This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

The present investigation was conducted to evaluate the effect of the crude extracts mixture of three plants (Tribulus terrestris, Phoenix dactylifera and Nasturtium officinale) on semen quality,sex hormones and reproductive performance of mature male mice. A group of 25 male mice given 150mg/kg/day of the powder of the plants mixture with the food for four weeks and another three groups of 25 animals each given intraperitoneal injection from each of the aqueous and ethanolic extracts with a doses 75, 150, and 300mg/kg/day for two weeks. A remarkable increase in sperm concentration and motility with a decreased abnormal morphology was obtained in the experimental groups. A significant increase in hormones level were recognized in most grou

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

The chemical composition of wastes of pressed grapes and found that the main components of wastes of pressed grapes, represented by the percentage of moisture was 6.47%, and the proportions are 3.71%. Either carbohydrates amounted to 85.77 %, either in fat models using petroleum ether Petroleum ether) was the increase of 0.27%. estimated the percentage of ash in the sampls was 3.78%, either fiber reached 69.47 %,, in addition to the test extracts towards the growth of seven types of bacteria, which included Bacillus subtilis, Bacillus cereus, Bacillus stearothermophilus, Escherishia coli, Staphylococcus aureus, Salmonella typhimurium and Pseudomonas fluorescens and yeast Candida albicans and Kluyveromyces marxianus, ( diffusion method ).

There many methods for estimation of permeability. In this Paper, permeability has been estimated by two methods. The conventional and modified methods are used to calculate flow zone indicator (FZI). The hydraulic flow unit (HU) was identified by FZI technique. This technique is effective in predicting the permeability in un-cored intervals/wells. HU is related with FZI and rock quality index (RQI). All available cores from 7 wells (Su -4, Su -5, Su -7, Su -8, Su -9, Su -12, and Su -14) were used to be database for HU classification. The plot of probability cumulative of FZI is used. The plot of core-derived probability FZI for both modified and conventional method which indicates 4 Hu (A, B, C and D) for Nahr Umr forma

Background: Diabetes is a metabolic disorder characterized by chronic hyperglycemia due to an inability to produce insulin. Uncontrolled or poorly controlled diabetes is clinically associated with increased susceptibility to delay healing. Many recent researches have shown that stem cell therapy can be the best choice for treatment of this disease. The aims of this research were investigating regeneration of pancreatic beta cells of diabetic induced rabbits after stem cell transplantation. Materials and Methods: 64 rabbits weighting an average of (2.5 - 3 kg) were used in this experimental study, and divided into 4 groups as follows; group A ( contains 16 healthy rabbits regarded as control group ) , Group B ( contains 16 diabetic rabbits