This paper deals with the preparation of new monomers and polymers which including heterocyclic unit. The diacid chlorides compounds [1-3] were prepared from the reaction of glutaric acid, adipic acid, terephthalic acid with thionyl chloride. Succinic acid reacted with ethanol to produce compound [4]. Compound [4] reacted with hydrazine hydrate to obtain succinic hydrazide [5].Compound [5] reaction with CS2 and KOH in absolute ethanol to produce compound [6].The polymers [7-12] have been created by reacting diacid chlorides compounds [1-3] with compound[5] or [6] in dry pyridine with some drops of DMF. The topology of produced compounds has characterized through their spectral and analytical data as in FT-IR spectra, Thermal analysis [DSC,

Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Background: The appointment system is a common practice in primary health care clinics in developed countries. The patients and health care providers in the primary health care setting perceived the appointment system as an indicator of good quality service.

Objective: The aim of this study was to survey patients’ and health care providers’ attitudes towards the introduction of an appointment system and their satisfaction with the existing ‘walk-in’ system in the primary health care setting.

Subjects and Methods: A questionnaire survey was conducted included a convenient sample of 234 patients as well as 76 health care providers from two primary health care center

In the recent decade, injection of nanoparticles (NPs) into underground formation as liquid nanodispersions has been suggested as a smart alternative for conventional methods in tertiary oil recovery projects from mature oil reservoirs. Such reservoirs, however, are strong candidates for carbon geo-sequestration (CGS) projects, and the presence of nanoparticles (NPs) after nanofluid-flooding can add more complexity to carbon geo-storage projects. Despite studies investigating CO2 injection and nanofluid-flooding for EOR projects, no information was reported about the potential synergistic effects of CO2 and NPs on enhanced oil recovery (EOR) and CGS concerning the interfacial tension (γ) of CO2-oil system. This study thus extensively inves

With the development of communication technologies, the use of wireless systems in biomedical implanted devices has become very useful. Bio-implantable devices are electronic devices which are used for treatment and monitoring brain implants, pacemakers, cochlear implants, retinal implants and so on. The inductive coupling link is used to transmit power and data between the primary and secondary sides of the biomedical implanted system, in which efficient power amplifier is very much needed to ensure the best data transmission rates and low power losses. However, the efficiency of the implanted devices depends on the circuit design, controller, load variation, changes of radio frequency coil’s mutual displacement and coupling coef

Due to the remarkable progress in photovoltaic technology, enhancing efficiency and minimized the costs have emerged as global challenges for the solar industry. A crucial aspect of this advancement involves the creation of solar cell antireflection coating, which play a significant role in minimizing sunlight reflection on the cell surface. In this study, we report on the optimization of the characteristics of CeO2 films prepared by pulsed laser deposition through the variation of laser energy density. The deposited CeO2 nanostructure films have been used as an effective antireflection coating (ARC) and light-trapping morphology to improve the efficiency of silicon crystalline solar cell. The film’s thickness increases as laser fluence i

Objective : Sciatic nerve block (popliteal approach) and femoral N block is a new technique other than general anesthesia in below knee surgery because it provides adequate muscle relaxation, with good intraoperative and post-operative analgesia. Nefopam is non opioid, non-respiratory depressant and non-sedative was mixed with local anesthetics drug to study the effects. This study was done to compare the onset and duration of sensory and onset time and duration of action of motor block following administration of either bupivacaine alone with administration of bupivacaine and Nefopam in patients undergoing below knee lower limb surgeries under ultrasound guided regional anesthesia.
Methods: 100 patients with American society of anest

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample