The study was conducted during the spring season of 2000 and2001. The objective was to study the changes in leaves number of sunflower plants and its leaf area during growth stages under hardening conditions to drought tolerance. Agricultural practices were made according to recommendations.Asplit-split plots design was used with three replications.The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available water.The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments:Control(unsoaking), soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room temperature

The objective of the work was to study the changes in height and stem diameter of sunflower plants during growth stages under hardening conditions to drought tolerance. Field experiments were carried out during the spring season of 2000 and2001. Agricultural practices were made according to recommendations.Asplit-split plots design was used with three replications.The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available water.The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments:Control(unsoaking), soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

      The study was conducted for the detection of Aflatoxin B1(AFB1) in the serum and urine of 42 early and middle childhood patients (26 male and  16 female ) with renal function disease, liver function disease, in additional to atrophy in the growth and other symptoms depending on the information within consent obtained from each patient, in addition to 8 children, apparently healthy, as  the control. The technique of HPLC was used for the detection of AFB1 from all samples. The results showed that out of 42 patient children, 19 (45.2%) gave positive detection of AFB1 in the serum among all age groups patients with a mean of 0.88 ng/ml and a range of (0.12-3.04) ng/ml. This was compared with the cont

Stool speeimens were collected from pati nts who presented for various medical c:omplaints  in out patien.t Laboratories (The Central Health  Laboratories  /  Baghdad,). Every ,$pecim-en  wa:s  examined  by Conventional   m jcroscopic  exatninatitnl  (CME) ·and  te.§t d,  by  IgG­ ELISA kit.

Antibody against d1e Entamoeba histolylica, det cted  by ELISA, has ·the potential  to  become a vah,mble adjunct  to blood diagn9stics and make it  more affective, .although there is no repJacement fo'e the

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The objective of the present study is to verify the actual carious lesion depth by laser
fluorescence technique using 650 nm CW diode laser in comparison with the histopathological
investigation. Five permanent molar teeth were extracted from adult individuals for different reasons
(tooth impaction, periodontal diseases, and pulp infections); their ages were ranging from 20-25 years
old. Different carious teeth with varying clinical stages of caries progression were examined. An
experimental laser fluorescence set-up was built to perform the work regarding in vitro detection and
quantification of occlusal dental caries and the determination of its actual clinical carious lesion depth by
650 nm CW diode laser (excitat

This research aims to design a high-speed laser diode driver and photodetector, the result is the
design of the high-speed laser diode driver with a short pulse of 10 ns at 30 KHz frequency and the
delivered maximum pulse voltage is 5.5 mV. Also, its optical output power of the laser diode driver is
about 2.529 mW for the centroied wavelength 1546.7 nm with FWHM of 286 pm and (1270-1610) nm.
The design of the circuit based on bipolar transistor where the input pulse signal is simply generated by
an arduino kit with 15 kHz frequency and then compensated to trigger to small signal amplifier which
was is simply NPN C3355 transistor and the output is a current driver to the laser diode. OptiSystem
software and Electronic

The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the ac

Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio