Prediction of drug synergy score using ensemble based differential evolution

Prediction of drug synergy score is an ill‐posed problem. It plays an efficient role in the medical field for inhibiting specific cancer agents. An efficient regression‐based machine learning technique has an ability to minimise the drug synergy prediction errors. Therefore, in this study, an efficient machine learning technique for drug synergy prediction technique is designed by using ensemble based differential evolution (DE) for optimising the support vector machine (SVM). Because the tuning of the attributes of SVM kernel regulates the prediction precision. The ensemble based DE employs two trial vector generation techniques and two control attributes settings. The initial generation technique has the best solution and the other is without the best solution. The proposed and existing competitive machine learning techniques are applied to drug synergy data. The extensive analysis demonstrates that the proposed technique outperforms others in terms of accuracy, root mean square error and coefficient of correlation.Inspec keywords: cancer, evolutionary computation, support vector machines, regression analysis, drugs, learning (artificial intelligence), medical computingOther keywords: ensemble based differential evolution, specific cancer agents, efficient regression‐based machine learning technique, drug synergy prediction errors, efficient machine learning technique, drug synergy prediction technique, support vector machine, prediction precision, trial vector generation techniques, initial generation technique, drug synergy data, drug synergy score prediction, medical field, SVM kernel attributes, ensemble based DE, control attribute settings, competitive machine learning techniques, root mean square error     

High‐Performance Microwave‐Derived Multi‐Principal Element Alloy Coatings for Tribological Application

The authors report the development of Al_xCoCrFeNi (x = 0.1 to 3) high entropy alloy (HEA) coatings using a simple and straightforward microwave technique. The microstructure of the developed coatings is composed of a cellular structure and diffused interface with the substrate. The microstructure of the HEA coatings varies as a direct function of Al content. An increase in Al fraction shows structural transformation from FCC to BCC along with the evolution of σ and B₂ as the major secondary phases. The diffusion of Mo from the substrate enhances the mixing entropy and promotes σ‐phase formation. The HEA coatings show significantly high hardness compared to SS316L substrate steel (227 HV) with a maximum value of 726 HV observed for three‐molar composition. The fracture toughness exhibits an inverse correlation with the Al fraction with the highest value of around 49 MPa m^1/2 observed for Al_0.1CoCrFeNi coating. The equimolar coating composition shows lowest erosion rates among all the tested samples due to optimum combination of the mechanical properties. The erosion resistance of the equimolar coating is 2 to 5 times higher than steel substrate and around 1.5 times higher than the non‐equimolar counterparts depending upon the impingement angles.

     

Hierarchical Voting-Based Feature Selection and Ensemble Learning Model Scheme for Glioma Grading with Clinical and Molecular Characteristics

Determining the aggressiveness of gliomas, termed grading, is a critical step toward treatment optimization to increase the survival rate and decrease treatment toxicity for patients. Streamlined grading using molecular information has the potential to facilitate decision making in the clinic and aid in treatment planning. In recent years, molecular markers have increasingly gained importance in the classification of tumors. In this study, we propose a novel hierarchical voting-based methodology for improving the performance results of the feature selection stage and machine learning models for glioma grading with clinical and molecular predictors. To identify the best scheme for the given soft-voting-based ensemble learning model selections, we utilized publicly available TCGA and CGGA datasets and employed four dimensionality reduction methods to carry out a voting-based ensemble feature selection and five supervised models, with a total of sixteen combination sets. We also compared our proposed feature selection method with the LASSO feature selection method in isolation. The computational results indicate that the proposed method achieves 87.606% and 79.668% accuracy rates on TCGA and CGGA datasets, respectively, outperforming the LASSO feature selection method.     

On modification of the relative complexity metric

Software reliability and software complexity are closely related issues in software development. An elegant definition of relative complexity was proposed in [1,2]. The definition given in [1,2] needs modification. Depending on how many factor loadings are used in the factor analysis different complexity results are obtained. Hence the definition of relative complexity given in those papers is subjective. The object of this paper is to suggest a modified definition of relative complexity. Different measures based on the magnitude of the eigenvalues obtained from the correlation matrix are suggested in this paper. The relative complexity of 27 programs given in [3] has been calculated using different factor loadings.     

Comparative Study of Silver Nanoparticles Coated and Uncoated NiO–Fe2O3–CaO–SiO2–P2O5 Ferromagnetic Bioactive Ceramics

Bioactive ferromagnetic ceramics of system xNiO–(3?x)Fe₂O₃–52CaO–30SiO₂–15P₂O₅, (x = 0, 3 mol%) have been prepared in the laboratory using sol–gel technique. Silver nanoparticles coating has been undertaken on the surface of synthesized samples. Comparative study of silver nanoparticles coated and uncoated samples has been undertaken with the help of transmission electron microscopy, X‐ray diffraction (XRD), degradation, drug delivery, hemolysis, antimicrobial, and cell culture studies. XRD patterns indicate the growth of hydroxyl apatite layer on the surface of coated as well as uncoated samples. Ferromagnetic properties of samples have been investigated with the help of vibrating sample magnetometer technique. Samples have shown good response as drug carriers under normal conditions as well as under the influence of magnetic field. Drug release mechanism and mesoporus nature of samples have been investigated with the help of Brunauer–Emmett–Teller technique. Nonreactivity of samples (coated and uncoated) with red blood cells and white blood cells show nontoxic nature of the samples. Coated samples have shown better antimicrobial properties against six different microorganisms, including some resistive strain like methicillin‐resistant Staphylococcus aureus with minimum inhibitory concentration of 0.05 mg/ml as compared to uncoated samples. It has been observed that samples also provide a healthy environment for the growth of MG 63 cell lines. It has been noticed that presence of silver nanoparticles on the surface of samples improve degradation and antimicrobial properties.     

High-Temperature Exposure Studies of HVOF-Sprayed Cr<Subscript>3</Subscript>C<Subscript>2</Subscript>-25(NiCr)/(WC-Co) Coating

In this research, development of Cr₃C₂-25(NiCr) + 25%(WC-Co) composite coating was done and investigated. Cr₃C₂-25(NiCr) + 25%(WC-Co) composite powder [designated as HP2 powder] was prepared by mechanical mixing of [75Cr₃C₂-25(NiCr)] and [88WC-12Co] powders in the ratio of 75:25 by weight. The blended powders were used as feedstock to deposit composite coating on ASTM SA213-T22 substrate using High Velocity Oxy-Fuel (HVOF) spray process. High-temperature oxidation/corrosion behavior of the bare and coated boiler steels was investigated at 700 °C for 50 cycles in air, as well as, in Na₂SO₄-82%Fe₂(SO₄)₃ molten salt environment in the laboratory. Erosion-corrosion behavior was investigated in the actual boiler environment at 700 ± 10 °C under cyclic conditions for 1500 h. The weight-change technique was used to establish the kinetics of oxidation/corrosion/erosion-corrosion. X-ray diffraction, field emission-scanning electron microscopy/energy-dispersive spectroscopy (FE-SEM/EDS), and EDS elemental mapping techniques were used to analyze the exposed samples. The uncoated boiler steel suffered from a catastrophic degradation in the form of intense spalling of the scale in all the environments. The oxidation/corrosion/erosion-corrosion resistance of the HVOF-sprayed HP2 coating was found to be better in comparison with standalone Cr₃C₂-25(NiCr) coating. A simultaneous formation of protective phases might have contributed the best properties to the coating.     

Surface engineering analysis of detonation-gun sprayed Cr3C2–NiCr coating under high-temperature oxidation and oxidation–erosion environments

Detonation-gun (D-gun) spray technology is a novel coating deposition process which is capable of achieving very high gas and particle velocities approaching 4–5 times the speed of sound. This process provides the possibility of producing high hardness coatings with strong adherence. In the present study, this technique has been used to deposit Cr₃C₂–NiCr coating on T22 boiler steel. Investigations on the behaviour of this coating subjected to high-temperature oxidation in air and oxidation–erosion in actual boiler environment at 700 ± 10 °C under cyclic conditions have been carried out. The weight change technique was used to establish the kinetics of oxidation. X-ray diffraction (XRD), field emission-scanning electron microscopy/energy-dispersive spectroscopy (FE-SEM/EDS) and EDS elemental mapping techniques were used to analyse the oxidation/oxidation–erosion products. The uncoated boiler steel suffered from a catastrophic degradation in the form of intense spalling of the scale in both the environments. The Cr₃C₂–NiCr coating showed good adherence to the boiler steel during the exposures with no tendency for spallation of its oxide scale.     

Wear behaviour of cryogenically treated tungsten carbide inserts under dry and wet turning conditions

Cryogenic treatment has been acknowledged as a means of extending the life of tungsten carbide inserts but no study has been reported in open literature regarding the effect of coolant on the performance of cryogenically treated tungsten carbide inserts in turning. In order to understand the effect of coolant, a comparative investigation of the wear behaviour of cryogenically treated tungsten carbide inserts in dry and wet orthogonal turning has been carried out in this study. The commercially available uncoated square-shaped tungsten carbide inserts with chip breakers were procured and cryogenically treated at ?196 °C and the cutting tests were executed in accordance to the International Standard Organisation, ISO 3685-1993 for continuous and interrupted machining mode. The criterion selected for determining the tool life was based on the maximum flank wear (0.6 mm) and the selection of cutting conditions was made to ensure the significant wear at a suitable time interval. The results showed that cryogenically treated tungsten carbide inserts performed significantly better in wet turning conditions under both continuous and interrupted machining modes especially at higher cutting speeds. A considerable increase in tool life was also recorded in interrupted machining mode as compared with continuous machining mode.     

Correction to: Analysis of Water Quantity and Quality Trade‑Offs to Inform Selective Harvesting of Inflows in Complex Water Resource Systems

Water Resources Management -     

Quantifying prognosis severity of COVID-19 patients from deep learning based analysis of CT chest images

Multimedia Tools and Applications - The COVID-19 pandemic has affected all the countries in the world with its droplet spread mode. The colossal amount of cases has strained all the healthcare...