This study was conducted to make an inventory of the monocot plants that were collected before and now which stored in the herbarium of Iraq Natural History Museum for identifying them. The herbarium contains avery large and varied number of plants from different parts in Iraq and for different and varied environments. The plants collected, arranged and identified using taxonomic keys specific to these families. Currently, the plant samples are in the herbarium of Iraq Natural History Museum to be an important scientific reference for all researchers inside and outside the country. With the identification of botanical scientists for each family, gender and year in which it was first diagnosed.

This study aimed to make an inventory of leguminous plants for the purpose of identifying the plants that were collected over long periods and stored in the herbarium of Iraq Natural History Museum. It was found that the herbarium contains a large and varied number of plants from different parts of Iraq and in different and varied environments. It was collected and arranged according to a specific system in the herbarium to remain an important source for all graduate students and researchers to take advantage of these plants. Also, the flowering and fruiting periods of these plants in Iraq were recorded for different regions. Most of these plants begin to flower in the spring and thrive in fields and farms.

The blade pitch angle (BPA) in wind turbine (WT) is controlled to maximize output power generation above the rated wind speed (WS). In this paper, four types of controllers are suggested and compared for BPA controller in WT: PID controller (PIDC), type-1 fuzzy logic controller (T1-FLC), type-2 fuzzy logic controller (T2-FLC), and hybrid fuzzy-PID controller (FPIDC). The Mamdani and Sugeno fuzzy inference systems (FIS) have been compared to find the best inference system used in FLC. Genetic algorithm (GA) and Particle swarm optimization algorithm (PSO) are used to find the optimal tuning of the PID parameter. The results of500-kw horizontal-axis wind turbine show that PIDC based on PSO can reduced 2.81% in summation error of power

Many studies of the relationship between COVID-19 and different factors have been conducted since the beginning of the corona pandemic. The relationship between COVID-19 and different biomarkers including ABO blood groups, D-dimer, Ferritin and CRP, was examined. Six hundred (600) patients, were included in this trial among them, 324 (56%) females and the rest 276 (46%) were males. The frequencies of blood types A, B, AB, and O were 25.33, 38.00, 31.33, and 5.33%, respectively, in the case group. Association analysis between the ABO blood group and D-dimer, Ferritin and CRP of COVID-19 patients indicated that there was a statistically significant difference for Ferritin (P≤0.01), but no-significant differences for both D-dimer and CRP.

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

Background & objective: Difficult intubation remains a risk for patients undergoing general anesthesia (GA) or mechanical ventilation in an intensive care unit (ICU). Macroglossia is a known factor for difficult intubation. But it is not routine to assess the tongue size to predict difficult intubation. Studies are found deficient in comparing usefulness of measuring thyromental distance and the tongue thickness (TT) measured by ultrasonography to estimate difficult intubation. We compared tongue thickness measured by ultrasonography and thyromental distance as a means to anticipate difficult intubation. Methodology: A convenient sample of 60 patients; 32 males and 28 females, who were undergoing elective surgery with GA were i

The chronic renal disease is a principle common medical dilemma in Iraq. Peripheral arterial disease (PAD) is a prevalent infirmity in the hemodialysis people. The aim of present study was to estimate the prevalence of PAD in subjects with end-stage renal disease (ESRD). This cross-sectional study was done between January 2016 and May 2017 on ESRD subjects regularly attending renal dialysis unit in Al-Kindy teaching hospital in Baghdad, Iraq. PAD was diagnosed on the base of the ankle-brachial index (ABI) measured by using a hand-held Doppler ultrasound. Subjects with ABI ≤0.9 were supposed positive for PAD. A total of 150 ESRD cases were analyzed. The mean age of the subject was 49.52±15 years. Majority of them were males 87(58%). Most

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener