PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,

In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

To determine the potential of gingival crevicular fluid (GCF) volume, E‐cadherin and total antioxidant capacity (TAC) levels to predict the outcomes of nonsurgical periodontal therapy (NSPT) for periodontitis patients.

The study involved preparing a new compound by combining between 2-hydroxybenzaldehyde and (Z)-3-hydrazineylideneindolin-2-one resulting in Schiff bases and metal ions: Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) forming stable minerals-based-Schiff complexes. The formation of resulting Schiff bases is detected spectrally using LC-Mss which gave corresponding results with theoretical results, 1H-NMR proves the founding of N=CH signal, FT-IR indicates the occurrence of imine band and UV-VIs mean is proved the ligand formation. On the other hand, minerals-based-Schiff was characterized using the same spectral means that relied with ligand (Schiff bases). Those means gave satisfactory results and proved the suggested distinguishable geometries.

The study involved preparing a new compound by combining between 2- hydroxybenzaldehyde and (Z)-3-hydrazineylideneindolin-2-one resulting in Schiff bases and metal ions: Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) forming stable minerals-based-Schiff complexes. The formation of resulting Schiff bases is detected spectrally using LC-Mss which gave corresponding results with theoretical results, 1H-NMR proves the founding of N=CH signal, FT-IR indicates the occurrence of imine band and UV-VIs mean is proved the ligand formation. On the other hand, minerals-based-Schiff was characterized using the same spectral means that relied with ligand (Schiff bases). Those means gave satisfactory results and proved the suggested distinguishable geometries

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

  Many production companies suffers from big losses because of  high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.

  The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.

  I had adopted in this research fuzzy linear program model with fuzzy figures