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An Overview of Nano-Catalysts in Biodiesel Production
Energy consumption and dependence on non-renewable resources is increasing over the years. The combustion of fossil fuels resulting in the emission of substantial amounts of CO2, NOX, SOX and some greenhouse gases. Biofuels are evolving as the primary alternatives to fossil fuels since they can be readily synthesised from discarded bioresources and yield lesser emission during the combustion process. However, the extraction of biofuels has thrown up new challenges that have widened the scope of the use of nano-particles in the synthesis of biofuels. From the literature, distinct findings concerning the use of nano-particles as a catalyst and process reactant during biodiesel production have been identified; this is majorly attributed to the fact that nano-catalysts enhance thermophysical properties, reaction speed and mass transport properties. Henceforth, the present paper aims to review, summarise and provide an insight into the research findings of effectively using nanocatalysts in biofuel production and consider the significance and its relevance for further researchers in the domain of biofuels. 2022, Books and Journals Private Ltd.. All rights reserved. -
Tunable Capacitive Behavior in Metallopolymer-based Electrochromic Thin Film Supercapacitors
Volumetric capacitance is a more critical performance parameter for rechargeable power supply in lightweight and microelectronic devices as compared to gravimetric capacitance in larger devices. To this end, we report three electrochromic metallopolymer-based electrode materials containing Fe2+as the coordinating metal ion with high volumetric capacitance and energy densities in a symmetric two-electrode supercapacitor setup. These metallopolymers exhibited volumetric capacitance up to 866.2 F cm-3at a constant current density of 0.25 A g-1. The volumetric capacitance (poly-Fe-L2: 544.6 F cm-3> poly-Fe-L1: 313.8 F cm-3> poly-Fe-L3: 230.8 F cm-3at 1 A g-1) and energy densities (poly-Fe-L2: 75.5 mWh cm-3> poly-Fe-L1: 43.6 mWh cm-3> poly-Fe-L3: 31.2 mWh cm-3) followed the order of the electrical conductivity of the metallopolymers and are among the best values reported for metal-organic systems. The variation in the ligand structure was key toward achieving different electrical conductivities in these metallopolymers with excellent operational stability under continuous cycling. High volumetric capacitances and energy densities combined with tunable electro-optical properties and electrochromic behavior of these metallopolymers are expected to contribute to high performance and compact microenergy storage systems. We envision that the integration of smart functionalities with thin film supercapacitors would warrant the surge of miniaturized on-chip microsupercapacitors integrated in-plane with other microelectronic devices for wearable applications. 2022 American Chemical Society. All rights reserved. -
Influence of Consumers Self Perception on Devaluation of Ugly Produce Marketing Strategies to Reduce Food Waste in the Indian Context
Ugly produce refers to aesthetically imperfect fruits and vegetables and also fruits and vegetables with minor blemishes. Ugly produce does not refer to spoilt, rotten, or germ-infected fruits and vegetables. The basic premise of this study is from self-signaling and self-perception theories. The self-signaling theory states that when people make a choice, they disclose something of their character and personality not just to others, but also to themselves. Self-perception theory (SPT) developed by psychologist Daryl Bem asserts that people develop their attitudes by observing their own behavior and further concluding what attitudes must have caused it. Classically, consumers undervalue ugly produce because of altered self-perceptions; simply visualizing the consumption of imperfect produce acts as a self-indicative signal that negatively affects how consumers view themselves. Due to this, the unattractive produce, even though perfectly edible and with the same taste and nutritional value, is rejected by consumers merely based on shape or some other cosmetic blemish. We discussed the strategies adopted by Indian startups and organizations to reduce food waste. Deep discounting is the strategy followed by food retailers worldwide to sell ugly produce, however, this is not the best strategy as it leads to losses for both the retailers as well as the farmers. We suggested alternative strategies successfully followed by foreign retailers, such as spreading awareness, boosting self-confidence and esteem among consumers, attracting kids, etc., which can be followed by Indian food retailers for selling ugly fruits and vegetables. 2022, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
RayleighBard convection in a BoussinesqStokes ferromagnetic fluid under sinusoidal and non-sinusoidal internal heat modulation
Internal heat modulation has several applications in nuclear reactor design and safety, as well as meteorology. In this paper, the influence of internal heat modulation on RayleighBard convection in a BoussinesqStokes ferromagnetic fluid is explored using linear and nonlinear analyses. The impact of the square, sine, triangular, and sawtooth wave type of internal heat modulation on the onset of convection and heat transport is considered. Using a Venezian method, linear stability analysis is performed to derive the correction Rayleigh number and the critical Rayleigh number for all four waveforms. A nonautonomous Lorenz model is derived and solved for the amplitude to obtain the Nusselt number, which quantifies the heat transport. The impact of the nondimensional parameter on the convective onset and heat transfer under heat source/sink modulation is analyzed. The study shows that all four types of internal heat modulation destabilize the system. It is also found that the presence of a heat source/sink modulation affects the impact of all four types of internal heat modulation on heat transport. 2022 Wiley Periodicals LLC. -
QSPR Analysis of Polycyclic Aromatic Hydrocarbons
Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. The First and Second Zagreb Indices are one among the earliest and extensively explored molecular descriptors. The study on equitable zagreb indices have been initiated earlier by Akram Alqesmah, Anwar Alwardi and R. Rangarajan based on the equitable degree of the vertices. In this paper, we introduce the first and second equitable and non-equitable zagreb polynomials and compute the exact values of the respective equitable and non-equitable zagreb indices for polycyclic aromatic hydrocarbons. We have also utilised certain formulations for the determination of the corresponding relative equitable and non-equitable zagreb indices of the chemical graph. Further, QSPR analysis is carried out for the topological indices with regard to the physico-chemical properties of the polycyclic hydrocarbon molecules. 2022, Books and Journals Private Ltd.. All rights reserved. -
Nickel-Based Inks for Flexible Electronics - A Review on Recent Trends
Inkjet printing (IJP) is an efficient, simple, scalable and low-cost additive manufacturing technique for the deposition of functional materials on substrates used in flexible electronic devices, sensors, and light-emitting diodes to name a few. Nanoparticle ink, metal oxide decomposition (particle-free ink), polymer ink, and semiconductor ink are classifications of the inks used in IJP. Effective printing of the material is possible when the ink parameters (viscosity, particle size, surface tension) and its derived dimensionless quantities (Weber number, Reynolds' number, and Ohnesorge number) fall within a desirable range. The formation of the coffee-ring effect during the post-printing process is one of the major concerns, which affects the morphology and electrical conductivity of the printed pattern. In this review, a summary of recent developments of Ni-based inks in terms of formulation, sintering and properties is presented, along with the effect of combining Ni with other materials such as NiO, Ag, Cu, Zn, Fe, carbon, and rare earth metals on the film properties. The precursors and solvents used for the Ni ink preparation, along with the additives and surfactants, have been presented to understand their impact on the film's properties and develop a design to choose the ideal precursor-solvent pair. Finally, the challenges in formulating inks and the necessity to develop a model to optimize the choice of solvent/ precursor are presented. The model would improve the selection of additives and precursors and reduce material wastage and enhance performance with fewer defects. 2022 World Scientific Publishing Company. -
BSLnO: Multi-agent based distributed intrusion detection system using Bat Sea Lion Optimization-based hybrid deep learning approach
Intrusion detection system (IDS) is a robust model that plays an essential role in dealing with intrusion detection, especially in detecting abnormal anomalies and unknown attacks. The major challenges faced by IDS are the computation time required for analysis, and the exchange of a huge amount of data from one division of the network to another. For the sake of tackling such limitations, this probe proposes a multi-agent enabled IDS for detecting intrusions using the Bat Sea Lion Optimization (BSLnO) algorithm. The proposed strategy consists of five phases, namely pre-processor agent, reducer agent, augmentation agent, classifier agent, and decision agent. Initially, input data is subjected to pre-processor agent, where pre-processing is carried out using data normalization and missing value imputation. Thereafter, the pre-processed result is fed up to the reducer agent, where dimension reduction is carried out using mutual information. The third step is data augmentation in which the dimensionality of data is enhanced. After that, the augmented result is subjected to classifier agent to classify intrusions or malicious activities present in the network based on hybrid deep learning strategies, namely deep maxout network and deep residual network. A developed BSLnO is implemented by incorporating Bat Algorithm (BA) and Sea Lion Optimization (SLnO) algorithm to train the hybrid classifier. The proposed scheme has acquired a higher precision of 0.936, recall of 0.904, and F-measure of 0.920. 2022 John Wiley & Sons Ltd. -
Analysis of the photo-thermal excitation in a semiconducting medium under the purview of DPL theory involving non-local effect
Non-local theory comprises a unique characteristics by analyzing the effects of all points of the body on a single point of the material. The present study enlightens the propagation of photo-thermal waves in a semiconductor by adopting the two phase lag theory of thermoelasticity in the frame of non-local effect. Normal mode analysis has been employed to obtain the exact expressions of the field quantities such as temperature, components of the displacement, carrier density, and components of the stress. Each field quantity is found to be influenced by the non-local parameter as well as phase lags. Quantitative results are determined in the time-domain by adopting a suitable technique of Laplace transform inversion which exhibit the influence of the non-locality effect on the distributions of field variables. Significant differences have been attributable to the studied fields due to the non-locality effect. Also, computational results are compared with the corresponding results obtained by using single phase lag theory proposed by Lord and Shulman (LS model)LS model single phase lag model (LS model). 2022, Springer Nature B.V. -
Climate-Smart Livelihood - A Case Study of Dodaballapura Taluk of Bangalore Rural District
More than a billion farmers around the world are on the frontier of climate change. These farmers' livelihoods are directly and indirectly affected by the impact of climate change. Climate smart livelihood explains the practices in agriculture sector which sustainably contributes to productivity and income. This study tries to explore the adaptation of climate smart livelihood techniques by the farmers in the Doddaballapur taluk of Bangalore rural district. The data was collected primarily from the five villages and 50 households of Doddaballapur taluk. The survey revealed that 81.67% of the respondents faced problems during adaptation of climate smart agriculture was due to poor support of local and national authorities with climate related issues and ranked it one of the major constraints. This was followed by lack of financial constraints, lack of knowledge about adaptive practices (78.50%), non-availability of agriculture inputs in time (76.17%), lack of education about the adaptation strategies (75.33%), unavailability of new technologies (78.83%), higher cost of the agricultural inputs used for the practices (71.17%), lack of improved communication facility about the climate change (71 %), migration of youth due to urbanization and better employment (70.83%), lack of knowledge about post-harvest technology (68.83%), lack of awareness about climate change issues (59.83 %). The study reveals that as most farmers believe they have low capacity to adapt to climate-smart agriculture due to lack of availability of resources. Government can help farmers through National Agricultural Extension Project (NAEP), Krishi Prashasthi, etc. 2022 - Kalpana Corporation. -
XENOPHOBIC ATTITUDES AND REPRESENTATIONS IN SOCIAL MEDIA DURING COVID-19 PANDEMIC IN INDIA; [ACTITUDES Y REPRESENTACIONES XENOFICAS EN LAS REDES SOCIALES DURANTE LA PANDEMIA DE COVID-19 EN LA INDIA]
Social media activity was reported to have significantly increased during the pandemic period as most of the daily routines transformed into the digital space. This paper attempted to explore the politics of representation in digital space using Foucauldian theories of power and discipline. A qualitative exploration of the xenophobic attitudes and representation was conducted on 123 young adults to understand how health concerns associated with the pandemic influenced social representations and marginalization of certain social sections and how participants recognized and understood their contribution to this group polarization. Thematic analysis of participant opinions indicated a significant change in polarization and attitude towards out-groups following the pandemic outbreak. The existing hierarchical homogenization and polarization of the marginalized moderated by polarized political affinities were found to be translated into digital space intensifying xenophobic attitudes thereby contributing to the evolution of new digital cultures and hierarchies in digital literacy. 2022 UNIVERSIDADE FEEVALE All rights reserved. -
Is Bitcoin a Safe Haven for Indian Investors? A GARCH Volatility Analysis
This paper attempts to understand the dynamic interrelationships and financial asset capabilities of Bitcoin by analysing several aspects of its volatility vis-a-vis other asset classes. This study aims to analyse the volatility dynamics of the returns of Bitcoin. An asymmetric GARCH model (EGARCH) is used to investigate whether Bitcoin may be useful in risk management and ideal for risk-averse investors in anticipation of negative shocks to the market (leverage effect). This paper also examines Bitcoin as an investment and hedge alternative to gold as well as NSE NIFTY using a multivariate DCC GARCH model. DCC GARCH models are also used to check whether correlation (co-movement) between the markets is time-varying, examine returns and volatility spillovers between markets and the effect of the outbreak of COVID-19 in India on the investigated markets. The results show that given the supply of Bitcoin is fixed, low returns realisation is equivalent to excess supply over demand wherein investors are selling off Bitcoin during bad times. The positive co-movement between Bitcoin and gold during the COVID-19 outbreak shows that investors perceived Bitcoin as a relatively safe investment. However, overall analysis shows that Bitcoin was not considered a safe hedge and an investment option by Indian investors during the study period. 2022 by the authors. -
Cross-language contributions of rapid automatized naming to reading accuracy and fluency in young adults: evidence from eight languages representing different writing systems
Rapid automatized naming (RAN) is a strong predictor of reading across languages. However, it remains unclear if the effects of RAN in first language (L1) transfer to reading in second language (L2) and if the results vary as a function of the orthographic proximity of L1L2. To fill this gap in the literature, we examined the role of RAN in reading accuracy and fluency in eight languages representing different writing systems. Seven hundred and thirty-five university students (85 Chinese-, 84 Japanese-, 100 Kannada-, 40 Oriya-, 115 English-, 115 Arabic-, 105 Portuguese-, and 91 Spanish-speaking) participated in our study. They were assessed on RAN (Digits and Objects) and reading (accuracy and fluency) in both L1 and L2 (English). Results of hierarchical regression analyses showed significant effects of L1 RAN on L2 reading accuracy in the Chinese-, Portuguese-, and Spanish-speaking groups. In addition, L2 RAN was a significant predictor of reading fluency in L1 in the same language groups. No cross-language transfer was observed in the other languages. These findings suggest first that L1 and L2 RAN capture similar processes and controlling for one does not leave unique variance for the other to explain. Second, to the extent there is cross-language transfer of RAN skills, this appears to be independent of the orthographic proximity of the languages. 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Ar-HGSO: Autoregressive-Henry Gas Sailfish Optimization enabled deep learning model for diabetic retinopathy detection and severity level classification
Diabetic Retinopathy (DR) is one the most important problems of diabetics and it directs to the main cause of blindness. When proper treatment is afforded for DR patients, almost 90% of patients are protected from visual damage. DR does not produce any symptoms at the initial phase of the disease, thus various physical assessments, namely pupil dilation, visual acuity test, and so on are needed for DR disease detection. It is more complex to detect the DR during manual testing, because of the variations and complications of DR. The early detection and appropriate treatment assist to prevent vision loss for DR patients. Thus, it is very indispensable to categorize the levels and severity of DR for recommendation of essential treatment. In this paper, Autoregressive-Henry Gas Sailfish Optimization (Ar-HGSO)-based deep learning technique is proposed for DR detection and severity level classification of DR and Macular Edema (ME) based on color fundus images. The segmentation process is more essential for proper detection and classification process, which segments the image into various subgroups. The Deep Learning approach is utilized for effective identification of DR and severity classification of DR and ME. Moreover, the deep learning technique is trained by the designed Ar-HGSO scheme for obtaining better performance. The performance of the devised technique is evaluated using the IDRID dataset and DDR dataset. The introduced Ar-HGSO-based deep learning approach obtained better performance than other existing DR detection and classification techniques with regards to testing accuracy, sensitivity, and specificity of 0.9142, 0.9254, and 0.9142 using the IDRID dataset. 2022 Elsevier Ltd -
Generalized Ricci solitons on Riemannian manifolds admitting concurrent-recurrent vector field
Let (M,g) be a Riemannian manifold admitting a concurrent-recurrent vector field ?. We prove that if the metric g is a generalized Ricci soliton such that the potential field V is a conformal vector field, then M is Einstein. Next we show that if the metric of M is a gradient generalized Ricci soliton, then either of these three occurs: (i) ?? is invariant along gradient of potential function; (ii) M is Einstein; (iii) the potential vector field is pointwise collinear to concurrent-recurrent vector field ?. Finally, we investigate gradient generalized Ricci soliton on a Riemannian manifold (M,g) admitting a unit parallel vector field, and in this case we show that if g is a non-steady gradient generalized Ricci soliton, then the Ricci tensor satisfies Ric=-??{g-?????}, where ?? is the canonical 1-form associated to ?. 2022, The Author(s), under exclusive licence to The Forum DAnalystes. -
HTLML: Hybrid AI Based Model for Detection of Alzheimers Disease
Alzheimers disease (AD) is a degenerative condition of the brain that affects the memory and reasoning abilities of patients. Memory is steadily wiped out by this condition, which gradually affects the brains ability to think, recall, and form intentions. In order to properly identify this disease, a variety of manual imaging modalities including CT, MRI, PET, etc. are being used. These methods, however, are time-consuming and troublesome in the context of early diagnostics. This is why deep learning models have been devised that are less time-intensive, require less high-tech hardware or human interaction, continue to improve in performance, and are useful for the prediction of AD, which can also be verified by experimental results obtained by doctors in medical institutions or health care facilities. In this paper, we propose a hybrid-based AI-based model that includes the combination of both transfer learning (TL) and permutation-based machine learning (ML) voting classifier in terms of two basic phases. In the first phase of implementation, it comprises two TL-based models: namely, DenseNet-121 and Densenet-201 for features extraction, whereas in the second phase of implementation, it carries out three different ML classifiers like SVM, Nae base and XGBoost for classification purposes. The final classifier outcomes are evaluated by means of permutations of the voting mechanism. The proposed model achieved accuracy of 91.75%, specificity of 96.5%, and an F1-score of 90.25. The dataset used for training was obtained from Kaggle and contains 6200 photos, including 896 images classified as mildly demented, 64 images classified as moderately demented, 3200 images classified as non-demented, and 1966 images classified as extremely mildly demented. The results show that the suggested model outperforms current state-of-the-art models. These models could be used to generate therapeutically viable methods for detecting AD in MRI images based on these results for clinical prospective. 2022 by the authors. -
The catalytic reduction of 4-nitrophenol using MoS2/ZnO nanocomposite
Nanocomposite MoS2/ZnO was prepared by an exfoliation process and characterized. A flower-like morphology was obtained for the hybrid where uniformly spread ZnO is stacked over thin layers of MoS2. A tight interface between the two components coupled with the energy band bending at the junction has resulted in a high activity of the composite towards the reduction of 4-nitrophenol. A complete reduction to 4-aminophenol from 4-nitrophenol took place within 15 min under the optimized conditions. The catalyst has a recyclability of six times without any perceptible decrease in the catalytic activity. 2022 The Author(s) -
Reading Patterns, Engagement Style and Theory of Mind
Theory of mind (TOM) refers to a set of abilities which enables understanding of mental states including beliefs, emotions and intentions of self and others. The purpose of this paper is to study the effect of different reading patterns including frequency of reading fiction and genre preference on TOM performance. It also aims to compare the accuracy of TOM performance under explicit goal directed and non-directed reading conditions. To achieve this objective, a sample of 72 Indian college students were randomly allocated to two groups and were evaluated on the Reading the Mind in the Eyes Test (RMET) and the Short Story Task (SST). The two groups differed with respect to task instructions aimed at mobilizing different manner of engagement (goal directed and nondirected) with the prose in the SST. The individual reading habits and preferences of all the participants were recorded by a self report questionnaire. Scores on the novel SST showed significant positive correlation with RMET scores. No significant difference in TOM performance with respect to the different engagement styles was found, indicating that TOM abilities function continuously and equally effectively when being used in goal directed and nondirected conditions. Notably, participants who reported to prefer literary fiction performed significantly better on the SST task than the participants who prefer popular fiction. This positive link between literary fiction and TOM has important implications in clinical and developmental fields and necessitates further research. 2021, National Academy of Psychology (NAOP) India. -
Polycystic ovary syndrome: An exploration of unmarried women's knowledge and attitudes
Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder among women of reproductive age and a chief cause of subfertility attributed to ovulation. Besides, lack of knowledge about PCOS, its treatment, and lifestyle changes influence the prognosis. The present qualitative inquiry investigates the knowledge and attitudes of unmarried women towards the syndrome, associated treatment, and necessary lifestyle changes in the fight against the same. A total of 15 participants with PCOS were selected using purposive sampling (n from southern parts of India viz. Kerala and Tamil Nadu states. The telephonic interviews were conducted in late November and early December 2020. He conventional content analysis emerged with six major themes. The themes capsulated women's knowledge, causes, complications and risk factors, treatment of PCOS their perceived importance of health promotive behaviours such as physical activity, sleep patterns, and perceived support from society. The importance of diet, exercise and a healthy lifestyle were additional relevant factors stressed by the respondents. Although the medicines helped participants attain regular menstrual cycles, they also had side effects reported in the discussion. Few respondents reported that they lacked the necessary awareness of PCOS when diagnosed at a younger age. The study enhances the understanding of PCOS from a qualitative approach that has cultural relevance apart from pertinent clinical and lifestyle implications. 2022 The Author(s) -
Impact of bioconvection on the free stream flow of a pseudoplastic nanofluid past a rotating cone
In the current work, the repercussions of Brownian motion and thermophoresis on the three-dimensional free stream flow of tangent hyperbolic (pseudoplastic) nanofluid past a rotating cone are explored. The tangent hyperbolic model expresses the characteristics of a shear-thinning nanofluid. Furthermore, oxytactic microorganisms were used as mixers to actively stabilize the nanoparticles. The movement of these microorganisms within the nanofluid gives rise to a major phenomenon termed bioconvection. The flow of nanofluid past a rotating cone finds applications in the field of nuclear reactors, biomedical applications, solar power collectors, steam generators, and so on. The mathematical model is designed using Buongiorno's model that describes the two major slip mechanisms experienced by the nanoparticles moving within a fluid namely thermophoretic force and Brownian motion. The model thus formed is nondimensionalized using the apt similarity transformation. The resulting system is solved by the (Formula presented.) technique by adapting the shooting method. The velocity, temperature, concentration, and motile density profiles are graphically interpreted for different flow parameters involved in the study. It was observed that thermophoresis reduces concentration and enhances the temperature whereas Brownian motion enhanced both temperature and concentration profiles. Also, the increase in the mixed convection parameter effectively decreased the temperature of the nanofluid. 2022 Wiley Periodicals LLC. -
Nanoparticle aggregation kinematics on the quadratic convective magnetohydrodynamic flow of nanomaterial past an inclined flat plate with sensitivity analysis
The study focuses on the aggregation kinematics in the quadratic convective magneto-hydrodynamics of ethylene glycol-titania ((Formula presented.)) nanofluid flowing through an inclined flat plate. The modified Krieger-Dougherty and Maxwell-Bruggeman models are used for the effective viscosity and thermal conductivity to account for the aggregation aspect. The effects of an exponential space-dependent heat source and thermal radiation are incorporated. The impact of pertinent parameters on the heat transfer coefficient is explored by using the Response Surface Methodology and Sensitivity Analysis. The effects of several parameters on the skin friction and heat transfer coefficient at the plate are displayed via surface graphs. The velocity and thermal profiles are compared for two physical scenarios: flow over a vertical plate and flow over an inclined plate. The nonlinear problem is solved using the RungeKutta-based shooting technique. It was found that the velocity profile significantly decreased as the inclination of the plate increased on the other hand the temperature profile improved. The heat transfer coefficient decreased due to the increase in the Hartmann number. The exponential heat source has a decreasing effect on the heat flux and the angle of inclination is more sensitive to the heat transfer coefficient than other variables. Further, when radiation is incremented, the sensitivity of the heat flux toward the inclination angle augments at the rate 0.5094% and the sensitivity toward the exponential heat source augments at the rate 0.0925%. In addition, 41.1388% decrement in wall shear stress is observed when the plate inclination is incremented from (Formula presented.) to (Formula presented.). IMechE 2021.