The plant Conyza canadensis, which belongs to Asteraceae (Compositae) family and known as Canadian horseweed. It was used as traditional medicine in China, Pakistan, India, and Africa for the treatment of various diseases causing by bacteria, fungi, or viruses. The plant has antimicrobial, antioxidant, anticoagulant, anti-inflammatory, and anticancer pharmacological activity. This study provides the first phytochemical investigation of the plant in Iraq and is concerned with extraction, fractionation, isolation, and purification of some of the important phytochemicals detected in the plant-like phenolic acids, flavonoids, and alkaloids. Also, the literature survey has revealed that the plant has a substantial antimicrobial activity, so it was deemed desirable to make a study for the antimicrobial activity of the plant. The whole plant was collected from Baghdad city / College of Pharmacy/ University of Baghdad farm during July (2020). The aerial parts and roots were washed thoroughly, dried in shade, chopped, pulverized into a coarse powder, and then weighed. The shade-dried crushed plant materials were first defatted by maceration in hexane for 24 h. Then extracted by two extraction methods (hot method using soxhlet apparatus and cold method by maceration in solvent), using 85% aqueous ethanol as solvent extraction, and fractionated by petroleum ether, chloroform, ethyl acetate, and n-butanol. The phytochemical screening of the ethanolic extract from both extraction methods revealed alkaloids, saponin glycosides, coumarins, flavonoids, steroids, phenolic compounds, proteins, anthraquinones, terpenoids, and cardiac glycosides. However, depending on the percentage yields, the hot method yield was better than the cold method, so the extraction method by soxhlet was preferred upon maceration as it gives a higher percentage yield. The petroleum ether, chloroform, and ethyl acetate fractions were analyzed by thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC) for their steroids, alkaloids, and polyphenolic (phenolic acids and flavonoids) contents, respectively. The different chromatographic results revealed the presence of stigmasterol and β- sitosterol in petroleum ether fraction, harmine alkaloid in chloroform fraction, quercetin, quercitrin, apigenin, p-coumaric acid, and caffeic acid in ethyl acetate fraction of the Iraqi C. canadensis plant. Three polyphenolics compounds (p-coumaric acid, caffeic acid, apigenin) were isolated from ethyl acetate fraction by preparative thin-layer chromatography plates (PLC), and Harmine alkaloid was isolated from chloroform fraction by high-performance liquid chromatography (HPLC) using a fraction collector. The isolated compounds were subjected to various chromatographic and spectral analytical techniques for their identification, such as TLC, FTIR, HPLC, and high-performance thin-layer chromatography (HPTLC). Petroleum ether fraction was analyzed for the detection of coumarins by TLC. One compound was isolated, purified by PLC, symbolized as MS compound, and identified by FTIR and 1H -NMR since there is no standard available for this compound. The isolated MS compound could be pyranocoumarin glycoside. To investigate the essential oil composition of Iraqi C. canadensis, hydrodistillation of fresh aerial part of the plant was done using Clevenger-type apparatus for 3hr. The essential oils components and the hexane fraction obtained by maceration of the plant material in hexane solvent were identified using GC/MS analysis. The results of GC/MS analysis of the essential oil were abundant by hydrocarbon compounds, particularly by sesquiterpene hydrocarbon. This study also involves a preliminary determination of the antimicrobial activity of ethyl acetate fraction of the plant against two Gram-positive bacteria (Staphylococcus aureus and Staphylococcus epidermidis), two Gram-negative bacteria (Escherichia coli and Klebsiella sp.) and one fungi species (Candida albicans) by measuring the inhibition zone diameter around the hole in mm, compared with streptomycin and fluconazole standard drugs for antibacterial and antifungal activity, respectively. The antimicrobial results showed significant antibacterial activity against S.aureus (gram-positive bacteria) and important antifungal activity against Candida albicans. In contrast, no antibacterial activity was demonstrated against the tested gram-negative bacteria. Furthermore, the antibacterial activity exerted against S. epidermidis (gram-positive bacteria) was affected by dilution dimethyl sulfoxide (DMSO).
In this paper, the problem of resource allocation at Al-Raji Company for soft drinks and juices was studied. The company produces several types of tasks to produce juices and soft drinks, which need machines to accomplish these tasks, as it has 6 machines that want to allocate to 4 different tasks to accomplish these tasks. The machines assigned to each task are subject to failure, as these machines are repaired to participate again in the production process. From past records of the company, the probability of failure machines at each task was calculated depending on company data information. Also, the time required for each machine to complete each task was recorded. The aim of this paper is to determine the minimum expected ti
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Pseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data
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Species of genus Chrotogonus (surface grasshoppers) are phytophagous and damaging to various economical important plants in their seedling stages. In order to know the biodiversity of surface grasshoppers, the detailed study has been conducted from four provinces of Pakistan. During this study, biodiversity, taxonomy, diagnosis, morphometric analysis, habitat, global distribution, and remarks of each species have been described. Total of 826 specimens were collected and sorted out into three species and three subspecies: C. (Chrotogonus) homalodemus homalodemus (Blanchard, 1836), C. (Chrotogonus) homalodemus (Blanchard, 1836), C. (Chrotogonus) trachypter
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A new adsorbent was developed by integrating algae biomass (AG) into a chitosan (CN) matrix, followed by structural enhancement via crosslinking with pyromellitic dianhydride (PMDA) through a hydrothermal synthesis approach. This process resulted in the formation of a robust AG@CN-PMDA composite with improved physicochemical characteristics suitable for advanced adsorption applications. The AG@CN-PMDA composite was evaluated for its efficiency in removal of the cationic dye methyl violet 2B (MV 2B) from aqueous solution. The adsorption process was refined through the Box-Behnken design (RSM-BBD), evaluating three essential parameters: adsorbent dosage (A: 0.02–0.1 g/100 mL), pH (B: 4–10), and time (C: 5–20 min). The ideal conditions f
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
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تعد صناعة السمنت في العراق من اقدم الصناعات الحديثة واكثرها تطورا وتقدما ومن اقواها تاثيرا في الاقتصاد القومي. واذ توفر في صناعة السمنت العراقي كافة المستلزمات الناجحة من حيث توفر المواد الاولية والخبرات الفنية والتقنية واسواق ثابتة وراسخة محليا وعالميا فقد كان من المفروض ان يتم التوسع في هذه الصناعة، وان التخطيط لهذه الصناعة امرا ضروريا خاصة وان مادة السمنت هي احدى اهم المواد الرئيسة التي يؤثر توفره
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio
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