The study of biopolymers and their derivative materials had received a considerable degree of attention from researchers in the preparation of novel material. Biopolymers and their derivatives have a wide range of applications as a result of their bio-compatibility, bio-degradability and non-toxicity. In this paper, chitosan reacted with different aldehydes(2,4 –dichloro- benzaldehyde or 2-methyl benzaldehyde), different ketones (4-bromoacetophenone or 3-aminoacetophenone) to produce chitosan schiff base (1-4) . Chitosan schiff base (1-4) reacted with glutaric acid or adipic acid in acidic media in distilled water according to the steps of Fischer and Speier to produce compounds (5-12)

This study was aimed to monitor oral zinc sulfate role on local cervical proinflammatory cytokines in HPV-infected women comparing with these cytokines before treatment application. A cervical secretion got from 28 infected women before and after treatment with zinc sulfate, these samples assessed various markers of inflammation including interleukin-1β, IL-8, and IL-12. Results manifested that improve and clear the cervical HPV infections after three months of zinc treatment 46.43% and 21.43%, respectively. Viral infections with single and multiple HPV high-risk types are raising of studied cytokines after 3-month compared with single HPV low-risk type. Moreover, this increasing was statistically significant only in IL-12 and IL-1. Women

Background: Oral health represents an important base for human well-being; the heath of the body begins from oral cavity. Great deal has been applied to increase knowledge in the field of oral health in order to develop appropriate preventive program. This study was conducted in order to estimate the percentage and severity of dental caries and gingivitis among children attending Preventive Department in Collage of Dentistry, University of Baghdad and to determine dental treatment need for those patients, further more to study the relation of these variables with dental knowledge. Materials and Methods: The study group consists of 163 children with an age ranged from 6 to 14 years, who attended the preventive clinic for the first time to be

This study involved the effect of the aqueous extracts of two plants, Origanum vulgare L.(1), Trigonella Foenum Graecum L. (Fenugreek) seeds(2) on the growth of cancer cell lines. Rhabdomyo sarcomas (RD) of human cell line and female intestine cells of Albino mice (L20B) in vitro System. These extracts were compared with the known anticancer drug Cis-platinum(Cis-Pt) as a positive control. The phytochemical tests were used for screening the active compounds in plants. The inhibition activity assay was used as a parameter of the cytotoxic effect of these extracts. Cancer cell lines were treated with four concentrations of Cis-platin, 31.25, 62.5, 125 and 250 ?g/ml for 72 hour exposure time. The same concentrations were used for the other ext

In this work, the performance of the receiver in a quantum cryptography system based on BB84 protocol is scaled by calculating the Quantum Bit Error Rate (QBER) of the receiver. To apply this performance test, an optical setup was arranged and a circuit was designed and implemented to calculate the QBER. This electronic circuit is used to calculate the number of counts per second generated by the avalanche photodiodes set in the receiver. The calculated counts per second are used to calculate the QBER for the receiver that gives an indication for the performance of the receiver. Minimum QBER, 6%, was obtained with avalanche photodiode excess voltage equals to 2V and laser diode power of 3.16 nW at avalanche photodiode temperature of -10

A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing