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

    The characterization and design of this study of new liquid crystals with a V shape compounds containing thiazolidine-2,4-dione and 1,3-phenylene as a core unite with mesophase properties were reported. Preparation  and characterization of chloroacetic acid, water, and thiourea to produce thiazolidine-2,4-dione [I] in the presence of strong hydrochloric acid. The 4-hydreoxybenzaldehyde and n-alkyl bromide were reacted with potassium hydroxide to create the n-alkoxy benzaldehyde., then the compound [I] reacted with [II]n in presence of piperidine to produce compounds [III]n. Also, converted resorcinol to a corresponding  compound [IV] by refl

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

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

At the beginning of the twentieth century distorting handling totalitarian phenomena of art, which can be called the stage of the test, transition from the theory of ideal theory and other realistic is not cushy, since it requires vision and reading and other concepts, and in light of this dialectic manifested research problem by asking the following Is affected by the design idealism and realism. Through the above mentioned questions, the researcher found rationale for addressing this problem, the study through his research, which is marked (idealism and realism in a comparative study design). And demonstrated the importance of research in the identification of the concept and the effectiveness of the two theories idealism and realism a

This study includes design and synthesis of new non-steroidal anti-inflammatory agents (NSAIDs) with expected cyclooxygenase-2 (COX-2) selective inhibition to achieve better activity and low gastric side effects. Two series of compounds have been designed and synthesized as potential NSAIDs,these  are:     Salicylamide derivatives (compounds 3,4,5 ) and Diflunisal derivatives (compounds 10&11). In vivo acute anti-inflammatory effect of one of the synthesized agents (compound 3)  was evaluated in the rat using egg-white induced paw edema model of inflammation. Preliminary pharmacological study revealed that compound 3 exhibited less anti-inflammatory effect  compared to that of aspirin after

Series of new complexes of the type [M2 (L)Cl4 ] are prepared from the new ligand[N1 ,N4 -bis(benzo[d]thiazol-2- yl)succinamide (L) derived from ethan-1,2-dicarbonyl chloride and 2-aminobenzothiozole,where, M= Ni(ii), Cu(ii) and Zn(ii) alsocomplexes of mix-ligands, the type [M(L)(8-HQ)]Cl, where, M = Ni(ii), Cu(ii) and Zn(ii),8-HQ= 8-Hydroxyquinoline. Chemical forms are obtained from their 1 H, 13CNMR, Mass spectra (for (L)), FT-IR and U.V spectrum, melting point, molar conduct.Using flame (AA), % M is determined in the complexes.The content of C, H, N and S in the (L) and its complexes was specified. Magnetic susceptibility and thermal analysis (TGA) of prepared compounds were measured.The propose geometry for all complexes[M2 (L)Cl4 ] wa