A new benzylidene derivative, namely N-benzylidene-5-phenyl-1,3,4-thiadiazol-2-amine (BPTA), has been synthesized and instrumentally confirmed with Elemental Analysis (CHN), Nuclear Magnetic Resonance (NMR), and Fourier Transform Infrared Spectroscopy (FT-IR). Titanium Dioxide (TiO2) nanoparticles (NPs) were synthesized and characterized by X-ray. The mutualistic complementary dependence of BPTA with TiO2 nanoparticles as anti-corrosive inhibitor on mild steel (MS) in 1.0 M hydrochloric acid has been tested at various concentrations and various temperatures. The methodological work was achieved by gravimetric measurement methods complemented with surface analysis. The synthesized inhibitor concentrations were 0.1 mM to 0.5 mM and the temperatures ranging from 303–333 K. The BPTA with TiO2-NP as a synergistic inhibitor becomes superior inhibitive effects with more than 96% inhibition competence of MS coupons in a harsh acidic medium. The efficiency of the inhibition improved with increasing BPTA content and also increase with the Synergistic effects of BPTA with TiO2-NP. The excellent effectiveness was performed with the 0.5 mM concentration of BPTA and become higher with adding of TiO2-NP rising to the maximum inhibition efficiency (IE). However, the inhibition efficacy declined as the temperature rises. Results of BPTA as corrosion inhibitor indicated the obedience of the adsorption of the inhibitor of mixed type on the surface of MS to Langmuir adsorption isotherm. It was found that the BPTA and performance depend on the Synergistic effects, concentrations of the TiO2-NP and BPTA, in addition to the solution temperature. Nevertheless, the quantum calculations have confirmed the direct correlation of the electronic characteristics of BPTA with the corrosive inhibitive influence.
Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel
... Show MoreThis research addresses a problem manifested in a main question: what is the role of the digital media in marketing the artistic products? in order to determine the role played by the digital media in the disclosure and promotion of the artistic product, its price and places of distribution, as the basic elements of the marketing mixture.
This is a descriptive research in which the researcher used the survey method to check the opinions of a sample chosen according to the (proportion) method from the research community represented by instructors and students of the college of Fine Arts- University of Dayala.
... Show Moreفي السنوات الأخيرة، أدى التقدم التكنولوجي في إنترنت الأشياء (IoT) وأجهزة الاستشعار الذكية إلى فتح اتجاهات جديدة وإعطاء حلول عملية في مختلف قطاعات الحياة. يتم التعرف على إنترنت الأشياء كتنولوجيا حديثة تربط بين مختلف انواع الشبكات. تم تحسين أنواع مختلفة من قطاعات الرعاية الصحية في المجال الطبي بناءً على هذه التكنولوجيا. أحد هذه القطاعات الهامة هو نظام مراقبة الصحة (HMS). تعتبر مراقبة المريض عن بعد لاسلكيًا وبت
... Show MoreThe catalytic wet air oxidation (CWAO) of phenol has been studied in a trickle bed reactor
using active carbon prepared from date stones as catalyst by ferric and zinc chloride activation (FAC and ZAC). The activated carbons were characterized by measuring their surface area and adsorption capacity besides conventional properties, and then checked for CWAO using a trickle bed reactor operating at different conditions (i.e. pH, gas flow rate, LHSV, temperature and oxygen partial pressure). The results showed that the active carbon (FAC and ZAC), without any active metal supported, gives the highest phenol conversion. The reaction network proposed account
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
In this paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.
1,3,4-oxadizole and pyrazole derivatives are very important scaffolds for medicinal chemistry. A literature survey revealed that they possess a wide spectrum of biological activities including anti-inflammatory and antitumor effects.
To describe the synthesis and evaluation of two classes of new niflumic acid (NF) derivatives, the 1,3,4-oxadizole derivatives (compounds 3 and (4A-E) and pyrazole derivatives (compounds 5 and 6), as EGFR tyrosine kinase inhibitors in silico and in vitro.
The designed compounds were synthesized using convent
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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