Leishmaniasis is one of the important parasitic diseases, affecting mainly low social class people indeveloping countries, and is more prevalent and endemic in the tropical and subtropical regions of old worldand new world. Despite ofbroad distribution in Iraq,little known about the geneticcharacteristics of thecausative agents. So this study was aimed to evaluate the genetic varietyoftwo IraqiLeishmaniatropicaisolatesbased on heat shock protein gene sequence 70 (HSP70) in comparison with universal isolates recordedsequences data. After amplification and sequencing of HSP70 gene,the obtainedresults were alignment alongwith homologous Leishmania sequences retrieved from NCBI by using BLAST. The analysis results showedpresence of particular g

B3LYP/6-31G, DFT method was applied to hypothetical study the design of six carbon nanotube materials based on [8]circulene, through the use of cyclic polymerization of two and three molecules of [8]circulene. Optimized structures of [8]circulene have saddle-shaped. Design of six carbon nanotubes reactions were done by thermodynamically calculating (Δ S, Δ G and Δ H) and the stability of these hypothetical nanotubes depending on the value of HOMO energy level. Nanotubes obtained have the most efficient gap energy, making them potentially useful for solar cell applications.

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

Photonic Crystal Fiber Interferometers (PCFIs) are greatly used
for sensing applications. This work presents the fabrication and
characterization of a relative humidity sensor based on Mach-
Zehnder Interferometer (MZI), which operates in reflection mode.
The humidity sensor operation based on the adsorption and
desorption of water vapour at the silica-air interface within the PCF.
The fabrication of this sensor is simple, it only includes splicing and
cleaving the PCF with SMF.PCF (LMA-10) with a certain length
spliced to SMF (Corning-28).
The spectrum of PCFI exhibits good sensitivity to humidity
variations. The PCFI response is observed for a range of humidity
values from (27% RH to 85% RH), the positi

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parall

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

Earthquakes occur on faults and create new faults. They also occur on  normal, reverse and strike-slip faults. The aim of this work is to suggest a new unified classification of Shallow depth earthquakes based on the faulting styles, and to characterize each class. The characterization criteria include the maximum magnitude, focal depth, b-constant value, return period and relations between magnitude, focal depth and dip of fault plane. Global Centroid Moment Tensor (GCMT) catalog is the source of the used data. This catalog covers the period from Jan.1976 to Dec. 2017. We selected only the shallow (depth less than 70kms) pure, normal, strike-slip and reverse earthquakes (magnitude ≥ 5) and excluded the oblique earthquakes. Th

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi