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%.

     

Key Role of a-Top CO on Terrace Sites of Metallic Pd Clusters for CO Oxidation

Pd-based catalysts are the most widely used for CO oxidation because of their outstanding catalytic activity and thermal stability. However, fundamental understanding of the detailed catalytic processes occurring on Pd-based catalysts under realistic conditions is still lacking. In this study, we investigated CO oxidation on metallic Pd clusters supported on Al₂O₃ and SiO₂. High-angle annular dark-field scanning transmission electron microscopy revealed the formation of similar-sized Pd clusters on Al₂O₃ and SiO₂. In contrast, CO chemisorption analysis indicated a gradual change in the dispersion of Pd (from 0.79 to 0.2) on Pd/Al₂O₃ and a marginal change in the dispersion (from 0.4 to 0.24) on Pd/SiO₂ as the Pd loading increased from 0.27 to 5.5 wt %; these changes were attributed to differences in the metal-support interactions. Diffuse reflectance infrared Fourier-transform spectroscopy revealed that fewer a-top CO species were present in Pd supported on Al₂O₃ than those in Pd supported on SiO₂, which is related to the morphological differences in the metallic Pd clusters on these two supports. Despite the different dispersion profiles and surface characteristics of Pd, O₂ titration demonstrated that linearly bound CO (with an infrared signal at 2090 cm⁻¹) reacted first with oxygen in the case of CO-saturated Pd on Al₂O₃ and SiO₂, which suggests that a-top CO on the terrace site plays an important role in CO oxidation. The experimental observations were corroborated by periodic density functional calculations, which confirmed that CO oxidation on the (111) terrace sites is most plausible, both kinetically and thermodynamically, compared to that on the edge or corner sites. This study will deepen the fundamental understanding of the effect of Pd clusters on CO oxidation under reaction conditions.     

Classify the Higgs decays with the PFN and ParticleNet at electron–positron colliders

Various Higgs factories are proposed to study the Higgs boson precisely and systematically in a model- independent way. In this study, the Particle Flow Network and ParticleNet techniques are used to classify the Higgs decays into multicategories, and the ultimate goal is to realize an "end-to-end" analysis. A Monte Carlo simulation study is performed to demonstrate the feasibility, and the performance looks rather promising. This result could be the basis of a "one-stop" analysis to measure all the branching fractions of the Higgs decays simultaneously.     

Single-atom Fe Embedded Co3S4 for Efficient Electrocatalytic Oxygen Evolution Reaction

Constructing atomically dispersed active sites with densely exposed and dispersed double metal-S_x catalytic sites for favorable OER catalytic activity remains rare and challenging. Herein, we design and construct a Fe₁S_x@Co₃S₄ electrocatalyst with Fe single atoms epitaxially confined in Co₃S₄ nanosheets for catalyzing the sluggish alkaline oxygen evolution reaction(OER). Consequently, in ultralow concentration alkaline solutions(0.1 mol/L KOH), such a catalyst is highly active and robust for OER with low overpotentials of 300 and 333 mV at current densities of 10 and 30 mA/cm², respectively, accompanying long-term stability without significant degradation even for 350 h. In addition, Fe₁S_x@Co₃S₄ shows a turnover frequency(TOF) value of 0.18 s⁻¹, nearly three times that of Co₃S₄(0.07 s⁻¹), suggesting the higher atomic utilization of Fe single atoms. Mössbauer and in-situ Raman spectra confirm that the OER activity of Fe₁S_x@Co₃S₄ origins from a thin catalytic layer of Co(Fe)OOH that interacts with trace-level Fe species in the electrolyte, creating dynamically stable active sites. Combined with experimental characterizations, it suggests that the most active S-coordinated dual-metal site configurations are 2S-bridged (Fe-Co)S₄, in which Co-S and Fe-S moieties are shared with two S atoms, which can strongly regulate the adsorption energy of reaction intermediates, accelerating the OER reaction kinetics.     

Acidity Modification of ZSM-5 for Methane Conversion in Co-feeding Method with MTA Reaction

Acidity plays a vital role in methane conversion by co-feeding method, which is one of the best strategies to improve the utilization and gentle the reaction conditions of methane. In this work, Zn, Ni, Mo, La, Ga, Fe and Co-impregnated ZSM-5 zeolites have been prepared with the same substitutions to variate the acidities and tested in co-aromatization of methanol with methane. It is demonstrated that the new medium-strong acid sites formed by metal and strong acid sites are the key role to activate methane in co-reaction. Zn-modified ZSM-5 catalyst is preferred to exhibit the best methane conversion of 12%, whose aromatic selectivity increases from 27.2% to 52.2% compared with that of HZSM-5. Besides, the addition of methane further improves the production of high-valued aromatics compared with methanol to aromatics (MTA) reaction.     

A volatolomic approach using cerumen as biofluid to diagnose bovine intoxication by Stryphnodendron rotundifolium

An innovative volatolomic approach employs the detection of biomarkers present in cerumen (earwax) to identify cattle intoxication by Stryphnodendron rotundifolium Mart., Fabaceae (popularly known as barbatimão). S. rotundifolium is a poisonous plant with the toxic compound undefined and widely distributed throughout the Brazilian territory. Cerumen samples from cattle of two local Brazilian breeds (‘Curraleiro Pé-Duro’ and ‘Pantaneiro’) were collected during an experimental intoxication protocol and analyzed using headspace (HS)/GC–MS followed by multivariate analysis (genetic algorithm for a partial least squares, cluster analysis, and classification and regression trees). A total of 106 volatile organic metabolites were identified in the cerumen samples of bovines. The intoxication by S. rotundifolium influenced the cerumen volatolomic profile of the bovines throughout the intoxication protocol. In this way, it was possible to detect biomarkers for cattle intoxication. Among the biomarkers, 2-octyldecanol and 9-tetradecen-1-ol were able to discriminate all samples between intoxicated and nonintoxicated bovines. The cattle intoxication diagnosis by S. rotundifolium was accomplished by applying the cerumen analysis using HS/GC–MS, in an easy, accurate, and noninvasive way. Thus, the proposed bioanalytical chromatography protocol is a useful tool in veterinary applications to determine this kind of intoxication.     

Study of Endogen Substrates,Drug Substrates and Inhibitors Binding Conformations on MRP4 and Its Variants by Molecular Docking and Molecular Dynamics

Multidrug resistance protein-4 (MRP4) belongs to the ABC transporter superfamily and promotes the transport of xenobiotics including drugs. A non-synonymous single nucleotide polymorphisms (nsSNPs) in the ABCC4 gene can promote changes in the structure and function of MRP4. In this work, the interaction of certain endogen substrates, drug substrates, and inhibitors with wild type-MRP4 (WT-MRP4) and its variants G187W and Y556C were studied to determine differences in the intermolecular interactions and affinity related to SNPs using protein threading modeling, molecular docking, all-atom, coarse grained, and umbrella sampling molecular dynamics simulations (AA-MDS and CG-MDS, respectively). The results showed that the three MRP4 structures had significantly different conformations at given sites, leading to differences in the docking scores (DS) and binding sites of three different groups of molecules. Folic acid (FA) had the highest variation in DS on G187W concerning WT-MRP4. WT-MRP4, G187W, Y556C, and FA had different conformations through 25 ns AA-MD. Umbrella sampling simulations indicated that the Y556C-FA complex was the most stable one with or without ATP. In Y556C, the cyclic adenosine monophosphate (cAMP) and ceefourin-1 binding sites are located out of the entrance of the inner cavity, which suggests that both cAMP and ceefourin-1 may not be transported. The binding site for cAMP and ceefourin-1 is quite similar and the affinity (binding energy) of ceefourin-1 to WT-MRP4, G187W, and Y556C is greater than the affinity of cAMP, which may suggest that ceefourin-1 works as a competitive inhibitor. In conclusion, the nsSNPs G187W and Y556C lead to changes in protein conformation, which modifies the ligand binding site, DS, and binding energy.     

Visible-Light-Induced Heptacene Generation under Ambient Conditions: Utilization of Single-crystal Interior as an Isolated Reaction Site

The photo-induced generation of unstable molecules generally requires stringent conditions to prevent oxidation and the concomitant decomposition of the products. The visible-light-induced conversion of two heptacene precursors to heptacene was studied. Single crystals of bis- and mono-α-diketone-type heptacene precursors ( 7-DK2 and 7-DK1 , respectively), were prepared to investigate the effect of precursor structure on reactivity. The photoirradiation of a 7-DK2 single crystal cleaved only one α-diketone group, forming an intermediate bearing a pentacene subunit, while that of a 7-DK1 single crystal gave rise to characteristic absorption peaks of heptacene and their increase in intensity with photoirradiation time, indicating the generation of heptacene without decomposition. Heptacene production was not observed when the precursors were photoirradiated in solution, implying that the single crystal interior provided isolation from the external environment, thus preventing heptacene oxidation.     

Model selection based on Lorenz and concentration curves,Gini indices and convex order

In order to determine an appropriate amount of premium, statistical goodness-of-fit criteria must be supplemented with actuarial ones when assessing performance of a given candidate pure premium. In this paper, concentration curves and Lorenz curves are shown to provide actuaries with effective tools to evaluate whether a premium is appropriate or to compare two competing alternatives. The idea is to compare the premium income for sub-portfolios gathering low risks (identified as low by means of the premiums under consideration) to the true one, or equivalently, to the actual losses. Numerical illustrations performed on hypothetical data and real ones demonstrate the usefulness of the proposed approach.