A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

Normal thyroid function is essential for neonatal growth and brain development. In a newborn infant with severe disease, endocrine regulation of hormones can be affected by abnormal metabolism. The assessment of thyroid parameters results in the recognition of a dysfunction and its association with disease severity

Objective(s): To Evaluate Diabetes self –management among patients in Baghdad City and to compare
between these patients self-management relative to the type of the disease.
Methodology: A descriptive design was conducted in Baghdad city, started from November 16th 2017 to the
end of May 17 th 2018 in order to evaluate Diabetes self-management. Purposive (non-probability) sample,
which was consisted of (120) patients who were diagnosed with D.M. The sample is comprised of (60) patient
with diabetes type I and (60) patient with diabetes type II. It is consisted of (60) male and (60) female. A
questionnaire is constructed for the purpose of the study. It is composed of (42) items. Reliability and validity of
the ques

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

Objective: The aim of this study was to compare the marginal microleakage between bulk-fill, preheated bulk-fill, and bulk-fill flowable composite resins above and below cemento-enamel junction (CEJ) using micro-computed tomography. Methods: Sixty freshly extracted premolar teeth were prepared with a slot shaped cavities of a total of 120 Class II: 3mm (bucco-lingual), 2mm (mesio-distal) with mesial-gingival margin located 1mm coronal to CEJ, and distal gingival margin located 1mm apical to the CEJ. The samples were randomly divided into two main groups according to the restorative material (Tetric EvoCeram and 3M Filtek), and each group was further sub-divided into three subgroups according to the consistency (bulk fill, preheated bulk fil

Nutrient agar medium with various concentrations of cefotaxime was used for isolation spontaneous mutants from wild type strain of P.aeruginosa PHA-1. Eighty-two mutants were successfully isolated with the viable count 52×107 , these mutants were confirmed as spontaneous not physiological adaption mutants by reculture on the same medium. Then, wild type PHA-1 and mutants were examined for production pyocyanin; a blue greenish pigment was clearly noticed on King A medium. Remarkably the mutant strain named S300-8 was distinguished in productivity in comparison with wild type strain PHA-1; the amount of pigment was 56.0667mg/l and 74.53mg/l respectively. In addition, pyocyanin produced by mutant strain S300-8 revealed a potent efficacy again

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m