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Basal cell markers:34BE12 and p63, improving detection of basal cells in atypical prostatic lesions
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Background: The diagnosis of prostatic pathology may be of challenging , as some  difficult and suspected, atypical  cases may lack basal cell layer by routine H&E sections . Antibodies against 34BE12(HMW-CK) and p63 aid the diagnosis of such cases , to distinguish benign from  malignant prostatic lesions.

Objective: to identify basal cells in atypical prostatic lesions ,and distinguish benign from malignant prostatic lesions.

Type of the study:  A retro-spective  study.

Methods:  115cases of  paraffin embedded prostatic tissue blocks ,diagnosed as : 76 cases were benign prostatic hyperplasia( BPH) , 9 cases were  high grade –prostatic intraepithelial neoplasia (HG-PIN) , and 30 cases were prostatic carcinoma(PCa) .Sections from each blocks were prepared for immunostaining with 34BE12 and p63.

Results : basal cells were detected in cases of BPH , and HG-PIN , and absent  in all cases of prostatic carcinoma ,using basal cell markers . Negative benign glands(>2) were found in 71.6% and 38.2%  for   BPH  and 57.1% and 55.6% for HG-PIN immunostained  with high molecular weight cytokeratin (34BE12) and p63 , respectively, and significantly reduced to 9.0% and 11.1% for BPH and HG-PIN, respectively  with combined using of both markers .Conclusion : Combination of both   basal cell markers (34BE12 , p63) improving basal cell detection in atypical ,suspected prostatic lesions and distinguish benign from malignant lesions.

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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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

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Mon Jun 23 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Early detection of periodontitis among young adult cigarette smokers and non-smokers using cone beam computed tomography
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Background: Periodontitis is an inflammatory disease that affects the supporting tissues of the teeth; Smoking is an important risk factor for periodontitis induces alveolar bone loss and cause an imbalance between bone resorption and bone deposition. The purpose of this study is to detect and compare the presence of incipient periodontitis among young smokers and non-smokers by measuring the distance between cement-enamel junction and alveolar crest (CEJ-Ac) using Cone Beam Computed Tomography (CBCT). Material and methods: The total sample composed of fifty two participants, thirty one smokers and twenty one non-smokers (age range 14-22 years). Periodontal parameters: plaque index (PLI), gingival index (GI) were recorded for all teeth exc

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Publication Date
Mon Apr 29 2024
Journal Name
Journal Of The College Of Basic Education
Detection Of Biofilm Formation By Beta- Lactam Resistance Klebsiella Pneumoniae Isolated From Clinical Specimens And Aquatic Samples
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Publication Date
Wed Feb 15 2023
Journal Name
Full Text Book Of Minar Congress 7
EVALUATING THE CHANGE DETECTION OF(NDVI) FOR BABYLON CITY USING REMOTE SENSING AND GIS TECHNIQUES (2015-2020)
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The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Change detection of the land cover for three decades using remote sensing data and geographic information system
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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Isolation and Identification of Salmosamonella typhi from clinical samples with molecular detection of O-antigen encoded genes
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Abstract

Antibiotic treatment of  S.typhi is difficult as compared to treatment of acute infection. Antibiotic resistance carried against S.typhi  by using 6 kinds of antibiotics from  different classes, their results  showed that all isolates were  high resistance to Ampicillin (99%), Gentamicin (98%), Amikacin (79%) and   less  resistances  Trimethoprim (55%) ,  Imipenem (60%)  and Ceftriaxone(66%)  .

The present study focused on the molecular detection of Wzx flippase, Wzy polymerase genes in some Salmonella typhi isolates, Samples were collected from typhoid patients by classical lab work. Antibiotics susceptibilit

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Publication Date
Sun May 18 2025
Journal Name
Discover Food
Analysis of the effectiveness of natural treatments for preserving apricots and the YOLOv7 application for early damage detection
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Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa

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