A lower extracellular pH is one of the few well-documented physiological differences between tumour and normal tissues. On the other hand, elevated glutathione (GSH) level has been detected in many tumours compared with healthy surrounding tissues. The compound II: 3-(9H-purin-6-yl-thio) carbonothionyl methyl-8-oxo-7-(2-thiophen-2-yl) acetamido-5-thia-1-azabicyclo-4-octo-ene-carboxylic acid was a cephalothin derivative contain 6-mercaptopurine (6-MP). Compound II react with general base catalysis in slightly acidic pH or with sulfhydryl nucleophiles to release the chemotherapeutic drug 6-MP. The generation of compound II was accomplished following multistep reaction procedures. The structure of compound II and its intermediate was confir

This paper presents a method of designing and constructing a system capable of acquiring
the third dimension and reconstructs a 3D shape for an object from multi images of that object using
the principle of active optical triangulation. The system consists of an illumination source, a photo
detector, a movement mechanism and a PC, which is working as a controlling unit for the hard ware
components and as an image processing unit for the object multi view raw images which must be
processed to extract the third dimension. The result showed that the optical triangulation method
provides a rapid mean for obtaining accurate and quantitative distance measurements. The final
result's analysis refers to the necessity of usin

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

The development of a meaningful dissolution procedure for drug products with limited water solubility has been a challenge to both the pharmaceutical industry and the agencies that regulate them. Natural surfactants aid in the dissolution and subsequent absorption of drugs with limited aqueous solubility. In vitro, various techniques have been used to achieve adequate dissolution of the sparingly water – soluble or water insoluble drug products such as the use of mechanical methods (i.e., increased agitation and the disintegration method) or hydro alcoholic medium or large volumes of medium. The necessity of assuring the quality of drugs , especially those with low aqueous solubility and in vivo absorption , has led to the development and

Polycystic ovarian syndrome, additionally called PCOS is the most widespread endocrine illness amongst women. The aetiology of PCOS is attributed to a multi-factorial interplay among environmental and genetic effects. The overarching goal evaluates the correlation among blood concentrations of total testosterone, sex-hormone-binding globulin (SHBG), estradiol (E2), follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in ladies with PCOS and the impact of obesity, age, marital popularity on the obtained results. This study was conducted at the National Center for Educational Laborites /Medical City/ Baghdad. The study comprised of a sample of 83 women, elderly between 17 -45 years, who had been selected in a random manner

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Accurate and correct price prediction of gold is significant to maintain the stability and fair operation of gold markets as well as the efficiency and proper functioning of financial markets related to gold trading. Gold prices have a long history of non-linear and non-stationary behavior that generates highly complex datasets which are very difficult to forecast with high accuracy and reliability. At the same time Support Vector Regression (SVR) has been utilized as a robust information for prediction not only gold prices but also overall metal price movements. First, the predictive capability of SVR is highly sensitive to hyperparameter selection which needs to be thoroughly tuned and optimized for potentially optimal performance. Theref