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Microstructural Features and Mechanical Behavior of Laser Welded Magnesium Alloy Sheet
Get PDFMagnesium Alloy is gaining momentum now a days as it is light in weight and possess moderate strength. Automotive and aerospace industries and electronics companies looking for light and strong and smart materials to save fuel and emission free environments, which magnesium alloy can meet. As Tailor welded magnesium alloy sheets are in demand, AZ31B -H24 magnesium alloy sheet with 2 mm thickness is selected in this research work. Laser welding is used to join magnesium alloy sheets in butt configuration. The samples are analyzed, and observations and challenges are addressed with help of micrographs for further scope of work. Effect of laser welding on grain or microstructure changes are also outlined. Thorough micro structural analysis is carried out with an objective to capture grain structure near parent metal, left and right-hand sides of heat affected zone and weld line. Impact and hardness tests are conducted to assess the mechanical behavior of laser welded samples
Morphological Operations and Histogram Analysis of SEM Images using Python
Get PDFCharacterization of any Material / Element requires SEM (Scanning Electron Microscopy) analysis. Images captured from SEM are further considered for analysing the Morphology, structure of the material. Due to non-conduction or any technical issues, the image captured may not be accurate for analysis. If the image is accurate also morphological operations can’t be performed. In this paper, SEM images are processed to study the histogram analysis for equalizing the image, morphological operations via. Erosion, Dilation etc using Python programming
Pharmacological evaluation and kinetics of in vitro drug release efficacy of biofabricated silver nanoparticles using medicinally important Justicia neesii Ramamoorthy
Get PDFGreen nanotechnology, the science that utilizes various plant resources for the synthesis of nanoparticles without posing any chemical hazard has proved to be highly efficient and environment friendly technique. This opens up options for the synthesis of novel nanoparticles with desirable characteristics required for various application viz., biosensors, biomedicine, cosmetics, nanobiotechnology, as antimicrobials, electronics, sensing etc. In this context, here, we have made an attempt for cost effective and eco-friendly synthesis of silver nanoparticles (AgNPs) using the extract of medicinally important plant Justicia neesii Ramamoorthy. The phytochemical analysis of the extract exhibited the presence of glycosides, flavonoids, lignins, phenols, phytosterols, reducing sugars, saponins, etc. The absorbance peak of the biofabricated nanoparticles at 425 nm as indicated by UV-Vis spectrophotometer broadens with increase in time indicating their poly dispersity nature and particle size analyzer revealed the average size to be in the range of 20-45 nm. The antioxidant and antimicrobial activity of the synthesized AgNPs demonstrated promising results. The kinetics of in vitro drug release profile of the drug loaded AgNPs was carried out and the data obtained was correlated with various mathematical models. The drug release from AgNPs at both the pH’s shows good fit to the First order model which is obvious from the high values of coefficient of correlation which logically means that the release of drug from AgNPs is dependent on the concentration present within the nanoparticles
Effect of Calotropis procera (Aiton) Dryand.based zinc oxide nanoparticles on the cotton pest Spodoptera litura Fab.
Get PDFMajor loss in agricultural crops is caused by insect pests. In India, various synthetic insecticides are used against pests. These are much expensive and cause environmental hazards. The nanoparticles, as an alternative approach is gaining considerable interest in this field. In the present study, we explored the biological synthesis of zinc oxide nanoparticles using Giant milkweed, Calotropis procera (Aiton) Dryand. and its effects on the tobacco cutworm, Spodoptera litura. The reduction of zinc ions (Zn2+) to zinc nanoparticles (ZnO NPs) was prepared by mixing 50 g of C. procera leaves with 100 mL of single distilled water in a 250 mL glass beaker. To synthesize nanoparticles, 50 mL of C. procera leaf extract was taken using a stirrer-heater and 5 g of zinc oxide was added at 60ºC, boiled, then kept in a hot air oven at 70ºC for 24 h. Finally, the obtained light yellow coloured powder was carefully collected and characterized using X-ray diffraction (XRD) analysis. The results revealed that the biologically synthesized zinc oxide nanoparticles pesticide was highly effective against the pest. The weight of the pest decreased from low concentration to high concentration. It is concluded that the Calotropis Procera based zinc oxide nanoparticles could be used for the control of Spodoptera litura
Learning How to Detect Salient Objects in Nighttime Scenes
Get PDFThe detection of salient objects in nighttime scene settings is an essential research issue in computer vision. None of the known approaches can accurately anticipate salient objects in the nighttime scenes. Due to the lack of visible light, spatial visual information cannot be accurately perceived by traditional and deep network models. This paper proposed a Mountain Basin Network (MBNet) to identify salient objects for distinguishing the pixel-level saliency of low-light images. To improve the objects localizations and pixel classification performances, the proposed model incorporated a High-Low Feature Aggregation Module (HLFA) to synchronize the information from a high-level branch (named Bal-Net) and a low-level branch (called Mol-Net) to fuse the global and local context, and a Hierarchical Supervision Module (HSM) was embedded to aid in obtaining accurate salient objects, particularly the small ones. In addition, a multi-supervised integration technique was explored to optimize the structure and borders of salient objects. In the meantime, to facilitate more investigation into nighttime scenes and assessment of visual saliency models, we created a new nighttime dataset consisting of thirteen categories and a total of one thousand low-light images. Our experimental results demonstrated that the suggested MBNet model outperforms seven current state-of-the-art methods for salient object detection in nighttime scenes
An Industry Framework for Remote Health Monitoring using Machine Learning Models to Predict a Disease
Get PDFRemote health monitoring frameworks gained significant attention due to their real intervention and treatment standards. Most conventional works object to developing remote monitoring frameworks for identifying the disease at the earlier stages for an appropriate diagnosis. Still, it faced the problems with complexity in operations, increased cost of resources, misprediction results, which requires more time consumption for data gathering, and reduced convergence rate. Hence, the proposed work intends to design a machine learning based remote health monitoring framework for predicting heart disease and diabetes from the given medical datasets. In this framework, the Industry based smart devices are used to gather the health information of patients, and the obtained information is integrated together by using different nodes that includes the detecting node, visualization node, and prognostic node. Then, the medical dataset preprocessing is performed to normalize the attributes by identifying the missing values and eliminating the irrelevant qualities. Consequently, the Unified Levy Modeled Crow Search Optimization (U-CSO) algorithm is employed to select the optimal features based on the global fitness function, which helps increase the accuracy and reduce the training time of the classifier. Finally, the Most Probabilistic Guided Naïve Distribution (MP-ND) based classification model is utilized for predicting the label as to whether normal or disease affected. During an evaluation, two different datasets, such as PIMA and Hungarian, are used to validate and compare the results of the proposed model by using various performance measures. A Patients' health status can be monitored remotely for disease detection and proper diagnosis
Efficient coal concentration using a short-chain amine-type compound as collector reagent: Flotation and optimization studies
Get PDFThis work presents the flotation of a sub-bituminous coal using 1-butylamine as a short-chain amine collector. The flotation results have been obtained with 1-butylamine (coal yield: 100%) and compared with those achieved with a quaternary amine (coal yield: 95.4%), kerosene (coal yield: 100%) and diesel (coal yield: 95.7%). The best results have been obtained with 1-butylamine. Less depressant effect has been observed with 1-butylamine. The FTIR signals have been attenuated when the coal is conditioned with 1-butylamine. Zeta potential measurements have also been changed after conditioning. The contact angle of water and graphite has decreased from 82.3° to 32.2°. An optimization has been performed using a Box-Behnken experimental design. Flotation has significantly affected by time and collector dosage. The pH is not a significant factor. The optimal conditions for the best efficiency using 1-butylamine as a collector are 2.0 min of flotation and 10-3 mol/L of collector
Adsorption of methylene blue dye onto acid-treated tej residue: Kinetic, equilibrium and thermodynamic study
Get PDFDye-containing wastewater is a very toxic and a major threat to the deterioration of water quality and makes it unsuitable for domestic purposes. This drives low cost and eco-friendly adsorbents from environmental waste have been investigated to treat dye-containing wastewater. In the present study, tej residues (TR) have been successfully employed as a natural and non-conventional low-cost adsorbent for the removal of methylene blue (MB) dye from an aqueous solution. Optimization of maximum operating condition has been carried out by batch mode experiment and the result shows maximum removal efficiency of 82.1821 % at pH 8.0, adsorbent dosage 0.4g, initial dye concentration 20 ppm, contact time 60 min, and temperature 25°C on the acid-treated surface of tej residue. Adsorption kinetics of the adsorbent has been evaluated by pseudo-first-order, pseudo-second-order and intra-particle diffusion, and it is observed that the pseudo-first-order kinetic model is better fitted with a good correlation coefficient, and the equilibrium data fitted well with the Freundlich isotherm model. The Langmuir isotherm model estimates that the maximum adsorption capacity of the monolayer is found to be 215.053 mg/g. Thermodynamics parameters such as ΔG0, ΔH0 and ΔS0 indicate that the sorption process is feasible and exothermic
Characterisation and microbial activity of neem oil nano-emulsions formulated by phase inversion temperature method
Get PDFThis study has been carried out to prepare neem oil-in-water nano-emulsions stabilized by Brij 30 surfactant using the phase inversion temperature (PIT) method at three different temperatures, i.e., 60, 75 and 80°C. Compositions of homogenous phase have been identified in the pseudo-ternary phase diagram. Among the total seventeen formulations, three formulations (NB1, NB2 and NB3) have been short-listed and characterized for emulsion size and viscosity. The selected formulations have shown emulsion size of 348-981 nm in diameter. The volume percentage ratio of Brij 30 to neem oil have shown significant effect on the droplet size of nano-emulsions. Formulations having lower concentration of Brij 30 have displayed a smaller emulsion droplet size (348 nm). The NB3 formulation (4% neem oil, 11% Brij 30 and 85% deionized water) has exhibited the highest stability after 60 days of storage. Antimicrobial study has shown that in contrast to raw neem and Ampicillin (synthetic drug), NB1 exhibited best result in terms of minimum inhibition concentration (MIC) reduction by 100% against E-coli, P. aeruginosa, S. aureus and S. pyogenus
