Background: Osteoporosis (OP) is a chronic and a progressive disease characterized by low bone mass and micro-architectural deterioration of bone tissue, resulting in an increased risk of fracture. Osteocalcin is a non-collagenous protein synthesized and secreted by osteoblasts. Its main physiological functions are calcium ion homeostasis, maintain the normal bone mineralization rate, inhibit the abnormal formation of hydroxyapatite crystal, and to be involved in bone remodeling through a negative feedback mechanism.
Objective: This study was planned to evaluate serum level of bone formation marker osteocalcin (OC) in postmenopausal women with and without primary osteoporosis; and study the correlation between serum osteocalcin level

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classi

The study is based on the selective binding ability of the drug compound procaine (PRO) on a surface imprinted with nylon 6 (N6) polymer. Physical characterization of the polymer template was performed by X-ray diffraction and DSC thermal analysis. The imprinted polymer showed a high adsorption capacity to trap procaine (237 µg/g) and excellent recognition ability with an imprinted factor equal to 3.2. The method was applied to an extraction column simulating a solid-phase extraction to separate the drug compound in the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate more than the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate of more t

This research including lineament automated extraction by using PCI Geomatica program, depending on satellite image and lineament analysis by using GIS program. Analysis included density analysis, length density analysis and intersection density analysis. When calculate the slope map for the study area, found the relationship between the slope and lineament density.
The lineament density increases in the regions that have high values for the slope, show that lineament play an important role in the classification process as it isolates the class for the other were observed in Iranian territory, clearly, also show that one of the lineament hit shoulders of Galal Badra dam and the surrounding areas dam. So should take into consideration

The new organic reagent 2-[Benzo thiazolyl azo]-4,5-diphenyl imidazole was prepared and used as complexing agent for separation and spectrophotometric determination of Cu2+ ion in some samples include plants, soil, water and human blood serum. Initially determined all factors effect on extraction method and the results show optimum pH was (pHex=9), optimum concentration was 40?g/5mLCu2+ and optimum shaking time was (15min.), as well stoichiometry study appears the complex structure was 1:1 Cu2+: BTADPI. Interferences effect of cations were studied. Synergism effect shows MIBK gave increasing in distribution ratio (D). Organic solvent effect appears there is no any linear relation between dielectric constant for organic solvent used and dis

Ninety five samples were collected from different samples (urine, ear and wounds swaps), from hospitals in Baghdad city. The results of cultural, microscopic , biochemical tests indicated that in urine samples E.coli have high occurrence frequency 19 (47.5%) followed by Proteus mirabilis 18(45%) and Klebsiella species 1 (2.5%), while in wounds samples each of Pseudomonas spp. and Proteus mirabilis 10 (25%) , then followed by E.coli with 5 (12.5%) and Klebsiella species 3 (7.5%). Ear swaps samples revealed that Pseudomonas aeruginosa 7 (46%) was the major bacterium followed by Proteus mirabilis 4(26.6).Sensitivity test against eleven antimicrobial agents was done for all of the Proteus mirabilis isolates (32 isolates). The results display