JOURNAL OF EDUCATION AND SCIENCE

The aim of this study was to measure osteoporosis in the right heel bone. A total of 123 Iraqi men and women with low back pain (LBP) participated in the study (18 males and 105 females). Quantitative Ultrasound (QUS) was used to assess osteoporosis, speed of sound (SOS), broadband ultrasound attenuation (BUA), and calcaneus bone quality index (BQI). A dual x-ray absorptiometry (DXA) was used to determine tissue thickness, fracture risk factor, and abdominal fat percentage. The results indicate that SOS was 1495.43±18.780 m/sec. Participants had a Z-score of -1.10±1.56. The fracture risk factor for participants was 1.622± 1.90 when DXA measurements were taken. Low back pain measurements revealed that the age group between 51-60 years had the highest prevalence. The correlation between the T-score and the calcaneal SOS is a linear relationship with a P-value of 0.0001. When we examine the relationship between the Z-score and the calcaneal BUA, we see that it is linear and statistically significant (P-value less than 0.0001). The correlations between calcaneal BQI and BMI, as well as between calcaneal BUA and tissue thickness, were found to be statistically insignificant (P-value = 0.8 and 0.8, respectively). The correlation between calcaneal SOS and abdominal fat percent appears to be statistically significant (P-value=0.05) (linear correlation is weak).

A sensitive fluorometric method, with few steps and suitable for the daily routine, was made for examining adrenaline hydrochloride and dopamine hydrochloride. The reliance in this paper was on the nucleophilic substitution interaction of the mentioned drugs with 1,2-naphthoquinone sulfonate (NQS) in an aqueous pH 6 to give a fluorescent product with a maximum emission wave at ʎem 471 nm after being excited at a maximum excitation wave at ʎ ex 300 nm. The plots have complied within the range of 0.01- 4.0, 0.01-2 µg/ml, and The detection limits (0.0062, 0.0027) and quantitation limits were (0.0207, 0.0091) µg/ml, for adrenaline and dopamine respectively. The accuracy (% recovery) was between (99.21% - 100.72%) and the relative standard deviation (RSD%) is better than 0.95%. It was also found that the formed product was in a ratio of 1:2 reagent to the drug. The estimation of adrenaline and dopamine has been successfully tested on the injection, and it is in good agreement with its approved value and with that of the British Pharmacopoeia method.

Recently, character recognition and deep learning have caught the attention of many researchers. Optical Character Recognition (OCR) usually takes an image of the character as input and generates the identical character as output. The important role that OCR does is to transform printed materials into digital text files. Convolutional Neural Network (CNN) is an influential model that is generous with bright results in optical character recognition (OCR). The state-of-the-art performance which exists in deep neural networks is usually used to handle frequently recognition and classification problems. Many applications are using it, for instance, robotics, traffic monitoring, articles digitization, etc. CNN is designed to adaptively and automatically learn features by using many kinds of layers (convolution layers, pooling layers, and fully connected layers). In this paper we will go through the advantages and recent usage of CNN in OCR and why it’s important to use it in handwritten and printed text recognition and what subjects we can use this technique for. Researchers are progressively using CNN for the machine-printed characters and recognition of handwritten, that is because CNN architectures are suitable for recognition tasks by inputting some images

This study includes development of a sensitive spectrophotometric method for the determination of acetylcysteine in aqueous solution. The method is based on the oxidation of acetylcysteine with a ferric ion, followed by reacting of produced ferrous ion with 2,2׳-bipyridyl to form a pink complex , which is stable and water-soluble and has the highest absorption at a wavelength of 524 nm. The limits of Beer's law were in the concentration range of (5-180) µg of acetylcysteine in a final volume of 20 milliliters (0.25-9.0 µg.ml-1) and the molar absorptivity of 8633.28 L. mol-1 .cm-1 , Sandell's sensitivity index of 0.0189 µg.cm-2. The relative error of -4.28% – 4.98 % and relative standard deviation of ± 0.56% - ± 3.75% depending on the concentration level. The limit of detection limit(LOD) and limit of quantitation (LOQ) were calculated and equal to 0.01837 and 0.06124 µg/ml respectively, no inference was observed in the common pharmaceutical excipients. The results obtain by proposed method were in good agreement with those obtain from official British pharmacopoeia using t-test (at 95% confidence limit) which indicates that there is no significant differences between them. The method was successfully applied to determine acetylcysteine in its pharmaceutical preparations.

This study aim to show the effect of soil contamination with crude oil and its derivatives on the dry weight and Nutrient minerals on flax (Linum usitatissimum L.) and safflower (Carthamus tinctorius L.). This experiment was carried out in plastic pots and under Plastic house conditions, the treatment was carried out with crude oil, used car's engine oil and used generator's engine oil at three concentrations 1-2-3% for each treatment ,in addition to the comparison treatment. The results showed a significant decrease in the dry weight of the shoot systems of flax and safflower when treated with crude oil at a concentration of 3% amounted to 0.043-0.124 g, respectively, and the dry weight of the root systems amounted to 0.022-0.015 g, respectively. There was also a significant decrease in the concentration of calcium in the shoot system of flax and safflower plants when treated with crude oil and used generator oil at a concentration of 3% amounted to (1,900-1.950) mg\g, respectively. The calcium concentration has also decreased in the root system of flax and safflower plants when treated with used generator and car oil at the concentration 3% amounted to 1.500-1.600 mg\g, respectively. Potassium concentration decreased in the shoot and root systems of flax and safflower plants when treated with generator engine oil and crude oil at a concentration of 3% and reached 6.900-10.45 and 4.150-8.800 mg\g, respectively, compared to the control treatment and other treatments

Both The functionality and the non-functionality for what the system does as well as doesn't of software systems requirements are documented in a Software Requirements Specification (SRS).
Moreover in requirements engineering, system requirements classify into several categories such as functional, quality and constraint classes.
Therefore, we evaluate several machine learning approaches as well as methodologies that mentioned in previous literature in term of automatic requirements extraction, then the classification based on methodically reviewing for many previous works on software requirements classification to assist software engineers in selecting the best requirement classification technique. Therefore, the study aim to get answer for several questions that related to: What machine learning algorithms were used for the classification process of the requirements, How these algorithms work and how they're evaluated, What methods were used for extracting features from a text, What evaluation criteria were used in comparing results and What machine learning techniques and methods were provided the highest accuracy.

In our work we introduced a new type of open sets is defined as follows: If for each set that is not empty M in X, M≠X and M ∈τ^∝such that A ⊆ int(A∪M). then A in (X,τ) is named h∝-open set. We also go through the relationship between h∝- open sets and a variety of other open set types as h-open sets, open sets, semi-open sets and ∝-open sets. We proved that each h-open and open set is h∝-open and there is no relationship between∝-open sets and semi-open sets with h∝-open sets. Furthermore, we begin by introducing the concepts of h∝-continuous mappings, h∝-open mappings, h∝-irresolute mappings, and h∝-totally continuous mappings, We proved that each h-continuous mapping in any topological space is h∝-continuous mapping, each continuous mapping in any topological space is h∝-continuous mapping and there is no relationship between∝-continuous mappings and semi-continuous mappings with h∝-continuous mappings as well as some of its features. Finally, we look at some of the new class's separation axioms.

At the present time, the reliance on computers is increasing in all aspects of life, so it is necessary to protect computer networks and computing resources from complex attacks against the network. This is done by building tools, applications, and systems that detect attacks or anomalies adapting to ever-changing architectures and dynamically changing threats. Providing network security is one of the most important things in network communications, more networks grow and the more devices are added to the network, need more requirement to provide network security, a network security system is necessary to protect devices and data of network users, helps protect information shared on the network, protection of people's personal information and helps prevent users from falling victim to pirates
The goal of this paper is to build a Network Intrusion Detection System (NIDS) based on deep learning techniques such as Convolutional Neural Network (CNN), which demonstrated its efficiency in predicting, classifying, and extracting high-level features in network traffic.

In recent years, the use of computing has increased along with medical skills, and this had impressive results in terms of classification and treatment, in addition to facilitating the matter of medical personnel. This was evident during the Corona pandemic, which infected millions around the world, which. There is an urgent need for software tools to help classify the disease without the need to resort to doctors. The matter is not limited to the classification of corona disease, but it also extends to the expansion of the discovery of other diseases such as malaria, skin cancer and other diseases that afflict large numbers of people. Malaria is an infectious disease caused by the Plasmodium parasite, and according to some statistics, the total number of infections in 2019 reached about 228 million cases around the world. As for skin cancer, it is considered one of the serious diseases that affect humans because the skin plays a key role in protecting muscles and bones, and therefore cancer will affect all body functions.
CNN have made great strides in many intractable problems in image processing and classification, but their performance depends on their hyperparameters which is a tedious task if done manually. Therefore, experts in the field of deep learning aspire to improve its performance sometimes by integrating it with other algorithms such as Particle Swarm Optimization, Gray Wolf Optimization, Genetic Algorithm or firefly. All of these algorithms gave different results than the others, that is, they gave different levels of performance.

This paper deals with the spatial prediction in Geostatistics. This paper depend on interpellation methods of spatial statistic (ordinary kriging technique) to combination with fuzzy logic under uncertainty for spatial data prediction. This work includes the best linear unbiased estimator prediction by using formals of linear prediction and variance kriging to find prediction by Appling on real spatial data. The data adopted from real spatial data represented the depth of real underground water wells with real location from Mosul city/Iraq. We took (100) real data with locations in study area. We applied empiricism variogram function to get the properties of variogram function. We combination between kriging technique with fuzzy logic (Mamdani Fuzzy Model). To get the best Mathematical model under uncertainty. We getting the results between kriging and fuzzy logic using Matlab language.This study is a continuation of the research conducted in this context Which is very important to highlight.

The study included the selection of groundwater from three villages north of the city of Mosul, namely the villages of (Hassan Jallad, Ghazil and al-Khrab), with two wells from each village for six months, with one sample from each well per month to study its physical and chemical characteristics and determining the extent to which it can be used for drinking and various household uses. By studying the characteristics (groundwater temperature, electrical conductivity, dissolved oxygen in water, pH, water hardness, as well as positive and negative dissolved ions in water). The results of the study indicated that the temperature of the groundwater is stable and had little variation throughout the study period, while the value of the electrical conductivity reached (1738) µS/cm in the well (5) in Alkharab village, while the concentration of dissolved oxygen decreased to an average of (1.3) mg / liter in the well (1) in Hasan jalaad village.Meanwhile the hardness values ​​ranged between (842-312) mg / liter, However the results indicated that the values ​​of calcium ions ranged between (268-72) mg / liter, while the values ​​of magnesium ions ranged between (69-27) mg / liter On the other hand The values ​​of sodium and potassium ions reached to the limits of (22) mg/L and (3.90) mg/L, respectively. As for the studied negative ions (bicarbonate, chlorides and sulfates), they reached (460) mg/L, (68) mg/L and (510) ) mg/L, respectively

The study included the selection of groundwater from three villages north of the city of Mosul, namely the villages of (Hassan Jallad, Ghazil and al-Khrab), with two wells from each village for six months, with one sample from each well per month to study its physical and chemical characteristics and determining the extent to which it can be used for drinking and various household uses. By studying the characteristics (groundwater temperature, electrical conductivity, dissolved oxygen in water, pH, water hardness, as well as positive and negative dissolved ions in water). The results of the study indicated that the temperature of the groundwater is stable and had little variation throughout the study period, while the value of the electrical conductivity reached (1738) µS/cm in the well (5) in Alkharab village, while the concentration of dissolved oxygen decreased to an average of (1.3) mg / liter in the well (1) in Hasan jalaad village.Meanwhile the hardness values ​​ranged between (842-312) mg / liter, However the results indicated that the values ​​of calcium ions ranged between (268-72) mg / liter, while the values ​​of magnesium ions ranged between (69-27) mg / liter On the other hand The values ​​of sodium and potassium ions reached to the limits of (22) mg/L and (3.90) mg/L, respectively. As for the studied negative ions (bicarbonate, chlorides and sulfates), they reached (460) mg/L, (68) mg/L and (510) ) mg/L, respectively

Zinc Oxide (ZnO) is one of the important semiconductor materials which contribute effectively to the development of the semiconductor industry technology. ZnO nanostructures (NSs) were synthesized using thermal chemical vapor deposition (TCVD) technique under atmospheric pressure at different evaporation boat-substrate distances. ZnO NSs were prepared by oxidizing Znic acetate dihydrate powder within quartz tube instead of its outside. The effect of change evaporation boat-substrate distance (2.5, 4.5, 6.5 and 8.5 cm) on the optical and structural properties of ZnO NSs were studied. ZnO NSs were characterized by UV-Visible spectrophotometer, X-ray diffraction (XRD) technique and photoluminescence (PL) spectroscopy to evaluate its optical and structural properties. Optical band gap measurement results exhibited a red-shifted from (3.25 eV) to (3.05 eV), as the separation distance increased from (2.5 cm) to (8.5 cm), respectively. XRD technique confirms that metal oxide was ZnO and having hexagonal structure. The average crystallite size of the samples was decreased from 63.4 to 58.3 nm, with the increase in separation distance from 2.5 to 8.5 cm. Also, the sharpness, strong intensity and narrow width of dominant diffraction peak indicate the high crystallinity of the prepared ZnO NSs. The PL spectra of the ZnO NSs revealed a wide deep-level emission for all the prepared samples. ZnO NSs grown by TCVD technique may provide potential applications in nano-photovoltaics and nano-photodetectors.

The hematopoiesis in the bone marrow in the early stages of life is very complex and involves many cellular factors under very strict micro-environments. The two important cellular factors are heat shock proteins and antioxidant enzymes. The aim of the study was to study the gene expression profile of healthy rats’ bone marrow cells and niches particularly heat shock proteins and antioxidant genes. A total of thirty healthy Wister Albino rats at one, two, and three months old were involved throughout the study. Bone marrow samples were collected at a specified date according to the study design and utilized for qPCR test for expression of Hsps27, 90α, 90β, and antioxidant enzymes glutathione peroxidase1 (GPX1), catalase CAT and superoxide dismutase (SOD3) genes. The results revealed that there was a clear expression of both Hsps90α andβ in bone marrow cells throughout the study as well as the GPX1 gene. Furthermore, there was an increase in fold change of Hsps90α and β as well as GPX1, CAT, and SOD3 proteins as age progressed. In conclusion, hematopoietic cell differentiation and proliferation are regulated by bone marrow microenvironment stress conditions and by the expression of different Hsps and antioxidant genes. The protein folding process is a defense mechanism to protect the HSCs, and progenitors from un/misfolded proteins and to keep proteostasis.