Mechanical Properties and Metallurgical Characterization of Dissimilar Welded Joints between AISI 316 and AISI 4340

In the present study, the influence of six different process parameters and three interactions on joint tensile strength, toughness, fusion zone microhardness variation are studied during dissimilar tungsten inert gas welding between austenitic stainless steel AISI 316 and alloy steel AISI 4340. Detailed experimental study using fractional factorial experimental design and subsequent statistical analysis show that higher tensile strength, toughness can be achieved using ER 309 filler material and suitably selecting the other process parameters and heating conditions. Addition of small proportion of hydrogen in shielding gas increases the heat transfer efficiency, melting and subsequent penetration. Preheating of AISI 4340 material reduces the chance of solidification cracking and post-heating helps to improve the joint mechanical property. Microstructural observations show that improper selection of process parameters may lead to micro-pores and degrade the joint quality. Successful joining of the dissimilar materials greatly depends on the selection of optimum process parameters, filler material and shielding gas.     

Sensing behavior of silica-coated Au nanoparticles towards nitrobenzene

In the present work, we report silica-stabilized gold nanoparticles (SiO₂/Au NPs) as a wide-range sensitive sensing material towards nitrobenzene (NB). Surface hydroxyl groups of silica selectively form Meisenheimer complex with electron-deficient aromatic ring of NB and facilitate its immobilization and subsequent catalytic reduction by Au cores. Silica-coated Au NPs were synthesized and characterized for their chemical, morphological, structural, and optical properties. SiO₂/Au NPs-modified electrodes were characterized with impedometric and cyclic voltammetric electrochemical techniques. SiO₂/Au NPs are found to have a higher optical detection window of range, 0.1 M to 1 μM and a lower electrochemical detection window of range, 10⁻⁴ to 2.5 × 10⁻² mM with a detection limit of 12.3 ppb. A significant enhancement in cathodic peak current, C ₁, and sensitivity (102 μA/mM) was observed with modified electrode relative to bare and silica-modified electrodes. The I _P was found to be linearly co-related to NB concentration (R ² = 0.985). The interference of cationic and anionic species on sensor sensitivity was also studied. Selectivity in the present sensing system may be further improved by modifying silica with specific functional moieties.     

Potential applications of carbomer in oral mucoadhesive controlled drug delivery system: a review

Carbomers are extensively being used in controlled drug delivery systems (CDDS). They are also finding numerous applications in oral mucoadhesive drug delivery because of their ability to interact with the mucus glycoprotein and to remain localized to a specific site. The present review aims at giving an insight into the potential application of carbomers in mucoadhesive CDDS. This review deals with the physicochemical properties of carbomers and various mechanisms of mucoadhesion. The mechanism for the release of the drug, both water soluble and water insoluble, is discussed. The use of carbomers in oral delivery of peptides or protein-based drugs is also covered.     

Automatic License Plate Recognition System for Vehicles Using a CNN

Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with regard to unusual varieties of license plates or their success at night. We present an efficient ALPR system that uses a CNN for character recognition. A combination of pre-processing and morphological operations was applied to enhance input image quality, which aids system efficiency. The system has various features, such as the ability to recognize multi-line, skewed, and multi-font license plates. It also works efficiently in night mode and can be used for different vehicle types. An overall accuracy of 98.13% was achieved using the proposed CNN technique.     

A Comprehensive Review on Medical Diagnosis Using Machine Learning

The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high accuracy. The use of machine learning could assist the doctors in making decisions on time, and could also be used as a second opinion or supporting tool. This study aims to provide a comprehensive review of research articles published from the year 2015 to mid of the year 2020 that have used machine learning for diagnosis of various diseases. We present the various machine learning algorithms used over the years to diagnose various diseases. The results of this study show the distribution of machine learning methods by medical disciplines. Based on our review, we present future research directions that could be used to conduct further research.     

Processing of materials at cryogenic temperature and its implications in manufacturing: A review

Processing of materials at cryogenic temperature has improved the properties of materials such as hardness, toughness, wear resistance, tensile strength, dimensional stability, corrosion resistance, etc. However, the extent of improvement in the properties of materials subjected to cryogenic treatment as claimed in the literature is diverse and sometimes contradictory to each other. Contradictions have also been reported regarding its various aspects like tempering prior and postcryogenic treatment, tempering temperature, aging before cryogenic treatment and cryogenic parameters like soaking temperature, soaking time, and cooling rate. There is need of investigating the cryogenic treatment in relation to pre and postheat treatment conditions. In this study, an attempt has been made to review the various research articles published in the literature on the subject matter extensively. Cryogenic processing of cutting tools and workpiece material has also emerged as a potential technique for improving the performance of cutting tools during metal cutting as well as for improving the machinability and weldability of workpiece materials. The implications of cryogenic treatment in the perspective of manufacturing have been revealed clearly through review of related studies. The various findings reported in the literature have been highlighted systematically and futuristic directions have been proposed to encourage research work in the area of cryogenic treatment.     

Detection of Social Interaction in Smart Spaces

The pervasive sensing technologies found in smart environments offer unprecedented opportunities for monitoring and assisting the individuals who live and work in these spaces. An aspect of daily life that is important for one's emotional and physical health is social interaction. In this paper we investigate the use of smart environment technologies to detect and analyze interactions in smart spaces. We introduce techniques for collect and analyzing sensor information in smart environments to help in interpreting resident behavior patterns and determining when multiple residents are interacting. The effectiveness of our techniques is evaluated using two physical smart environment testbeds.     

Friction and wear characteristics of jatropha oil-based biodiesel blended lubricant at different loads

Around the globe there is demand for the development of bio-based lubricants, which will be biodegradable, nontoxic, and environmental friendly. This paper outlines the friction and wear characteristics of jatropha biodiesel-contaminated bio-lubricant using a pin-on-disc tribometer. To formulate the bio-lubricants, jatropha oil-based biodiesels were blended at the ratios 4, 12, and 20% by volume with the base lubricant SAE 20 W 40. Tribological characteristics of these blends were carried out at 3.8 m/s sliding velocity and loads applied were 50, 100, and 160 N. Experimental results showed that the lubrication regime that occurred during the test was boundary lubrication while the main wear mechanism was adhesive wear. During testing, the lowest wear was found with the addition of 4 and 12% jatropha oil-based biodiesel, and above this contamination, the wear rate was increased considerably. The addition of 4 and 12% jatropha oil-based biodiesel with the base lubricant acted as a very good lubricant additive, which reduced the friction and wear rate diameter during the test. It has been concluded that JBO 4 and JBO 12 can act as an alternative lubricant to increase the mechanical efficiency at 3.8 m/s sliding velocity and contribute to reducing the dependence on petroleum-based products.     

Release of diltiazem hydrochloride from hydrophilic matrices of polyethylene oxide and carbopol

The mucoadhesion, swelling, and drug release behavior of polyethylene oxide (PEO) and carbopol (CP) matrices were studied using a water soluble model drug diltiazem hydrochloride. The mucoadhesive strength of the matrices increased with increase in polymer content. The results showed that PEO was more mucoadhesive than CP. Mucoadhesion of the tablets was dependent upon the swelling. Swelling was ascertained by measuring the axial and radial expansion of matrix tablets following exposure to media of physiological ionic strength. There was a marked increase in the swelling index of matrices containing high polymer content of PEO as compared to CP. Drug release kinetics were found to be closely related to dissolution and swelling properties of the matrices. The release was found to be non-fickian with n (release exponent) values ranging from 0.45-0.58. At a constant polymer content (15.84% w/w), the main contributing factor for the mucoadhesion, swelling, and release was the amount of PEO.     

ZnO@CdS core–shell thin film: fabrication and enhancement of exciton life time by CdS nanoparticle

In the present study photoluminescence behavior of ZnO and ZnO@CdS core–shell nanorods film has been reported. ZnO nanorods were grown on the glass coated indium tin oxide (ITO) surface by seeding ZnO particle followed with nanorods growth. These nanorods were coated with CdS by chemical bath deposition techniques to have ZnO@CdS thin film and further annealed at 200 °C for their adherence to the ITO surface. The coating was characterized for surface morphology using SEM and optical behavior using UV–visible spectrophotometer. Energy dispersive X-ray (EDX) was used for compositional analysis and time resolve photoluminescence decay for excitons life time measurement. The absorption spectrum reveals that the absorption edge of ZnO@CdS core–shell heterostructure shifted to 480 nm in the visible region whereas ZnO nanorods have absorption maxima at 360 nm. The excitons lifetime of ZnO@CdS was found to be increased with the thickness of the CdS layer on ZnO nanorod. These ZnO@CdS core–shell nanostructures will be of great use in the field of photovoltaic cell and photocatalysis in a UV–visible region.