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Elicitor and precursor-induced approaches to enhance the in vitro production of L-DOPA from cell cultures of Mucuna pruriens
Elicitation and precursor feeding are two important strategies in the in vitro techniques to enhance metabolite production to meet the demand of mankind. The secondary metabolites produced by the plants are extensively used in pharmaceutical, food and agro-chemical industries. One such metabolite is 3,4 dihydroxyphenylalanine (L-DOPA) produced from Mucuna pruriens (L.) DC. is used since ancient times to treat Parkinson's disease. Though all parts produce L-DOPA, the seed has the highest quantity. To overcome the extensive usage of the natural sources whose growth and metabolite production is highly dependent on edaphic and ecological factors, in vitro techniques like establishing cell culture for continuous production of metabolites, precursor feeding and elicitation of cell cultures to enhance the metabolite production has been reported in the present study. Callus was developed from the in vitro leaf explant and cell suspension culture was established in the liquid Murashige and Skoog's medium fortified with 0.5 mg/L picloram. Amino acid precursors like tyrosine, phenylalanine and chemical elicitors like methyl jasmonate, salicylic acid, sodium nitroprusside and silver nitrate were exposed to cell cultures for different periods (3, 6 and 9 days respectively). The precursors showed a better response in enhancing both the biomass and L-DOPA when compared to the elicitors. 500 and 1000 mg/L tyrosine showed a 1.6- and an 8.1-fold increase in biomass and L-DOPA production respectively when supplemented with MS media. However, though all the elicitors enhanced the L-DOPA production by 1.13.3-folds they did not show much significant increase in biomass. Precursor feeding approaches enhanced the metabolite considerably more than the elicitor treatment. Based on the productivity (Biomass L-DOPA conc.) precursors like Tyrosine>Phenylalanine and elicitors like Sodium nitroprusside>Silver nitrate>Methyl jasmonate>Salicylic acid showed better response. 2022 Elsevier B.V. -
A generic cyber immune framework for anomaly detection using artificial immune systems
Intrusion detection systems play a significant role in computer security. Artificial immune systems are the prime contender in developing an anomaly-based intrusion detection system due to their simplicity. The fundamental goal of this paper is to create a generic framework for an artificial immune system which is fast and accurate in detecting anomalies using artificial immune system concepts. Natural killer cells in the immune system and their quick response to foreign pathogens inspired the adaptation of those cells into an artificial immune system based framework. A natural killer cell-based framework is proposed to improve the accuracy and speed of anomaly detection. The structure of the proposed framework includes major histocompatibility complex class 1 representation, affinity calculation, cell generation, and cell proliferation. This framework addresses the overlapping and hole problem while creating natural killer cells to increase the system's performance. The negative selection algorithm and the positive selection algorithm generate the cells that enhance the anomaly detection technique and give high precision. The parameter response time introduced in this paper is crucial for an intrusion system to be used in real-time. 2022 Elsevier B.V. -
A mini review on recent advancements in inclined solar still
Water shortage is a global problem, and the demand for fresh water is growing at an ever-increasing rate. The only method to meet the demand for water is via water filtration. Water purification may be done in a variety of methods, including cleaning saltwater or holding rainfall and then releasing it into the environment. There are still several kinds of solar still are available, which may be utilized to improve the amount of water that is generated. The inclined solar still (ISS) is a particularly successful option because it has a large outer water surface to supplement the normal potable water production, as well as because it has a shallow depth of water to increase the overall efficacy of the inclined solar still. Increasing the water's surface area has been the subject of much investigation. As a result of this study, an evaluation was conducted on the present state of various ISS designs in order to make advanced adjustments and research to increase the productivity of the ISS in order to meet the rising need for potable water. According to this analysis, active ISS and hybrid ISS are shown to be the most successful ISS methods. 2022 The Author(s) -
SVD-CLAHE boosting and balanced loss function for Covid-19 detection from an imbalanced Chest X-Ray dataset
Covid-19 disease has had a disastrous effect on the health of the global population, for the last two years. Automatic early detection of Covid-19 disease from Chest X-Ray (CXR) images is a very crucial step for human survival against Covid-19. In this paper, we propose a novel data-augmentation technique, called SVD-CLAHE Boosting and a novel loss function Balanced Weighted Categorical Cross Entropy (BWCCE), in order to detect Covid 19 disease efficiently from a highly class-imbalanced Chest X-Ray image dataset. Our proposed SVD-CLAHE Boosting method is comprised of both oversampling and under-sampling methods. First, a novel Singular Value Decomposition (SVD) based contrast enhancement and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are employed for oversampling the data in minor classes. Simultaneously, a Random Under Sampling (RUS) method is incorporated in major classes, so that the number of images per class will be more balanced. Thereafter, Balanced Weighted Categorical Cross Entropy (BWCCE) loss function is proposed in order to further reduce small class imbalance after SVD-CLAHE Boosting. Experimental results reveal that ResNet-50 model on the augmented dataset (by SVD-CLAHE Boosting), along with BWCCE loss function, achieved 95% F1 score, 94% accuracy, 95% recall, 96% precision and 96% AUC, which is far better than the results by other conventional Convolutional Neural Network (CNN) models like InceptionV3, DenseNet-121, Xception etc. as well as other existing models like Covid-Lite and Covid-Net. Hence, our proposed framework outperforms other existing methods for Covid-19 detection. Furthermore, the same experiment is conducted on VGG-19 model in order to check the validity of our proposed framework. Both ResNet-50 and VGG-19 model are pre-trained on the ImageNet dataset. We publicly shared our proposed augmented dataset on Kaggle website (https://www.kaggle.com/tr1gg3rtrash/balanced-augmented-covid-cxr-dataset), so that any research community can widely utilize this dataset. Our code is available on GitHub website online (https://github.com/MrinalTyagi/SVD-CLAHE-and-BWCCE). 2022 Elsevier Ltd -
Enhanced visible light induced dye degradation and antibacterial activities of ZnO/NiO nanocomposite synthesized using Clitoria ternatea flower extract
In this study, ZnO/NiO Nanocomposites (NCs) were prepared using a rapid, simple and eco-friendly green synthesis method using medicinal flower extract of Clitoria ternatea and their visible light assisted dye degradation and antibacterial properties were investigated. The synthesised ZnO/NiO NCs were characterised by ultravioletvisible (UVVis) spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), High resolution transmission electron microscopy (TEM) and Selected area electron diffraction (SAED) studies. XRD results revealed that ZnO/NiO NCs exhibit hexagonal wurtzite and cubic crystal structure with an average crystallite size of 18 nm. HRTEM images revealed roughly spherical and hexagonal morphology with an average particle size of 23 nm. The antibacterial activity of ZnO/NiO NCs examined against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacteria using well diffusion method indicated significant antibacterial activity. The photocatalytic activity of the ZnO/NiO NCs showed 83.4 % and 84.4 % of dye degradation efficiency, respectively against Bromophenol Blue (BPB) and Crystal Violet (CV) dye for 150 min under sun light irradiation. The result shows that the ZnO/NiO NCs investigated in this study exhibited a strong potential agent and was successful in the removal of dye from wastewater. 2022 Elsevier B.V. -
Effectiveness of public policy in reviving the COVID-19 hit economy: Evidences from Kerala, India
The economic crisis triggered by the COVID-19 urgently required active policy interventions to enhance the revival strategies of the world economy. This paper examines the effectiveness of policy intervention of the State Government of Kerala in India in mitigating the risks caused by the pandemic. The policy effectiveness is evaluated by analyzing the data collected from a sample of 300 beneficiaries with the help of descriptive statistics, ordered probit (OP) model, and semi nonparametric extended OP (SNEOP) model. Our results are assertive with the fact that state policies are effective in reviving the crisis-hit economy as they have primarily helped low-income groups and other marginalized communities. The majority of BPL families, self-help group members, and social security beneficiaries rated government policies as highly or fairly effective. Though the policies are found to be highly effective among those who have suffered income loss, the study does not find sufficient evidence to believe that the government interventions are effective in helping those who have lost their jobs. The level of effectiveness is inversely related to age, education, and family size. Our results suggest that an extensive fiscal package is required to help people recover from the crisis. 2021 John Wiley & Sons Ltd. -
Optimized heat transport in Marangoni boundary layer flow of a magneto nanomaterial driven by an exponential interfacial temperature distribution
In a small boundary layer of the fluid interface, the temperature distribution deviates from being linear with the spatial coordinate and exhibits an exponential form. Hence, the Marangoni convective flow of a nanoliquid driven by an exponential interfacial temperature distribution is modeled in this study. Due to practical applicability, the working fluid is chosen to be ethylene glycol-based magnesium oxide nanoliquid, which is modeled using experimentally estimated properties. In the system, the external effects of an inclined magnetism, thermal radiation, and an internal heat source are considered. Heat transport is rigorously analyzed using an empirical model, which is estimated using the robust response surface methodology (RSM) to find the optimal working conditions and to estimate the sensitivity. The modeled problem is simulated numerically using the finite difference-based scheme and a parametric analysis is conducted to study the effect of magnetic field, inclination of magnetic field, radiation, and internal heat source parameters. The internal heat generation (increase of 0.94%) factor dominates the augmentation in the thermal field but at some distance, the thermal radiation factor has a predominant impact (58.99%). The inclination angle of the magnetic field has a prominent decremental impact on the velocity profile. Also, the radiative heat flux enhances the temperature profile. Optimal working conditions are estimated to be with a magnetic inclination of 10 and using a liquid with 0.25% volume fraction of 100 nm. This study finds applicability in crystal growth, drying silicon wafers, and heat exchangers. 2022 Wiley-VCH GmbH. -
Highly Luminescent MOF and Its in Situ Fabricated Sustainable Corn Starch Gel Composite as a Fluoro-Switchable Reversible Sensor Triggered by Antibiotics and Oxo-Anions
Frequent use of antibiotics and the growth of industry lead to the pollution of several natural resources which is one of the major consequences for fatality to human health. Exploration of smart sensing materials is highly anticipated for ultrasensitive detection of those hazardous organics. The robust porous hydrogen bonded network encompassing a free-NH2 moiety, Zn(II)-based metal-organic framework (MOF) (1), is used for the selective detection of antibiotics and toxic oxo-anions at the ppb level. The framework is able to detect the electronically dissimilar antibiotic sulfadiazine and nitrofurazone via fluorescence "turn-on"and "turn-off"processes, respectively. The antibiotic-triggered reversible fluoro-switching phenomena (fluorescence "on-off-on") are also observed by using the fluorimetric method. An extensive theoretical investigation was performed to establish the fluoro-switching response of 1, triggered by a class of antibiotics and also the sensing of oxo-anions. This investigation reveals that the interchange of the HOMO-LUMO energy levels of fluorophore and analytes is responsible for such a fluoro-switchable sensing activity. Sensor 1 showed the versatile detection ability which is reflected by the detection of a carcinogenic nitro-group-containing drug "roxarsone". In view of the sustainable environment along with quick-responsive merit of 1, an in situ MOF gel composite (1@CS; CS = corn starch) is prepared using 1 and CS due to its useful potential features such as biocompatibility, toxicologically innocuous, good flexibility, and low commercial price. The MOF composite exhibited visual detection of the above analytes as well as antibiotic-triggered reversible fluoro-switchable colorimetric "on-off-on"response. Therefore, 1@CS represents a promising smart sensing material for monitoring of the antibiotics and oxo-anions, particularly appropriate for the real-field analysis of carcinogenic drug molecule "roxarsone"in food specimens. 2022 American Chemical Society. -
Porous carbons derived from Arecanut seeds by direct pyrolysis for efficient CO2 capture
In this report, we demonstrate the preparation of a series of carbon nanospheres (CNSs) with high surface area and tunable sizes from natural bioresource, Arecanut kernels, by using direct pyrolysis. This method offers a convenient approach to induce porosity in the synthesized carbons without the need for an activating agent. The textural parameters including the specific surface area, pore volume, and pore size can be controlled by the simple adjustment of the carbonization temperature from 700 to 1000C. The CNSs prepared at 700C showed a low specific surface area, whereas the higher carbonization temperatures (8001000C) supported the rise in specific surface area of the products (433.61001.4 m2/g). The carbon, hydrogen, and nitrogen (CHN) analysis revealed that the CNSs exhibited a high purity with the carbon percentage ranging between 96 and 99%. The synthesized materials were tested as adsorbents for CO2 gas, and it was found that the CNSs with the highest specific surface area of 1001.4 m2/g registered the CO2 adsorption capacity of 14.1 mmol/g at 0C and 30 bar, which is a reasonably high value among reported porous carbons prepared without activation. This value of CO2 adsorption also stands above the activated carbon and multiwalled carbon nanotubes. The excellent CO2 adsorption capability of these adsorbents along with their low-cost synthesis offers a feasible pathway for designing such materials for other applications as well. 2021, Qatar University and Springer Nature Switzerland AG. -
Biotic elicitation mediated in vitro production of L-DOPA from Mucuna pruriens (L.) DC. cell cultures
With the emerging rise in the need for drugs extracted from various plant sources, there also arises the need for the optimum production of the drugs on a larger scale and conservation of those medicinal plants using different in vitro techniques and biotechnological approaches. Plant tissue culture techniques play a prominent role in mass multiplication of the plant. Whereas, strategies such as precursor feeding, elicitation, increases the metabolite content several-fold. Thus, an attempt of using the biotic elicitors for enhancing L-DOPA production, the anti-Parkinsons drug from Mucuna pruriens (L.) DC. cell cultures, has been reported in the present study. Aqueous extracts of algae [Amphiroa anceps (AA), Gracillaria ferogusonii (GF), Kappaphycus striatum (KS), and Sargassum lanceolatum (SL)], fungus [Aspergillus sps. (AS), Penicillium sps. (PE), and Cordyceps sps (CO)], and polysaccharide [Chitosan (CH)] solution were exposed to the cell cultures for 3, 6, and 9 d, respectively, and their effect on biomass and L-DOPA production was noted. This is the first report demonstrating the enhancement of biomass and L-DOPA from M. pruriens cell cultures with the use of various algal and fungal elicitors. Based on productivity (L-DOPA concentration biomass volume), it was observed that Cordyceps showed the best result and enhanced both biomass and metabolite to a greater scale. The elicitors, which showed a significant increase, are as follows: CO > AS > PE > CH > AA > KS > GF > SL. On the whole, it was noted that fungal extracts showed better results than algae. 2022, The Society for In Vitro Biology. -
Industrial Applications of Hybrid Nanocatalysts and Their Green Synthesis
Abstract: The era of industrial revolution has been hugely dependent on a myriad of catalysts. The present era has contributed another dimension to this by the advent of nanocatalysts. The last decades saw even more fine tuning with the use of hybrid nanocatalysts by the integration of a plethora of functionalities into a single nanoparticle. The extremely high surface area, low toxicity, easy recovery and reusability, high product output and possibilities of green synthesis makes hybrid nanocatalysts significant in various fields like bioremediation, fuel cell production, cleaner energy production, dye degradation etc. Metal based hybrid nanocatalysts are highly appealing due to their extremely high surface over volume ratio, entailing unique electronic properties and access to more reaction sites. The recent years have seen more thrust being given to greener modes of synthesis of nanocatalysts, rather than the classical modes (which uses hazardous chemicals), aligning with sustainability goals.The current review is an attempt to explore the myriad uses of magnetic, metal and metal oxide hybrid nanocatalysts and their green synthesis methods. Optimizing the use of hybrid nanocatalysts in various domains would definitely help us achieve the SDGs of the United Nations for a more sustainable life on this planet. Graphical Abstract: [Figure not available: see fulltext.] Highlights: Types of hybrid nanocatalysts have been described. Industrial applications of hybrid nanocatalysis has been summarized. Ways of greener synthesis of hybrid nanocatalysts for environmental sustainability depicted. Advantages and limitations of hybrid nanocatalysts have been evaluated. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Physical vapor deposition and enhancement of optoelectronic properties of SnSe2 platelets
Stoichiometric tin diselenide (SnSe2) platelet crystals have been prepared by physical vapor deposition (PVD) method under high vacuum (~ 106mbar) using a homemade dual-zone furnace. The driving force for growth was optimized in terms of temperature difference (?T = 270 to 420C) of nutrient and growth zones. Good quality platelets, devoid of any screw dislocations, hillocks, defects etc. were crystallized at ?T = 400C by layer growth mode as per the 3D optical profiler and electron microscopic images. Rietveld refinement of the PXRD data using FullProf suite software justified hexagonal crystal structure with a = 3.811 c = 6.137and the computed density (5.967g/cm3) is in agreement with that obtained based on Archimedes principle. Chemical homogeneity of these samples was probed by EDAX, XPS and Raman analysis. The thermal and mechanical behavior was investigated by TGA as well as Vickers microhardness experiments. The values of optical band gap (1.20eV), absorption coefficient (7.25 105cm?1), resistivity (2.70 ? cm), mobility (32.70 cm2V?1s?1) and carrier concentration (3.08 1016cm?3) have been evaluated using UVVis-NIR, photoluminescence, and Hall effect measurements. The enhancement of optoelectronic parameters of the as-grown SnSe2 platelets free of polytypism, throws light on their potential for photovoltaic applications. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
A Cognitive Similarity-Based Measure to Enhance the Performance of Collaborative Filtering-Based Recommendation System
Advances in technology and high Internet penetration are leading to a large number of businesses going online. As a result, there is a substantial increase in the number of customers making online purchases and the number of items available online. However, with so many options available to choose from, users have to face the information overload problem. Several techniques have been developed to handle this, but the performance of the recommendation system (RS) has been recorded unprecedentedly. The collaborative filtering (CF) of RS is the most prevalent technique, which suggests personalized items to users based on their past preferences. The efficacy of this technique mainly depends on the similarity calculation, which the traditional or cognitive approach can ascertain. In the traditional approach, a similarity measure utilizes the user's ratings on an item to compute the similarity. Most similarity measures in this approach suffer from either data sparsity and/or cold-start problems. To address both of them, a new similarity measure based on the Jaccard and Gower coefficients, the efficient Gowers-Jaccard-Sigmoid Measure (EGJSM), is proposed in this article. It also includes a nonlinear sigmoid function to penalize the bad ratings. The performance of EGJSM is evaluated by conducting experiments on benchmark datasets, and the results depict that the proposed technique outperforms several existing methods. Along with this, a cognitive similarity (CgS) measure has been proposed, which considers cognitive features such as genre and year of release along with rating information, to calculate similarity. The CgS method also outperforms the proposed EGJSM method and produces almost 4% and 1% lower mean absolute error (MAE) and root-mean-squared error (RMSE) values than that. 2014 IEEE. -
A Statistical Analysis and Comparison of the spread of Swine Flu and COVID-19 in India
Introduction: The world is currently experiencing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [COVID-19], however, this is not a new phenomenon; it occurred in 2009-2010 in the form of novel influenza A. (H1N1). The H1N1 virus primarily afflicted people between the ages of 26 and 50, but SARS-CoV-2 primarily afflicted those over the age of 60, increasing the number of deaths owing to their weakened immunity. The report provides a case study of the impact of H1N1 and SARS-CoV-2 in India. Methods: Data is obtained from The Hindustan Times newspaper, GoI press releases and World Health Organization (WHO) reports. Results: The incidence rate was initially low and it was only by the 10-15th week that it started increasing. There is an initial upward trend before levelling out followed by a second wave and third wave. COVID-19 exhibited a steeper growth, where the steps taken by the Government were ineffective leading to higher death cases. Kerala was affected due to the travellers returning from the Middle East, while Maharashtra and Delhi saw large incidence rates due to the migrant influx and communal gathering. Conclusion: The most effective and practical approach is to test the symptomatic patients and aggressive testing to contain the transmission. Awareness campaigns to educate the public about social distancing and personal hygiene is more practical. There is still scope of improvement with regards to the public health care support, preparedness and response. Lockdown measures could have been avoided if the initial screening was conducted properly. 2022 UPM Press. All rights reserved. -
Fractional study of a novel hyper-chaotic model involving single non-linearity
The applications of hyperchaotic systems (HCSs) can be widely seen in diverse fields associated with engineering due to their complicated dynamics, randomness, and high delicacy and sensibility. In the present work, we aim to investigate a new hyper-chaotic system involving a single non-linearity under the fractional CaputoFabrizio (CF) derivative for the first time. In fact, there is no previous study using fractional derivatives in this system. A new mathematical system using a fractional-order operator will be designed with the novel operator. The CaputoFabrizio non-integer operator is aimed to be employed to capture complex nature. In order to solve the extracted dynamical system, a quadratic numerical scheme is applied. This study contains stability and convergence sections for the considered method. Moreover, numerical results of the problem under various values of fractional orders and different values of initial conditions (ICs) are provided to show the performance of the suggested scheme. Figures of solutions for each dependent variable can be observed. 2022 The Author(s) -
Quality enhanced framework through integration of blockchain with supply chain management
Recently, there has been significant growth in the consumption of the most widely diversified Internet of Things (IoT) technological knowledge, and devices, which has resulted in an impact on not only electrical items and the agricultural and food industries (Agri-Food) supply chain networks. This has sparked intense curiosity about the development of information sharing that is reliable, traceable, and transparent, and also increased significant research and advancement efforts. Existing IoT-based trace & authenticity methods for agri-food distribution networks are constructed on top of centralized architectures, which creates the potential for significant issues such as data security, manipulation, and standard points of weakness. A creative and scraping methodological approach to implementing decentralized trust-free networks is represented by blockchain technologies, the decentralized blockchain technologies that underpin cryptocurrencies. The fault tolerance, data integrity, visibility, and complete tracing of saved transactional data, along with cohesive digital information of property resources and independent transactions implementations, are in fact features built into this digitalization. This study introduces Agri-BlockIoT, a completely decentralized blockchain-based traceable platform for managing a global agro-food distribution network that can seamlessly connect IoT systems that produce and consume digital information all along the distribution chain. We implemented a use caseto achieve transparency and traceability. Lastly, we analyzed and contrasted the implementations' capability in terms of delay, CPU, or network utilization. 2022 The Authors -
Hubble Space Telescope Captures UGC 12591: Bulge/disc properties, star formation and 'missing baryons' census in a very massive and fast-spinning hybrid galaxy
We present Hubble Space Telescope ( HST ) observations of the nearby, massive, highly rotating hybrid galaxy UGC 12591, along with observations in the UV to FIR bands. HST data in V , I , and H bands is used to disentangle the structural components. Surface photometry shows a dominance of the bulge o v er the disc with an H-band B / D ratio of 69 per cent . The spectral energy distribution (SED) fitting reveals an extremely low global star formation rate (SFR) of 0 . 1-0 . 2 M yr-1 , exceptionally low for the galaxy's huge stellar mass of 1 . 6 0 11 M, implying a strong quenching of its SFR with a star formation efficiency of 3-5 per cent. For at least the past 10 8 yr, the galaxy has remained in a quiescent state as a sterile, 'red and dead' galaxy. UGC 12591 hosts a supermassive black hole (SMBH) of 6 . 18 0 8 M, which is possibly quiescent at present, i.e. we neither see large (1kpc) radio jets nor the SMBH contributing significantly to the mid-IR SED, ruling out strong radiative feedback of AGN. We obtained a detailed census of all observable baryons with a total mass of 6 . 46 0 11 M within the virial radius, amounting to a baryonic deficiency of 85 per cent relative to the cosmological mean. Only a small fraction of these baryons reside in a warm/hot circumgalactic X-ray halo, while the majority are still unobservable. We discussed various astrophysical scenarios to explain its unusual properties. Our work is a major step forward in understanding the assembly history of such e xtremely massiv e, isolated galaxies. 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Fabrication of bismuth ferrite/graphitic carbon nitride/N-doped graphene quantum dots composite for high performance supercapacitors
Supercapacitors are potential energy storage devices with a broad range of applications. In this study, we are investigating a bismuth ferrite/graphitic carbon nitride/N-doped graphene quantum dots composite as an electrode material for supercapacitor applications. XRD patterns of the composite exhibit the different crystalline phases of the individual component and confirm the rhombohedral structure of the composite. The wafer-like structure of bismuth ferrite is produced via hydrothermal technique supported on 2D structures viz. graphitic carbon nitride and N-doped graphene quantum dots. Compared to bismuth ferrite and bismuth ferrite/graphitic carbon nitride (g-CN) binary composite, the bismuth ferrite/g-CN/N-doped graphene quantum dots demonstrates a superior specific capacitance of 1472 F g?1 at 1 A g?1 current density. After 3000 charging-discharging cycles, the device maintains its cycling stability with 87% capacitance retention. A supercapacitor device is assembled utilizing bismuth ferrite/graphitic carbon nitride/N-doped graphene quantum dots and activated carbon as electrodes. This device shows a significantly improved performance with an energy density of 53.1 Wh kg?1 and a power density of 705.4 W kg?1. As a result, the composite electrode developed in this study is proved to be a potential electrode material for high-performance energy storage devices. 2022 -
Synthesis and characterization of flyash reinforced polymer composites developed by Fused Filament Fabrication
Fused filament fabrication (FFF) has seen an upsurge in its utilization towards development of tailored made materials of polymer base. The advancement and diversity in fabricating the polymer composite parts by using FFF has seen the embracement of this technology in wider aspects, ranging from automotive, aerospace, construction and has marched towards day to day requirements. This research article focuses on development of polymer composite; by using flyash (FA), an industrial waste produced during coal combustion, as reinforcement in Acrylonitrile butadiene styrene (ABS) matrix, to study the physical and mechanical properties. FA, which is primarily made up of metal oxides, plays an imperative role as reinforcement. Easily and abundantly available, FA is being used in several applications to reduce the landfills utilization and also helps the environment. In this study FA was added as reinforcement in 5 and 10 wt. % respectively to ABS matrix and was developed into filament of 1.75 mm diameter. The developed ABS + FA polymer composite using FFF, were analyzed for physical and mechanical properties as per American Society for Testing and Materials (ASTM) standards. Microstructure studies were carried out for the developed composite to understand their behavior in enhancing the dimensional accuracy and tensile strength with incremental addition of FA up to 10 wt%. Tensile strength was enhanced by 28.19% and 36.13% for ABS + 5wt. % FA and ABS + 10wt. % FA respectively. Dimensional stability was also enhanced. Similarly, surface roughness analysis was carried out and it was observed to reduce with addition of FA. The surface roughness measurements provided suitable results of decrement by 9.64% and 14.6% for ABS + 5wt. % FA and ABS + 10wt. % FA respectively. Overall, the usage of FA along with FFF, has paved a path in sustainable and green technology in manufacturing. 2022 The Author(s). -
After-sale service experiences and customer satisfaction: An empirical study from the Indian automobile industry
For the growth of any industry, services play an essential role. Customers are more aware of the type of services they receive, and the expectations from the service providers are very high. Twenty-two percent total Gross Domestic Product (GDP) of the country is generated through the automotive industry. Global automotive majors have entered India and have dramatically changed the country's car production scenario. Changes to international technology design and adaptation have helped Indian car manufacturing compete globally, facing worldwide challenges. Considering services' high significance and essential role in the automobile industry, this study examined customer satisfaction with after-sales service experiences in the automobile sectorthis paper analyses customer satisfaction concerning automotive service interactions. The conceptual framework explains the impact on customer satisfaction in various car industries from various experiences, including employee behaviour, service lead time, service quality, service processes, and service costs. The respondents from Bangalore were selected. The data collection sampling approach used was convenience sampling. In a standardized questionnaire, data is collected from 400 respondents. The results demonstrate the substantial influence of service interactions on customer satisfaction. 2022 Elsevier Ltd