The purpose of this research work is to synthesize conjugates of some NSAIDs with sulfamethoxazole as possible mutual prodrugs to overcome the local gastric irritation of NSAID with free carboxyl group by formation of ester linkage that supposed to remain intact in stomach and may hydrolyze in intestine chemically or enzymatically; in addition to that attempting to target the synthesized derivative to the colon by formation of azo group that undergo reduction only by colonic bacterial azo reductaze enzyme to liberate the parent compound to act locally (treatment of inflammation and infections in colon)

The purpose of this research work is to synthesize conjugates of some NSAIDs with sulfamethoxazole as possible mutual prodrugs to overcome the local gastric irritation of NSAID with free carboxyl group by formation of ester linkage that supposed to remain intact in stomach and may hydrolyze in intestine chemically or enzymatically; in addition to that attempting to target the synthesized derivative to the colon by formation of azo group that undergo reduction only by colonic bacterial azo reductaze enzyme to liberate the parent compound to act locally (treatment of  inflammation and infections in colon).

Key words: Mutual prodrug, Ester linkage, Azo bond, Colon targeting

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

  Secnidazole was linked with ciprofloxacin as mutual prodrugs to get antibiotics with broader spectrum of activity, improved physicochemical properties and given by single dose to improve patient’s compliance. Furthermore, they provide structural modifications to overcome bacterial adaptation. The structures of the synthesized compounds were confirmed using FT-IR, mass spectrometry, elemental microanalysis (CHNO) and some physiochemical properties. This modification was led to an increase in Log P values for Mutual I (Log P 1.114) and Mutual II (Log P 1.97) compared with its values for Secnidazole (Log P -0.373) and ciprofloxacin (Log P -0.832). The solubility of prodrugs had been determined in different media, Mutual II showed 1

Learn new methods of teaching mathematics contribute to raising the level of pupils to acquire mathematical concepts primary stage
Attempt advancement in the level of mathematics teaching for the better through the use of modern teaching strategies. The research aims at the progress in the acquisition of mathematical concepts schoolgirls after subjecting the fourth grade to teach in active learning strategies, the number of research sample (60) schoolgirl, by (30) schoolgirl experimental group and 30 pupils of the control group. Clear from the results shown the presence of a statistically significant difference between the acquisition of concepts of schoolgirls two groups (experimental and control) for the benefit of pupils of the exp

In the knowledge society, artificial intelligence (AI) forms a cornerstone of global education. This quasi-experimental study examines the impact of an Intelligent Adaptive Learning Strategy (IALS) on flexible thinking (FT) and academic achievement among 60 3rd-year undergraduate students at the College of Education/University of Baghdad (experimental n = 30; control n = 30). The IALS was implemented via an AI-supported educational platform, while the control group received conventional instruction. Post-test intervention assessments included an FT test (10 items, content validity = 0.89, Cronbach’s α = 0.87) and an achievement test (10 objective items, α = 0.85). Results revealed statistically significant superiority of the exp

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration