Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Genetic Variations among Native and some Local Chicken Populations in Turkey

Genetic variations among native and local chicken populations in six different locations across Turkey were established using 15 ISSR primers, and produced 87 bright and reproducible bands. According to pairwise genetic differentiation among the populations (GST), the highest genetic differentiation was determined between the Samsun and Yozgat population and the lowest was observed between the Dulkadirli and Budak populations. Shannon’s index was calculated to be 0.239. The gene flow (Nm) among the populations was estimated to be 3.489, which indicated low levels of differentiation among the populations. Analysis of Molecular Variance (AMOVA) identified 13% of the total genetic variation between the populations and the rest of the differences were 87% within the populations. Cluster analysis revealed two main branches, one leading to the domestic chicken population collected from Samsun in the Black Sea region of Turkey, the other branch clustered into two branches; one branch consisting of the Denizli Native Chicken population and the other one of domestic chicken populations sampled from Central Anatolia populations. The study is important to clarify the indigenous chicken genetic resources in Turkey. The results could be used for future breeding research conducted by either the public or private sectors.
Is a Time-Of-Flight Camera Better than a Mouse for 3D Direct Selection in Virtual Worlds?

We present an empirical study on direct selection tasks in virtual environment (VE). The aim is to assess the interest of a new markerless hand tracking system, based on a time-of-flight 3D camera, on a classical mouse, by comparing performances and subjective judgments relatively to utility, usability and immersion. Performances were similar with our system, compared to the mouse, but the perceived usefulness and immersion were judged better. Our system remains lower than the mouse in terms of efficiency and satisfaction. The study reported here, through a simple selection task, demonstrates the interest of this type of camera for real time motion capture. This contribution is a first step and we have to further study more complex task like navigation in virtual environments and object manipulation (moving, scaling, and orientation).
The relationship between early maladaptive schemas and three dimensions of headache impact in Iranian outpatients with chronic migraine without aura

Introduction: Although many researches showed that there are several psychiatric comorbidities in people suffering from migraine headache, few studies investigated the relationship between deep psychopathological structures and headache variables. The purpose of the present study was to elucidate the relationship between early maladaptive schemas and three dimensions of headache impact, pain intensity, disability and affective distress among Iranian outpatient females suffering from chronic migraine without aura. Methods: 136 consecutive outpatients suffering from a chronic migraine without aura were recruited from 553 consecutive outpatients complaining of a persistent headache and/or referred to a specialized headache clinic in Baqiyatallah Hospital. All participants completed two questionnaires regarding Schema Questionnaire–Short Form McGill Pain Questionnaire–Short Form, Migraine Disability Assessment Scale, and the the State-Trait Anxiety Inventory-Trait subscale. Finally, Pearson product-moment correlation coefficients and multiple regression analyses were calculated to investigate relationships between the research variables. Results: The data analyses indicated that a significant amount of the variance of pain intensity was explained by self-sacrifice, emotional inhibition, and unrelenting standards/hypercriticalness. Also, self-sacrifice and unrelenting standards/hypercriticalness explained a significant amount of the variance of disability. Further, a significant amount of variance of affective distress explained by emotional inhibition and unrelenting standards/hypercriticalness. Discussion: The findings emphasize on the predictive role of this early maladaptive schemas, especially early maladaptive schemas of the domain of overvigilance/inhibition. Also, this study implicitly suggests that schema therapy can be an appropriate remedy for reducing headache impact dimensions, at least, in Iranian female outpatients suffering from migraine without aura .
2-deoxyglucose selection system for Agrobacterium-mediated transformation of Solanum lycopersicon and Nicotiana tabacum plants

An alternative marker to antibiotic and herbicide genes, 2-deoxyglucose-6-phosphate phosphatase (DOG1) gene was used to produce transgenic tomato (Solanum lycopersicon) and tobacco plants (Nicotiana tabacum) via Agrobacterium-mediated transformation approach. A binary vector, pBIDOG with T-DNA cassette consists of CaMV35S-DOG1-nos was mobilized into Agrobacterium tumefaciens LBA4404 via electroporation and subsequently transformed into tomato and tobacco tissues. Selection of transformants of both plants was carried out by using 600 mg/l 2-deoxyglucose (2-DOG) as selection agent. 2-DOG resistant calli were regenerated into shoots and PCR analysis revealed that 75% and 71% of putative transgenic tomato and tobacco shoots were positive for DOG1 gene, respectively. Southern blot analysis was carried out to confirm the integration of transgene. The expected ~1.5 kb band was obtained to prove the integration of DOG1 gene into the plant genome. Transgenic tomato and tobacco plants were successfully regenerated without any phenotypic changes when compared to wild-type plants. Therefore, this alternative selection system can be applied to other plant transformation systems to produce transgenic plants free from antibiotic and herbicide genes, especially for important economic crops. More importantly, this selection system does not lead to any extent hazard to human and animal that subsequently will improve public acceptance of future genetically modified products.
Laboratory study of the larvicidal efficacy of a local plant Hertia cheirifolia against the most abundant mosquito species, in Algeria

Mosquitoes are vectors of several diseases affecting humans and domestic animals worldwide. Plants seem to be alternative sources, instead of conventional pesticides, for mosquito control agents. Essential oils are used fumigants and have low toxicity to non target animals and toxicity to insect pests. The purpose of the present study was to assess the larvicidal activity of a medicinal plant, Hertia cheirifolia, against Culex pipiens mosquito, under laboratory conditions. The toxicological assays were carried out using a powder formulation of Hertia cheirifolia, with different concentrations (8, 16 and 48g/l), on the fourth instar larvae of Culex pipiens, for 24 hours as recommended by World Health Organization (WHO), to determine the two lethal concentration LC50 and LC90. The obtained results showed a highly significant effect of this plant with all tested concentrations, with dose response relation-ship mortality, for all treated larval stages. Using the highest concentration of 48g/l of the plant extract the mortality increased throughout the stages; when it was 98.66% for the L1, 93.33% for L2, 86.66% for L3 and 82.66% for the oldest stage L4. The lethal concentrations LC50 and LC90 were estimated with confidence limits, and their values increased inversely to the larval stages.
Method for forming a magnetic field of arbitrary shape from an established template

A strategy to design a particular form of magnetic field along an axis from a coaxial inductor is described. The procedure is illustrated with the design of a constant magnetic field inside a cubic inductor. It validates the goodness of the method by comparing the results with all possible combinations of inductance within a limited set of solutions.
Diversity In Performance Reporting. Empirical Evidence From The London Stock Exchange Concerning The Classification Of Interest Components Within The Income Statement

This study is motivated by the concerns of researchers, practitioners, and regulators regarding the drawbacks of non-statutory earnings subtotals. We investigate whether the flexibility in classifying subtotals within the income statement provided to managers under IFRS serves its intended purpose of facilitating the needs of investors. Responding to criticism, the IASB is currently deliberating on explicitly defining an EBIT subtotal. However, such an endeavour requires a clarification of how various interest components should be classified. In light of the IASB’s deliberations, we also investigate a European capital market’s treatment of two typically diffuse interest components interest on defined benefit obligations and finance leases by assessing their abilities to predict stock price and stock return. Using a sample of 391 non-financial firms on the London Stock Exchange, we document diversity among European firms in classification of the two interest components. Results show that the diversity in reporting practices does not result in more relevant disaggregation of earnings, suggesting flexibility do not facilitate the needs of investors. Furthermore, an explicitly defined EBIT subtotal might prove more relevant when industry-specific factors are taken into account. Moreover, this paper does not provide inferences as to how an EBIT subtotal may or may not be defined, however the results shed some light on how investors classify two typically diffuse interest components as opposed to how European firms classify them. This paper also contributes to the work of standard setters by providing an indication of which type of EBIT subtotal could be more beneficial to European capital markets.
Error Checking for Chinese Query by Mining Web Log

For the search engine, error-input query is a common phenomenon. This paper uses web log as the training set for the query error checking. Through the n-gram language model that is trained by web log, the queries are analyzed and checked. Some features including query words and their number are introduced into the model. At the same time data smoothing algorithm is used to solve data sparseness problem. It will improve the overall accuracy of the n-gram model. The experimental results show that it is effective.
Parallel kNN Queries for Big Data Based on Voronoi Diagram Using MapReduce

In cloud computing environments parallel kNN queries for big data is an important issue. The k nearest neighbor queries (kNN queries), designed to find k nearest neighbors from a dataset S for every object in another dataset R, is a primitive operator widely adopted by many applications including knowledge discovery, data mining, and spatial databases. This chapter proposes a parallel method of kNN queries for big data using MapReduce programming model. Firstly, this chapter proposes an approximate algorithm that is based on mapping multi-dimensional data sets into two-dimensional data sets, and transforming kNN queries into a sequence of two-dimensional point searches. Then, in two-dimensional space this chapter proposes a partitioning method using Voronoi diagram, which incorporates the Voronoi diagram into R-tree. Furthermore, this chapter proposes an efficient algorithm for processing kNN queries based on R-tree using MapReduce programming model. Finally, this chapter presents the results of extensive experimental evaluations which indicate efficiency of the proposed approach.
COMMONALITY COST ANALYSIS IN SUPPLY CHAIN BASED ON COMMON PLATFORM

This paper illustrates how common platform (CP) strategy can contribute to the effectiveness of the supply chain through commonality. Through reviewing the related literature and the practical data, which are collected through observations in manufacturing, a mathematical model is set up. This model was developed for reducing cost of part commonality in SCM and solved it by simulated annealing approach. Through applying this concept, chain members can reduce manufacturing variability, i.e. the variety of parts, materials, components, etc, and thereby enable companies to increase value by producing a variety of products. One can say that the logics of applying CP and commonality in manufacturing area is, to simplify the offering and processing of products in order to reduce the parts variety. This will be accomplished through standardizing components and resource sharing strategies, and will result in the costs and time reduction, and other non value added factors. This work is one of the first to present SCM based on CP concept for supporting decision makers. The main research questions include: 1) Why CP in SCM to be applied? 2) Which combination of commonality is suitable for reduce part and component variety, 3) how much cost saving obtain, and how can we contribute to its application.
Do we buy more or less when we want to learn? The knowledge strategies and structural forms of US cross-border acquisitions

Cross-border acquisitions may be a primary mode for accessing novel knowledge and the building up of knowledge capabilities. However, the successful exploration of novel business and/or location knowledge may require specific structural forms for the incorporation and internal transfer to occur. In this paper we examine the relationship between the knowledge strategy and the structural form of the acquisition, specifically the degree of equity acquired. Our analyses of 439 US cross-border acquisitions revealed a curvilinear effect of location-related knowledge exploration but a linear effect of business-related knowledge exploration on the structural form of cross-border acquisition. We conclude that the knowledge strategy, and perhaps the type of knowledge being sought, is related in complex manners to the structural form adopted.
ssociation Between Schizophrenia and the Syntaxin A Gene lbert

ackground: Both microarray and candidate molecule studies have demonstrated that protein and mRNA expression of syntaxin nd other genes involved in synaptic function are altered in the cerebral cortex of patients with schizophrenia. ethods: Genetic association between polymorphic markers in the syntaxin 1A gene and schizophrenia was assessed in a matched ase-control sample of 192 pairs, and in an independent sample of 238 nuclear families. esults: In the family-based sample, a significant genetic association was found between schizophrenia and one of the four single ucleotide polymorphisms (SNPs) tested: an intron 7 SNP (transmission disequilibrium test [TDT] 2 5.898; df 1; p .015, amily-based association test [FBAT] z 2.280, p .023). When the results for the TDT and case-control analyses were combined, the ssociation was stronger (n 430; zc 2.859; p .004). Haplotype analysis supported the association with several significant values hat appear to be driven by the intron 7 SNP. onclusions: The results should be treated with caution until replicated, but this is the first report of a genetic association between yntaxin 1A and schizophrenia.
CFD Simulation of a solid bowl centrifuge used for waste management

This study presents some initial results from the numerical simulation of the flow in a solid bowl centrifuge used for the particle separation in the industrial fluid processing. Fluent, Computational Fluid Dynamics (CFD) software was used to simulate this multiphase flow. Simplified two dimensional and three dimensional geometries were built and meshed from the real centrifuge geometry. The CFD results showed a boundary layer of axially fast moving fluid at the gas-liquid interface. Below this layer there was a thin recirculation. The obtained tangential velocity values are lower than the ones for the rigid-body motion. Also, the trajectories of solid particles were evaluated.
A Machine Learning Approach on Classifying Orthopedic Patients Based on Their Biomechanical Features

A person’s orthopedic health condition can be detected from his biomechanical features. Now a days, disease prediction can be done automatically. Application of machine learning algorithms in medical science is not new. Different algorithms are applied to detect diseases and classify patients accordingly. This paper aims to assist specialists to predict the type of orthopedic disease. In this paper we have applied various machine learning algorithms to find out how each algorithm performs to detect and classify orthopedic patients. Each of the patient in the dataset is represented by six biomechanical attributes derived from the shape and orientation of pelvis and lumbar spine. We performed our operation in two stages and got an average accuracy of more than 90 percent for most of the algorithms, whereas Decision Tree (DT) algorithm stood out from the rest providing 99 percent accuracy.
Preface Towards practical applications in ensemble hydro-meteorological forecasting

Y. He1,*, F. Pappenberger2, J. Thielen-del Pozo3, A. Weerts4, M. -H. Ramos5, and M. Bruen6 1Department of Geography, King’s College London, Strand, WC2R 2LS, London, UK 2European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK 3EC Joint Research Centre, IES, via E. Fermi, 2749, 21027 ISPRA (VA), Italy 4Deltares, Inland Water Systems – Operational Water Management, Rotterdamseweg 185, P.O. Box 177, 2600 MH Delft, The Netherlands 5Cemagref, UR HBAN, 1, rue Pierre-Gilles de Gennes CS 10030, 92761 Antony Cedex, France 6UCD School of Civil, Structural and Environmental Engineering, University College Dublin, Newstead, Belfield, Dublin 4, Ireland *now at: Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, NR4 7TJ, Norwich, UK
Effectiveness of five fungal isolates as mycorrhizal inoculants of birch seedlings

Five fungal isolates were tested under nursery and field conditions as potential ectomycorrhizal inoculants for Downy birch (Betula pubescens) seedlings for a harsh site. Thirteen inoculum treatments, along with non-inoculated control seedlings, were randomly selected for the experiment. In the nursery, inoculation treatments were variably effective in enhancing mycorrhization and the inclusions of either Laccaria laccata, Paxillus involutus or Thelephora terrestris into inoculum treatments increased mycorrhization. Mycorrhization increased seedling height and reduced seedling root collar diameter relative to seedling height. In the field, mycorrhization and the inclusion of L. laccata into inoculation treatments in the nursery had positive effects on seedling survival while the isolate diversity and the inclusion of Cadophora finlandica into inoculation treatments in the nursery had negative effects. Furthermore, the isolate diversity and the inclusion of T. terrestris into inoculation treatments in the nursery had negative effects on shoot growth in the field. The results indicate that three of the isolates tested: Hebeloma velutipes, L. laccata and P. involutus, could potentially be used as mycorrhizal inoculants of birch seedlings for reclamation areas in Iceland, but further studies are needed.
Scaffolding English L2 Academic Reading through Contextualized Grammar

This study investigated the perceptions of Thai EFL students at the university level towards their English learning experiences. The two-pronged approach to data collection comprised a 27-item questionnaire administered to graduate students ( n = 26) enrolled in an academic reading class and, following the dictum of triangulation, semi-structured interviews with three participants representing three levels of English proficiency. Aiming to shed light on the role of contextualized grammar in an academic reading class, the findings suggest that most participants considered course contents (e.g., analyzing sentences and locating main ideas) of great benefit. Moreover, doing focus-on-form exercises enabled them to see how English sentences were strung together to form a holistic meaning. In conjunction with this are the reported appropriate use of learning strategies and supportive teaching performances which helped them to realize that English L2 academic reading through contextualized grammar is useful and practical. Key words : perceptions; contextualized grammar; English L2 academic reading
3D modeling of natural heterogeneous objects: an introduction to methods and algorithms

The field of three-dimensional (3D) modeling of natural heterogeneous object is relatively new and its results have many applications in science and engineering. This process starts by taking medical images through several parallel slices. These slices are then stacked in volume data and reconstructed into volume models in order to visualize the 3D object structure. This document provides a general description of the most well-known modeling methods and algorithms with a discussion of relative advantages and disadvantages for using them in generation of high-fidelity models built from medical image data such as computerized axial tomography (CAT).
Heterogeneous network-based chronic disease progression mining

Healthcare insurance fraud has caused billions of dollars in losses in public healthcare funds around the world. In particular, healthcare insurance fraud in chronic diseases is especially rampant. Understanding disease progression can help investigators detect healthcare insurance frauds early on. Existing disease progression methods often ignore complex relations, such as the time-gap and pattern of disease occurrence. They also do not take into account the different medication stages of the same chronic disease, which is of great help when conducting healthcare insurance fraud detection and reducing healthcare costs. In this paper, we propose a heterogeneous network-based chronic disease progression mining method to improve the current understanding on the progression of chronic diseases, including orphan diseases. The method also considers the different medication stages of the same chronic disease. Extensive experiments show that our method can outperform the existing methods by 20% in terms of F-measure.
Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests

A method for the parameterization of ice-phase microphysics is proposed and used to develop a new bulk microphysics scheme. All ice-phase particles are represented by several physical properties that evolve freely in time and space. The scheme prognoses four ice mixing ratio variables, total mass, rime mass, rime volume, and number, allowing 4 degrees of freedom for representing the particle properties using a single category. This approach represents a significant departure from traditional microphysics schemes in which ice-phase hydrometeors are partitioned into various predefined categories (e.g., cloud ice, snow, and graupel) with prescribed characteristics. The liquid-phase component of the new scheme uses a standard two-moment, twocategory approach. The proposed method and a complete description of the new predicted particle properties (P3) scheme are provided. Results from idealized model simulations of a two-dimensional squall line are presented that illustrate overall behavior of the scheme. Despite its use of a single ice-phase category, the scheme simulates a realistically wide range of particle characteristics in different regions of the squall line, consistent with observed ice particles in real squall lines. Sensitivity tests show that both the prediction of the rime mass fraction and the rime density are important for the simulation of the squall-line structure and precipitation.