Cold atmospheric plasma (CAP) is used widely in medical and biological fields because of non-thermal effected. Direct application of plasma is preferred in medical functions, so, direct application of cold plasma has obtained by the floating electrode dielectric barrier discharge (FE-DBD) system. The purpose of this paper to review the effect of (CAP) on the reproductive hormones (testosterone, LH, E2, progesterone, for male rats. The study appeared that no significant effect on E2 and progesterone hormone for all time of exposure, besides this significant difference in LH hormone (P<0.05) at 15 sec, (P<0.0001) at 30, 90 sec and (P<0.001) at 60 sec of exposure to plasma. Added to that significant difference (P<0.01) at 15, 30, 60 sec and no

Asthma is a chronic respiratory disease highly prevalent worldwide. Recent studies have suggested a role for microbiome-associated gut–lung axis in asthma development. In the current study, we investigated if Resveratrol (RES), a plant-based polyphenol, can attenuate ovalbumin (OVA)-induced murine allergic asthma, and if so, the role of microbiome in the gut–lung axis in this process. We found that RES attenuated allergic asthma with significant improvements in pulmonary functions in OVA-exposed mice when tested using plethysmography for frequency (F), mean volume (MV), specific airway resistance (sRaw), and delay time(dT). RES treatment also suppressed inflammatory cytokines in the lungs. RES modulated lung microbiota and cause

A batch adsorption system was applied to study the adsorption of methylene blue from aqueous solution by Iraqi bentonite and treated bentonite with different amount of zinc oxide (ZnO). The adsorption capacities of methylene blue onto bentonite were evaluated. The equilibrium between liquid and solid phase was described by Langmuir model better than the Freundlich model. Langmuir and Freundlich constants have been determined. The separation factor or equilibrium parameter, RL which is used to predict if an adsorption system is favourable or unfavourable was calculated for all cases.

Development of improved methods for the synthesis of metal oxide nanoparticles are of high priority for the advancement of material science and technology. Herein, the biosynthesis of ZnO using hydrahelix of beta vulgaris and the seed of abrus precatorius as an aqueaus extracts adduced respectivily as stablizer and reductant reagent. The support are characterized by spectroscopic methods ( Ft-IR, Uv-vis ).The FTIR confirmed the presence of ZnO band. The Uv-visible showed absorption peak at corresponds to the ZnO nanostructures. X-ray diffraction, scaning electron microscopy (SEM), dispersive X-ray spectroscopy (EDX) techniques are taken to investigation the size, structure and composition of synthesised ZnO nanocrystals. The XRD pattern mat

ان تصنيع رمال مطلية بأوكسيد الحديد من خلال ترسيب الجزيئات النانوية لذلك الاوكسيد على سطوح الرمال واستخدامها في الحاجز التفاعلي النفاذ لإزالة ايونات الكادميوم والنحاس من المياه الجوفية الملوثة الهدف الرئيسي للدراسة الحالية. تم توصيف بيانات الامتزاز نتيجة تفاعل المادة المازة مع المادة الممتزة قيد الدراسة بشكل جيد من خلال نموذج لانكمير والذي كان أفضل من نموذج فراندلش. لقد وجد ان اعلى قيم لقابلية الامتزاز با

The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca