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Detection of line shape parameters in normal and abnormal biological tissues
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Doppler broadening technique is suggested to monitor the development of tumours. It depends on the sensitivity of positronium (Ps) annihilation parameters to the sub- microstructural changes in biological tissues. This technique uses high resolution HpGe detector to measure the lineshape parameters (S and W) in normal mice's mammary tissues and adenocarcinoma mammary tissues as a function of tumour growth. The results demonstrate that the central parameter (S) decreases and the wing parameter (W) increases as the tumour grow. It is found that the S parameter changes considerably with the distribution of voids which are affected by the tumour development. Therefore the present technique can successfully be employed to monitor the development of tumours

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Publication Date
Thu Jul 01 2010
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NEW SUB-SPECIES OF CHUKAR PARTRIDGE ALECTORIS CHUKAR (GRAY 1830) (PHASIANIDAE, GALLIFORMES) FROM NORTH EAST OF IRAQ WITH BIOLOGICAL OBSERVATIONS
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Chukar partridge Alectoris chukar (Gray, 1830) is the only species of the 46 species of the genus Alectoris to be found in Iraq. At least there are fourteen subspecies of chukar were described from east Europe, the Middle East and west Asia, two of them were known to be found in Iraq, A.c. Kurdestanica (Meinertzhagen, 1923) from Alpine bio-geographical zone of altitude more than 2000m high, and A.c. werae Zarundny and Loudon, 1904, from the foothills of altitude not more than 400m. In between these two regions, there is another bio-geographical region known as the Irano-toranian zone 400-2000m high. Using morphological, ecological, behavioural, reproduction and hybridization criteria this study discove

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Molecular Structure
Synthesis, spectral studies, DFT, biological evaluation, molecular docking and dyeing performance of 1-(4-((2-amino-5-methoxy)diazenyl)phenyl) ethanone complexes with some metallic ions
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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
THE STUDY ON ABILITY OF ESCHERICHIA COLI ISOLATED FROM DIFFERENT CLINICAL CASES TO BIOFILM FORMATION AND DETECTION OF CSGD GENE RESPONSIBLE FOR PRODUCE CURLI (FIMBRIAE)
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A total of 165 clinical sample included Urine, Swab wounds and Burns were collected from Baghdad Governorate. Results showed that rate all isolates of E. coli was 50(30.3%) and rate of urine infection was 46(92%) and rate of swab wounds infection 4(8%). Where was diagnostic based on streaked on MacConkey agar, then single colony was transferred to Eosin Methylene Blue (EMB). Identification some of the biochemical test included: Catalase test, Oxidase test, Indole test, Methyl red, Vogues - Proskauer test and Citrate Utilization test. Then confirmed by the Vitek - 2 Compact System. The ability of E.coli isolate to biofilm formation to be studied it is considered one of the most important factors of virulence and has role in causing injury an

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Publication Date
Sat Dec 31 2016
Journal Name
Al-kindy College Medical Journal
A Comparison of Sagittal Sections of Short T1inversion Recovery and T2 Weighted Fast Spin Echo Magnetic Resonance Sequences for Detection of Multiple Sclerosis Spinal Cord Lesions
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Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement,

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Assessment the Effect of Lactobacillus Acidophilus on Escherichia Coli Serotype O157:H7 with Detection of Some Virulence Factors
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Aim: To evaluation the effect of Lactobacillus acidophilus on Enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7 with detection of some virulence factors. Methods: Two hundred and fifty specimens (stool) from children under five years for both sexes were collected from some hospitals. All isolates were diagnosed according to morphological characteristics, biochemical tests. Monoplex pattern of PCR was used also for detection different genes in (7) Escherichia coli )O157:H7 (isolates; include 16SrRNA, eae, lifA, Stx1,Stx2 that encoded for ribosomal RNA, intimin, lymphocyte inhibitory factor, shiga toxins. Three types of probiotics strains were obtained, Lactobacillus fermentum, Lactobacillus plantarum and Lactobacillus acidophilus (A

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Publication Date
Thu Sep 01 2016
Journal Name
Physica Medica
Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm

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Publication Date
Thu Sep 26 2024
Journal Name
Journal Of Optics
Cysteine-cupped CdSe/CdS quantum dots as an opticalbiosensor for early skin cancer detection
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This study represents an optical biosensor for early skin cancer detection using cysteine-cupped CdSe/CdS Quantum Dots (QDs). The study optimizes QD synthesis, surface, optical functionalization, and bioconjugation to enhance specificity and sensitivity for early skin cancer cell detection. The research provides insights into QD interactions with skin cancer biomarkers, demonstrating high-contrast, precise cellular imaging. Cysteine-capped CdSe/CdS absorption spectra reveal characteristic peaks for undamaged DNA, while spectral shifts indicate structural changes in skin-cancer-damaged DNA. Additionally, fluorescence spectra show sharp peaks for undamaged DNA and notable shifts and intensity variations when interacting with skin cancer. This

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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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