The refractive indices, nD densities 𝜌, and viscosities  of binary mixtures of sulfolane + n -butanol + sec- butanol + iso- butanol + tert – butanol + n-propanol and iso- propanol were measured at 298.15K. Form experimental data, excess molar volum VE , excess molar refractivity ∆nD, excess molar viscosity  E and excess molar Gibbs free energy of activation of viscous flow G *E were calculated. From n-propanol – sulfolane and iso- propanol sulfolane mixtures showed negative ∆nD, n-butanol – sulfolane, sec-butanal – sulfolane, iso-butanol – sulfolane and tert- butanol sulfolane , nD was positive over the whole mole fraction rang , while VE ,  E and G *E show a negative deviation. The

Vanadium dioxide nanofilms are one of the most essential materials in electronic applications like smart windows. Therefore, studying and understanding the optical properties of such films is crucial to modify the parameters that control these properties. To this end, this work focuses on investigating the opacity as a function of the energy directed at the nanofilms with different thicknesses(1–100) nm. Effective mediator theories(EMTs), which are considered as the application of Bruggeman’s formalism and the Looyenga mixing rule, have been used to estimate the dielectric constant of VO2 nanofilms. The results show different opacity behaviors at different wavelength ranges(ultraviolet, visible, and infrared). The results depict that th

During the last few years, the greener additives prepared from bio-raw materials with low-cost and multifunctional applications have attracted considerable attention in the field of lubricant industry. In the present work, copolymers derived from sunflower and linseed oils with decyl methacrylate were synthesized by a thermal method using benzoyl peroxide (BPO) as a radical initiator. Direct polymerization of fatty acid double bonds in the presence of a free radical initiator results in the development of environmentally friendly copolymeric additives (Co-1 and Co-2). Fourier Transform Infrared (FTIR) and Proton Nuclear Magnetic Resonance (1H-NMR) were used to characterize the resulting copolymers. Thermal decomposition of copolymers was de

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

  Necessary and sufficient conditions for the operator equation I AXAX n  * , to have a real positive definite solution X are given. Based on these conditions, some properties of the operator A as well as relation between the solutions X andAare given.

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

Oilwell cementing operations are crucial for drilling and completion, preserving the well's productive life. However, weak and permeable formations pose a high risk of cement slurry loss, leading to failure. Lightweight cement, like foamed cement, is used to avoid these difficulties. This study is focused on creating a range of foamed slurry densities and examining the effect of gas concentration on their rheological properties. The foaming agent and foam stabilizer are tested, and the optimal concentration is determined to be 2% and 0.12%, respectively, by the weight of the cement.

Furthermore, the construction of samples of foam cement with different densities (0.8, 1.0, 1.2, 1.4, and 1.6) g/cc is performed to f