Miracle-dz/UniFAR-FTUs huggingface dataset:
MONITORING TRANSIENT PHENOMENA IN POWER NETWORKS: THE KEYPOINT OF ENERGETIC DISTRIBUTION SECURITY

Transient signals generated in electrical systems are different origins and they could be considered as normal or as default. Their monitoring and analysis is crucial while the phenomena behind them could lead to a partial or total destruction of the system. Because of their brief occurrence, the transient signal analysis is a challenging field in signal processing domain. In this paper, we illustrate firstly the different operational methods to deal with the transient signals issued from electrical systems. Some classes for transient signal analysis are investigated and tested on real data. The experiments presented have been done in collaboration of EDF (Electricité de France) R&D department in the period 2007-2009.
A Mitogenomic Exploration of the Phylogeny and Evolution of Extant Anurans

Phylogenetic relationships among major clades of anuran amphibians were analyzed using mitogenome sequences of 54 frog species from 41 genera. Anurans are under two major groups Archaeobatrachia and Neobatrachia. Mesobatrachia was introduced later this classification. Our phylogenetic study based on mitogenome authenticated four groups (1. Bombinatoridae + Alytidae; 2. Megophyridae + Pelobatidae + Pelobytidae; 3. Bombinatoridae + Alytidae cluster with Leiopelmatidae; 4. Pipidae + Rhinophrynidae). Our phylogenetic study confirms Neobatrachia is monophyletic and Archaeobatrachia is paraphyletic.
Message Classification for Generalized Disease Incidence Detection with Topologically Derived Concept Embeddings

— In this paper which is a culmination of previous work on creating machine learning models for message classification for generalized automated disease incidence detection in twitter messages, we investigate the use of topologically derived embeddings as opposed to previous work which relies on data driven approaches for obtaining said embeddings. This is inspired by the fact that in previous work the best performing models employ concept level representations of messages using concepts in an ontology however, the method employs a data driven approach which builds concept representations from our corpus based on the relative distribution of concepts. In this paper we tackle the question of whether it is feasible to build some static, universal conceptual embedding for natural language processing tasks related to automated disease monitoring in the social web.
The Revelation of Insider Trading using the Spread: A Comparison with the Sports Betting Market

This article compares methodologies which can be used to detect insider trading on financial markets and frauds on sports betting industry. There is a lot of evidence coming from the literature showing the similarities on financial markets and sports betting market. Furthermore, some authors highlight a spread enlargement depending on the proportion of uninformed investors during insider trading on the financial markets. Considering that, we used the bid-ask spread to see if such a phenomenon exists on sport betting industry. We used a sample of 10 litigious tennis games compared with a control-sample to examine spread’s behavior in the betting industry. We find out that, as on financial markets, spreads of litigious games increase on gambling markets before the beginning of the match, when the proportion of uninformed bettors is low. So, we can make two conclusions: on the one hand, the spread behavior could be used to detect frauds on gambling markets. On the other hand, we confirm spread’s behavior during insider trading on financial markets, which is comforting the strong hypothesis of the market efficiency theory.
Organizations’ Investment in Cloud Computing: Designing a Decision Support Platform

—Selecting the technologies suitable for an organization is a very critical and difficult task especially in the absence of historical data. Organizations have to outsource expensive cloud experts to design their technology mix and help them set their strategy. Vendors’ experts can help organizations but with the expense of less network optimization and more vendor lock-in. This paper presents a generic and vendor-neutral decision support solution that aids decision makers in setting their strategy towards cloud computing. The novelty of this proposed solution is based on its decision algorithm that uses machine learning to enhance its accuracy in selecting the suitable/recommended technologies for each user.
Naïve Bayes for Function Tagging in Myanmar Language

This paper proposes an approach to annotate function tags for unparsed text. We address the question of whether data-driven function tag assignment method can be applied to Myanmar language. We assign function tags directly basing on lexical information, which is easily scalable for languages that lack sufficient parsing resources or have inherent linguistic challenges for parsing. We investigate a supervised sequence learning method to automatically recognize function tags. In order to demonstrate the effectiveness and versatility of our method, we investigate function tag assignment for unparsed text by applying Naïve Bayesian theory. Our approach to functional analysis is to classify, so far as possible, all the processes and states which languages must describe, and to identify the functional elements which are needed for each one to construct a meaningful sentence.
Pemberian Ekstrak Air Panas Spirulina platensis melalui Perendaman Terhadap Total leukosit, Indeks fagositosis dan konsentrasi TNF-α Osphronemous gouramy

ABSTRAK Penelitian ini bertujuan untuk mengetahui pengaruh imunostimulan ekstrak air panas Spirulina (Spirulina platensis) pada ikan gurame Osphronemous gouramy. Pada penelitian ini ekstrak air panas Spirulina diuji apakah dapat meningkatkan mekanisme non- spesifik melalui parameter total leukosit, indeks fagositosis dan konsentrasi TNF-α pada hari ke 3, 5, 7dan 14 setelah perendaman ekstrak air panas Spirulina dengan dosis 15 ppm, 30 ppm, 60 ppm dan tanpa imunostimulan (kontrol) selama 3 jam. Hasil penelitian menunjukkan ekstrak air panas Spirulina dapat meningkatkan total leukosit dan indeks fagositosis pada darah dan konsentrasi TNF-α pada serum darah. Data dianalisis menggunakan Analisis Varian dilanjutkan dengan Duncan. Pada hasil menunjukkan ekstrak air panas Spirulina dapat meningkatkan total leukosit, indeks dan konsentrasi TNF-α (P<0.05). Ekstrak air panas Spirulina dengan dosis 30 ppm dapat meningkatkan total leukosit dan indeks fagositosis pada hari keempat belas dan konsentrasi TNF-α pada hari ke tujuh dbandingkan kontrol. Ekstrak air panas Spirulina dapat memberikan pengaruh pada imun non-spesifik ikan gurame. Kata kunci: Osphronemus gouramy, ekstrak air panas, Spirulina platensis
Exploration of model performances in the presence of heterogeneous preferences and random effects utilities

This work is a cross-disciplinary study of econometrics and machine learning (ML) models applied to consumer choice preference modelling. To bridge the interdisciplinary gap, a simulation and theory-testing framework is proposed. It incorporates all essential steps from hypothetical setting generation to the comparison of various performance metrics. The ﬂexibility of the framework in theory-testing and models comparison over economics and statistical indicators is illustrated based on the work of Michaud, Llerena and Joly (2012). Two datasets are generated using the predeﬁned utility functions simulating the presence of homogeneous and heterogeneous individual preferences for alternatives’ attributes. Then, three models issued from econometrics and ML disciplines are estimated and compared. The study demonstrates the proposed methodological approach’s ef-ﬁciency, successfully capturing the differences between the models issued from different ﬁelds given the homogeneous or heterogeneous consumer preferences.
Musa and Ensete nematode pest status in selected African countries

Most of the bananas in Africa are produced in two major, tropical production regions. In West and Central Africa, cultivars of the plantain subgroup, mainly False Horn and French Horn, predominate. In East Africa, however, the endemic East African highland bananas and diverse introduced cultivars predominate (Sebasigari and Stover 1987, Wilson 1987). In both production regions, bananas are mainly produced by smallholder farmers. Enset (Ensete ventricosum (Welw.) Cheesman) is cultivated from mid-altitude to the highlands (ca. 1500-3000 masl) of the south, southwest and central regions of Ethiopia (Bezuneh and Feleke 1996, Westphal 1975). Musa and Ensete production in many regions is declining due to a combination of abiotic and biotic production constraints, soil fertility decline being one of the major abiotic production constraints (Karamura 1993, Kena 1996). The major diseases found in plantain and highland bananas are black Sigatoka, caused by the fungus Myscophaerella fijiensis (Stover and Simmonds 1987) and virus diseases (Tushemereirwe et al. 1996, Hughes et al. 1998). Major pests are the banana weevil, Cosmopolites sordidus (Gold et al. 1994) and different plant parasitic nematodes, including Radopholus similis, Pratylenchus goodeyi, Pratylenchus coffeae, Helicotylenchus multicinctus and Meloidogyne spp. (Sarah 1989, Bridge 1993, Luc and Vilardebo 1961, Gowen and Quénéhervé 1990, Kashaija et al. 1994). Bacterial wilt and virus diseases are major biotic constraints of Ensete (Quimo and Tessera 1996). The relative importance of the major nematode pest species attacking Musa and Ensete in the different geographic regions and production systems is poorly understood (Frison et al. 1997). This paper therefore aims at providing an overview of data collected in diagnostic surveys conducted in Africa, which are used to prioritize nematode constraints by Musa genotype and region, based on occurrence and densities. The data are supplemented by results of yield loss studies conducted in various countries.
Comparison of DNA Concentration and Purity of Animal Blood Extracted using Different DNA Extraction Kits

The efficiency of DNA extraction from whole blood using appropriate method is very important for molecular analysis. Therefore, the aim of this study was to compare the purity and concentration of DNA extraction method from bovine (Bos taurus), chicken (Gallus gallus), and porcine (Sus scrofa) blood. The DNA of blood samples was extracted using three types of kit, namely InnuPREP Blood DNA Mini Kit, Wizard Genomic DNA Purification Kit, and QIAamp DNA Blood Mini Kit. The results showed that blood DNA extracted using QIAamp DNA Blood Mini Kit was found to be the most effective and consistently produced high concentrated and pure DNA for three animal samples. The purity of DNA ranged from 1.73 ± 0.05 Å to 1.94 ± 0.21 Å and the range of blood DNA concentration extracted using the QIAamp DNA were between 13.73 ± 2.11 and 25.01 ± 2.08 ng/? l. However, the blood DNA of porcine was not successfully extracted using InnuPREP Blood DNA Mini Kit and Wizard® Genomic DNA Purification Kit. These results were very crucial for the subsequent use of amplification using polymerase chain reaction (PCR) and to facilitate accurate detection in further analysis.
Named Entity Recognition of Electronic Medical Records Based on BERT

： In view of the poor performance exhibited by traditional words or word vectors in expressing context semantics, as well as the insufﬁciency of traditional RNN parallel computing ability in Chinese medical EMR named entity recognition, a named entity recognition model of medical EMR based on Bert has thus been proposed. In this model, the BERT pre-training language model can better represent the context semantics in electronic medical records, with the iterative expanded convolutional neural network (IDCNN) characterized with a better recognition effect on convolutional coding of local entities, and with the multiple head attention (MHA) computing the attention probability of each word and all words for many times to obtain the long-distance dependence of EMR sentences. The experimental results show that the BERT-IDCNN-MHA-CRF model can better identify medical entities in electronic medical records, and compared with the baseline model, the precision, recall and F 1 values of the model are increased by 1.80% , 0.41%
DeepRank: Adapting Neural Tensor Networks for Ranking the Recommendations

Ranking results are vital in order to display the most relevant search results to the user. Similarly, ranking properties according to the user’s context is important for enhancing user experience. In this paper we propose an expressive neural tensor network to ﬁnd similarity between two property entities to rank the properties when searched for. Previous similarity techniques do not take into account the numerous complex features used to deﬁne a property. We showed that performance can be enhanced if the property entities are represented as an average of their constituting features before ﬁnding the similarity between them. After training the model using the context and the user’s preferences, we tested it to ﬁnd out the similarity between the properties suggested to the user and the one’s in the user’s history, and then ranked the results from most to least similar. Our model hence takes into account each feature dynamically and predicts similarity with an accuracy of 86.6 percent.
Effects of Indoor and Outdoor Laboratory Instructions on Secondary School Students’ Attitude and Achievement in Physics in Jama’are Educational Zone, Bauchi State, Nigeria

This study ascertained the Effects of Indoor and Outdoor Laboratory Instructions on Students Attitude and Achievement in Physics. The study employed the quasi-experimental research design of the nonequivalent control group pretest-posttest type. Six research questions were raised and answered using the mean and standard deviation, while six null hypotheses were formulated and tested at 0.05 level of significance. t-test of independent sample was used for all the hypotheses. The target population consisted of 750 SS II Physics students (350 male students and 400 female students) in all the 10 co-educational secondary schools (8 public and 2 private schools). An intact sample of 80 SS II Physics students (32 male and 48 female) from two sampled co-educational secondary schools were involved in gathering data for the study. Two instruments were used to gather data for the study, they are; a 15 items Likert-scale Secondary School Physics Attitude Questionnaires (SSPAQ) and 40 multiple-choice Secondary School Physics Achievement Test (SSPAT). Each of the instruments was validated by three experts. The reliability coefficient of the SSPAQ was found to be 0 78 and the reliability coefficient of SSPAT was obtained as 0.95 using the Cronbach‟s coefficient alpha method on the Statistical Package for Social Sciences (SPSS) software version 23. Findings from the studies showed that the nature of the secondary school students‟ attitude and achievement to Physics is more positive after exposure to indoor and outdoor laboratory instructions; the male and female students taught with out-door laboratory method had a better positive attitude and achievement than those taught with indoor method. Based on the findings of the study, it was recommended that non-conventional teaching approaches such as out-door laboratory instruction, should be introduced into the teaching of Physics in the nation‟s secondary schools to reinforce the hitherto adopted conventional teaching method. Keyword: Indoor, Outdoor, Laboratory, Instructions, Secondary School, Students, Attitude, Physics, Educational. Reference to this paper should be made as follows: Usman, I. S. , & Danladi, A. (2020). Effects of indoor and outdoor laboratory instructions on secondary school students‟ attitude and achievement in physics in Jama‟are educational zone, Bauchi State, Nigeria. International Journal of Scientific Research in Education, 13(3), 566-580. Copyright © 2020 IJSRE
A Review on Gold Nanoparticle: An Emerging Trend in Nanomedicine and Biomedical Application

Nanotechnology has become a recent trend and one of the most interesting and advanced areas of research. The advantage of using nanoparticles include improved bioavailability, targeting the drug to a specific location in the body, and to provide a controlled release therapy. Among nanoparticles, gold nanoparticles contribute to advances due to their unique properties. These particles are widely used in various biomedical applications & as a drug delivery system due to their inert nature, high dispersity, and biocompatibility. This review describes the preparation, evaluations, and applications of gold nanoparticles in biomedical fields and targeted drug delivery. AASIYA NAHAS*, DEEPU. S, G J VAISHNAVEE M.Pharm, Mar Dioscorus College Of Pharmacy, Sreekaryam, Thiruvananthapuram, Kerala, India. Associate Professor, Mar Dioscorus College Of Pharmacy, Sreekaryam, Thiruvananthapuram, Kerala, India Submission: 20 August 2020 Accepted: 26 August 2020 Published: 30 September 2020 www.ijppr. humanjournals.com Citation: AASIYA NAHAS et al. Ijppr.Human, 2020; Vol. 19 (2): 350-367. 35
A secure version of asymptotic numerical method via convergence acceleration

The paper deals with the numerical computation of difficult problems requiring many steps and many degrees of freedom such as the finite element analysis of wrinkling of film–substrate systems. The asymptotic numerical method (ANM) is well adapted to such computations but with a progressive loss of accuracy during step chaining. Thus, correction phases are necessary, which are rarely carried out within ANM. A convergence acceleration algorithm and a step-length adaptation have been included to limit the growth of computation time and to strengthen the reliability of the procedure. This modified version of the ANM is assessed by simulating the appearance and evolution of sinusoidal wrinkles under uniaxial compression. Résumé. L’article étudie le calcul numérique de problèmes difficiles nécessitant de nombreux pas et un grand nombre de degrés de liberté, comme l’étude par éléments finis du plissement de systèmes film– substrat. La méthode asymptotique numérique (ANM) est bien adaptée à de tels calculs, mais avec une lente perte de précision lors de l’enchainement de nombreux pas de calculs. Donc des étapes de correction sont indispensables, ce qui est rarement fait lors de calculs par ANM. L’algorithme de cheminement est complété par une méthode d’accélération de convergence et par une technique d’adaptation de la longueur de pas pour minimiser le temps de calcul et pour fiabiliser la procédure. Cette version modifiée de la méthode asymptotique numérique a été évaluée par la simulation de l’apparition de plis sinusoïdaux en compression
Management Information Systems & Their Impact on Improving the Quality of Service at the Commercial Bank Customers

This study aimed to identify the ( Management Information Systems & Their Impact on Improving the Quality of Service at The Commercial Bank Customers ), was conducted this study in the year 2015/2016 m, and chose researcher random sample consisted of (50) customers at the Commercial Bank in Saudi Arabia, the study concluded that there are impact on the management information systems of Improving the Quality of Service, the study recommended to Improve policies designed to activate the management information systems because of its impact on improving the quality of service provided to customers
SINGLE MOLECULE FRET OF LACI-DNA-IPTG LOOP CONFORMATIONS

Title of Document: SINGLE MOLECULE FRET OF LACI-DNAIPTG LOOP CONFORMATIONS Kathy A. Goodson, Doctor of Philosophy, 2012 Directed By: Associate Professor, Jason D. Kahn, Department of Chemistry & Biochemistry This work focuses on the Escherichia coli lactose repressor protein (LacI) which represses expression of the lac operon. In order to repress transcription, the tetrameric LacI protein binds a primary promoter-proximal operator, O1, and one of two auxiliary operators, O2 or O3. The binding of these two sites to a single LacI molecule occurs via DNA loop formation. Induction of the lac operon by allolactose reduces the affinity of LacI for DNA, but induction does not completely prevent looping in vivo. The synthetic inducer isopropyl-! -D-thiogalactoside (IPTG) acts similarly to allolactose. Model DNA constructs have been used to demonstrate, through fluorescence resonance energy transfer (FRET) analysis, that LacI may change conformation in order to form more than one loop structure. This work employs single molecule FRET to investigate LacI-induced loop formation in DNA looping constructs, as a function of IPTG concentration, on freely diffusing LacIDNA complexes. The results include evidence for the persistence of DNA loop formation under at saturating IPTG concentration, and they provide a detailed view of how LacI conformation affects DNA loop formation. In addition, this work explores possible changes in geometry in LacI-induced DNA loops through the use of model DNA constructs that produce alternative loop topologies. We propose that inducerbound LacI-DNA looped complexes may control the kinetics of induction and rerepression of the operon. SINGLE MOLECULE FRET OF LACI-DNA-IPTG LOOP CONFORMATIONS
MONOTONICITY–PRESERVING PERTURBATIONS OF RUNGE-KUTTA SCHEMES

Exact solutions of some ordinary differential systems have qualitative properties, e.g., monotonicity, positivity, etc., which are relevant in the context of the problem. In these cases, it is convenient to preserve them numerically. For Runge-Kutta (RK) methods, the above qualitative properties can be ensured under stepsize restrictions given in terms of the radius of absolute monotonicity, also known as SSP or Kraaijevanger’s coefficient. However, some well known RK methods have a trivial SSP coefficient and, therefore, monotonicity cannot be ensured. For one of these methods, in [6] a second spatial discretization of the PDE is used wherever a negative coefficient appears in the time integration method; this process can be interpreted as a perturbation of the original RK method [2]. During the last years, several authors have studied perturbed RK methods (also known as downwind RK methods) to find high order schemes with optimal SSP coefficients (see, e.g., [5]). But monotonicity preservation is not the only numerical property of interest in applications, and one may wish to use a particular method that has small or zero SSP coefficient. In this case, we can use a perturbation of the scheme that ensures a larger monotonicity–preserving time step. In this talk we show some results on optimal monotonicity–preserving perturbations of a given explicit RK method. The presentation is based on the paper [5]. This framework can also be used to explain the qualitative correct solutions obtained in the context of positivity when some problems are integrated with explicit RK schemes that have trivial SSP coefficients (or IMEX RK methods that have trivial regions of absolute monotonicity) [1, 3].