One of the most difficult tasks in modern medical societies is the process of identifying a cure for many infectious diseases caused by drug-resistant microbes. Therefore, it has become necessary to discover new compounds that work in this regard. The currently prepared Schiff base, derived from thiazole, has a biological activity against bacteria and biofilms and its activity increases when it is associated with copper, zinc and platinum ions and forms metal complexes. This study highlights the synthesis and evaluation of novel biological compounds as inhibitors of bacterial growth and biofilms. A three newly complexes are resulting from the reaction of a new Schiff base ligand (LC) with metal ions (Zn, Cu, Pt). The new ligand (LC)

A multistep synthesis was established for the preparation of a new vanillic acid-1, 2, 4-1triazole-3-thiol conjugate (4). Finally, several aromatized aldehydes reacted with compound (4) to produce Schiff bases derivatives (5–11). The purpose of this research is to prepare new vanillic acid derivatives with 1, 2, 4-triazole-3-thiol heterocyclic ring structures and to evaluate their antimicrobial activity in a preliminary assessment. Fourier-transform infrared (FT-IR) and proton nuclear magnetic resonance spectroscopy (¹H-NMR) were used to verify the structures of the newly synthesized compounds. all the final synthesized compounds (

Background Type two diabetes (T2DM) is characterized by insufficient insulin production and secretion. Additionally, the body develops insulin resistance which affects 90–95% of diabetics. Complex cytokines, receptors, genetic pathways, and the immune system are involved in T2DM. Interleukin-18 (IL-18) is one of the inflammatory cytokines associated with Type 2 diabetes. Environmental and genetic variables, including genetic polymorphisms, can increase T2DM risk and its consequences. Single nucleotide gene polymorphisms (SNPs) are important risk factors for diabetes that can be used to find the disease early and treat it better. Objective This study aimed to determine the levels of IL-18 in the serum of Iraqi patients with Type 2 diabetes

Interleukins (IL-2 and IL-4) are increased in asthmatics and were reported to induce resistance to steroid therapy in some patients who fail to get benefit from glucocorticoids when used in full dose and for long period of time. In this context, the present study was conducted on Iraqi patients to provide additional laboratory mean, beside the clinical diagnosis, for the decision whether the asthma is steroid sensitive or resistant by monitoring the level of immunoglobulins, complement proteins and interleukins among asthmatic patients (steroid sensitive or resistant) and the possible contribution of other factors like age, sex and environments in the development of steroid resistance. A total number of 55 asthmatics and 28 normal subjec

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu