Russian Journal of General Chemistry - On the basis of 4-(thien-2-yl)-3-aminopyridine-2(1H)-one, the corresponding chloroacetamide and condensed 1H-pyrido[2,3-b][1,4]oxazine-2(3H)-one were... 相似文献
Journal of Applied Spectroscopy - The concentration of heavy metals in drinking water is an important standard for water quality evaluation and water pipeline corrosion detection. This research... 相似文献
Russian Physics Journal - The results of a study of the dislocation structure evolution in polycrystals of homogeneous solid solutions in low-stability states in Cu-Mn-based alloys with FCC crystal... 相似文献
The European Physical Journal A - The goal of the present paper is twofold. First, a novel expansion many-body method applicable to superfluid open-shell nuclei, the so-called Bogoliubov in-medium... 相似文献
The machining process is primarily used to remove material using cutting tools. Any variation in tool state affects the quality of a finished job and causes disturbances. So, a tool monitoring scheme (TMS) for categorization and supervision of failures has become the utmost priority. To respond, traditional TMS followed by the machine learning (ML) analysis is advocated in this paper. Classification in ML is supervised based learning method wherein the ML algorithm learn from the training data input fed to it and then employ this model to categorize the new datasets for precise prediction of a class and observation. In the current study, investigation on the single point cutting tool is carried out while turning a stainless steel (SS) workpeice on the manual lathe trainer. The vibrations developed during this activity are examined for failure-free and various failure states of a tool. The statistical modeling is then incorporated to trace vital signs from vibration signals. The multiple-binary-rule-based model for categorization is designed using the decision tree. Lastly, various tree-based algorithms are used for the categorization of tool conditions. The Random Forest offered the highest classification accuracy, i.e., 92.6%.
Juglandis Mandshuricae Cortex is the bark of Juglans mandshurica Maxim., which has been used as a folk medicine plant in China and India. In this study, an ultra-high performance liquid chromatography–quadrupole/orbitrap high-resolution mass spectrometry method was developed to clarify and quantify the chemical profiling of Juglandis Mandshuricae Cortex rapidly. A total of 113 compounds were characterized. Among them, seven flavonoids were simultaneously quantified in 15 min, including myricetin, myricetrin, taxifolin, kaempferol, quercetin, quercitrin, and naringenin. The method was validated for accuracy, precision, and the limits of detection and quantification. All calibration curves showed a good linear relationship (r > 0.9990) within test ranges. The intra- and inter-day relative standard deviations were less than 2.16%. Accuracy validation showed that the recovery was between 95.6 and 101.3% with relative standard deviation values below 2.85%. The validated method was successfully applied to determine the contents of seven flavones in Juglandis Mandshuricae Cortex from seven sources and the contents of these places were calculated respectively. This method provides a theoretical basis for further developing the medicinal value of Juglandis Mandshuricae Cortex. 相似文献
Crystallography Reports - A geometrical and topological analysis has been performed, and self-assembly of the crystal structures of intermetallic compounds CsnMk (М = Na, K, Rb, Pt, Au, Hg,... 相似文献
JETP Letters - The magnetic properties of Co-doped CdS has been investigated by ab initio calculations using the GGA + U approximation. The study reveals the ferromagnetic ordering of Co-doped CdS... 相似文献
Journal of Applied Spectroscopy - The aromaticity in the lowest triplet T1-state of NH-tautomers of corrole free bases with different peripheral substitution architecture was investigated using... 相似文献