This study was aimed to conduct one of the vertical garden systems , selecting suitable plant species that with stand the climate conditions of Baghdad city in outer space to determine the appropriate growing medium for the (LWS), and to assess the impact of spraying with potassium silicate on the resistance of the cultivated plants to heat stresses . The study carried out at at Al-Batool Park of (Al-Kadhimiya Holy City). Two experiments were carried out, each one with a different plant species, including Wedelia trilobata and Tradescantia pallida, during the winter season of 2021 and summer season of 2022. The experiments were designed using a split block design. The experiments included two factors, the first being the growing med

This study included the estimation of growth rate, viability and morphological changes in different culture media (NNN, P-Y, RPMI- 1640, and Panmed). Promastigotes cultured in RPMI-1640 showed maximal growth rate after (2, 4, 6) days of cultivation (27.26 ± 0.05), (172.20 ± 0.1) and (343.81 ± 1.48) million parasites / ml for each day respectively, while P-Y media gave the highest mean of growth rat after (8 and 10) days of cultivation (307.16 ± 1.67) and (303.5 ± 4.96) million parasites / ml for each day respectively. P-Y medium showed the maximal percentage of viability after (2, 4, 6, 8, and 10) days of cultivation (99.76 ± 0.5) %, (98.30 ± 0.17) %, (96.1 ± 0.1) %, (92.5 ± 0.52) % and (87.26 ± 0.05) % for each day respectively.

Background: This study was designed to investigate the relationship between the ramus notch depth and some of the craniofacial measurements in Iraqi adults with skeletal Cl I, Cl II and Cl III; and to find out if there were any differences in the ramus notch between the skeletal classes.Materials and method: The sample consisted of 174 pretreatment digital lateral cephalometric radiographs of Iraqis aged between 18-25 years old (85 females and 89 males). Seven linear and six angular measurements were analyzed using AutoCAD (2007) software computer program. Descriptive statistics and gender differences were done for the measurements. ANOVA test compared the ramus notch depth between the skeletal classes, while Pearson correlation coefficient

Aim: The study aimed to investigate the presence of the specific B1 gene T gondii in blood and milk samples from natural infected cattle and pregnant women (16-30 weeks) whose examination performed by the officers at the women's and children's Educational hospital in Al-Diwaniyah, Iraq. Materials and methods: A total of 150 serum samplings were collected analysed and scanned for Anti-T gondi antibodies (75 naturally-infected goats and 75 pregnant women with Toxoplasma). Polymerase chain reaction (PCR) was used to detect of B1(399pb) gene in 26 goat's blood samples and 7 samples from pregnant women. Results: A quick-test anti-cassette gondii results showed 26 positive samples of goats in a percentage of 34,666 percent, while a higher percent

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,

Abstract Background: This study is aimed to assess the maxillary incisors’ root position, angulation, and buccal alveolar bone thickness in both genders and different classes of malocclusion using cone‑beam computed tomography (CBCT). Materials and Methods: Two hundred and six CBCT images were gathered and analyzed by three‑dimensional On‑Demand software to measure the variables of 803 maxillary central and lateral incisors. Genders and class difference was determined by unpaired t‑test, one‑way ANOVA, and Chi‑square tests. Results: Buccal root position of the maxillary incisors accounted for in the majority of the cases followed by the middle and palatal positions. The thickness of alveolar bone appears to have nearly the sam

Background: Legionella pneumophila (L. pneumophila) is gram-negative bacterium, which causes Legionnaires’ disease as well as Pontiac fever. Objective: To determine the frequency of Legionella pneumophila in pneumonic patients, to determine the clinical utility of diagnosing Legionella pneumonia by urinary antigen testing (LPUAT) in terms of sensitivity and specificity, to compares the results obtained from patients by urinary antigen test with q Real Time PCR (RT PCR) using serum samples and to determine the frequency of serogroup 1 and other serogroups of L. pneumophila. Methods: A total of 100 pneumonic patients (community acquired pneumonia) were enrolled in this study during a period between October 2016 to April 2017; 92 sam

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad