Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Diversity and Structure Analysis of Pea Grown in Iraq Using Microsatellite Markers

The diversity and population structure of twenty-two genotypes of peas (Pisum sativum L.) grown in Iraq were estimated using microsatellite [simple sequence repeats (SSRs)]. Nineteen SSR primers generated sixty-eight polymorphic bands with an average of 3.789 polymorphic bands per primer. The highest number of polymorphic bands stated for the locus AA5 (eight alleles). Means of gene diversity, PIC, marker index, resolving power and Shannon index were 0.562, 0.513, 2.090, 2.703 and 0.833, respectively. Principal component analysis and hierarchical cluster analysis clustered the pea genotypes into three major clades. Genotypes G1 (ORP-2), G5 (ORP-11) and G6 (ORP-12) and G7 (ORP-13) were genetically the most distant from the other genotypes. Analysis of molecular variance (AMOVA) revealed that differences among the populations accounted for 14 % of the total variation, whereas difference within the population was 86 %. The population structure assay conceded that the genotypes were grouped into two evident subpopulations. Only three genotypes: G4 (ORP10), G11 (Ns minima) and G17 (Karina) were considered to be admixture. The multi-locus0T 0T5TF5TRSTR0T 0Tanalysis revealed strong differentiation within the populations and significant isolation by distance.0T The results of this study revealed that 0Tdifferent origins of genotypes had played a remarkable role in shaping the current patterns of genetic variation among these populations, many of which serve as good candidates for conservation and breeding programs.
Structure of fish assemblages on coastal rocky shores of the Azores

The structure of fish assemblages was investigated from the surface down to 25 m depth on Azorean rocky shores. A total of 57 fish species was recorded by visual censuses, most species (66%) occurring in the whole depth range studied. Fish abundance was dominated by 11 species, mainly sparids, labrids, carangids and pomacentrids, which constituted over 88% of the total number of individuals recorded. The trophic structure of the fish assemblages studied in the Azores was characterized by the dominance of benthic mesocarnivores and high proportions of herbivores and pelagic macrocarnivores. RESUMO. A estrutura das comunidades ictiologicas dos fundos rochosos dos Acores foi estudada desde a superficie ate aos 25 m de profundidade. Um total de 57 especies de peixes foi identificado com recurso a censos visuais. A maioria das especies (66%) ocorreu em toda a gama de profundidades estudada. A fauna ictiologica era dominada, em termos de abundância, por 11 especies, principalmente pertencentes as familias Sparidae, Labridae, Carangidae e Pomacentridae, os quais constituiram mais de 88% do numero total de individuos observados. A estrutura trofica das comunidades ictiologicas estudadas nos Acores apresentou- se dominada por meso-carnivoros bentonicos e proporcoes elevadas de herbivoros e macro-carnivoros pelagicos.
Automatic Deidentification by using Sentence Features and Label Consistency

Deidentification of clinical records has drawn a great deal of attention in the medical field. Since texts in clinical records are mostly ungrammatical and fragmented, previous approaches have relied only on local information, namely contextual words surrounding a current target word. The present paper proposes a new approach employing three types of non-local features, which does not come from surrounding words: (1) sentence features, corresponding to the previous/next sentence information and (2) label consistency, preferring the same label for the same word sequence. The experimental results showed high performance (precision 98.29%; recall 96.66%; f-measure 97.47), demonstrating the feasibility of the proposed approach.
Implementing Authentic Materials through Critical Friends Group (CFG): A Case from Turkey

TThe purpose of this exploratory case study is to investigate the use of authentic materials through Critical Friends Groups (CFG) in a language preparatory program, at a private university in Turkey. Specifically, the study attempted to identify the perceptions and observed behaviours of native and nonnative EFL instructors on the use of authentic materials, find out the potential reasons behind the implementation of authentic materials in their classroom practices and finally, examine the influence of incorporating authentic materials through CFG on classrooms practices as well as teachers’ professional development. The participants were eight EFL instructors offering English courses in the exiting preparatory program. Data were collected through interviews, lesson observations and reflective essays. The findings revealed that participating in CFG has transformational impact on instructors regarding their classroom practices as well as on their continuous professional development.
TO CREDIT BY NON-FINANCIAL FIRMS *

In order to study the availability of credit to non-fi nancial fi rms, we use in this article two different approaches, one based on prices and the other on amounts of loans. Using unique data sets, the fi rst exercise is to estimate an econometric model for the interest rates on new or renegotiated loans made by non-fi nancial fi rms in June 2010, controlling for characteristics of the loan and the company. Then, we show that the part of the increase between June 2010 and October 2011 in interest rates for similar loans that is explained by variations in the characteristics of loans and businesses is residual. This suggests that factors such as the increase in banks’ fi nancing and capital costs may have been the source of this increase in interest rates. In the exercise with quantities, we estimate a model of the amount of credit using a panel of loans (or companies), including loan (or fi rm) fi xed effects. We show that the typical credit amount of a non-fi nancial fi rm fell rapidly from the beginning of 2009 on, attaining a minimum of several years. This decline was especially sharp for companies which fi rst sought credit.
A Consumer Level 3D Object Scanning Device using Kinect for Web-based C2C Business

3D scanner captures the appearance and geometry of a real object, and forms a virtual one which can be displayed in 3D on computers. However, the high cost of 3D scanning devices inhibits the popularity of scanned 3D objects on the web and related applications. Our system targets for developing a consumer-level 3D scanning device suitable for naïve web users with the use of a novel natural depth sensing device – Kinect. As the Kinect device is a low-cost, robust and fast depth camera with color, these essential features enable us to acquire RGBD images from different views of the target object. To facilitate the registration of point clouds from various depth images, we first combine marker-based tracking system to estimate the current view angle of Kinect during capture. Then, we employ the Iterative Closest Point (ICP) algorithm with the efficiency feature detection to reconstruct a single point cloud representing the 3D object surface. To reduce size of point cloud, a down-sampling is applied to remove redundant and densely sampled points in the model. The whole process of capturing, storing, uploading and displaying 3D data on web application is done with minimal user involvements. Users can freely control the viewing angle of their favorite product with the 3D scanned point cloud object displayed in the browser; this greatly enhances user's shopping experience. We believe that the introduction of attractive and fashionable 3D product on the web will gain significant attention from customers and evolve habits and traditions in e-commerce, especially for C2C business, e.g. auction sites like ebay and taobao, in which sellers can promote their goods for sale with scanned 3D models
Deep Learning for Stock Market Prediction : Exploiting Time-Shifted Correlations of Stock Price Gradients

Although the application of machine learning to financial time series in stock markets, as an enhancement of technical analysis, experienced an increased interest in the last decades, research on more recent techniques from the area of deep learning for this purpose, and for the testing of economic theory, remains sparse. More generally, a surge in research on deep-layered models for time series analysis led to applications in a variety of fields, establishing this topic as a challenging subject. The first part of the tested hypothesis states that deep-layered feedforward artificial neural networks are able to learn complex time-shifted correlations between step-wise trends of a large number of noisy time series, using only the preceding time steps’ gradients as inputs. The second part states that such correlations are present in stock prices, and that these models can be used to predict changes in a price’s trend based on other stocks’ trend gradients of the previous time step, delivering empirical evidence against both the random market hypothesis and the efficient-market hypothesis. In more narrowly defined terms, this applied part is situated at the intersection of computational finance and financial econometrics. Using the stocks of the S&P 500 Index as an experimental dataset, the models developed for this thesis are able to successfully predict trend changes based solely on information about other stocks’ preceding gradients, with accuracies above chosen market baselines and adhering to methods used for a rigorous statistical validation of the results. Apart from the applicability of the investigated approach to a vast array of problems dealing with complex relationships between numerous and noise-laden time series, this thesis presents compelling evidence against both economic hypotheses.
The Stability of Parabolic Problems with Nonstandard p(x, t)-Growth

In this paper, we study weak solutions to the following nonlinear parabolic partial differential equation ∂ t u − div a ( x , t , ∇ u ) + λ ( | u | p ( x , t ) − 2 u ) = 0 in Ω T , where λ ≥ 0 and ∂ t u denote the partial derivative of u with respect to the time variable t, while ∇ u denotes the one with respect to the space variable x. Moreover, the vector-field a ( x , t , · ) satisfies certain nonstandard p ( x , t ) -growth and monotonicity conditions. In this manuscript, we establish the existence of a unique weak solution to the corresponding Dirichlet problem. Furthermore, we prove the stability of this solution, i.e., we show that two weak solutions with different initial values are controlled by these initial values.
An optimal power management strategy for power split plug-in hybrid electric vehicles

Model Predictive Control (MPC) can be an interesting concept for designing a power management strategy for Hybrid Electric Vehicles (HEVs) according to its capability of online optimisation by receiving current information from the powertrain and handling hard constraints on such problems. In this paper, a power management strategy for a power split plug-in HEV is proposed using the concept of MPC to evaluate the effectiveness of this method on minimising the fuel consumption of those vehicles. Also, the results are compared with dynamic programming.
E STIMATION OF STOCHASTIC TRAFFIC CAPACITY USING EXTREME VALUE THEORY AND CENSORING : A CASE STUDY IN S ALEM

In this work, we introduce a method of estimating stochastic freeway capacity using elements of both extreme value theory and survival analysis. First, we define capacity data, or estimates of the capacity of the roadway, as the daily maximum flow values. Then, under a survival analysis premise, we introduce censoring into our definition. That is, on days when flows are sufficiently high and congestion occurs, corresponding flow maxima are considered true estimates of capacity; otherwise, for those days that do not observe high flows or congestion, flow maxima are deemed censored observations and capacities must be higher than the observations. By extreme value theory, the collection of flow maxima (block maxima) can be appropriately approximated with a generalized extreme value (GEV) distribution. Because of small sample sizes and the presence of censoring, a Bayesian framework is pursued for model fitting and parameter estimation. To lend credence to our proposed methodology, the procedure is applied to real-world traffic stream data collected by the New Hampshire Department of Transportation (NHDOT) at a busy location on Interstate I-93 near Salem, New Hampshire. Data were collected over a period of 11 months and raw data were aggregated into 15-minute intervals. To assess our procedure, and to provide proof of concept, several validation procedures are presented. First, using distinct training and validation subsets of our data, the procedure yields accurate predictions of highway capacity. Next, our procedure is applied to a training set to yield random capacities which are then used to predict breakdown in the validation set. The frequency of these predicted breakdowns is found to be statistically similar to observed breakdowns observed in our validation set. Lastly, after comparing our methodology to other methods of stochastic capacity estimation, we find our procedure to be highly successful.
Transfer Entropy Characterization of TBI Cases

Traumatic brain injury (TBI) is an important public health problem worldwide. This paper introduces transfer entropy as a measure to identify any standard between arterial blood pressure and electrocardiogram signal for patients diagnosed with TBI. Therefore, we will review the basic definitions of information theory and transfer entropy, which interpretation is influenced not only by the Kullback-Leibler divergence, but also by conditioned mutual information. For transfer entropy measurement we used Kraskov-StögbauerGrassberger (KSG) technique. It is observed that directionality in transfer entropy can provide clinical decision support for TBI cases. Keywords— Arterial blood pressure, electrocardiogram, transfer entropy, traumatic brain injury.
Simulation of Thermo-fluid Interactions in Cryogenic Stage Turbine Startup System Using AUSM+-UP-based Higher-order Accurate Flow Solver

High-speed turbines are used in upper stage liquid engines of launch vehicles and the most common ones include LH2 and LOX turbines used in the cryogenic stages. The main constraints in the design of turbine system for a liquid engine are thermal loads, mass flow and pressure drops in various systems ahead of the turbine inlet. The temperature of the combustion products/gases reaching the turbine blades must be well below the melting point of the turbine blade material and the mass flow rate must be sufficient to generate the required power. Turbine can be started in two ways, by generating gases using a solid propellant-based spinner motor, and using compressed gases stored in gas bottles. The first method involves design challenges but requires less space and weight. On the other hand, second method is simple but requires more space. Because of the space and weight constraints associated with the upper stages, first method is preferred and discussed in this paper. It consists of a solid propellant-based spinner motor with a convergent-divergent nozzle, a guiding duct connecting nozzle exit, and the turbine inlet manifold in the form of a torroid with nozzle block having 39 guiding nozzles. The combustion products generated by the spinner motor are guided to the manifold through the guiding duct. Inlet manifold acts as a reservoir and supplies hot gases uniformly to the turbine through 39 nozzles. This study addresses the role of computational fluid dynamics in the design of turbine startup system using unstructured cell-centered AUSM+-UP-based finite volume solver with the twoequation turbulence model. The flow and the thermal characteristics of the solid motor with a convergentdivergent nozzle were studied to evaluate the gas temperature, operating pressure, and flow velocities. The guiding duct along with the inlet manifold was analysed separately to find the drop in temperature and pressure within the system. From the simulation results, the mass flow through each guiding nozzle, and hence, energy available could be evaluated to ensure proper functioning of the turbine. Defence Science Journal, 2009, 59(3), pp.215-229 , DOI:http://dx.doi. org/10.14429/dsj.59. 1515
0 Authenticity Effects of Leader ’ s Emotion Expression on Leadership Effectiveness and Followers ’ Trust

This paper explores the consequences of authentic and inauthentic emotion expression by leaders. We develop a conceptual model describing how the authenticity of leader’s emotion expression influences followers’ trust in their leader as an explanation of the leader’s subsequent effectiveness. Theory suggests that leaders are more likely to gain trust from followers and, therefore, to be more effective, when they express authentic emotion as opposed to feigned emotion. Implications and future directions are discussed.
Phylogenetics, zoogeography, and the role of dispersal and vicariance in the evolution of the Rana catesbeiana (Anura: Ranidae) species group

The Rana catesbeiana species group consists of seven species, each variously distributed across eastern North America. We estimated the evolutionary relationships among 31 exemplars and used the phylogenetic hypothesis to examine the potential modes of speciation and relative role of dispersal in the evolution and zoogeography of this species group. Phylogenetic relationships based on 1554 combined base pairs of the cytochrome b and ND2 mitochondrial genes suggest that the species are closely related, having undergone rapid radiation from a common ancestor during the late Miocene or Pliocene. A Pleistocene origin for the rare R. okaloosae is suggested by its pattern of paraphyly with R. clamitans and by its geographically restricted distribution, although hybridization as the explanation for paraphyly cannot be ruled out. Dispersal–vicariance analysis suggested a Coastal Plain biogeographical region origin of the species group, supporting the notion that the region was an important centre of anuran diversification, with post-speciation dispersal playing a major role in explaining the distribution of the widespread species, R. catesbeiana, R. clamitans, and R. septentrionalis. High sea levels during the late Tertiary, greatly reducing and insularizing parts of the southern Coastal Plain region may have played a major role in the diversification of this group. © 2003 The Linnean Society of London, Biological Journal of the Linnean Society, 2003, 80, 601–624.
Apprentissage multi-vue de co-similarités pour la classification

En classification, les donnees se presentent souvent sous la forme d'une matrice de donnees unique [objets/caracteristiques]. Cependant, dans de nombreuses applications, plusieurs types d'objets lies par des relations peuvent exister, ce qui conduit a avoir plusieurs matrices representant chacune une vue particuliere sur les donnees. C'est le cas dans l'etude des reseaux sociaux ou les differents nœuds d'un graphe d'interaction font intervenir des utilisateurs, des documents, des termes, etc. Dans ce papier, nous introduisons une architecture permettant d'etendre les capacites de l'algorithme de calcul de co-similarite \x-sim afin de le rendre apte a travailler sur des collections de matrices decrivant les relations entre plusieurs paires d'objets differents (multi-view clustering). Nous montrons que cette architecture offre un cadre formel interessant et permet de delivrer souvent des resultats superieurs ou egaux aux approches classiques mono-relation tout en permettant, grâce a une parallelisation possible des calculs, de reduire la complexite en temps et en espace des problemes traites.
Educating Competitive Students for a Competitive Nation: Why and How Has the Chinese Discourse of Competition in Education Rapidly Changed Within Three Decades?

In the late 1980s, the Chinese government instituted massive educational reforms to promote competition between schools and between students. By the late 1990s, however, educational reforms shifted to regulating and reducing competition in primary and secondary education. Why did a rapid policy swing occur? What was the rationale for the policy change? This article examines the Chinese discourse of competition in education by presenting a textual analysis of 101 commentary articles published by Chinese educators between 1986 and 2014. It reports two different views of competition among Chinese educators, one of which strongly prevailed throughout the 28 years. It also documents historical change in the authors’ perceptions of competition: in the late 1980s, as a powerful solution to the educational and social problems facing China, and, by the late 1990s, as a major educational problem itself.
MANIPULATOR BASE PLACEMENT SOLVED WITH HEURISTIC SEARCH

In some cases, the decision to place the robot base is based on human judgments like symmetry and space available into manufacturing cells, yet this not guaranteed the best position of robot respect to some parameter, such as dexterity or energy consumption. This paper proposes a method to locate the frame base of serial manipulators using energy calculation and heuristic search, specifically describes the behavior of a six-degree-of-freedom industrial robot based on dynamic simulations for point-to-point operations. The results are restricted to classic joint trajectory planning and the success of the proposed methodology is compared with the base placement using symmetry.
STATISTICAL DESIGNS AND RESPONSE SURFACE TECHNIQUE FOR THE OPTIMIZATION OF EXTRA CELLULAR LACCASE ENZYME PRODUCTION BY USING PLEUROTUS SP.

A response surface methodology (RSM) was used for the optimization of extra cellular laccase production using Pleurotus sp. Central composite experimental design was applied in the analysis of results and this procedure required limited number of experiments performed while providing possible interactions of selected components. Optimum values of tested variables for the maximum laccase production were; mannitol 4.8gm/l, beef extract 3gm/l and pH 6.2 and copper sulphate 4 mg/l, the maximum laccase production was 90.861U/ml. Only 27 experiments were attained this optimum conditions for enzyme production and the coefficient of determination was 89.0%. In the present study, we have demonstrated that the use of central composite factorial design for high yield of enzymes.
Alleviating the Small-Signal Oscillations of the SMIB Power System with the TLBO–FPSS and SSSC Robust Controller

Power systems are subjected to small–signal oscillations that can be caused by sudden change in the value of large loads. To avoid the dangers of these oscillations, the Power System Stabilizers (PSSs) are used. When the PSSs can not be effective enough, installation of the Thyristor–based compensators to increase the oscillations damping is a suitable method. In this paper, a Static Synchronous Series Compensator (SSSC) is used in Single–Machine Infinite–Bus (SMIB). To control the signal of the output voltage of SSSC, a robust controller is used. Also, we proposed a hybrid control method to adjust the PSS voltage using Teaching–Learning Based Optimization (TLBO) algorithm and Fuzzy Inference System (FIS). Objective functions of designing parameters are based on Integral of Time multiplied by Absolute value of the Error (ITAE). The time–variations of angular speed deviations are investigated in different modes, including: with SSSC/PSS, without SSSC/PSS, different input mechanical power, and different system parameters.