Miracle-dz/UniFAR-FTUs huggingface dataset:
Electromagnetic Interference Generated from Fast Switching Power Electronic Devices

This paper investigates the negative effects of electromagnetic interference (EMI) due to fast switching power devices (high dv/dt and di/dt) used in power electronic converters and industrial equipment. Mitigation techniques have been explored to reduce EMI noise effectively. Remedial measures to reduce the risk of equipment malfunction and health risk due to EMI have been explored. In this paper, EMI generation and propagation mechanism, high rates of change of voltage and current in fast switching power devices (such as IGBT), modelling and identifying EMI noise sources and coupling paths have been discussed. A practical EMI measurement system has been suggested to extract more information from EMI noise through analysis in frequency-domain and time-domain, and to test equipment emitting EMI to comply with electromagnetic compatibility (EMC) standards. Different filter topologies have been investigated for minimizing EMI noise and effect of high dv/dt and di/dt due to high frequency switching. dv/ All power electronics equipments generate and emit unwanted electrical signals (EMI noise) that can lead to performance degradation of other electrical/electronic equipments. They generate high- frequency conducted and radiated EMI noise and draw distorted line currents due to the sharp edges of the switching waveforms with high dv/dt. The undesirable EMI effects are interference with wireless systems (e.g., radio, TV, mobile, data transmission), malfunction of biomedical equipments (e.g., cardiac pace maker), misbehaviour of security doors of banks, ABS brake systems of cars, and electronic control systems in airplanes and the increase in power system losses associated with improper performance or failure of a range of industrial power equipments. It is necessary to find a mitigation technique to overcome this problem and to avoid costly equipment failures in industry. To
Mediterranean Journal of Hematology and Infectious Diseases Mendelian Susceptibility to Mycobacterial Purpose: Screen Patients with Possible Presentations for Msmd. Methods: Patients with Disseminated Bcg Infection following Vaccination, Infections or Recurrent Tuberculosis Inf Clinic at Cairo Unive

Background: Tuberculosis remains a major health problem in developing countries especially with the emergence of multidrug resistant strains. Mendelian Susceptibility (MSMD) is a rare disorder with impaired immunity against mycobacterial pathogens. Reported MSMD etiologies highlight the crucial role of the Interferon gamma /Interleukin 12 (IFN axis and the phagocyte respiratory burst axis. have declared that no competing interests exist. an Open Access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, Calmette Guerin vaccination policy in Egypt, especially given the high consanguinity rate. Introduction. Tuberculosis (TB) still constitutes a leading cause of mortality and morbidity especially in developing countries. Patients with Mendelian Susceptibility to Mycobacterial Disease (MSMD) present clinical disease caused by weakly pathogenic mycobacteria such as Bacillus Calmette-Guérin (BCG) vaccines and/or nontuberculous environmental mycobacteria in otherwise healthy individuals. 1 These patients are also vulnerable to Mycobacterium tuberculosis. 2,3 MSMD is generally attributed to defects in the Interleukin 12-Interferon gamma (IL-12/IFN-) pathways. IFN- immunity is important for control of intracellular organisms like Mycobacterium tuberculosis, atypical mycobacteria, BCG, and Salmonella. Upon ingestion of these intracellular organisms, the macrophage secretes IL-12, which binds to its receptor (IL12RB1 and IL12RB2) present at the surface of T and NK cells, leading ultimately to IFN-γ secretion by these cells. IFN-γ then binds its receptor (composed of IFNGR1 and IFNGR2) on the macrophage and activates genes including IL-12 and the respiratory burst NADPH oxidase which will allow the macrophage to kill the ingested bacteria. 4 IFNGR1 and IFNGR2, STAT1, IL12B and IL12RB1 are all identified players that are involved in interleukin 12/23-dependent IFN- mediated immunity. Human mutations in IFNGR1, IFNGR2 and STAT1 impair the cellular response to IFN-, whereas mutations in IL12B and IL12RB1 impair the IL-12/23-dependent production of IFN-.
PDP: protein domain parser

UNLABELLED We have developed a program for automatic identification of domains in protein three-dimensional structures. Performance of the program was assessed by three different benchmarks: (i) by comparison with the expert-curated SCOP database of structural domains; (ii) by comparison with a collection of manual domain assignments; and (iii) by comparison with a set of 55 proteins, frequently used as a benchmark for automatic domain assignment. In all these benchmarks PDP identified domains correctly in more than 80% of proteins. AVAILABILITY http://123d.ncifcrf. gov/.
Towards scalable and simple software-DSM systems

Large-scale PC clusters, such as ACSI Lightning with 2,816 processors and the AIST supercluster with more than 3,000 processors, have been constructed. Although software distributed shared memory (S-DSM) provides an attractive parallel programming model, almost all S-DSM systems proposed are only useful on a cluster of less than or equal to 16 nodes. They lack scalability.
Nucleosynthesis in multi-dimensional SN Ia explosions

We present the results of nucleosynthesis calculations based on multi-dimensional (2D and 3D) hydrodynamical simulations of the thermonuclear burning phase in type Ia supernovae (hereafter SN Ia). The detailed nucleosynthetic yields of our explosion models are calculated by post-processing the ejecta, using passively advected tracer particles. The nuclear reaction network employed in computing the explosive nucleosynthesis contains 383 nuclear species, ranging from neutrons, protons, and α -particles to 98 Mo. Our models follow the common assumption that SN Ia are the explosions of white dwarfs that have approached the Chandrasekhar mass ($M_{\rm ch}\sim 1.39$), and are disrupted by thermonuclear fusion of carbon and oxygen. But in contrast to 1D models which adjust the burning speed to reproduce lightcurves and spectra, the thermonuclear burning model applied in this paper does not contain adjustable parameters. Therefore variations of the explosion energies and nucleosynthesis yields are dependent on changes of the initial conditions only. Here we discuss the nucleosynthetic yields obtained in 2D and 3D models with two different choices of ignition conditions ( centrally ignited , in which the spherical initial flame geometry is perturbated with toroidal rings, and bubbles , in which multi-point ignition conditions are simulated), but keeping the initial composition of the white dwarf unchanged. Constraints imposed on the hydrodynamical models from nucleosynthesis as well as from the radial velocity distribution of the elements are discussed in detail. We show that in our simulations unburned C and O varies typically from ~40% to ~50% of the total ejected material. Some of the unburned material remains between the flame plumes and is concentrated in low velocity regions at the end of the simulations. This effect is more pronounced in 2D than in 3D and in models with a small number of (large) ignition spots. The main differences between all our models and standard 1D computations are, besides the higher mass fraction of unburned C and O, the C/O ratio (in our case is typically a factor of 2.5 higher than in 1D computations), and somewhat lower abundances of certain intermediate mass nuclei such as S, Cl, Ar, K, and Ca, and of 56 Ni. We also demonstrate that the amount of 56 Ni produced in the explosion is a very sensitive function of density and temperature. Because explosive C and O burning may produce the iron-group elements and their isotopes in rather different proportions one can get different 56 Ni-fractions (and thus supernova luminosities) without changing the kinetic energy of the explosion. Finally, we show that we need the high resolution multi-point ignition (bubbles) model to burn most of the material in the center (demonstrating that high resolution coupled with a large number of ignition spots is crucial to get rid of unburned material in a pure deflagration SN Ia model).
Seeing is believing: The importance of visualization in real-world machine learning applications

The increasing availability of data sets with a huge amount of information, coded in many dierent features, justies the research on new methods of knowledge extraction: the great challenge is the translation of the raw data into useful information that can be used to improve decision- making processes, detect relevant proles, nd out relationships among features, etc. It is undoubtedly true that a picture is worth a thousand words, what makes visualization methods be likely the most appealing and one of the most relevant kinds of knowledge extration methods. At ESANN 2011, the special session \Seeing is believing: The importance of visualization in real-world machine learning applications" reects some of the main emerging topics in the eld. This tutorial prefaces the session, summarizing some of its contributions, while also providing some clues to the current state and the near future of visualization methods within the framework of Machine Learning.
Increasing Prevalence of Aminoglycoside-Resistant Enterococcus faecalis Isolates Due to the aac(6’)-aph(2”) Gene: A Therapeutic Problem in Kermanshah, Iran

Background: Enterococci are important pathogens in nosocomial infections. Various types of antibiotics, such as aminoglycosides, are used for treatment of these infections. Enterococci can acquire resistant traits, which can lead to therapeutic problems with aminoglycosides. Objectives: This study was designed to identify the prevalence of, and to compare, the aac(6’)-aph(2”) and aph(3)-IIIa genes and their antimicrobial resistance patterns among Enterococcus faecalis and E. faecium isolates from patients at Imam Reza hospital in Kermanshah in 2011 - 2012. Patients and Methods: One hundred thirty-eight clinical specimens collected from different wards of Imam Reza hospital were identified to the species level by biochemical tests. Antimicrobial susceptibility tests against kanamycin, teicoplanin, streptomycin, imipenem, ciprofloxacin, and ampicillin were performed by the disk diffusion method. The minimum inhibitory concentrations of gentamicin, streptomycin, kanamycin, and amikacin were evaluated with the microbroth dilution method. The aminoglycoside resistance genes aac(6’)-aph(2”) and aph(3”)-IIIa were analyzed with multiplex PCR. Results: The prevalence of isolates was 33 (24.1%) for E. faecium and 63 (46%) for E. faecalis. Eighty-nine percent of the isolates were high-level gentamicin resistant (HLGR), and 32.8% of E. faecium isolates and 67.2% of E. faecalis isolates carried aac(6’)-aph(2”). The prevalence of aph(3”)-IIIa among the E. faecalis and E. faecium isolates was 22.7% and 77.3%, respectively. Conclusions: Remarkably increased incidence of aac(6’)-aph(2”) among HLGR isolates explains the relationship between this gene and the high level of resistance to aminoglycosides. As the resistant gene among enterococci can be transferred, the use of new-generation antibiotics is necessary.
Convergence Analysis of a Multiscale Finite Element Method for Singularly Perturbed Problems

In this paper we perform an error analysis for a multiscale finite element method for singularly perturbed reaction-diffusion equations. Such a method is based on enriching the usual piecewise linear finite element trial spaces with local solutions of the original problem, but the approach does not require these functions to vanish on each element edge. Piecewise linear plus bubbles are the choice for the test functions allowing static condensation; thus our method is of Petrov--Galerkin type. We perform convergence analysis in different asymptotic regimes, and we show convergence in an appropriate norm with respect to the small parameter. Numerical results show that the new method is able to compute solutions even on coarse meshes.
CrystalBall : A Framework for Mining Variants of Association Rules

The mining of informative rules calls for methods that include different attributes (e.g., weights, quantities, multiple-concepts) suitable for the context of the problem to be analyzed. Previous studies have focused on algorithms that considered individual attributes but ignored the information gain in each rule when the interaction of two or more attributes are taken into account. Motivated by the above, we developed a framework called CRYSTALBALL that supports declarative mining of different rules (i.e., variants) involving several attributes. It eliminates the time and cost of engineering algorithms as practiced in previous studies, and introduces a foundation for cross-variant enhancements. The framework consists of a generic rule mining engine (VI), and a variant description language (VDL) for defining attribute-specific behavior. Besides demonstrating the flexibility of the framework, we also discuss the experimental studies, the limitations of the framework, as well as future work in the paper.
Knowledge Management from the ontological Standpoint

What is an adequate philosophy for knowledge management for an ontologist working in information science? I will contend that the relevant part of knowledge management, namely the theory of knowledge representation, lacks proper foundations. In particular, I will criticize the traditional philosophical approach to knowledge representation, which I call pragmatist conceptualism. I argue on the one hand that its emphasis on pragmatism falls short of providing a reflective and principled methodology, and that on the other hand conceptualism is doomed by its neglect of reality. This paper outlines and defends a clear standpoint of philosophical realism together with a commensurate methodology for the task of the knowledge engineer.
An Efficient Network Anomaly Detection Scheme Based on TCM-KNN Algorithm and Data Reduction Mechanism

Network anomaly detection plays a vital role in securing network security and infrastructures. Current research focuses concentrate on how to effective reduce high false alarm rate and usually ignore the fact that the poor quality data for the modeling of normal patterns as well as the high computational cost make the current anomaly detection methods not act as well as we expect. Based on these, we first propose a novel data mining scheme for network anomaly detection in this paper. Moreover, we adopt data reduction mechanisms (including genetic algorithm (GA) based instance selection and filter based feature selection methods) to boost the detection performance, meanwhile reduce the computational cost of TCM-KNN. Experimental results on the well-known KDD Cup 1999 dataset demonstrate the proposed method can effectively detect anomalies with high detection rates, low false positives as well as with high confidence than the state-of-the-art anomaly detection methods. Furthermore, the data reduction mechanisms would greatly improve the performance of TCM-KNN and make it be a good candidate for anomaly detection in practice.
Cooperative communication system with systematic Raptor codes

Implementing rateless codes in cooperative scheme has attracted a lot of interest recently. It is an efficient and flexible solution for many practical communication areas, such as Digital Video Broadcasting (DVB). In this paper, we propose a relay scheme using systematic Raptor code which is standardized in 3GPP. The advantage of systematic over non-systematic Raptor code is that when there is no packet lost in the transmission, there is no need for decoding. To improve the performance, Reed-Solomon (RS) code is concatenated as an inner code. Every two Raptor symbols to which a 32-bit cyclic redundancy check (CRC) are appended will be encoded into one RS codeword. Additionally, we develop ways of optimizing the system with channel state information (CSI) at the transmitter, including adaptive RS coding rates and adaptive cooperation of relay. It is shown from the simulation results that besides the inherent advantage of systematic coding, this scheme has a noticeable efficiency gain over the system without relay.
Understanding People's Mental Models of Mid-Air Interaction for Virtual Assembly and Shape Modeling

Naturalness of the mid-air interaction interface for virtual assembly and shape modeling is important. In order to design an interface perceived as "natural" by most people, common behaviors and mental patterns for mid-air interaction of people have to be recognized, which is an area merely explored yet. This paper serves this purpose of understanding the users' mental interaction models, in order to provide standards and recommendation for devising a natural virtual interaction interface. We tested three kinds of tasks --- manipulating tasks, deforming tasks and tool-based operating tasks on 16 participants. We have found that: 1) different features of mental models were observed for different types of tasks. Interaction techniques should be designed to match these features; 2) virtual hand self-avatar helps estimate size of virtual objects, as well as helps plan and visualize the complex process and procedures of a task, which is especially helpful for tool-based tasks; 3) bimanual interaction is witnessed as a dominant interaction mode preferred by the majority; 4) natural gestures for deforming tasks always reflect forces exerted. These suggestions are useful for designing a midair interaction interface matching users' mental models.
Effects of Traditional Flood Irrigation on Invertebrates in Lowland Meadows

Lowland meadow irrigation used to be widespread in Central Europe, but has largely been abandoned during the 20th century. As a result of agri-environment schemes and nature conservation efforts, meadow irrigation is now being re-established in some European regions. In the absence of natural flood events, irrigation is expected to favour fauna typical of lowland wet meadows. We analysed the effects of traditional flood irrigation on diversity, densities and species composition of three invertebrate indicator taxa in lowland meadows in Germany. Unexpectedly, alpha diversity (species richness and Simpson diversity) and beta diversity (multivariate homogeneity of group dispersions) of orthopterans, carabids, and spiders were not significantly different between irrigated and non-irrigated meadows. However, spider densities were significantly higher in irrigated meadows. Furthermore, irrigation and elevated humidity affected species composition and shifted assemblages towards moisture-dependent species. The number of species of conservation concern, however, did not differ between irrigated and non-irrigated meadows. More variable and intensive (higher duration and/or frequency) flooding regimes might provide stronger conservation benefits, additional species and enhance habitat heterogeneity on a landscape scale.
Phenotypic and Evolutionary Plasticity of Organ Masses in Response to Voluntary Exercise in House Mice1

Abstract We used a novel mouse model to study the effects of selective breeding for high locomotor activity (14 generations) on relative organ sizes, hematocrit (Hct), and blood hemoglobin (Hb) concentration. We also examined effects of exercise training and genotype-by-environment interactions by housing animals for 8 weeks with wheels that were either free to rotate or locked. Mice from the four replicate High-Runner (HR) lines were smaller in total body mass but had larger body mass-adjusted kidneys relative to the four Control lines (P < 0.05). Control and HR lines did not differ significantly for mass-adjusted tail length or masses of the “triceps surae” hindlimb muscle group, heart (ventricle), spleen, liver, adrenal glands or gonads. Wheel access caused a reduction in body mass and an increase in relative heart mass. In females only, wheel access caused a reduction in relative spleen mass. Wheel access did not affect relative tail length or relative mass of the triceps surae, liver, adrenal gland or gonads. Significant interactions between selection history and wheel access were observed in females for spleen, liver, and gonad mass as well as Hct and Hb. Wheel access caused increases in both Hct and Hb, mainly in the HR lines. The mini-muscle phenotype, caused by a Mendelian recessive allele that halves hindlimb muscle mass, was significantly associated with several other body composition traits, including reduced body mass, increased tail length, increased heart mass, increased liver mass (females only), increased mean adrenal gland mass (females only), increased mean kidney mass (males only), and reduced Hct (wheel-access females only). Results are discussed in context of the beneficial acclimation hypothesis, genotype-by-environment interactions, and the potential for “nurture” to be self-reinforcing of “nature” in some complex behavioral-physiological phenotypes.
International Conference on Intelligent and Advanced Systems 2007 Visual-based Fuzzy Navigation System for Mobile Robot: Wall and Corridor Follower

– This paper presents the development of a visual–based fuzzy navigation system that enables a mobile robot in moving through a corridor or following a wall. The system employs a camera to detect the existence of walls on the left, the right, and the front of the robot. A mamdani-type fuzzy logic controller uses the information gathered by the camera to determine the turning angle and the speed of the robot. The fuzzy system is tested using an OpenGL-based 3D simulator that capable in animating the movement of the robot as well as generating the images captured by the camera. The results of the test confirm that the controller shows a good performance in navigating the robot.
Natural dynamics modification for energy efficiency: A data-driven parallel compliance design method

We present a data-driven method for designing parallel compliance. Designing such compliance helps the system to improve energy efficiency, mainly by reducing negative work. The core idea is to design a controller first and then find springs working in parallel with each actuator such that force-displacement graph is lined up around displacement axis. By doing so, we simply shape the natural dynamics for performing the task efficiently. Maximum torque reduction for actuators is a byproduct of this design method. The method can be used in different cyclic robotic application, especially in legged locomotion systems. In this paper, we design a spinal compliance for a bounding quadruped robot in Webots. The results show that the power consumption and the maximum torque are reduced significantly.
Combining Support Vector Machines by Means of Fuzzy Aggregation

The paper deals with a recently proposed approach to combining classifiers by means of fuzzy ag- gregation. The approach relies on the quasi-Sugeno integral and on the t-conorm integral as a generalization of the Choquet and Sugeno integral, which have been used for combining classifiers so far. New theoretical devel- opment is presented, in particular a proposition concerning the measures used in the quasi-Sugeno integral, and the approach is elaborated specifically for support vector machines. Finally, experience is reported that was gained when using the approach to combine support vector machines in a neurophysiologic application.