Miracle-dz/UniFAR-FTUs huggingface dataset:
Deadline constrained Cost Effective Workflow scheduler for Hadoop clusters in cloud datacenter

Cloud computing has attracted many enterprises owing to its pay as go model and highly scalable resources. Many enterprises exploit cloud infrastructure not only for storage but also for its analytics. Currently, one of the well accepted key for analytical platform is Hadoop on datacenter. Cloud vendors host Hadoop clusters on the datacenter to provide high performance analytical computing facilities to its customers. As many concurrent users operate on the clusters for their jobs, scheduling should be very effective to complete the job in time and at same time use the resources efficiently with effective cost management. Various schedulers such as FIFO, fair share, capacity schedulers etc., are available for the Hadoop platform. These schedulers view jobs as a separate scheduling entity. And not many schedulers, schedule the workflow on datacenter. In this paper, we propose a Cost Effective Workflow scheduler for Hadoop and implement it. The job execution deadline and the financial costs are used to measure its performance.
Energetics of newly‐mated queens and colony founding in the fungus‐gardening ants Cyphomyrmex rimosus and Trachymyrmex septentrionalis (Hymenoptera: Formicidae)

Abstract The energetics of colony founding is investigated in the fungus gardening ants (Attini) Trachymyrmex septentrionalis and Cyphomyrmex rimosus. Similar to most ants, inseminated queens of these two species found nests independently unaccompanied by workers (haplometrosis). Whereas most ant founding queens seal themselves in a chamber and do not feed when producing a brood entirely from metabolic stores (claustral founding), the majority of fungus gardening ants must forage during the founding phase (semiclaustral founding). Laboratory‐reared T. septentrionalis individuals comprise 84 dealate females collected after mating flights in June 2004. Twenty are immediately killed to obtain values for queen traits and another 20 after worker emergence for queen, fungus garden and worker traits. Cyphomyrmex rimosus comprise 22 dealate females collected in June 2005; ten of which are immediately killed and similarly prepared. Newly‐mated T. septentrionalis queens have 25% of their dry weight as fat; whereas newly‐mated C. rimosus queens contain 11% fat. These amounts are 50–75% less than most independently founding ant species. Trachymyrmex septentrionalis queens lose merely 5% of their energetic content during colony founding, whereas the total energetic content of their brood is more than three‐fold the amount lost by the queen. Incipient T. septentrionalis colonies produce approximately half as much ant biomass per gram of fungus garden as do mature colonies. Similar to most ants, T. septentrionalis produces minim workers that are approximately 40% lighter than workers from mature colonies. Regardless of their size, T. septentrionalis workers contain much lower fat than do workers of claustral species. These data indicate that fungus gardening is adaptive because colonies can produce much cheaper offspring, making colony investment much lower.
Working the limits of method: the possibilities of critical reflexive practice in marketing and consumer research

Developed primarily through feminist critiques of the production of knowledge, researcher reflexivity has been identified in consumer research (Wallendorf and Brucks 1993; Hirschman 1993; Thompson 2002) and in the wider social sciences (e.g. Wasserfall 1993; Mauthner and Doucet 2003) as a way to address power and control in the research encounter, to attend to the researcher/researched dynamic and to give insightful commentaries into the research process itself. Following the call for consumer and marketing researchers to "exhibit a degree of reflexivity" in order to "recognise the role of the researcher in the production of knowledge" (Tadajewski and Brownlie 2008, p. 10), this paper develops a structured approach to the possibilities of critical reflexive practice in marketing and consumer research.
A Fast Directionally Constrained Minimization of Power Algorithm for Extracting a Speech Signal Perpendicular to a Microphone Array

— In this paper, an extended method of the directionally constrained minimization of power (DCMP) algorithm for broadband signals is proposed. The DCMP algorithm is one of the useful techniques of extracting a target signal from observed signals of a microphone array system. In the DCMP algorithm, output power of the microphone array is minimized under a constraint of constant responses to directions of arrival (DOAs) of specific signals. In our algorithm, by limiting the directional constraint to the perpendicular direction to the sensor array system, the calculating time is reduced.
Skelemin Association with αIIbβ3 Integrin: A Structural Model

Over the last two decades, our knowledge concerning intracellular events that regulate integrin’s affinity to their soluble ligands has significantly improved. However, the mechanism of adhesion-induced integrin clustering and development of focal complexes, which could further mature to form focal adhesions, still remains under-investigated. Here we present a structural model of tandem IgC2 domains of skelemin in complex with the cytoplasmic tails of integrin αIIbβ3. The model of tertiary assembly is generated based upon NMR data and illuminates a potential link between the essential cell adhesion receptors and myosin filaments. This connection may serve as a basis for generating the mechanical forces necessary for cell migration and remodeling.
Implementation of Importance-Driven Volume Rendering

Common volume visualization methods mostly guarantee a high quality rendering of volume data with integrated object specific pervoxel based rendering. Especially, in medical or engineering data not only the representation of surfaces of visible volume objects are of particular interest, but also possible volume objects which are actually hidden by other objects in the view direction could contain important information. Thus, volume object occlusion becomes very important in volume visualization applications. This report presents an efficient implementation using (Importance-Driven Volume Rendering IDVR) to render all volume objects along the view direction in relation to the associated object importance values. Due to the higher importance of specific volume objects particular parts of objects with less importance will be cut or suppressed in their transparency if they are in front of more important object. Thus, the user is able to clearly view those important but hidden objects, regardless which view direction has been chosen. IDVR actually is an addition to the common rendering pipeline and thus can be efficiently combined with other known volume visualization methods, in particular with realistic and nonphotorealistic shading methods. Considering highly complex volume data sets containing various different volume objects, the IDVR enhancement of our application will introduce an easy solution to take care of entirely visualize individually defined volume objects despite of any occlusion and from which view direction they are looked at.
Microglia modulate respiratory rhythm generation and autoresuscitation

Inflammation has been linked to the induction of apneas and Sudden Infant Death Syndrome, whereas proinflammatory mediators inhibit breathing when applied peripherally or directly into the CNS. Considering that peripheral inflammation can activate microglia in the CNS and that this cell type can directly release all proinflammatory mediators that modulate breathing, it is likely that microglia can modulate breathing generation. It might do so also in hypoxia, since microglia are sensitive to hypoxia, and peripheral proinflammatory conditions affect gasping generation and autoresuscitation. Here, we tested whether microglial activation or inhibition affected respiratory rhythm generation. By measuring breathing as well as the activity of the respiratory rhythm generator (the preBötzinger complex), we found that several microglial activators or inhibitors, applied intracisternally in vivo or in the recording bath in vitro, affect the generation of the respiratory rhythms both in normoxia and hypoxia. Furthermore, microglial activation with lipopolysaccharide affected the ability of the animals to autoresuscitate after hypoxic conditions, an effect that is blocked when lipopolysaccharide is co‐applied with the microglial inhibitor minocycline. Moreover, we found that the modulation of respiratory rhythm generation induced in vitro by microglial inhibitors was reproduced by microglial depletion. In conclusion, our data show that microglia can modulate respiratory rhythm generation and autoresuscitation. GLIA 2016;64:603–619
Following in the Steps of ʿĀʾisha: Ḥassāniyya-Speaking Tijānī Women as Spiritual Guides (Muqaddamāt) and Teaching Islamic Scholars (Limrābuṭāt) in Mauritania

Women in Ḥassāniyya-speaking Sunnī Muslim communities in Mauritania have long served as spiritual guides (muqaddamāt) and as teaching scholars (limrābuṭāt) for other women. Yet those who have done so have tended to come from a small number of prominent scholarly families. Furthermore, their activities have usually remained hidden outside of their immediate social circles and are actively excluded from the historical record. In recent years, however, a boom in Islamic learning has led to a diversification in the social backgrounds of women acting as Islamic teachers and spiritual guides. At the same time, women’s spaces of Islamic learning have become increasingly visible. This article illustrates these changes in women’s exercise of Islamic authority by recounting the life stories of several female spiritual guides and teaching scholars in Nouakchott who adhere to the Tijānī Sufi order. It also draws on historical documents and government survey data to contextualize these changes. The stories presented here highlight important aspects of women’s performance of religious authority. One is the centrality of the concept of “knowing Islam,” which entails familiarity with the Qurʾan and a range of other Islamic texts. Another is the centrality of historical models, especially that of the Prophet’s wife ʿĀʾisha, in offering contemporary women justification for engaging in the teaching and production of Islamic knowledge. Ultimately, however, estimating changes in women’s participation in Is-lamic knowledge and authority remains a difficult task because it has long been hidden and even actively erased from the historical record.
Testing of Cylindrical Surrounding Double-Gate MOSFET Parameters Using Image Acquisition

In this paper, we have analyzed the image acquisition of the Cylindrical Surrounding Double-Gate (CSDG) MOSFETs for the purpose of RF switch for the advanced wireless telecommunication systems. The proposed model will emphasize on the basics structure of the single image sensor for two dimensional images of a three dimension devices, so that we can obtained a satisfied or say smooth device structure and hence some of its parameter. The physical significance of these basic structure elements are also has been discussed.
Resting-State fMRI Functional Connectivity: Big Data Preprocessing Pipelines and Topological Data Analysis

Resting state functional magnetic resonance imaging (rfMRI) can be used to measure functional connectivity and then identify brain networks and related brain disorders and diseases. To explore these complex networks, however, huge amounts of data are necessary. Recent advances in neuroimaging technologies, and the unique methodological approach of rfMRI, have enabled us to an era of Biomedical Big Data. The recent progress of big data sharing projects with their challenges are discussed. This increasing amount of neuroimaging data has greatly increased the importance of developing preprocessing pipelines and advanced analytic techniques, which are better at handling large-scale datasets. Before applying any analysis method on rfMRI data, several preprocessing steps need to be applied to reduce all unwanted effects. Three alternative ways to get access to big preprocessed rfMRI data are presented involving the minimal preprocessing pipelines. There are several commonly used methods to examine functional connectivity. However, they become limited in the analysis of big data, and a new tool to explore such data is necessary. We propose a number of novel methods rooted in algebraic topology and collectively referred to as Topological Data Analysis to rfMRI functional connectivity. Their properties for big data analysis are also discussed.
Automatic evaluation of Dutch pronunciation by using speech recognition technology

The ultimate aim of the research reported on in this paper is to develop a system for automatic assessment of foreign speakers' pronunciation of Dutch. The aim of the experiment was to determine whether pronunciation ratings assigned by human experts could be predicted on the basis of scores calculated by an automatic speech recognizer. To this end 20 native and 60 non-native speakers of Dutch read ten phonetically rich sentences over the telephone. The automatic speech recognizer was trained with read speech of 4019 Dutch subjects with varying regional accents. The results show that the human scores can be accurately predicted, even in the case of telephone speech. Analysis of the various types of human ratings and automatic measures provides more insight into the relationship between human and machine scores and indicates how the automatic measures can be further improved to achieve even greater predictive power.
Image Binarization of Grey Level Images using Elitist Genetic Algorithm

binarization is a technique of converting a grey level image into a binarized image consisting of only two pixel intensities, i.e., black and white. Elitist Genetic Algorithm along with K-means clustering technique used here facilitates the gradual partition of the image into either of the two intensities by finding a suitable threshold value for the same. Elitist Genetic Algorithm is an improvised version of Simple GA which preserves the best results for subsequent optimization steps. Genetic Algorithms are imitation of the process of natural selection that aims at keeping the best, discarding the rest. The algorithm stops when a suitably chosen fitness function optimizes the fitness value obtained in every iteration using the operators of GA like selection, crossover, and mutation till no further change in fitness value is noticed. The result is an output image showing the binarized form of the input image.
Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles

The wide range of protein biological functions, such as enzymatic activity, ligand- and protein-proteininteractions and allosteric regulation, is strictly related to their ﬂexibility and dynamics[1]. To modelthe inﬂuence of protein motions across this broad spectrum of events Molecular Dynamics (MD) sim-ulations are now routinely used. The identiﬁcation of the most functionally relevant conformations isgenerally done by grouping the conformations according to a criterion of geometrical similarity andpopular choices include hierarchical clustering, single, complete and average linkage and k-means [10]. These geometrical approaches rely on the assumption that the identiﬁed conformational states also corre-spond to the energetic states [10]. Good candidates to improve this match are Artiﬁcial Neural Networks(ANNs) which are capable to discover the relationships between the measured variables only from theavailable dataset [9]. Among the class of ANNs, successfully applied to artiﬁcial life systems [2], SelfOrganizing Maps (SOMs) [6] represent a particularly powerful data driven model that has been widelyapplied for exploration and clustering of high-dimensional datasets [9, 6]. We recently developed anapproach which combines SOMs and hierarchical clustering to efﬁciently compare conformational en-sembles obtained from multiple MD simulations of proteins [3]. To reliably apply the SOM analysis tothese speciﬁc input data we identiﬁed and optimized a small number of SOM parameters. In particular,we conﬁrmed that the map size is a crucial parameter and that a well-selected number of neurons iscrucial both to reduce the computational cost of the analysis and to provide an intermediate topologicalrepresentation of the input conformational space [3]. As a result the original MD trajectories can berepresented by the few conformations that best represent the clusters obtained. Here we make a step fur-ther; the proposed approach consists of processing all the atom positions of each conformation won bya given SOM neuron using a similarity network. Different similarity measures between atoms behaviorare used to compile a similarity matrix which is inputted to a network model [8]. Network algorithmsare then used to automatically discover and interpret the behavior of the original protein conformationalensembles exploiting the atomic coordinates enclosed in the SOM neuron.
The Impact of Standardized Testing on University Entrance Issues in Kyrgyzstan

In Kyrgyzstan, the breakup of the USSR raised many issues related to equity and fairness in education, one of which is the distribution of public funds to support scholarship admissions to higher education institutions. After 1992, public institutions could begin to charge tuition fees, but as a legacy of the USSR, Kyrgyzstan continues providing "budget-funded places" (public scholarships) for higher education study. In recent years, the number of these scholarships has been shrinking, resulting in increased competition for budget-funded places, and unfortunately, their distribution has been unfair and discriminatory against students from remote regions and poorer families. To address these issues, the merit-based National Scholarship Test (NST) was introduced in 2002 to identify the most deserving youth, irrespective of where they live and their backgrounds. Moreover, as a crucial part of the test implementation, quota categories have been introduced to ensure the proportional representation of youth from various geographic backgrounds at institutions of higher education. In the years since its introduction the NST has achieved both successes and setbacks. Generally considered a huge step forward, the NST has been able to impact equity in education on a broad scale. However, challenges still remain.
Modular layout-friendly cell library design applied for subthreshold CMOS

A new method for designing digital cell libraries is presented where basic building blocks for logic and memory may be built from identical stacks of transistors in series, only, simplifying the design. Simulations in subthreshold operation is included, suggesting that the method could in principle be used for any synchronous finite state machine. A standard 4 transistor implementation and an 8-transistor version using our suggested approach, having equal total areas, are compared using statistical simulations in 65 nm CMOS, taking local variations into account. The average standard deviations of circuit delays for the traditional NAND implementation were then less than half (44 %), when compared to the new 8 transistor implementation. Anyway, for the same sizing, the traditional NAND2 had about twice the total active area, about 37 % higher static power consumption, 127 % higher active power consumption and about 51 % higher energy per operation, according to simulations. The static power consumption was also about 33 % higher for the traditional NAND, compared to the suggested approach based on combining a couple of 4-transistor "slices". Combining identical "slices" of transistors enabling in principle a range of combinatorial and memory building blocks could greatly simplify library cell design, or subsets of cell libraries.
Open loop V/f control of multiphase induction machine under open-circuit phase faults

One of the main advantages of multiphase induction machines is their higher fault-tolerant capability. Under phase(s) loss, the machine currents can be optimally controlled to satisfy certain optimization criteria. In this paper, a simple open loop controller based on the conventional V/f control scheme of a five-phase induction machine is introduced which can ensure equal phase currents and minimum torque ripples under one phase open. The presented approach can be extended to any number of phases with any number of open phases. The fundamental dq components of the stator voltage are decided as in conventional V/f control. The measured currents are decomposed to their sequence components. The fundamental sequence is used to calculate the optimum reference third sequence current components that ensure equal stator currents under phase(s) open. The third sequence stator voltage components, that ensure equal remaining phase currents, are obtained using Proportional-Resonant (PR) controllers. The input errors of these controllers represent the difference between the actual third sequence current components and its optimum reference values. A prototype five-phase machine is used for experimental verification.
The Aggregation and Neurotoxicity of TDP-43 and Its ALS-Associated 25 kDa Fragment Are Differentially Affected by Molecular Chaperones in Drosophila

Almost all cases of sporadic amyotrophic lateral sclerosis (ALS), and some cases of the familial form, are characterised by the deposition of TDP-43, a member of a family of heteronuclear ribonucleoproteins (hnRNP). Although protein misfolding and deposition is thought to be a causative feature of many of the most prevalent neurodegenerative diseases, a link between TDP-43 aggregation and the dysfunction of motor neurons has yet to be established, despite many correlative neuropathological studies. We have investigated this relationship in the present study by probing the effect of altering TDP-43 aggregation behaviour in vivo by modulating the levels of molecular chaperones in a Drosophila model. More specifically, we quantify the effect of either pharmacological upregulation of the heat shock response or specific genetic upregulation of a small heat shock protein, CG14207, on the neurotoxicity of both TDP-43 and of its disease associated 25 kDa fragment (TDP-25) in a Drosophila model. Inhibition of the aggregation of TDP-43 by either method results in a partial reduction of its neurotoxic effects on both photoreceptor and motor neurons, whereas inhibition of the aggregation of TDP-25 results not only in a complete suppression of its toxicity but also its clearance from the brain in both neuronal subtypes studied. The results demonstrate, therefore, that aggregation plays a crucial role in mediating the neurotoxic effects of both full length and truncated TDP-43, and furthermore reveal that the in vivo propensity of these two proteins to aggregate and their susceptibility to molecular chaperone mediated clearance are quite distinct.