas Putida EC112. The main research hypothesis formulated that the transition metal catalyst, MnO2(s), can increase the bioavailable carbon and energy from recalcitrant NOM (e.g., humic acids (HA)) in biological filters. Mn and HA can be found in most natural waters, including groundwaters, lakes and streams. To test the hypothesis, the potential for strain EC112 growth and Mn(II) oxidation utilizing the organic substrate products from the oxidation reaction between HA and MnO2(s) was assessed. Biological Mn(II)-oxidation kinetics were investigated in batch (suspended cell) and continuous flow (biofilm) bioreactors at optimal pH and temperature conditions for strain EC112. Batch kinetics was successfully characterized with the Monod model. Continuous flow steady-state kinetics was modeled with a single, first-order kinetic parameter. Enhanced Mn(II) removal capacity was observed for strain EC112 in batch and continuous flow reactors in the presence of HA and MnO2(s). The effect of MnO2(s) on HA biodegradability was studied and optimal conditions for biodegradation were identified. Biofilter Mn(II) releases were observed during the continuous flow bioreactor experiments. Release conditions were identified and releases modeled using pseudo first-order kinetics. Changes in HA structure induced by MnO2(s) oxidation were studied with Fourier transform infrared (FT-IR) and proton nuclear magnetic spectroscopy (1H-NMR). KETWORDS: Biological filtration, drinking water, humic acids, manganese, Pseudomonas Putida. Michael Snyder Student’s Signature
A spiking neural architecture that learns tasks

Cognitive architectures based on neural networks typically use the Basal Ganglia to model sequential behavior. A challenge for such models is to explain how the Basal Ganglia can learn to do new tasks relatively quickly. Here we present a model in which task-specific procedural knowledge is stored in a separate memory, and is executed by general procedures in the Basal Ganglia. In other words, learning happens elsewhere. The implementation discussed here is implemented in the Nengo cognitive architecture, but based on the principles of the PRIMs architecture. As a demonstration we model data from a mind-wandering experiment.
Optimal algorithms for experts and mixtures of Gaussians

This thesis makes contributions to two problems in learning theory: prediction with expert advice and learning mixtures of Gaussians. The problem of prediction with expert advice can be cast as a sequential game between an algorithm and an adversary as follows. At each time step, an algorithm chooses one of n options (or experts) and the adversary sets a cost for each expert. The algorithm’s goal is to minimize its regret, i.e. its cost relative to the best expert in hindsight. The celebrated multiplicative weights algorithm is known to be optimal if the the game is terminated at a fixed, known time and the number of experts is large. Optimal algorithms are also known when the number of experts is 2, 3, or 4. If the game does not terminate at a known time or is run indefinitely, the optimal algorithm is not known for any number of experts. We contribute to this problem by giving the optimal algorithm when there are 2 experts. Our algorithm is designed by considering a continuous analogue of the problem, which is solved using ideas from stochastic calculus. In the second part of the thesis, we look at distribution learning, which is a fundamental task in statistics that has been studied for over a century. We consider such a problem where the distribution is a mixture of k Gaussians in d dimensions. The objective is density estimation: given i.i. d. samples from the unknown distribution, produce a distribution whose total variation from the unknown distribution is within some desired accuracy. We contribute to this problem by designing an algorithm with nearoptimal sample complexity.
Knee-Based Decision Making and Visualization in Many-Objective Optimization

As an essential component in multi- and many-objective optimization, decision-making process either selects a subset of solutions from the whole Pareto front or guides the search toward a small part of the Pareto front during the evolutionary process. In recent years, for many-objective optimization problems (MaOPs), a number of evolutionary algorithms have been developed to search for Pareto optimal solutions. However, there is a lack of research works focusing on designing decision-making approaches. In order to overcome this deficiency, we propose a novel knee-based decision-making method to search for several solutions of interest (SOIs) from a large number of solutions on the Pareto front, each of which contains the best convergence performance at least within its neighborhood and can be identified as a global or local knee solution. The optimization performance achieved by all SOIs approximates the performance of the whole Pareto front as much as possible. Furthermore, in order to relieve the difficulties in the decision-making process on MaOPs, a new visualization approach is developed based on this proposed decision-making approach. It provides information about the shape and location of the Pareto front, the possible bulge, as well as the convergence degree and distribution of solutions. The experimental results on several benchmark functions demonstrate the superiority of the proposed design in the selection of SOIs and visualization of high-dimensional objective space.
Comparison between Inflexible and Flexible Charging of Electric Vehicles—A Study from the Perspective of an Aggregator

This paper is about the problem of the management of an aggregator of electric vehicles participating in an electricity market environment. The problem consists in the maximization of the expected profit through a formulation given by a stochastic programming problem to consider the uncertainty faced by the aggregator. This uncertainty is due to the day-ahead market prices and the driving requirements of the owners of the vehicles. Depending on the consent of the owners, inflexible charging to flexible charging is considered. Thus, the aggregator can propose different profiles and charging periods to the owners of electric vehicles. Qualitatively, as expected, the more flexible the vehicle owners, the higher the expected profit. The formulation, however, offers more to the aggregator and provides the ability to quantify the influence of consent of favorable driving requirements in the expected profit, allowing the aggregator to consider rewarding the owners of vehicles with more flexibility. Case studies addressed are for comparison of the influence of owners having inflexibility, partial flexibility, or flexibility in the expected profit of the aggregator.