Artificial intelligence–based models for the qualitative and quantitative prediction of a phytochemical compound using HPLC method

Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile , Annona squamosal , Camellia sinensis (tea), and coriander ( Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, three different nonlinear models including artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM),in addition to a classical linear model [multilinear regression analysis (MLR)], were used for the prediction of the retention time (tR) and peak area (PA) for isoquercitrin using HPLC. The simulation uses concentration of the standard, composition of the mobile phases (MP-A and MP-B), and pH as the corresponding input variables. The performance efficiency of the models was evaluated using relative mean square error (RMSE), mean square error (MSE), determination coefficient (DC), and correlation coefficient (CC). The obtained results demonstrated that all four models are capable of predicting the qualitative and quantitative properties of the bioactive compound. A predictive comparison of the models showed that M3 had the highest prediction accuracy among the three models. Further evaluation of the results showed that ANFIS–M3 outperformed the other models and serves as the best model for the prediction of PA. On the other hand, ANN–M3proved its merit and emerged as the best model for tR simulation. The overall predictive accuracy of the best models showed them to be reliable tools for both qualitative and quantitative determination.     

The efficacy of tilted axial MRI of the CNS

The angle between the straight axial plane and the orbito-meatal line was measured in 156 consecutive magnetic resonance examinations. Inconsistent head positioning caused this angle to vary by as much as 44 degrees. Careful positioning of the patient by the technologist can minimize this variability, leading potentially to improved image interpretation. To assess the merit of a standardized orientation for MR examinations of the head, straight axial and tilted axial MR scans were compared in 34 patients. The tilted images were obtained parallel to the orbito-meatal line and were found to be superior for visualization of the cerebellum. When correlative x-ray CTs are available or when an abnormality in the posterior fossa is suspected, tilted axial MR scans should be employed.     

Gram-scale synthesis of (+)-discodermolide

[formula: see text] A triply convergent, highly efficient second-generation synthesis of the potent antimitotic agent (+)-discodermolide (1) has been achieved on a 1-g scale.     

Kinetics of the reaction Cl + CH4 → CH3+ HCl from 200° to 500deg;K

The rate constant for the reaction \documentclass{article}\pagestyle{empty}\begin{document}${\rm Cl} + {\rm CH}_4 \mathop {\longrightarrow}\limits^1 {\rm CH}_3 + {\rm HCl}$\end{document} has been determined over the temperature range of 200°–500°K using a discharge flow system with resonance fluorescence detection of atomic chlorine under conditions of large excess CH₄. For 300° > T > 200°K the data are best fitted to the expression k₁ = (8.2 ± 0.6) × 10^?12 exp[?(1320 ± 20)/T] cm³/sec. Curvature is observed in the Arrhenius plot such that the effective activation energy increases from 2.6 kcal/mol at 200° < T < 300°K to 3.5 kcal/mol at 360° < T < 500°K. The data over the entire range may be fitted by the expression k₁ = 8.6×10^?18 T^2.11 exp[?795/T]. These results are compared with other experimental studies and with a semiempirical transition state calculation. Their atmospheric significance is discussed.     

Sobolev spaces and symbolic calculus

We use elementary theory of distributions and geometry of Euclidean spaces to obtain a theorem on the symbolic calculus of several variables in spaces of Fourier series with weights.     

Lipschitz spaces and Suslin sets

Every bounded Suslin set in the plane is the set of eigenvalues of some bounded operator in a separable B-space.     

Ray helicity: geometric invariant for multidimensional resonant wave conversion

For a multicomponent wave field propagating into a multidimensional conversion region, the rays are shown to be helical, in general. For a ray-based quantity to have a fundamental physical meaning, it must be invariant under the following two groups of transformations, which are used to construct solutions: congruence transformations (which involve linear combinations of components of the multicomponent wave field) and canonical transformations (which act on the ray phase space). It is shown that for conversion between two waves there is a new invariant not previously discussed: the intrinsic helicity of the ray.     

Noise-induced escape on time scales preceding quasistationarity: New developments in the Kramers problem

Noise-induced escape from the metastable part of a potential is considered on time scales preceding the formation of quasiequilibrium within that part of the potential. It is shown that, counterintuitively, the escape flux may then depend exponentially strongly, and in a complicated manner, on time and friction. (c) 2001 American Institute of Physics.     

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