Pollen morphology characterization is an important field in taxonomy. This study aims to identify and characterize the pollen morphology for fourteen species from subfamily Caesalpiniodeae (Fabaceae). The results showed the similarity of all species pollen in terms of being monad and tri,zono-colporate type, and each Ceratonia siliqua and Senna occidentalis distinguished by having tetra,zono-colporate pollen as well, and the results revealed the prevalence of reticulate configuration in most studies species, while Ceratonia siliqua characterized by striates configuration, Cassia fistula distinguished by verrrucate-gemmate wall, and Senna species by verrrucate- perforate, as for the shape, showed a discrepancy in the general shape fr

Piracy on phonograms is now, rightly, the crime of the electronic age. Despite the protection sought by States to provide for such registrations, whether at the level of national legislation or international agreements and conventions, but piracy has been and continues to pose a significant threat to the rights of the producers of those recordings, especially as it is a profitable way for hackers to get a lot of money in a way Illegal, which is contrary to the rules of legitimate competition. Hence, this research highlights the legal protection of producers of phonograms in light of the Iraqi Copyright Protection Act No. (3) of 1971, as amended.

In this study, 158 clinical samples were collected from hospitalized burn patients during the period from December 2012 to June 2013 in Karbala province\ Iraq. Bacterial isolates were identified using conventional biochemical tests and then identification was confirmed by using Vitek-2 compact system. Pseudomonas aeruginosa recovery was 60 isolates in this study. These isolates were analyzed for antibiotic susceptibility by the disk diffusion test (DDT) according to Kirby Bauer's method using seven clinically important antipseudomonal agents: carbapenems (Imipenem and Meropenem), pencillins (Piperacillin), cephalosporins (Ceftazidim), monobactam (Aztreonam), quinolones (Ciprofloxacin) and aminoglycosides (Gentamicin). The results of resista

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

KE Sharquie, AA Noaimi, MA Al-Shukri, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3