Synthesis,Molecular Docking,and Hemorheological Activity of New 4-(Thien-2-yl)-3-aminopyridine-2(1H)-one Derivatives

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...     

Circularly polarized luminescence based on small organic fluorophores

Circularly polarized luminescence (CPL) has attracted attention as a next-generation light signal because of its carrying more information compared with normal and linearly polarized lights as well as its potential wide application in information fields. Recently, much attention has been paid to small organic molecules-based CPL emitters because of easy synthesis, fine structural modification at molecular level, and tunable wide range emission wavelength. This review highlights the development of small organic molecules-based CPL emitters in the past 5 years (2017–2021). The progress suggests that small organic molecules-based CPL emitters provide a simple and efficient way to generate CPL.     

Separation,Preconcentration, and Determination of Lead,Cadmium, and Iron Using Cloud Point Extraction with Flame Atomic Absorption Spectrometry

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...     

Dislocation Structure Evolution in Low-Stability States of Solid Solutions of Alloys Under Their Deformation

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...     

Geometrically nonlinear dynamic analysis of the stiffened perovskite solar cell subjected to biaxial velocity impacts

Nonlinear Dynamics - The perovskite solar cell (PSC) is one of the most promising photovoltaic candidates along with the highly increasing demand for green electricity. One of the main concerns...     

Alpha-gamma decay studies of $$^{247}$$ Md

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...     

Metal organic frameworks as advanced extraction adsorbents for separation and analysis in proteomics and environmental research

Science China Chemistry - Human health is always under global spotlight, but now it suffers from severe environmental issue and various diseases. Developing highly selective and effective...     

Application of Machine Learning for Tool Condition Monitoring in Turning

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%.

     

Dynamic stability of a class of fractional-order nonlinear systems via fixed point theory

In this paper, the problem of the uniform stability for a class of fuzzy fractional-order genetic regulatory networks with random discrete delays, distributed delays, and parameter uncertainties is studied. Although there is a portion of literature on using fixed point theorems to study the stability of fractional neural networks, most of them required the fractional order to be in $\left(\frac{1}{2},1\right)$. However, the case of the fractional-order belonging to $(0,\frac{1}{2})$ has not been discussed. To solve it, this work proposes a novel idea of using fixed point theory to study the stability of fuzzy (0,1) order neural networks, the problem of the uniqueness of the solution of the considered genetic regulatory networks is resolved, and a novel sufficient condition to guarantee the uniform stability of above genetic regulatory networks is also derived. Eventually, an example is given to demonstrate that the obtained result is effective.