In this research, the multi-period probabilistic inventory model will be applied to the stores of raw materials used in the leather industry at the General Company for Leather Industries. The raw materials are:Natural leather includes cowhide, whether imported or local, buffalo leather, lamb leather, goat skin, chamois (raw materials made from natural leather), polished leather (raw materials made from natural leather), artificial leather (skai), supplements which include: (cuffs - Clocks - hands - pockets), and threads.This model was built after testing and determining the distribution of demand during the supply period (waiting period) for each material and completely independently from the rest of the materials, as none of the above mate

Objective- the study aim to determine the cardiac patient knowledge about anticoagulant medications using and its relationship with demographic data(age. gender. level of education. occupational). Methodology- A descriptive study(quasi-experimental)design was carried out to determine cardiac patient knowledge consider to using anticoagulant medications . Starting from(1th Jun 2017 to5th October 2018).To achieve the objectives of the study, a non-probability sample (a purposive sample) consisted of random sample comprised of (30) patients were taken anticoagulant medications ..The measurement of patient knowledge were collected through the use of questionnaire which is related to patient knowledge toward using the anticoagulant medication

The gamma dose rates and specific activity of 137Cs, 60Co and 40K in
samples of soil taken from places near the landfill radiation at Al-
Tuwaitha site were measured using a portable NaI(Tl) detector. The
results of gamma dose rates in samples were ranged from 52.6
nGy.h-1 to 131nGy.h-1. Then the specific activity of 137Cs, 60Co and
40K in soil were determined using high pure germanium (HPGe)
detector. The specific activities were varied from 1.9 to 115500 Bq.
kg-1 for 137Cs, from 6.37 to 616.5 Bq. kg-1 for 60Co, and from 3 to
839.5 Bq. kg-1 for 40K. The corresponding health risk for the annual
effective dose equivalent varied from 1.85×10-14 to 15.7mSv/y. The
results were compared with various internationa

Hypothesis Nanofluid flooding has been identified as a promising method for enhanced oil recovery (EOR) and improved Carbon geo-sequestration (CGS). However, it is unclear how nanoparticles (NPs) influence the CO2-brine interfacial tension (γ), which is a key parameter in pore-to reservoirs-scale fluid dynamics, and consequently project success. The effects of pressure, temperature, salinity, and NPs concentration on CO2-silica (hydrophilic or hydrophobic) nanofluid γ was thus systematically investigated to understand the influence of nanofluid flooding on CO2 geo-storage. Experiments Pendant drop method was used to measure CO2/nanofluid γ at carbon storage conditions using high pressure-high temperature optical cell. Findings CO2/nano

The purpose of this study is to elucidate the microfacies and the biozones present in the studied rocks as well as to determine their environments or deposition. The study depends mainly on the benthonic foraminiferal assemblages identified from (27) rock thin sections made available from an outcrop at Wadi Banat Al-Hassan area in the Upper Euphrates Valley. X-Ray diffraction was also used to determine the type of carbonate minerals present in the studied rocks.

The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

This research aims to understand complexity management and its impact on the use of the dynamic capabilities of a sample of private colleges.  Private colleges are currently facing many crises, changes, unrest and high competitive pressures.  Which is sometimes difficult or even impossible to predict.  The recruitment of dynamic capabilities is also one of the challenges facing senior management at private colleges to help them survive and survive.  Thus, the problem of research was (there is a clear insufficiency of interest in Complexity Management and trying to employ it in improving the dynamic capabilities of Colleges that have been discussed?). A group of private colleges was selected as a