Blastocystis is a ubiquitous human and animal protozoa that inhabit the gastrointestinal tract. Metronidazole is considered the standard drug for the treatment of Blastocystis infection; however, there is growing evidence of treatment failure, hazardous side effects, and appearance of strains resistant to metronidazole. In the last era, many studies have been implicated in the quest for new treatments for Blastocystis infection, especially natural products. Attention has been focused on the effect of Amygdalin (B17) and pumpkin seed on eradicating parasitic infections. The current work was built up to explore the in vitro efficacy of two natural compounds, Amygdalin (B17) and pumpkin seeds against Blastocystis isolated from symptomatic patients. In vitro incubation of the parasite with B17 (200, 400µgmL¯¹), pumpkin seed (200, 400 µgmL¯¹) and metronidazole (100, 150µgmL¯¹) was counted at different periods (one, two, twenty-four and forty-eight hours) and morphological changes were evaluated using Light Microscope. Blastocystis detected from patients with symptoms was subtype 1. The B 17 and pumpkin seed demonstrated statistically significant (p<0.05) growth reduction of Blastocystis in culture. Such results showed the possible therapeutic effects of B 17 and pumpkin seed against blastocystosis as effective safe natural alternatives.
In this paper the definition of fuzzy normed space is recalled and its basic properties. Then the definition of fuzzy compact operator from fuzzy normed space into another fuzzy normed space is introduced after that the proof of an operator is fuzzy compact if and only if the image of any fuzzy bounded sequence contains a convergent subsequence is given. At this point the basic properties of the vector space FC(V,U)of all fuzzy compact linear operators are investigated such as when U is complete and the sequence ( ) of fuzzy compact operators converges to an operator T then T must be fuzzy compact. Furthermore we see that when T is a fuzzy compact operator and S is a fuzzy bounded operator then the composition TS and ST are fuzzy compact
... Show MoreSolar collectors, in general, are utilized to convert the solar energy into heat energy, where it is employed to generate electricity. The non-concentrating solar collector with a circular shape was adopted in the present study. Ambient air is heated under a translucent roof where buoyant air is drawn from outside periphery towards the collector center (tower base). The present study is aimed to predict and visualize the thermal-hydrodynamic behavior for airflow under inclined roof of the solar air collector, SAC. Three-dimensional of the SAC model using the re-normalization group, RNG, k−ε turbulence viscus model is simulated. The simulation was carried out by using ANSYS-FLUENT 14.5. The simulation
... Show MoreThis work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
... Show MoreIn this work, we study several features of the non-zero divisor graphs (ℵZD- graph) for the ring Zn of integer modulo n. For instance, the clique number, radius, girth, domination number, and the local clustering coefficient are determined. Furthermore, we present an algorithm that calculates the clique number and draws the non-zero divisor for the ring Zn.
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
... Show MoreHigh-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,
... Show MoreAbstract We have been studied and analysis the electronic current at the interfaces of Au/PTCDA system according to simple quantum mode for the electronics transition rate due to postulate quantum theory. Calculation of electronic current were performed at interface of Au/PTCDA as well as for investigation the feature of electronic density at this devices. The transition of electronic current study under assume the electronic state of Au and PTCDA were continuum and the states of electrons must be closed to energy level for Au at Fermi state, and the potential at interface feature depended on structure of Au and PTCDA material. The electronic transition current feature was dependent on the driving force energy that results of absorption ene
... Show MoreOne of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
... Show More