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...     

Finite-sample properties of estimators for first and second order autoregressive processes

Statistical Inference for Stochastic Processes - The class of autoregressive (AR) processes is extensively used to model temporal dependence in observed time series. Such models are easily...     

Mechanical Characteristics of Diamond-Like Moiré Films

JETP Letters - The mechanical characteristics of diamond-like films, such as Dn21.8, Dn27.8, and Dn29.4 moiré diamanes, formed by the hydrogenation of graphene layers twisted at an angle of...     

Infrared Reflection Spectra of (FeIn2S4)x∙(In2S3)1–x Solid Solutions

Journal of Applied Spectroscopy - IR reflectance spectroscopy at 50–450 cm–1 was used to study homogeneous monocrystals of (FeIn2S3)x?(In2S3)1–x grown by the method of...     

The comparable structural,elastic anisotropic and thermophysical properties of advanced U–Si fuel to baseline UO2: a DTF method

The European Physical Journal B - Molecular dynamics and Monte Carlo methods are common measurements to study the diffusion coefficients of the fluid particles under restricted conditions. Here,...     

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%.

     

Quantum Key Distribution with Untrusted Detectors Accessible to an Eavesdropper

JETP Letters - A simple fundamental modification of quantum key distribution protocols has been proposed: it is not required to protect the results of avalanche detectors from an eavesdropper, but...     

Carbohydrate-based nanostructured catalysts: applications in organic transformations

The requirement of green and sustainable materials to prepare heterogeneous catalysts has intensified for practical reasons over the past few decades. Carbohydrates are possibly the most plentiful and renewable organic materials in nature with inimitable physiochemical properties, plausible low-cost and large-scale production, and sustainability features could be exploited in the generation of nanostructured heterogeneous catalysts. This review article outlines the organic transformations catalyzed by diverse carbohydrate-based nanostructured catalysts in greener and environmentally friendly processes. Selected examples are highlighted for a variety of organic reactions exploiting the proposed catalysts’ reactivity and reusability, and interactions with the intrinsic nature of the applied carbohydrate supports; advantages and speculated challenges of the introduced catalysts are deliberated as well.     

Intermetallic Compounds CsnMk (М = Na,K, Rb,Pt, Au,Hg, Te): Geometrical and Topological Analysis,Cluster Precursors,and Self-Assembly of Crystal Structures

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,...     

X-ray Diffraction Study of Structural Changes in High-Strength Ceramics Based on Zirconium Oxide with Additions of Ytterbium and Neodymium Oxides after Hydrothermal Treatment

Crystallography Reports - A surface structural analysis of two ceramic samples of zirconium oxide (ZrO2) sintered at 1550°C, stabilized in the tetragonal form, before and after hydrothermal...