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.
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
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In this research Bi2S3 thin films have been prepared on glass substrates using chemical spray pyrolysis method at substrate temperature (300oC) and molarity (0.015) mol. Structural and optical properties of the thin films above have been studied; XRD analysis demonstrated that the Bi2S3 films are polycrystalline with (031) orientation and with Orthorhombic structure. The optical properties were studied using the spectral of the absorbance and transmission of films in wavelength ranging (300-1100) nm. The study showed that the films have high transmission within the range of the visible spectrum. Also absorption coefficient, extinction coefficient and the optical energy gap (Eg) was calculated, found that the film have direct ener
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The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO2) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO2. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO2/
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This research explores the obstacles teachers encounter in executing the smart schools initiative within the framework of Iraq, where educational facilities and digital preparedness are still at an early stage. Although worldwide trends reveal the growing use of smart technologies in education, Iraq has been hindered by systemic barriers, such as archaic curricula, restricted access to technologies, and an unqualified teaching staff. Data were collected using a validated questionnaire on 122 public school teachers working in Baghdad with a descriptive-analytical methodology. The study divided challenges into five areas: infrastructure, teacher preparedness, administrative support, curricular adaptation and cultural resistanc
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The aim of this study is to explain methods to be followed for the recovery Alsnav Hor, who represents the northwest portion of the Hammar Marsh in the province of Dhi Qar, after the drought in which that happened in 2008. The study included description of the region before the drought, the description of its natural and human environments, the economic events and activities, then the study included drought throughout the region, the environmental impacts caused by drought, its impact on social reality, economic and healthy for its environment, and then reached to the problems of social and economic in the region, depending on the Field studies and documented in the specialized government departments, information analysis for the
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Abstract: Colloidal gold nanoparticles (ringworm Palm or in the form of paper willow) have been prepared from HAuCl4 containing aqueous solution by hot chemical reduction method. The colloidal gold nanoparticles were characterized by SEM, EDX, and UV-VIS absorption spectroscopy. It was found that the variation of reduction time from boiling point affects the size of the nanoparticles and also in chemical reduction approach the size of nanoparticles can be controlled by varying the amount of variation the volume of reductant material with respect to the volume of HAuCL4.
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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