Thermodynamics of interaction of acetylene with cuprous ion in an aqueous medium

Thermodynamic data for formation of Cu.C₂H₂⁺ and Cu⁺.C₂H- complexes in aqueous CuCl-NH,Cl-HCl medium have been obtained by the potentiometric technique. The data are of interest in homogeneous liquid phase catalytic conversion of acetylene to various products.     

Machine Learning Technique to Detect Radiations in the Brain

The brain of humans and other organisms is affected in various ways through the electromagnetic field (EMF) radiations generated by mobile phones and cell phone towers. Morphological variations in the brain are caused by the neurological changes due to the revelation of EMF. Cellular level analysis is used to measure and detect the effect of mobile radiations, but its utilization seems very expensive, and it is a tedious process, where its analysis requires the preparation of cell suspension. In this regard, this research article proposes optimal broadcasting learning to detect changes in brain morphology due to the revelation of EMF. Here, Drosophila melanogaster acts as a specimen under the revelation of EMF. Automatic segmentation is performed for the brain to attain the microscopic images from the prejudicial geometrical characteristics that are removed to detect the effect of revelation of EMF. The geometrical characteristics of the brain image of that is microscopic segmented are analyzed. Analysis results reveal the occurrence of several prejudicial characteristics that can be processed by machine learning techniques. The important prejudicial characteristics are given to four varieties of classifiers such as naïve Bayes, artificial neural network, support vector machine, and unsystematic forest for the classification of open or nonopen microscopic image of D. melanogaster brain. The results are attained through various experimental evaluations, and the said classifiers perform well by achieving 96.44% using the prejudicial characteristics chosen by the feature selection method. The proposed system is an optimal approach that automatically identifies the effect of revelation of EMF with minimal time complexity, where the machine learning techniques produce an effective framework for image processing.     

Electrochemical reduction of 2,3′-dinitrobenzidine in buffered aqueous methanol

2,2-dinitrobenzidine (2,3-DNB) gives a single diffusion-limited irreversible polarographic wave in buffered aqueous methanol. Microcoulometric experiments indicate a transfer of ten electrons in the reduction and cyclic voltammetric studies show direct proof for the existence of a nitroso intermediate. Based on the results obtained, a suitable mechanism is proposed for the reduction of 2,3-DNB in buffered methanolic solutions.     

Kernel Granulometric Texture Analysis and Light RES-ASPP-UNET Classification for Covid-19 Detection

This research article proposes an automatic frame work for detecting COVID -19 at the early stage using chest X-ray image. It is an undeniable fact that coronovirus is a serious disease but the early detection of the virus present in human bodies can save lives. In recent times, there are so many research solutions that have been presented for early detection, but there is still a lack in need of right and even rich technology for its early detection. The proposed deep learning model analysis the pixels of every image and adjudges the presence of virus. The classifier is designed in such a way so that, it automatically detects the virus present in lungs using chest image. This approach uses an image texture analysis technique called granulometric mathematical model. Selected features are heuristically processed for optimization using novel multi scaling deep learning called light weight residual–atrous spatial pyramid pooling (LightRES-ASPP-Unet) Unet model. The proposed deep LightRES-ASPP-Unet technique has a higher level of contracting solution by extracting major level of image features. Moreover, the corona virus has been detected using high resolution output. In the framework, atrous spatial pyramid pooling (ASPP) method is employed at its bottom level for incorporating the deep multi scale features in to the discriminative mode. The architectural working starts from the selecting the features from the image using granulometric mathematical model and the selected features are optimized using LightRES-ASPP-Unet. ASPP in the analysis of images has performed better than the existing Unet model. The proposed algorithm has achieved 99.6% of accuracy in detecting the virus at its early stage.     

Investigation of graphene‐on‐metal substrates for SPR‐based sensor using finite‐difference time domain

In this study, the authors investigated the effects of a single layer graphene as a coating layer on top of metal thin films such as silver, gold, aluminum and copper using finite‐difference time domain method. To enhance the resolution of surface plasmon resonance (SPR) sensor, it is necessary to increase the SPR reflectivity and decrease the full‐width‐half maximum (FWHM) of the SPR curve so that there is minimum uncertainty in the determination of the resonance dip. Numerical data was verified with analytical and experimental data where all the data were in good agreement with resonance angle differing in <10% due to noise present in components such as humidity and temperature. In further analysis, reflectivity and FWHM were compared among four types of metal with various thin film thicknesses where graphene was applied on top of the metal layers, and data was compared against pure conventional metal thin films. A 60 nm‐thick Au thin film results in higher performance with reflectivity of 92.4% and FWHM of 0.88° whereas single layer graphene‐on‐60 nm‐thick Au gave reflectivity of 91.7% and FWHM of 1.32°. However, a graphene‐on‐40 nm‐thick Ag also gave good performance with narrower FWHM of 0.88° and reflection spectra of 89.2%.Inspec keywords: graphene, surface plasmon resonance, finite difference time‐domain analysis, reflectivity, metallic thin films, silver, gold, aluminium, copper, chemical sensors, biological techniquesOther keywords: graphene‐on‐metal substrates, SPR‐based sensor, finite‐difference time domain, metal thin films, surface plasmon resonance sensor, SPR curve, resonance angles, reflectivity, C, Ag, Au, Al, Cu     

镍-磷-碳化硼化学复合镀层的研制

在由碳酸镍15 g/L、次磷酸32 mL/L、次磷酸钠15 g/L、乳酸32mL/L、乙酸189/L、丙酸3mL/L、二甲胺1.7g/L及碳化硼(即B4C)0～25 g/L组成的稳定镀液中,采用化学镀的方法在低碳钢上制备了Ni-P-B4C复合镀层.其显微硬度采用韦氏硬度法测量,耐磨性用Taber磨耗试验机测量,微观形貌...     

Optimization of ultrasound-assisted solvent extraction (UASE) based on oil yield,antioxidant activity and evaluation of fatty acid composition and thermal stability of Coriandrum sativum L. seed oil

Food Science and Biotechnology - Ultrasound is one of emerging technique’s which is being investigated extremely on food applications and extraction process. In this study,...     

Investigation on temperature-dependent structural,dielectric and impedance characteristics of Cu-doped CaFexTi1-xO3-δ nanotitanates

Journal of Materials Science: Materials in Electronics - In recent days, the development of low-cost, sustainable, efficient electrode materials for energy storage applications is of great...