This study concerned with phytochemical investigation and methods of extraction and separation of active constituents from Valeriana officinalis plant cultivated in Iraq. Due to the large number of active constituents in Valeriana officinalis, it was necessary to make analytical study of its constituents to determine the chemical nature of these constituents and then determine the main classes (terpenes and iridoids) using chemical reagents specific for each class. Different organic solvents like ethanol (70%) used in soxhlet apparatus and hexane, ethyl acetate and methanol were used separately to extract the main active constituents by maceration. Through comparison between these solvents using thin layer chromatograph

Within this paper, we developed a new series of organic chromophores based on triphenyleamine (TPA) (AL1, AL-2, AL-11 and AL-22) by engineering the structure of the electron donor (D) unit via replacing a phenyle ring or inserting thiophene as a π-linkage. For the sake of scrutinizing the impact of the TPA donating ability and the spacer upon the photovoltaic, absorptional, energetic, and geometrical characteristic of these sensitizers, density functional theory (DFT) and time-dependent DFT (TD-DFT) have been utilized. According to structural characteristics, incorporating the acceptor, π-bridge and TPA does not result in a perfect coplanar conformation in AL-22. We computed EHOMO, ELUMO and bandgap (Eg) energies by performing frequency a

Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the optimal

The majority of Iraqi translator-student have problems at two main levels: the conceptual level and the productive level. From different perspectives, such problems are either related to ‘language’ or to ‘cognition’. This binary view is an indication to the implicit and interchangeable relationship between language and cognition. The relationship between cognition language and translator starts with the first language and its effect on the Iraqi translators. Identifying the effect is the aim of the present study. It is hypothesized that Iraqi students are negatively influenced by the problems and weaknesses of first language schema. This reflects the major claim and later concludes that first language instruction in the Iraq

The anatomic characteristics of the leaves of 22 taxa of Stachys L. representing seven of the currently recognized sections distributed in northern Iraq, were examined. The study did not found any variations in the characteristics of the stomata system of the leaves.Therewere variations with a good taxonomic value in other anatomic characteristics.Thevariations in characters of the mesophyll tissue in S.kurdica var.brevidens Bom ex Bhattacharjeewas bifacial but in S.kurdica var.kurdica Boiss. & Hohen.was unifacial .The study also found that the taxa S.benthamiana Bioss., S.lanigera (Bornm.) Rech.f. andS.kotscyi Bioss. with 3 vascular bundles in the middle vein while the taxa S.ballotiformis Vatke., S.megalodonta Hausskn. &Bo

The anatomic characteristics of the leaves of 22 taxa of Stachys L. representing seven of the currently recognized sections distributed in northern Iraq, were examined. The study did not found any variations in the characteristics of the stomata system of the leaves.Therewere variations with a good taxonomic value in other anatomic characteristics.Thevariations in characters of the mesophyll tissue in S.kurdica var.brevidens Bom ex Bhattacharjeewas bifacial but in S.kurdica var.kurdica Boiss. & Hohen.was unifacial .The study also found that the taxa S.benthamiana Bioss., S.lanigera (Bornm.) Rech.f. andS.kotscyi Bioss. with 3 vascular bundles in the middle vein while the taxa S.ballotiformis Vatke., S.megalodonta Hausskn. &Bornm.exP.H.Davis

Direct agglutination test was used to evaluate the immunogenicity of three different antigens inoculated in hamsters as one , two and three doses which were: Group (1) inoculated with autoclaved killed Leishmania tropica , Group (2) inoculated with BCG vaccine alone while Group (3) inoculated with mixed antigens (autoclaved killed Leishmania "AKL"+ BCG).(4) Control animals inoculated with phosphate buffer saline. The maximum level of antibody titers were evaluated in animal inoculated with one , two or three dose of mixed antigens (320 , 640 and 1280) respectively when it compared with animals inoculated with corresponding doses of AKL antigen (80 , 160 and 320) respectively. While the minimum level of antibody titers were observed in ani

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a