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Experimental studies on combustion performance of beeswax-paraffin blended solid fuels in a hybrid rocket
Get PDFThe study intends to investigate the physical, chemical and thermal characteristics of paraffin blended fuels to determine their suitability as a solid fuel in a hybrid rocket. Wax fuels are a viable and efficient alternative to conventional rocket fuels, having excellent structural strength and thermal and mechanical properties. By utilizing both axial and swirl injection technique, the combustion performance of paraffin – beeswax blended fuels have been tested with a fabricated cylindrical grain in a laboratory-scale rocket setting along with oxygen. The test outcomes revealed solid fuel compositions of more beeswax content in paraffin wax on an oxygenated gaseous environment with a swirl-flow injection method has the highest average regression rate of 1.649 mm/sec at 181 kg/m2s mass flux. Axially injected oxygen with pure paraffin wax has the lowest value of 0.85 mm/sec at 96 kg/m2s. The regression rate comparisons revealed that oxygen injection by a swirl injector increased the regression rates by 40% for mass fluxes greater than 80 kg/m2s. Compared to other studies, the combustion efficiencies have been obtained in this study are good. Blended fuels can manage and increase combustion efficiencies for axial and swirl flow conditions. Swirl injectors outperform axial injectors for oxygen injection and allow for a higher proportion of Beeswax combined with paraffin. This study exclusively designed and manufactured an axial injector and swirl injector, according to the required dimensions of a lab-scale hybrid rocket's combustion chamber, injector, and exhaust nozzle, and their performances have been evaluated
Patent Waiver on Covid Vaccine: Access for all or Global Supply Crisis?
Get PDFThe Coronavirus disease 2019 or COVID-19, pandemic has transpired disastrous effects in the world in multiple forms ranging from the high death tolls to the steep fall in global economy. Even so, it had managed to provide a silver lining in the form of unanimity of researchers from several disciplines, who united to contribute blood, sweat and tears to present to the world the miracle of science- vaccines. One can only imagine the extent of investment which has gone into development of the few vaccines we have today. In fact the research continues to be in full swing, with the hope and zest to better. While every country fights the pandemic with vigor, it is the pharmaceutical R&D which is expected of breakthrough discoveries as a solution. Where the pressure to succeed is tremendous, millions invested and no option to fail is it not justified to expect and deserve patent for the same. This paper will dwell into the justification of patent over Covid-19 vaccines, the ongoing debate over patent waiver and analyze whether the waiver will in fact facilitate greater access and affordability of vaccines or prove to be an impediment for global supply
Enhanced antitumor effect of curcumin loaded solid lipid nanoparticles in Dalton’s ascites lymphoma mice
Get PDFCurcumin is widely known for its antibacterial, antioxidant and anti inflammatory effects and has been reported to possess anticancerous activity as well. However, its medical application is limited because of poor bioavailability and rapid metabolism. In this study, we encapsulated curcumin in solid lipid nanoparticles and studied its anticancerous effect in Dalton’s Ascites Lymphoma (DAL) mice model. The physicochemical characteristics of curcumin solid lipid nanoparticles (CUR-SLN) were assessed and the anticancer efficacy was determined by in vivo studies. The curcumin solid lipid nanoparticles were synthesized by solvent emulsification evaporation method with particle size less than 100 nm. Antitumor effect of nanocurcumin (50 mg/kg) and curcumin (100 mg/kg) was evaluated in Dalton’s Ascites Lymphoma bearing mice. Pathological and immunohistochemical parameters were studied. Mean survival time and percentage increase in lifespan were assessed. Nanocurcumin group showed more significant influence in reducing tumor volume and weight, inducing apoptosis, reducing angiogenesis and invasion restoring antioxidant parameters and increased mean survival time. Curcumin and nanocurcumin inhibited the activation of nuclear factor-kappa B (Nf-kB), and thereby proved the pathway by which it induced anti-angiogenic and anti-invasive property
A Comprehensive Review on Audio based Musical Instrument Recognition: Human-Machine Interaction towards Industry 4.0
Get PDFOver the last two decades, the application of machine technology has shifted from industrial to residential use. Further, advances in hardware and software sectors have led machine technology to its utmost application, the human-machine interaction, a multimodal communication. Multimodal communication refers to the integration of various modalities of information like speech, image, music, gesture, and facial expressions. Music is the non-verbal type of communication that humans often use to express their minds. Thus, Music Information Retrieval (MIR) has become a booming field of research and has gained a lot of interest from the academic community, music industry, and vast multimedia users. The problem in MIR is accessing and retrieving a specific type of music as demanded from the extensive music data. The most inherent problem in MIR is music classification. The essential MIR tasks are artist identification, genre classification, mood classification, music annotation, and instrument recognition. Among these, instrument recognition is a vital sub-task in MIR for various reasons, including retrieval of music information, sound source separation, and automatic music transcription. In recent past years, many researchers have reported different machine learning techniques for musical instrument recognition and proved some of them to be good ones. This article provides a systematic, comprehensive review of the advanced machine learning techniques used for musical instrument recognition. We have stressed on different audio feature descriptors of common choices of classifier learning used for musical instrument recognition. This review article emphasizes on the recent developments in music classification techniques and discusses a few associated future research problems
EEG Signal Classification Automation using Novel Modified Random Forest Approach
Get PDFDigitalization and automation are the two aspects in the medical industry that define compliance with industry 4.0. Automation is essential for speeding up the diagnosis process, while digitalization leads to smart medicine and efficient diagnosis. Epilepsy is one such disease that can use these automation techniques. The automatic monitoring of epilepsy EEG is of great significance in clinical medicine. Aiming at the non-stationary characteristics of EEG signals, the classification of EEG signals is based on the combination of overall empirical mode. It is proposed using the random forest method. The EEG signal data set has an epileptic interval over 200 single-channel signals with a seizure period. A total of 819,400 data are used as samples. First, the overall epileptic EEG signal modal is decomposed into multiple intrinsic modal functions. The effective features are extracted from the first-order intrinsic modal function. Finally, random forest and Least Square SVM (LS-SVM) are considered to classify the EEG signals characteristics. The correct recognition rate of random forest and LS-SVM is compared. The results show that random forest classification method has an ideal classification effect on epilepsy EEG signals during and between seizures. The recognition accuracy is 99% and 60%, which is higher than the accuracy of the LS-SVM. The proposed method improves clinical epilepsy. The efficiency of EEG signals analysis
Automated Evaluation of Surface Roughness using Machine Vision based Intelligent Systems
Get PDFMachine vision systems play a vital role in entirely automating the evaluation of surface roughness due to the hitches in the conformist system. Machine vision systems significantly abridged the ideal time and human errors for evaluation of the surface roughness in a nondestructive way. In this work, face milling operations are performed on aluminum and a total of 60 diverse cutting experiments are conducted. Surface images of machined components are captured for the development of machine vision systems. Images captured are processed for texture features namely RGB (Red Green Blue), GLCM (Grey Level Co-occurrence Matrix) and an advanced wavelet known as curvelet transforms. Curvelet transforms are developed to study the curved textured lines present in the captured images and this module is capable to unite the discontinuous curved lines present in images. The CNC machined components consists of visible lay patterns in the curved form, so this novel machine vision technique is developed to identify the texture well over the other two extensively researched methods. Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) intelligent models are developed to evaluate the surface roughness from texture features. The model average error attained using RGB, GLCM, Curvelet transform-based machine vision systems are 12.68, 7.8 and 3.57 respectively. In comparison, the results proved that computer vision system based on curvelet transforms outperformed the other two existing systems. This curvelet based machine vision system can be used for the evaluation of surface roughness. Here, image processing might be crucial in identifying certain information. One crucial issue is that, even as performance improves, cameras continue to get smaller and more affordable. The possibility for new applications in Industry 4.0 is made possible by this technological advancement and the promise of ever-expanding networking
Stability indicating HPLC method for the simultaneous analysis of Gatifloxacin and Loteprednol in eyedrop formulation using design of experiment approach
Get PDFDesign of experiment (DOE) assisted simple, rapid, precise and accurate stability indicating HPLC method has been developed for simultaneous estimation of Gatifloxacin (GTF) and Loteprednol (LOT) along with their forced degradation products. The developed method has been optimized and developed by using central composite design (CCD) in response surface methodology (RSM). Trails have been undertaken and ratio of phosphate buffer in mobile phase, pH of buffer and flow rate are selected as factors. Resolution, tailing factor (GTF) and tailing factor (LOTE) are selected for determining the system response in the process of method optimization. The responses have been optimized using the Derringer’s desirability function. The effective separation is achieved on Phenomenex EVO-C18 column (250 mm x 4.6 mm i.d, 5 μm particle size) with mobile composed of 10 mM phosphate buffer, pH 3.5 and organic phase composed of mixture of acetonitrile and methanol 60:40 % v/v, the flow rate was 1.0 mL/min, the signals were detected at 267 nm. The developed method was validated for linearity, accuracy, precision, and robustness. The method was applied successfully for stability samples
Modeling and Control of PV Emulator with Different Controllers and Transient Load Conditions
Get PDFTo keep up with the pace of renewable energy, PV Emulators are encouraged during the design and installation stages. Short circuit current, maximum power point and open circuit voltage are required to analyze the complete characteristic plot of PV panel.This paper focuses on the modeling and control of PV Emulators, as well as the comparison of the results obtained by implementing P,PI, PID and FOPID as conventional controllers with AI-based PSOPI, PSOPID and ANFIS controllers. This work will aid in minimizing time, cost and on-site constraints, allowing timely installation of PV panels after covid. Another distinguishing feature of this paper is the comparative analysis of designed models with various control strategies and their associated performance indices over complete range of PV characteristics
Green synthesis of 5-methylpyridinium derivatives by C2-functionalization of pyridine-1-oxide derivatives and their antibacterial activity
Get PDFAn innovative green economic route has been developed for one pot multicomponent synthesis of 5-methylpyridinium derivatives by the reaction of 3-methylpyridine-1-oxide, aromatic aldehyde and β-ketoester catalysed by different ionic liquids (ILs), [BMIM][OH], [BMIM][Cl], [BMIM][Ac] in good to excellent yields. A relative study reinforced that [BMIM][OH] is the best IL for this C2-functionsalization reaction. The main highlights of this synthetic protocol are simple work-up, cost effectiveness and environmentally benign processing. The synthesized derivatives have been assessed for possible antibacterial activity against Staphylococcus aureus and Escherichia coli by using the microdilution method. The results of antibacterial activity suggests that compound 4I shows best antibacterial activity and other compounds show good to moderate activity
Synthesis and characterization of bioactive isoxazole and 1,3,4-oxadiazole heterocycle containing scaffolds
Get PDFHerein we disclosed the design, synthesis, and study of the biological property of isoxazole and 1,3,4-oxadiazole containing framework. Set of 2-(4-(4-nitrophenoxy)phenyl)-5-(4-(5-(4-(pentyloxy)phenyl)isoxazol-3-yl)phenyl)-1,3,4-oxadiazole derivatives have been constructed. Synthesized compounds have been screened for anti-fungal and anti-bacterial activities. Among them, Compound 8a have shown excellent anti-fungal activity against C.albicans fungi. And 8b and 8c exhibited significant anti-bacterial activity with MIC 50 μg/mL against S. pyogenus and S. aureus pathogens, respectively.