HCl is separated from HCl –H₂SO₄  solution by membrane distillation process(MD). The flat –sheet membranes made from polyvinylidene fluoride (PVDF) and polypropylene (pp.). Plate and frame these types of membrane where used in the process. The feed is a mixture of HCl and H₂SO₄ acids compositions depended on metals treated object.HCl concentration increased in the permeate during the process but sulfuric acid increased gradually in the feed .During the concentration of solution acids concentrations in the feed at the beginning were 50 g/dm³ of sulfuric acid and 50 g/dm³ of hydrochloric acid at 333K feed temperature the permeate flux was 71 dm

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

In the recent years, some of the newly constructed asphalt concrete pavements in Baghdad as well as other cities across Iraq showed premature failures with consequential negative impact on both roadway safety and economy. Frequently, load associated mode of failure (rutting and fatigue) as well as, occasionally, moisture damage in some poorly drained sections are the main failure types found in those newly constructed road.

In this research, hydrated lime was introduced into asphalt concrete mixtures of wearing course in two methods. The first one was the addition of dry lime on dry aggregate and the second one was the addition of dry lime on saturated surface dry aggregate moisturized by 2.0 to 3.0 percent of wa

Seeds of the two rice genotypes namely Amber 33 (A33) and Amber Baghdad (AB) were divided into two groups; the first was presoaked in different concentrations of ethyl methane sulphonate (EMS) as chemical mutagen for different duration times (3, 6 and 12) hrs, and the other was exposed to different exposure times of ultra violate (UV-B) radiation (280-320 nm) as physical mutagen for different times (20, 40 and 60) min at room temperature. Treated and non-treated seeds were transferred into the callus induction medium containing 2.5 mg/L 2,4- dichlorophenoxy acetic acid (2,4-D) and 0.5 mg/L benzyl adenine (BA) under aseptic conditions. Calli were divided into two groups the first was treated with several EMS concentrations (0.0, 0.50. 1.0, 1

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

KA Sharquie, AA Al-Nuaimy, Annals of Saudi Medicine, 2002 - Cited by 48

This research was carried out to determine the impact of heat shock, electric shock and seeds in soaking nitrous acid mutagen solution on three cultivars of faba beans plant (Zaina, Aguadulce and Local) at the year 2012-2013. Factorial experiment was arranged in randomized complete block design (RCBD) with three replicates were used. The results showed that heat shock lead to early plants of 50% in flowering and an increase in the number of branches/plant and the number of seeds/pod compared to other treatments, whereas the seeds soaked in nitrous acid mutagen solution gave the highest plant height, leaf area index, number of pods/plant, seed weight, seed yield kg/ha, and did not differ significantly with treatment of electric shock in the