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Design and Optimization of Friction Stir Welding of Al-Cu BUTT Joint Configuration using Taguchi Method
Friction stir welding (FSW) is a solid-state welding technique in which the joint quality was predominantly subjected to heat formation throughout the metal welding process. The weld joint produced from FSW was better than the other fusion welding process. In this research, the base plates AA6101 and C11000 of 5 mm thickness were joined using the hardened oil-hardened non-shrinkable steel(OHNS) tool by the FSW method. The design of experiment (DOE) was used to optimize the input parameters such as tool rotational speed (rpm), feed rate (mm/min), and tool pin offset (mm) on output parameter ultimate tensile strength (UTS). The design of experiment (DOE) was carried out by employing a Taguchi L9 orthogonal array, three factors, and three levels for obtaining a quality joint with good strength. The results of nine trial runs from the Taguchi experimental approach were formulated and analyzed using the statistical tool analysis of variance (ANOVA) using MINITAB 19 software. ANOVA analysis was employed to find the contribution of the input parameters toward the output. The optimized input process parameters will help to create effective weld joints. This study revealed that tool pin offset towards softer metal at medium tool rotational speed would create joints with the highest UTS. Scanning Electron Microscope (SEM) was applied to investigate the structural changes in the FSW of Al-Cu joints. 2022, Books and Journals Private Ltd.. All rights reserved. -
What is Remembered in Pandemic: A Commentary on the Mediated Memories of Piety in COVID-19
The paper explores how the experiences of the present pandemic are shaped by the memories of popular religious piety during past pandemics and epidemics. Taking insights from the works of Astrid Erll and Reinhart Koselleck, the process remembering-imagining system within the context of the pandemic is discussed by tracing the reemergence of pandemic deities and narratives of piety in India. Using digitally documented and disseminated narratives on piety emerging during COVID-19, an attempt is made to understand how these narratives shape the experiences, responses, and collective memory of the pandemic. Through a discussion of the shift in the imagination of political leadership and the moral responsibilities of the community, an attempt is made to highlight the mode in which the narratives on piety shape the contours of a time that is otherwise unimaginable. The mediated memories of popular religious piety make it possible to remember similar crisis times and to imagine and reinstate the social order that is threatened by this sudden unimaginable crisis. The paper thus argues that within the context of India, popular religious piety, though often overlooked, becomes a significant part of making sense and shaping the experiences of the pandemic time. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Garlic peel based mesoporous carbon nanospheres for an effective removal of malachite green dye from aqueous solutions: Detailed isotherms and kinetics
Biowaste based nanoadsorbents have gained much attention in the recent times for wastewater decolourization owing to their low cost, high surface area and high adsorption capacities. In the present research, garlic peel based nanoparticles (GCNP) were synthesized at different temperatures by a one step pyrolytic green approach for the effective removal of cationic dye, malachite green from the aqueous medium. The surface properties of Garlic nanoparticles were elucidated by N2 adsorption- desorption and all the GCNP samples were found to exhibit Type IV(a) isotherm indicating the presence of mesopores in carbon matrix. Using BET calculations, highest surface area (380 m2/g) was obtained for GCNP synthesized at 1000 ?C. Characterization of nanoparticles was done by XRD, EDAX, SEM and FTIR studies before and after the dye treatment. Adsorption studies conducted using different parameters like contact time, concentration and pH and dosage of adsorbent showed removal efficiency above 90% for the contact time of 70 min. Best adsorption experimental results were obtained for GCNP synthesized at 1000 C ascribable to its high surface area, higher total pore volume (0.26 cm2/g) and higher carbon content. Four adsorption isotherm models were used to validate batch equillibrium studies and the results showed data in good agreement with Langmuir and Freundlich isotherms with maximum Langmuir adsorbtion capactiy to be 373.7 mg/g. Kinetic modelling of the data showed best fit with the Pseudo second order model with rate constant value of 48.726 g mg?1 min?1. Regenerative studies were conducted conducted upto 6 cycles. Also the GC nanoparticles were tested for their compatibility in membrane form wherein, removal efficiency results were obtained for GCNP anchored in polyvinyl difluoride (PVDF) and polysulfone (PSF) membrane matrix for dye adsorption. 2022 Elsevier B.V. -
Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model
At these times, internet of things (IoT) technologies have become ubiquitous in the healthcare sector. Because of the increasing needs of IoT, massive quantity of patient data is being gathered and is utilized for diagnostic purposes. The recent developments of artificial intelligence (AI) and deep learning (DL) models are commonly employed to accurately identify the diseases in real-time scenarios. Despite the benefits, security, energy constraining, insufficient training data are the major issues which need to be resolved in the IoT enabled medical field. To accomplish the security, blockchain technology is recently developed which is a decentralized architecture that is widely utilized. With this motivation, this paper introduces a new blockchain with DL enabled secure medical data transmission and diagnosis (BDL-SMDTD) model. The goal of the BDL-SMDTD model is to securely transmit the medical images and diagnose the disease with maximum detection rate. The BDL-SMDTD model incorporates different stages of operations such as image acquisition, encryption, blockchain, and diagnostic process. Primarily, moth flame optimization (MFO) with elliptic curve cryptography (ECC), called MFO-ECC technique is used for the image encryption process where the optimal keys of ECC are generated using MFO algorithm. Besides, blockchain technology is utilized to store the encrypted images. Then, the diagnostic process involves histogram-based segmentation, Inception with ResNet-v2-based feature extraction, and support vector machine (SVM)-based classification. The experimental performance of the presented BDL-SMDTD technique has been validated using benchmark medical images and the resultant values highlighted the improved performance of the BDL-SMDTD technique. The proposed BDL-SMDTD model accomplished maximum classification performance with sensitivity of 96.94%, specificity of 98.36%, and accuracy of 95.29%, whereas the feature extraction is performed based on ResNet-v2 World Scientific Publishing Company. -
Finite Element Analysis of Hybrid Skin Sandwich Composite
Sandwich structured composite is a particular classification in composite materials. This type of structure has been mainly used in recent studies because of its high specific strength, low density, and stiffness. It is increasingly more commonly employed in structural designs due to its features and performance. The sandwich composites used in this investigation are made of aluminium alloys and areca fibre. The sandwich composites face sheet comes in a variety of thicknesses. The adhesive skin layer is also varied to investigate the effect of using natural fibre. The sandwich composite is subjected to 3 point bend test. The modal analysis is investigated using the finite element method. The 3D model of sandwich composites is modelled using solid works 2020. Using Altair Hyper Works, the boundary conditions and meshing is carried out. ANSYS Mechanical APDL is used to analyse the sandwich composites. This investigation analyses the behaviour of composite sandwich beams. 2022, Books and Journals Private Ltd.. All rights reserved. -
Investigation on window opening behavior in naturally ventilated hostels of warm and humid climate
A window is an inevitable element of a naturally ventilated building, and its usage improves indoor environmental conditions. Various research has presented window opening behavior models, stating that it may vary with region, climate, season, building type and many more environmental and non-environmental factors. Major studies in India relied on survey data and were not focused on continuous monitoring. Limited occupants behavior studies have been reported in warm and humid climatic zones, specifically in hostel buildings. Also, a realistic description of occupants window opening behavior is require for more accurate evaluation of building performance using energy simulation. Therefore, there is a need to study the window opening behavior to predict the indoor environment more accurately by using energy simulation tools. In this context, a one-year field research involving questionnaire survey, physical observation, and monitoring was conducted in different hostel buildings in Tiruchirappalli, India. Logistic models were developed to predict the window state in hostel buildings in warm and humid region based on physical observational and long-term monitoring data. It is found that window use is influenced by season, time of the day, weekdays, floor level, buildings orientation, user type, and gender. Results also showed that insects and animal menace (snakes, squirrels, lizards, mosquitoes etc.) impede window opening behavior. The study also presented a logistic model for window opening behavior based on outdoor environment conditions for simulation modeling. 2022 Elsevier B.V. -
Compositionally Homogeneous Soft Wrinkles on Elastomeric Substrates: Novel Fabrication Method, Water Collection from Fog, and Triboelectric Charge Generation
Functionality and stimuli-response of natural and artificial elastomeric materials depend significantly on the morphology of their surfaces. Structural transformability and tunable responsiveness of wrinkles on elastomeric materials can enable numerous applications in flexible electronics, optics, and adhesives. Currently existing fabrication techniques rely on sophisticated instrumentation, complex experimental setups, and expensive reagents. These methods are limited in terms of mechanical robustness of the wrinkles produced. Here, a simple, inexpensive, scalable, and reproducible strategy, making use of buckling instability for the creation of soft surface wrinkles on polydimethylsiloxane (PDMS), is presented. PDMS with lower elastic modulus is spin-coated onto a mechanically stretched film of PDMS with a higher elastic modulus. Thermal curing followed by the release of prestrain resulted in the formation of wrinkles in the top layer of the PDMS. The hydrophobic soft surface wrinkles with compositional homogeneity exhibit efficient fog water collection and triboelectric charge generation useful for the preparation of triboelectric nanogenerator devices. Furthermore, the substrates show high mechanical stability and mechanoresponsive optical behaviors. The simplicity and general applicability of the method presented here is expected to establish a promising pathway toward the formation of soft wrinkles in other elastomeric systems also, facilitating important applications in various fields. 2022 Wiley-VCH GmbH. -
Establishment of Mucuna pruriens (L.) DC. callus and optimization of cell suspension culture for the production of anti-Parkinsons drug: L-DOPA
It has become a huge challenge to satisfy the emerging demand for levo-3,4-dihydroxyphenylalanine (L-DOPA), an anti-Parkinsons drug in the international drug market. This is attributed to the conventional methods of extraction from the natural sources of Mucuna spp., which has a low germination rate, less viable seeds, and an irritating, itching trichomes on the pods. The need for an alternative method with continuous supply of L-DOPA without affecting the natural biodiversity has been achieved through in vitro procedures. However, there has not been a systematic approach to optimize the cultural conditions for the maximum productivity. Hence, in this study, we aim at optimizing the cultural conditions for high biomass and L-DOPA production. Various plant growth regulators such as auxins (indole acetic acid, indole butyric acid, picloram [Pic], naphthalene acetic acid, and 2,4-Dichlorophenoxyacetic acid), cytokinins (kinetin, benzylaminopurine, 2-isopentenyl adenine, and thidiazuron), and their combinations have been experimented to figure out the best combination to induce callus. At the same time, various factors such as growth kinetics, different media (MS, Gamborgs-B5, Chus-N6, and Nitsch and Nitsch), media strength (0.5, 1.0, and 2.0X), effect of different macro elements and their strength (0, 0.5,1, 1.5, 2, and 3X), inoculum density, different hydrogen ion concentration (pH), ammonium/nitrate concentration, different sucrose concentrations (010%), and other carbon sources have been investigated in detail for optimizing the cell suspension culture. It was found out that 0.5 mg/L Pic gave the best results for callus induction. With respect to biomass, 6-week growth period (135.7 g/L fresh weight [FW]), 1.0X MS media (126.87 g/L FW), 1.5X magnesium sulfate (266.3 g/L FW), ammonium/nitrate ratio of 21.57/18.8 mM (131.4 g/L FW), pH of 6.0 (129.47 g/L FW), 100 g/L of inoculum (222.2 g/L FW), 3% sucrose concentration (125.6 g/L FW), and 3% glucose (183.4 g/L FW) as other carbon sources were found to give the highest biomass. In terms of L-DOPA production, 3-week growth period (5.90 mg/g dry weight [DW]), 0.5X B5 medium (4.27 mg/g DW), 2.0X calcium chloride (5.06 mg/g DW), ammonium/nitrate ratio of 21.57/18.8 mM (3.44 mg/g DW), pH 6.5 (4.02 mg/g DW), inoculum density of 30 g/L (4.79 mg/g DW), and 2% sucrose (5.17 mg/g DW) resulted in a higher L-DOPA yield. 2022 Rakesh and Praveen. -
Decoding the X-Ray Flare from MAXI J0709-159 Using Optical Spectroscopy and Multiepoch Photometry
We present a follow-up study on the recent detection of two X-ray flaring events by MAXI/Gas Slit Camera observations in soft and hard X-rays from MAXI J0709-159 in the direction of HD 54786 (LY CMa), on 2022 January 25. The X-ray luminosity during the flare was around 1037 erg s-1 (MAXI), which got reduced to 1032 erg s-1 (NuSTAR) after the flare. We took low-resolution spectra of HD 54786 from the 2.01 m Himalayan Chandra Telescope and the 2.34 m Vainu Bappu Telescope (VBT) facilities in India, on 2022 February 1 and 2. In addition to H? emission, we found emission lines of He i in the optical spectrum of this star. By comparing our spectrum of the object with those from the literature we found that He i lines show variability. Using photometric studies we estimate that the star has an effective temperature of 20,000 K. Although HD 54786 is reported as a supergiant in previous studies, our analysis favors it to be evolving off the main sequence in the color-magnitude diagram. We could not detect any infrared excess, ruling out the possibility of IR emission from a dusty circumstellar disk. Our present study suggests that HD 54786 is a Be/X-ray binary system with a compact object companion, possibly a neutron star. 2022. The Author(s). Published by the American Astronomical Society. -
The convective heat transfer analysis of the casson nanofluid jet flow under the influence of the movement of gyrotactic microorganisms
Jet flows provide an effective mode of energy transfer or mass transfer in industrial applications. When compared to traditional cooling through convection, jet flows have high heat and mass transfer coefficients. Further, the devices equipped with jet flow provides efficient use of fluid and also offers enhanced heat and mass transfer rates. Hence in this study, the jet flow of Casson nanofluid containing gyrotactic microorganisms that stabilises the nanoparticle suspension is discussed. To control the fluid from outside external magnetic field is imposed. The model with these characteristics are useful in the appliances like coolants in automobiles, nuclear reactors, micro-manufacturing, metallurgical process etc. Such a model is created by employing PDE, which are then transformed into a system of ODE. The DTM is employed to obtain the solution to system of equations, and the results are interpreted using graphs. It is perceived that the velocity of the nanofluid flow is decreased because of the increased yield stress created by the greater values of the Casson parameter. As a result, the temperature profile is found to be increasing. Meanwhile, it is observed that for increased value of chemical reaction parameter diminishes the nanoparticle concentration. The motile density is found to decrease for increase in the Peclet number and the bioconvection Schmidt number. Further, the thermophoresis improves the temperature and concentration profile of the nanofluid. 2022 Indian Chemical Society -
Being socially responsible: How green self-identity and locus of control impact green purchasing intentions?
This paper investigates the influence of green self-identity (GSI) and two attributes of locus of control, namely external environmental locus of control (ExLOC) and pro-environmental locus of control (PELOC), to predict perceived consumers effectiveness (PCE) on green purchase intentions (GPI) using attribution theory. For this study, data from 391 Indian consumers were analyzed using PLS-SEM via SMARTPLS version 3.2.9. Results show that GSI positively influences both ExLOC and PELOC. Furthermore, both aspects of locus of control are significant positive predictors of PCE and have partial mediation roles. The results not only imply comprehensively expound the process of green buying intentions of consumers through self-identity but also addresses the process of attribution. The study applied the Importance Performance Map Analysis (IPMA) to compare the relative importance and performance of three antecedents (i.e., ELOC, GSI, and PCE). The finding is of utmost importance for practitioners and public authorities to design more focused strategies to increase GPI among the masses to enhance the sales of green products. 2022 The Authors -
Assessing transmission excellence and flow detection based on Machine Learning
Excellence in transmission can be assessed in optical transport networks before providing any additional connections or upgrading the connections. Generally, the Physical Layer Model (PLM) is used to assess the transmission quality which has high probability in uncertainty and inaccuracy due to the circumstances of physical layer. The network efficiency is directly proportional to the margins. If the margins getting increases in the PLM, the efficiency of the network decreases. Maintaining the excellence in transmission is the biggest challenge when the margins getting increased. Other significant factors for excellence in transmission is scalable, minimum latency with maximum speed and energy efficient. Photonic switching is a hopeful solution for handling these challenges. Machine learning technique is proposed to assess the excellence of transmission and flow detection. ML-E and Precedence based scheduling algorithms are proposed for excellence of transmission and flow detection respectively. The proposed techniques justify variations, uncertainties in kits like fiber dilution, dispersion and optimizes PSON (packet switched optical network). Simulation results are demonstrated and the proposed work results indicates that it can outperform a benchmark in all aspects. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Preparation, characterization, and electrochemical properties of PEO/PVDF blend films
This paper reports the electrochemical properties of PEO, PEO/PVDF10, and PEO/PVDF30 blend films, The XRD spectra reveal the structural properties of the blend and, FTIR spectra provide the chemical interaction between the blends, and observed FESEM images of PEO/PVDF blend film shows the porous with spherulite grain structure and AFM images gives the surface topology. The thermal stability, melting point, and decomposes of the polymer blend film were examined through TGA, DTA, and DSC. CV curve shows the proper oxidation and redox reaction involved in the blend film, these results provide the prepared polymer blend film is a good candidate for used to the separator in energy storage applications. 2022 Elsevier B.V. -
Impact of COVID-19-Related Distress on Anxiety and Depression of College Students
The current study explores the impact of COVID-19 related distress factors on the mental well-being of college students. For the purpose of the study, mental well-being is measured through the depression symptoms and general anxiety levels of the students. The study used judgemental sampling to identify the respondents of the study. The final sample consisted of 147 respondents and the data was analysed on SPSS. The results suggested that while COVID-19 distress factors were not significant in predicting the level of depression symptoms experienced by the students, the general anxiety levels were significantly impacted by the distress factors. The findings are particularly useful for the teachers and institutions working to connect and teach through online platforms. 2022, Commonwealth of Learning. All rights reserved. -
FISCAL PERFORMANCE OF PANCHAYATI RAJ INSTITUTIONS (PRIs): AN EMPIRICAL ANALYSIS OF THE STATE OF ANDHRA PRADESH IN PRE AND POST-BIFURCATION PERIOD
The effectiveness of democratic decentralisation depends on the financial strength and independence of the local bodies. Financial autonomy is vital to reap the full potential benefits of decentralisation as the transfer of funds, functions, and functionaries will enable local bodies to be institutes of self-governance and not just delivery mechanisms. In the context of persistent fiscal distress across the local bodies, an attempt is made to empirically examine the fiscal performance of Panchayati Raj Institutions (PRIs) in Andhra Pradesh during 2010-11 to 2017-18, i.e. pre- and post-bifurcation periods of the State. The fiscal autonomy and the revenue dependency of PRIs across all three tiers in the State during the same period was also analysed. The study finds that the fiscal autonomy of top tiers, i.e. Mandal Praja Parishads (MPPs) and Zilla Praja Parishads (ZPPs) is negligible in both periods, while Gram Panchayats showed relatively better fiscal autonomy in both periods. 2022 National Institute of Rural Development. All rights reserved. -
Marine macrolides as an efficient source of FMS-like tyrosine kinase 3 inhibitors: A comprehensive approach of in silico virtual screening
Marine organisms are a definitive source of antibiotics and kinase inhibitors which provide cues for discovering novel drug leads. Marine macrolides are getting much attraction due to their enzyme inhibitory potential. The present study comprehensively dealt with the virtual screening and structure-based prediction of macrolide compounds against FMS-like tyrosine kinase 3 receptors (FLT3). The FLT3 was chosen as a biological target against the 990 marine macrolides. Before the virtual screening of macrolide compounds, validation of molecular docking was carried out by re-docking of co-crystallized Gilteritinib within the FLT3. Among the selected 990 candidates of marine macrolides, 311 were failed due to the generation of insufficient conformers. Amongst the successful compounds, 22 compounds were also failed to dock within the receptor, while the remaining 657 marine macrolide entities elicited successful docking. The HYBRID Chemguass4 Score ranged from -10.17 to -0.02. This vast difference in the HYBRID ChemGuass4 score is attributed to the difference in binding potential with the receptor's binding pocket. The top ten compounds were selected based on the HYBRID ChemGuass4 Score lower than -8.0 against FLT3. The pharmacokinetics and ADME properties revealed the drug likeliness of the macrolides. 2022 SAAB -
SR-Mine: Adaptive Transaction Compression Method for Frequent Itemsets Mining
Extraction of frequent itemsets is a key step in association rule mining. Frequent Pattern (FP) mining from a very large dataset is still a challenging research problem. The basic frequent itemset algorithms are Apriori and FP-growth. FP-growth uses Frequent Pattern Tree (FP-tree) to store the database information in a compressed form. A large number of research papers have been proposed as an improvement of the basic frequent itemset mining algorithms. Several researchers have proposed modifications to existing data structures as well as new data structures to improve the mining process. A new method, Size Reduced Mining (SR-Mine), is proposed to speed up the FP-tree creation. The proposed work is implemented with the basic FP-growth algorithm and with the other two recent algorithms based on FP-tree. The three modified algorithms have been tested with standard datasets and compared with the original algorithms. The proposed method can be applied with the frequent itemset mining algorithms which consider each transaction one by one to construct a data structure for mining. The experimental results show that the proposed method can improve the performance of the mining. 2021, King Fahd University of Petroleum & Minerals. -
Performance evaluation of artificial neural networks in sustainable modelling biodiesel synthesis
Biodiesel is a characteristic and inexhaustible homegrown fuel removed from creature fats or vegetable oil and liquor through a transesterification response. The exploration work means to assess the exhibition of biodiesel blend. In this paper, biodiesel was displayed and improved by utilizing a hereditary calculation and Artificial Neural Network (ANN). In AI, hereditary calculations and counterfeit neural organizations assume a significant part in displaying biodiesel blend. To upgrade an excellent arrangement hereditary calculation was created. The mix of ANN and Genetic Algorithm gives the ideal condition as the temperature of methanol molar proportion, impetus fixation. It tentatively decides the exhibition trademark like the Coefficient of determination and Absolute Average deviation (AAD). It predicts the Fatty Acid Methyl Ester (FAME) model productively than Response Surface Methodology (RSM). The exhibition examination is reenacted and hypothetical outcomes are recorded then it is contrasted with constant information to decide the exactness of ANN. 2022 Elsevier Ltd -
Synthetic Applications of Prins Cyclization in Natural Product Syntheses
The natural products having tetrahydropyran unit with multiple chiral centers serve as magnificent building blocks for various active pharmaceutical ingredients (APIs). Prins cyclization is one of the wonderful strategies to construct tetrahydropyran unit stereoselectively in asymmetric synthesis. In this account, we discuss our research efforts toward the synthesis of various natural products from the past two decades (20052020) by using Prins cyclization as a key step. Further, the synthetic utility of this reaction was investigated and well demonstrated on various molecules successfully. 2022 The Chemical Society of Japan & Wiley-VCH GmbH. -
Experimental Verification of Gain and Bandwidth Enhancement of Fractal Contoured Metamaterial Inspired Antenna
The performance of any antenna cannot be completely assessed purely on the basis of simulation results. All simulations are made by assuming an ideal environment where the fabrication tolerances and practical losses are not accounted for. Therefore, evidencing the performance experimentally becomes a crucial step. In this work, the experimental validation of a fractal contoured square microstrip antenna with four ring metamaterial structure, hereon referred to as optimized metamaterial inspired square fractal antenna has been presented. It is an extension to previously designed antenna and aims to experimentally verify the enhanced gain and bandwidth of this antenna. The design and simulation of the proposed antenna was accomplished by using Ansys HFSS v18.2. The end-to-end antenna spread area is 23 mm x 23 mm on a 46 mm x 28 mm x 1.6 mm FR4 substrate with ?r of 4.4. The simulated design was fabricated using Nvis 72 Prototyping Machine and measured in an anechoic chamber facility using vector network analyzer. The antenna resonates with the deepest S11 of-39.5 dB in a broad bandwidth of 2.53 GHz from 2.265 GHz to 4.79 GHz with experimental verification. The proposed antenna provides an enhanced gain of 8.81 dB at the most popularly used frequency of 2.5 GHz. The simulation and experimental results of resonance, gain and radiation pattern are found to agree maximally. The fractional bandwidth offered by this proposed antenna is 72.28%. The experimental validation confirms enhanced gain-bandwidth performance in a wide resonance band. Hence, this antenna is well recommended for wireless, energy harvesting rectenna and sub-6 GHz (2.5 GHz to 4.20 GHz) 5G applications. 2022, Advanced Electromagnetics. All rights reserved.