Background: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009.

Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes.

Abstract

Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

ABSTRACT : Bacillus cereus and Pseudomonas aeruginosa is the ability to produce a wide antimicrobial active compounds (Bacillin and S-Pyocin) against pathogenic microorganism. In vitro assay with the antagonists of both crude bacteriocin and partial by precipitation 75% ammonium sulfate showed that the effectively inhibited growth of the following (Candida kefyer and Fusarium spp) and Propionibacterium acnes. The results showed the inhibition zone of reached Bacillin (9-13 mm), while Pyocin (13 - 16mm) in solid medium.

الصيغة العامة للمعقدات الجديدة [M2(BDS)Cl4] الناتجة من تفاعل الليكاند الجديد] ن1,ن4-ثنائي(1أ –بنزو]د[ اميدازول-2-يل)-ن1,ن4-ثنائي(4-ثنائي مثيل امينو) بنزيل) سكسنمايد[ (BDS) مع الايونات الفلزية الكادميوم, الكوبلت, الزئبق, النحاس والنيكل. تم اشتقاق هذا الليكاند من تفاعل المواد الثلاث 4-(ثنائي ميثيل أمينو) بنزالدهيد، 2-أمينو بنزيميدازول، وكلوريد السكسينيل. تم تشخيص المركبات باستخدام مطيافية طيف الاشعة تحت الحمراء وطيف الرن

Periodontitis is a dysbiosis-driven inflammatory disease in which a pathogenic subgingival biofilm disrupts the host–microbe equilibrium and promotes progressive loss of tooth-supporting tissues. While periodontal destruction has traditionally been explained mainly through the host immune response, increasing experimental and clinical evidence suggests that epithelial–mesenchymal transition (EMT)-like changes in the gingival epithelium may contribute to barrier failure and tissue remodeling during disease progression. EMT is characterized by reduced epithelial adhesion and polarity, alongside a shift toward a mesenchymal-like phenotype with enhanced motility and impaired epithelial barrier function. This narrative review focuses

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices