Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological Pathotyping of Newcastle Disease Viruses in Sudan 2008–2013

The biological properties and pathogenicity of seven Newcastle disease virus field isolates were studied. These isolates were recovered from different outbreaks in Sudan (5 from chickens and 2 from pigeons) during 2008–2013. Based on intracerebral pathogenicity index, four NDV isolates were characterized as velogenic (their ICPI ranged 2.0–1.6) and three isolates were characterized as mesogenic (ICPI ranged 1.2–1.3). The mean death time for all isolates ranged from 54 to 76.8 hours. The elution time of the viruses from chicken erythrocytes and the ability to haemagglutinate mammalian red blood cells differed considerably in their reactions.
Analysis of the Performance of Coarse-Grain Reconfigurable Architectures with Different Processing Element Configurations

Several coarse-grain reconfigurable architectures have been proposed in recent years that consist of a large number of processing elements connected together in a network. These architectures vary widely from each other – particularly, the processing elements (PEs) in these architectures range from simple functional units to entire RISC cores and micro-controllers. In this paper, we study the effect of different PE architectures on the quality of results (performance) of mapping applications to coarse-grain architectures. We present a scheduling and mapping heuristic that takes the interconnections between PEs and the delays on these interconnections into consideration while mapping applications to the PEs of mesh-like coarse-grain architectures. We perform experiments in which we vary the number of functional units in the PEs, the functionality of these units, the number of PEs in the architecture, and the delays on the interconnect that connects the PEs. Our results for a set of designs derived from DSP applications demonstrate that larger grids do not necessarily translate into better performance. Often, there is not enough instruction-level parallelism (ILP) in the designs to fully utilize the PEs in the fabric. Also, our results show that increasing either the number of functional units in each PE or the interconnections among PEs leads to much better quality of results.
Size distribution dynamics reveal particle-phase chemistry in organic aerosol formation

Organic aerosols are ubiquitous in the atmosphere and play a central role in climate, air quality, and public health. The aerosol size distribution is key in determining its optical properties and cloud condensation nucleus activity. The dominant portion of organic aerosol is formed through gas-phase oxidation of volatile organic compounds, so-called secondary organic aerosols (SOAs). Typical experimental measurements of SOA formation include total SOA mass and atomic oxygen-to-carbon ratio. These measurements, alone, are generally insufficient to reveal the extent to which condensed-phase reactions occur in conjunction with the multigeneration gas-phase photooxidation. Combining laboratory chamber experiments and kinetic gas-particle modeling for the dodecane SOA system, here we show that the presence of particle-phase chemistry is reflected in the evolution of the SOA size distribution as well as its mass concentration. Particle-phase reactions are predicted to occur mainly at the particle surface, and the reaction products contribute more than half of the SOA mass. Chamber photooxidation with a midexperiment aldehyde injection confirms that heterogeneous reaction of aldehydes with organic hydroperoxides forming peroxyhemiacetals can lead to a large increase in SOA mass. Although experiments need to be conducted with other SOA precursor hydrocarbons, current results demonstrate coupling between particle-phase chemistry and size distribution dynamics in the formation of SOAs, thereby opening up an avenue for analysis of the SOA formation process.
Net Cluster: A Net-Reduction-Based Clustering Preprocessing Algorithm for Partitioning and Placement

The complexity and size of digital circuits have grown exponentially, and today's circuits can contain millions of logic elements. Clustering algorithms have become popular due to their ability to reduce circuit sizes, so that the circuit layout can be performed faster and with higher quality. This paper presents a deterministic net-reduction-based clustering algorithm called Net Cluster. The basic idea of the proposed technique is to put the emphasis on reducing the number of nets versus the number of cells, thereby capturing the natural clusters of a circuit. The proposed algorithm has proven a linear-time complexity of O(p), where p is the number of pins in a circuit. To demonstrate the effectiveness of the proposed clustering technique, it has been applied to multilevel partitioning and wire length-driven placement. The numerical experiments on the ISPD98 benchmark suite for partitioning and the ICCAD 2004 benchmark suite for placement demonstrate that by applying Net Cluster as a preprocessing step, the performance of state-of-the-art multilevel partitioners and placers can be further improved
Multi-machine power system stabilizer design using improved particle swarm optimization (PSO) with time- varying acceleration coefficients

An efficient and most famous tool to enhance damping of the power system low frequency oscillations is the conventional widely used lead-lag Power System Stabilizer (PSS). To achieve the desired level of robust performance under transient situation, selecting a suitable design method for optimal tuning of PSS parameters is very important in multi-machine power system. Because, it is a multimodal and difficult combinatorial optimization problem, this paper presents a novel parameter automation strategy for Particle Swarm Optimization (PSO) called PSO with Time-Varying Acceleration Coefficients (PSO-TVAC). This optimization method has a strong ability to successfully control both global and local search in each iteration process for considerably increasing the probability of finding the global optimum solution. The PSO-TVAC algorithm is applied to optimal tuning PSS parameters problem in order to reduce the PSS design effort and find the best possible solution within a reasonable computation time. For this reason, the robustly selection of PSSs parameters is converted as an optimization problem based on the time domain-based objective function under different operating conditions. The robustness of the proposed method is demonstrated on a multi-machine power system in comparison with the classical PSO and conventional method based designed PSSs. It is shown through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The analysis of the results shows that the improved PSO-TVAC is not only very effective but also provides an excellent ability for damping low frequency oscillations and greatly enhance the dynamic stability of the power system. Moreover, the proposed PSO-TVAC algorithm is superior than that of the classical PSO one in terms of accuracy, convergence and computational effort. Key words: Power system stabilizer (PSS) design, particle swarm optimization, power system dynamics, time-varying acceleration coefficients.
Robust Replication of Volatility Derivatives

We show that the information in European option prices reveals, robustly and nonparametrically, the no-arbitrage prices of general volatility derivatives – contracts on the realized variance of an underlying price process. Our explicit formulas are exact and valid across all dynamics satisfying an independence assumption on the instantaneous volatility. Our methods are moreover immunized, to first order, against the presence of correlation. We solve for not just valuation but also replication, via robust trading strategies which perfectly hedge volatility derivatives. Additionally, these results have relevance to the forecasting of realized volatility and the inference of volatility risk premia. ∗Bloomberg LP and Courant Institute, NYU. 731 Lexington Avenue, New York, NY 10022. pcarr@nyc.rr. com. †University of Chicago. 5734 S University Ave, Chicago IL 60637. rogerlee@uchicago.edu.
Molecular basis of bacterial resistance to organomercurial and inorganic mercuric salts

Bacteria mediate resistance to organomercurial and inorganic mercuric salts by metabolic conversion to nontoxic elemental mercury, Hg(0). The genes responsible for mercury resistance are organized in the mer operon, and such operons are often found in plasmids that also bear drug resistance determinants. We have subcloned three of these mer genes, merR, merB, and merA, and have studied their protein products via protein overproduction and purification, and structural and functional characterization. MerR is a metallo‐regulatory DNA‐binding protein that acts as a repressor both its own and structural gene transcription in the absence of Hg(II); in addition it acts as a positive effector of structural gene transcription when Hg(II) is present. MerB, organomercury lyase, catalyzes the protonolytic fragmentation of organomercurials to the parent hydrocarbon and Hg(II) by an apparent SE2 mechanism. MerA, mercuric ion reductase, is an FAD‐containing and redox‐active disulfide‐containing enzyme with homology to glutathione reductase. It has evolved the unique catalytic capacity to reduce Hg(II) to Hg(0) and thereby complete the detoxification scheme. —Walsh, C. T. ; Distefano, M. D. ; Moore, M. J.; Shewchuk, L. M. ; Verdine, G. L. Molecular basis of bacterial resistance to organomercurial and inorganic mercuric salts. FASEB J. 2: 124‐130; 1988.
Alias extraction by giving entity name using lexical pattern based approach

Many celebrities and experts from various fields may have been referred by not only their personal names but also by their aliases. If the person is referred by using their alias then it would be difficult to find the complete information about the same. So it is important to know the aliases to make the search more reliable. Extracting aliases are important in many task such as information extraction, name disambiguation etc. The main purpose of the project is to show the aliases of a given personal name. If the user is new he has to create his profile first. Once created he can successfully search for the aliases by giving two types of input like by giving personal name as an input or by giving one of the alias amongst existing. Admin has the charge of uploading aliases information and he can upload the additional information too if needed. There is possibility that it may extract more aliases so it is important to know which most appropriate aliases are for that ranking function is used. The proposed method gives higher MRR(Mean Reciprocal Rank).
A NEW TECHNIQUE INVOLVING DATA MINING IN PROTEIN SEQUENCE CLASSIFICATION

Feature selection is more accurate technique in protein sequence classification. Researchers apply some well-known classification techniques like neural networks, Genetic algorithm, Fuzzy ARTMAP, Rough Set Classifier etc for extracting features.This paper presents a review is with three different classification models such as fuzzy ARTMAP model, neural network model and Rough set classifier model.This is followed by a new technique for classifying protein sequences.The proposed model is typically implemented with an own designed tool using JAVA and tries to prove that it reduce the computational overheads encountered by earlier approaches and also increase the accuracy of classification.
3D point pattern matching based on spatial geometric flexibility

We propose a new method for matching two 3D point sets of identical cardinality with global similarity but local non-rigid deformations and distribution errors. This problem arises from marker based optical motion capture (Mocap) systems for facial Mocap data. To establish one-to-one identifications, we introduce a forward 3D point pattern matching (PPM) method based on spatial geometric flexibility, which considers a non-rigid deformation between the two point-sets. First, a model normalization algorithm based on simple rules is presented to normalize the two point-sets into a fixed space. Second, a facial topological structure model is constructed, which is used to preserve spatial information for each FP. Finally, we introduce a Local Deformation Matrix (LDM) to rectify local searching vector to meet the local deformation. Experimental results confirm that this method is applicable for robust 3D point pattern matching of sparse point sets with underlying non-rigid deformation and similar distribution.
A novel cache mapping scheme for dynamic set-based cache partitioning

In this research, we designed a novel cache mapping scheme for dynamic set-based cache partitioning. The cache mapping scheme facilitates allocation of any non-power-of-2 number of physical cache segments as a private cache to each process. An efficient near-optimal cache partitioning algorithm was designed for capturing working sets of running processes. Transparent cache reconfiguration was designed to enable immediately continuing process execution after cache repartitioning is computed. Experimental results validate its effectiveness in improving the overall hit ratio, the total number of memory accesses, and overall program performance with small number of communications.
Examining the Educational User Interface, Technology and Pedagogy for Arabic Speaking Children in Kuwait

The emergence of educational technology has resulted in a widespread popularity of different forms of education technologies among various multidisciplinary researchers. This is evident based on the high number of empirical, theoretical, and conceptual studies that are published on educational technology-related research. However, many open research questions and challenges remain unresolved. In this study, we are going to: 1) present an educational technology research agenda underpinned by extensive research and studies; 2) highlight the missing interconnections between empirical findings of published studies and the pedagogical theories; 3) discover if educational technology research is overly dominated by studies conducted in developed countries, while developing countries, for example, Arabic speaking populations in the Middle-East in general and the Gulf states, in particular, are overlooked by researchers. Based on our in-depth review of the existing literature, we will discuss the challenges of designing educational user interface, technology, and pedagogy-related research, and finally propose guidelines and recommendations for future research to overcome some of the existing challenges.
WAVELET REGULARIZATION OF A FOURIER-GALERKIN METHOD FOR SOLVING THE 2D INCOMPRESSIBLE EULER EQUATIONS

We employ a Fourier-Galerkin method to solve the 2D incompressible Euler equations, and study several ways to regularize the solution by wavelet filtering at each timestep. Real-valued orthogonal wavelets and complex-valued wavelets are considered, combined with either linear or nonlinear filtering. The results are compared with those obtained via classical viscous and hyperviscous regularization methods. Wavelet regularization using complex-valued wavelets performs as well in terms of L 2 convergence rate to the reference solution. The compression rate for homogeneous 2D turbulence is around 3 for this method, suggesting that memory and CPU time could be reduced in an adaptive wavelet computation. Our results also suggest L 2 convergence to the reference solution without any regularization, in contrast to what is obtained for the 1D Burgers equation.
Web service similarity with standardized descriptions

Nowadays, a web service is one of technologies that is reliable and promising in business practices. This is evidenced by the services created by the providers to support them. Web service similarity is very important to get a replacement Web service, when the web service used is disable. Web service similarity based on annotations and descriptions in this decade are being carried out. Unfortunately, annotations and descriptions given are not standard, so that the Web service similarity does not get the right web service. Furthermore, we propose standardized descriptions obtained directly from the source program of Web service that is generalized into a form WSDL file. This is very important to get a Web service that we are really looking for.
UAS Cloud Surveillance System

On UAV missions, flight information should be prompt for use to all participating team members. Supporting from 3G mobile communications, UAV flight data can be uplink onto Internet and share with all users at different locations. Using an Android smart phone for data acquisition on airborne and cope with Google Earth® 3D map, the proposed UAS surveillance system is constructed on the cloud. The ground computer offers My SQL database management for all downlink data and converts into user friendly format for easy access. With special attitude and altitude display modes to match with UAV dynamic performance, it offers very good flight awareness to operator and observers throughout mission. This paper presents a technical realization on the UAS cloud surveillance system for Ce-71 UAV operations with excellent sense in surveillance.
ASCA and ROSAT observations of the QSF3 field: the X-ray background in the 0.1–7 keV band

The X-ray background (XRB) from 0.1 to 7 keV has been studied using high spectral and spatial resolution data from the ASCA SIS and ROSAT PSPC. Analysing both the diffuse background radiation and resolved sources, we have carried out a series of joint spectral fits of the ASCA and ROSAT data. The spectrum of the XRB can be fit well by a single power-law from 1 to 7 keV; overall, the photon index of the power-law model ranges from 1.4 to 1.5, and no obvious excess is found between 1 and 3 keV. Below 1 keV, the models become more complicated and involve a mixture of extragalactic and Galactic sources. As some of the extragalactic contributions should be from point sources, we have examined the ASCA and ROSAT spectra of resolved sources individually: a stellar source having a well-fit thermal spectrum and two AGNs having a much steeper power-law spectrum (with photon index of about 3); the accumulated spectrum of other non-stellar sources resolved by ROSAT also has a steeper-than-average spectrum. Fitting the XRB spectrum observed by ASCA and the accumulated point source spectrum by ROSAT together by varying the contribution from steep spectrum sources, such as quasars, to the background, we find that they contribute less than 30 per cent in the 0.5--2 keV band and drop to below 10 per cent over 2--10 keV. This fraction is provided by sources brighter than a few times $10^{-15}$ \ergpercmpers (in the 0.5--2 keV band). Constrained by our spectral fitting results, the major contributor of the XRB must be a single population with similar flat spectra.
Automatic liver MR image segmentation with self-organizing map and hierarchical agglomerative clustering method

Medical image segmentation plays an important role in medical visualization and diagnosis. We study in this paper an automatic segmentation method for liver magnetic resonance (MR) images based on the self-organizing map (SOM) and hierarchical agglomerative clustering method. At first, the local features of the MR image pixels are extracted to feed the SOM after a pre-processing step. The output prototypes are then filtered with the hits map and a hierarchical agglomerative clustering method is applied to the prototypes to select the best segmentation according to a quantitative image evaluation index. The segmentation results after the post-processing show the proposed method to be effective and promising. Further research work is also recommended.
Declaring independence via the sketching of sketches

We consider the problem of identifying correlations in data streams. Surprisingly, our work seems to be the first to consider this natural problem. In the centralized model, we consider a stream of pairs (i,j) ∈ [n]2 whose frequencies define a joint distribution (X,Y). In the distributed model, each coordinate of the pair may appear separately in the stream. We present a range of algorithms for approximating to what extent X and Y are independent, i.e., how close the joint distribution is to the product of the marginals. We consider various measures of closeness including ℓ1, ℓ2, and the mutual information between X and Y. Our algorithms are based on "sketching sketches", i.e., composing small-space linear synopses of the distributions. Perhaps ironically, the biggest technical challenges that arise relate to ensuring that different components of our estimates are sufficiently independent.
Sticking out of the crowd: the molecular identity and development of cholecystokinin‐containing basket cells

Abstract Certain essential cognitive processes require the precise temporal interplay between glutamatergic (excitatory) pyramidal cells and γ‐aminobutyric acid (GABA)‐releasing inhibitory interneurons in the hippocampus. Basket cells, the main class of interneurons, target pyramidal cell somata and proximal dendrites and thus are poised to modify network oscillations. Though only present in limited numbers, the impaired development of basket cells can result in changes in the hippocampal circuitry leading to neurological disorders, such as schizophrenia. The diversity of the spatial origins, neurochemical make‐up, cytoarchitecture and network contributions amongst basket cells is a provocative example of interneuron heterogeneity in the hippocampus. This review discusses recent data concerned with the developmental trajectories of one subclass, the cholecystokinin‐containing basket cell, and emphasizes the significance of the short‐range intercellular guidance cues that have recently emerged to impact the formation and function of their inhibitory synapses.