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Serum Biomarkers are Promising Tools to Predict Traumatic Brain Injury Outcome
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Traumatic Brain Injury (TBI) is still considered a worldwide leading cause of mortality and morbidity. Within the last decades, different modalities were used to assess severity and outcome including Glasgow Coma Scale (GCS), imaging modalities, and even genetic polymorphism, however, determining the prognosis of TBI victims is still challenging requiring the emerging of more accurate and more applicable tools to surrogate other old modalities

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Detecting the effectiveness of two tools for detecting the talented from their teachers' points of view
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Education specialists have differed about determining the best ways to detect the
talented. Since the appearance of the mental and psychological measurement movement, some
scholars adopted intelligence ratios as a criterion to identify the talented and others went to
rely on the degree of academic achievement. Each of these two methods has its own flaws and
mistakes and a large number of talented children were victims of these two methods.
Therefore the need to use other scales for the purpose of detection of talented children
appeared because they provide valuable information which may not be obtained easily
through objective tests and these scales are derived from consecutive studies of gifted andtalented children

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Utilizing Artificial Intelligence Tools in Enhancing Training of Trainers (ToT) Programs: Modern Approaches and Practical Applications
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This study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, fo

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Publication Date
Sun Jun 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
PETROLOGY AND PROVENANCE OF THE NATURAL STONE TOOLS FROM Al-DALMAJ ARCHAEOLOGICAL SITE, MESOPOTAMIAN PLAIN, IRAQ
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Many stone tools were found on a hill south of the Hor Al-Dalmaj which is located in the central part of the alluvial plain of Mesopotamia, between the Tigris and Euphrates Rivers. The types of rocks from which the studied stone tools were made are not found in the alluvial plain, because it consists of friable sand, silt, and clay. All existing sediments were precipitated in riverine environments such as point bar, over bank, and floodplain sediments. The collected stone tools were described with a magnifying glass (10 x) and a polarized microscope after they were thin sectioned. Microscopic analysis showed that these stone tools are made of sedimentary, volcanic igneous and metamorphic rocks, such as: sandstones, limestones, chert, con

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Utilizing Artificial Intelligence Tools in Enhancing Training of Trainers (ToT) Programs: Modern Approaches and Practical Applications
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Publication Date
Fri May 12 2023
Journal Name
Journal Of Population Therapeutics And Clinical Pharmacology
Effect of Maternal Variables on some Physiological and Immunological Biomarkers in Iraqi Women Undergoing Caesarean Section
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Pregnancy and childbirth are physiological states characterized by sudden hormonal and immunologically described changes. The current study aimed to investigate the influence of maternal variables (age, previous abortion, placental position, and fetal position) on some physiological biomarkers, such as oxytocin (OT), prolactin (PRL), cortisol, and insulin growth factor 2 (IGF -2) and some immune biomarkers such as programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1) and interleukin 6 (IL-6) in Iraqi women undergoing caesarean section (CS). Blood samples were collected from 48 pregnant women in the age range (16-43 years) and serum was obtained to determine the levels of the above biomarkers. The effect of

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Publication Date
Mon Jun 26 2023
Journal Name
Journal Of Contemporary Medical Sciences
Molecular detection of mononucleotide biomarkers of microsatellite instability in sporadic colorectal carcinoma patients with clinicopathological correlation
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Objectives: To identify the frequency and types of microsatellite instability among a group of sporadic CRC patients and to correlate the findings with clinicopathological characteristics. Methods: During an 8-month period, all patients with sporadic CRC who attended to two teaching hospitals in Baghdad, Iraq were recruited to this cross-sectional study regardless of age, sex, ethnicity, or tumor characteristics. Demographic, clinical, and histopathological features were recorded. DNA was extracted from FFPE-blocks of the resected tumors and normal tissues. PCR amplification of five microsatellite mononucleotide repeat loci (BAT25, BAT26, NR-21, NR-24, and MONO-27) and 2 pentanucleotide repeat control markers (Penta C and Pent

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Publication Date
Mon Jul 21 2025
Journal Name
Biochemistry (moscow), Supplement Series B: Biomedical Chemistry
Evaluation of Ornithine Decarboxylase and Ferric Reducing Capacity Levels as Potential Biomarkers for Polycystic Ovary Syndrome
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Abstract—Background: Polycystic ovary syndrome (PCOS) is a prevalent hormonal disorder affecting reproductive- age women, often linked to metabolic issues like insulin resistance. Objective: this study aimed to evaluate ornithine decarboxylase (ODC) and ferric reducing capacity (FRC) levels in women with PCOS, with assess the effects of metformin and Primolut N treatment on their levels. Subjects and Methods: A case− control study was conducted with 150 married Iraqi women, categorized into three groups: 50 healthy controls, 50 untreated PCOS, 50 treated PCOS. Blood samples were analyzed for ODC, FRC levels and hormonal profiles. Statistical analysis applied independent t-test, Pearson’s correlation, ROC curve. Results: The ODC level

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Impact of Black Marketing on Purchasing Decisions: An Exploratory Study Using AI-Driven Analytical Tools
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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Rainwater Drainage Service Improvement Using a Number Of Quality Tools at the Directorate of Karbala Sewage
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The basic objective of the research is to study the quality of the water flow service in the Directorate of Karbala sewage and how to improve it after identifying the deviations of the processes and the final product and then providing the possible solutions in addressing the causes of the deviations and the associated quality gaps. A number of quality tools were used and applied to all data Stations with areas and activities related to the drainage of rainwater, as the research community determines the stations of lifting rainwater in the Directorate of the streams of Karbala holy, and the station was chosen Western station to apply the non-random sampling method intended after meeting a number of. It is one of the largest and m

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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