Introduction: A Pap test can detect pre-cancerous and cancerous cells in the vagina and uterine cervix. Cervical cancer is the easiest gynecologic cancer to be prevented and diagnosed using regular screening tests and follow-up. This study aimed to estimate the cytological changes and the precancerous lesions using Pap smear test and visual inspection of the cervices of Iraqi women, and also to determine the possible relationship of this cancer with patients’ demographic characteristics. Methods: The study included 140 women aged (18-67) years old referred to the National Cancer Research Center (NCRC), Baghdad, Iraq, during the period 2011-2016. Both visual inspections of the uterine cervix and Papanicolaou smear screening were performed for all of the participants. Results: Only 14% of the women under study were in postmenopausal, and 86% were in premenopausal period. Visual inspection of the cervix showed that 48.6% of the women had erosion lesions. Upon cytology examination, 92.8% of the women showed non-specific inflammation, 70% revealed reactive squamous metaplasia, 27% had Koilocytotic atypia, and 17% suffered from cervical intraepithelial neoplasia (CIN1) or low grade squamous intraepithelial lesion (LGSIL). Contraception was used by 68% of those women, while 34.3% of them used pills. Most women, 79%, had multiple births. The abnormal vaginal discharge occurred in 34% of the participants that is why they attended the center compared with only 25.7% who came for routine checking. Finally, 67% of the participated women did not make this test previously. Conclusion: We conclude routine screening and Pap smear testing for uterine cervix and vagina might be useful especially for sexually active women for preventing the occurrence of precancerous and later cancerous lesions in these organs.
Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
... Show MoreWith the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
... Show MoreMeta stable phase of SnO as stoichiometric compound is deposited utilizing thermal evaporation technique under high vacuum onto glass and p-type silicon. These films are subjected to thermal treatment under oxygen for different temperatures (150,350 and 550 °C ). The Sn metal transformed to SnO at 350 oC, which was clearly seen via XRD measurements, SnO was transformed to a nonstoichiometric phase at 550 oC. AFM was used to obtain topography of the deposited films. The grains are combined compactly to form ridges and clusters along the surface of the SnO and Sn3O3 films. Films were transparent in the visible area and the values of the optical band gap for (150,350 and 550 °C ) 3.1,
A new method is characterized by simplicity, accuracy and speed for determination of Oxonuim ion in ionisable inorganic acid such as hydrochloric (0.1 - 10) ,Sulphuric ( 0.1 - 6 ),nitric ( 0.1 - 10 ), perchloric ( 0.1 - 7 ), acetic (0.1 - 100 ) and phosphoric ( 0.1 - 30 ) ( mMol.L-1 )acids. By continuous flow injection analysis. The proposed method was based on generation of bromine from the Bro-3-Br-- H3O+. Bromine reacts with fluorescein to quenches the fluorescence . A sample volume no.1 (31μl) and no.2 (35μl) were used with flow rate of 0.95 mL.min-1 using H2O line no.1as carrier stream and 1.3 mL.min-1 using fluorescein sodium salt line no.2. Linear regression of the concentration ( mMol.L-1 ) Vs quenched fluorescence gives a correla
... Show MoreDrastic threat to the natural system is caused by the uncontrolled release of synthetic pollutants, including azo dyes. This study centered on the decolorization and biodegradation of water soluble azo dye reactive blue (RB) in a batch mode sequential anaerobic-aerobic processes. A local sewage treatment plant was the source where activated sludge was collected to be used as non-adapted mixed culture with both free and the alginate immobilized cells for RB biodegradation. Under anaerobic conditions, the free and immobilized mixed cells were proved to completely decolorize 10 mg/ L of RB within 20 and 30 h, respectively. Alginate- immobilized mixed cells, resulted in 88%, 87%, and 87% maximum COD removals with samples con
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