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Teaching Language Through Literature: Introducing Aspects of Literary Nonsense
Nonsense Literature first came into existence after the publishers of nursery rhymes started using the term to describe the works of childrens literature. It evolved into a genre of childrens literature that is widely accepted for being covertly intellectually stimulating. It uses puns, riddles, trick questions, contrasts in language, paradoxes and oxymorons to raise philosophically challenging questions that break our ideas of conventional patterns of understanding grammar, logic and reason. Nonsense literature is known for defying the rules of conventional linguistics. It plays with the boundaries of what is linguistically acceptable with its wordplay. However, nonsense literature understands and explores the structures of grammar, logic and reason better than any other literary genre. It is the best source of instruction for the ways in which the fundamental structures of grammar can be manipulated to create more structures of meaning which are transformational in nature. It uses the basic knowledge of grammar to create new ideas and rules using devices such as portmanteau and neologisms. Most course syllabi either focus on language or literature, never both simultaneously. Since literary nonsense plays with both linguistic structures in its writing and logic and reason in its story, it becomes the perfect material for teaching language as well as literature in the classroom. 2023, IUP Publications. All rights reserved. -
An optimized back propagation neural network for automated evaluation of health condition using sensor data
Ships and other large equipment must meet strict standards for equipment integrity and operational dependability in order to perform missions. To meet this demand, one of the essential linkages is to guarantee the long-term safe and healthy functioning of their power transmission equipment. The Optimized Back Propagation Neural Network (OBPNN) technique used in this study introduces a unique method for monitoring sensor data and evaluating the health state, with the SVM being optimized using the fish swarm algorithm (FSA). A major problem that maintenance is facing nowadays is reliable fault prediction. One of the trickiest difficulties is arguably automatically modelling typical behaviour from condition monitoring data, particularly when there is little information about actual failures. A data-driven learning framework with the best bandwidth selection is suggested to address this challenge. It is based on nonparametric density estimation for outlier identification and OBPNN for normality modelling. The distance to the separating hyper plane's log-normalization is used to provide a health score that is also available. The algorithm's viability is shown by experimental findings while evaluating the progression of a major defect over time in a marine diesel engine. Improved prediction capabilities and low false positive rates on healthy data are realized. 2023 The Authors -
Design of Triple Tuned Passive Harmonic Power Filter - A Novel Approach
Nowadays, there is a race between active and passive harmonic filters and still ambiguity persists. It is a proven fact that active harmonic filters (AHFs) are costly solutions though have proved better than passive harmonic filters. Except sizing and resonance problems, tuned passive harmonic filters (TPHFs) are proved to give economical solutions with little compromise on their performance. The accurate design of TPHFs gives a greater impact on its performance. The triple-TPHF (TTPHF) is essential to alleviate first three dominant ac side current harmonics simultaneously at the high voltage direct current (HVdc) converters and it is proved better than the single and double TPHFs. Existing equivalent methods of TTPHF design failed to give satisfactory performance under dynamic conditions. Hence, this article introduces a novel parametric method-based design of TTPHF, which will give better performance under static and dynamic loading conditions. The results also reveal that the proposed TTPHF design method will perform better than the existing methods. 2021 IEEE. -
Imprint of Fertiliser Policies on Farming Practices Evidence from the Top Five Consuming States
The policies related to the use of nitrogen fertilisers since independence are reviewed using primary and secondary databases to derive the present status of nitrogen, phosphorus, and potassium fertiliser use among farmers. Recommendations for increasing nitrogen use efficiency in agriculture for sustainability are provided. 2023 Economic and Political Weekly. All rights reserved. -
Marine brown algae (Sargassum wightii) derived 9-hydroxyhexadecanoic acid: A promising inhibitor of ?-amylase and ?-glucosidase with mechanistic insights from molecular docking and its non-target toxicity analysis
Jeopardized glucose hemostasis leads to cronic metaboic disorder like Diabetes mellitus and it is predicted to occur in ?700 million people in the coming 20 years. Our study aims to isolate Palmitic acid (C16H32O3), 9-Hydroxyhexadecanoic acid metabolite from Sargassum wightii to inhibit alpha-amylase and alpha-glucosidase to reduce postprandial hyperglycemia and decline the risk of diabetes. High docking score of palmitic acid with both ?-amylase and ?-glucosidase is observed in in-silico molecular docking analysis, in comparison to commercially available drug acarbose. The three hydrogen bond in palmitic acid interacts with the important amino acids like Arg195, Lys200 and Asp300 in Glide XP docking mode for alpha-amylase. For ?-glucosidase, quantum-polarized ligand docking (QPLD) was used with similar three hydrogen bond interactions. Both docking studies showed significant binding interaction of palmitic acid with ?-amylase (?5.66 and ?5.14 (Kcal/mol)) and with ?-glucosidase (?4.52 and ?3.51(Kcal/mol)) with respect to the standard, acarbose docking score. The bioactive palmitic acid isolated from the brown alga, Sargassum wightii is already seen to inhibit digestive enzyme with non-target property in Artemia nauplii and zebra fish embryos. Further studies are required to investigate its role in in vivo antidiabetic effects due to its non-toxic and digestive enzyme inhibitory properties. It can be recommended in additional pharmaceutical studies to develop novel therapeutics to manage diabetes mellitus. 2023 SAAB -
Predictors of Hypertension among Indian Women of Reproductive Age Group: An Analysis from NFHS-5 Data
Introduction: Hypertension among women not only augments the risk of cardiovascular diseases but also leads to antenatal and intra-natal complications. Materials and Methods: A subset of data collected during National Family Health Survey-5, comprising of 7,24,115 women, 1549 years of age was analysed to identify key predictors of hypertension, using Probit Regression Model (PRM) which was run separately for rural and urban women. Results: Overall prevalence of hypertension among women of reproductive age group was 11% (10.4% and 12% in rural and urban areas respectively). 5% and 13.41% of women were obese and 1.2% and 2.6% were diabetic in rural and urban areas respectively. Obese, uneducated, rich women and those on medications showed higher prevalence, while women consuming milk, eggs, chicken, fruits, and vegetables daily showed lower prevalence. On using PRM, significant predictors of hypertension were increasing age, rural residence, pregnancy, increasing weight, diabetes, illiteracy, access to medical insurance, and indulgence in alcohol and smoking. Conclusion: Findings from the study contribute to the body of evidence favouring multifactorial causation. Hypertension awareness should be promoted especially among rural residents, older women, with emphasis on intake of balanced diet with less consumption of sodium and increased intake of fruits and vegetables. 2023 National Journal of Community Medicine. -
Contemporary ethnobotany of pastoralism in semi-arid Deccan region-Koppal district, Karnataka, India
The aim of the current study is on ethnobotanical survey carried out in Koppal district of Karnataka, India. Study focused on exploration of traditional knowledge and pastoral practices of particular communities where livestock rearing activity is potent and use of ethnomedicinal plants in daily livelihood. The landscape was diverse in nature covering semi-arid to modest tropical climate, and unique topography encourage for wide range of vegetation useful for caters to feed the livestock. Methodology used for the study by participant observation, interviews, and transect walks, the study identified 48 plant species from 20 families, with Fabaceae and Poaceae being the most prevalent. These families play a vital role in providing nutritious fodder for livestock and sustaining pastoralists livelihoods. The study resulted pastoralists ethno-veterinary knowledge, where specific plants are used to treat cattle ailments and reflecting their deep understanding of traditional herbal remedies. However, the research finding revealed that some traditional knowledge may be diminishing with the younger generation, stressing the importance of knowledge preservation and transfer. The study underscores the potential benefits of integrating traditional practices with scientific research to optimize the selection and utilization of valuable fodder and veterinary plants. It is evident remarks to add up in the scientific data by collaboration between indigenous communities and scientific institutions for sustainable resource management. 2023, Indian journals. All rights reserved. -
Cloud-enabled Diabetic Retinopathy Prediction System using optimized deep Belief Network Classifier
Diabetic retinopathy disease is one of the notorious metabolic disorders happens due to increase of blood sugar level in human body. In computer vision, images are recognized as the indispensable tool for precise prediction and diagnosis of diabetic retinopathy. Therefore, the proposed research study considers the fundus images of various patients containing the diabetic disease. Basic idea behind this research is to introduce a stochastic neighbor embedding (SNE) feature extraction approach for the sake of dimensional reduction and unnecessary noise removal from the fundus images. After feature extraction, the proposed optimized deep belief network (O-DBN) classifier model is capable of measuring the image features into various classes that gives the severity levels of diabetic retinopathy disease. Moreover, the proposed cloud-enabled diabetic retinopathy prediction system using the SNE feature extraction and O-DBN classification model could outperform the existing online prediction systems in terms of sensitivity, specificity, F1-score, prediction time and accuracy. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Infusing Circular Reporting Model and Creative Marketing Mix for a Progressive Orange Economy: A Study with reference to Creative Business Units in Karnataka, India in the Post Covid-19 Pandemic
The orange economy which is also known as the creative economy has been an unrecognized industry though it has been a major contributor to economic growth and development. In this research an introspection has been done on four major economic factors such as: Choice of creativity with available resources, Marketing the good with unique strategies, Supply chain of good and services and tackling the demand fluctuations. These four factors rule the creative economy and hence the interlink between all these factors and its impact on the success of orange economy has been discussed in this research. The data has been collected from 30 small-owned creative business units which are spread across Karnataka. An interview schedule has been conducted with the creative business owners to understand the creative business units and its functionality. The structured interview has three layers which include (layer 1: questions related to creative business, layer 2: impact of Covid-19 pandemic on creative business units and layer 3: questions related to marketing, promotion and sales strategies used by creative business units. All the collected data has been exposed to a manual qualitative content coding to find new variables, new themes, cause, and effect and to construct a new conceptual model. The model has been suggested to the creative business units for active consideration and implementation. If the creative business units make use of the suggested marketing mix and strategies, they will be able to sustain themselves in the post-Covid-19 pandemic. The Author(s) 2023. -
Educational Deprivation of the Tribes Insights from the Block-level Study
The paper examines the nature of tribal deprivation, with specific focus on the issue of education. The research delves into the supply- and the demand-side factors, which determined the state of education within a region. Reaffirming the deprivation faced by the tribal communities, the study identifies specific factors that cause marginalisation. It points to the failure of the uniform tribal development programme to deal with the context-specific problems and thereby achieving the targeted results. The paper suggests the importance of not assuming the homogeneity of tribal societies, and need for public policies that are sensitive to this fact, in order to translate the goal of empowerment into a reality. 2023 Economic and Political Weekly. All rights reserved. -
Design and Implementation of Active Clamp Flyback Converter for High-Power Applications
This paper proposes a solar-powered isolated DCDC converter for high-power applications. The main aim of this paper is to achieve voltage regulation in the output side of the converter and to integrate a lossless active clamp flyback circuit (LACF) to compensate for the high-voltage issues that arise from one-stage DCDC converters. Hardware is developed with a power rating of 2 kW to test the performance of the proposed circuit. The circuit is designed using low-voltage devices and features such as soft switching and regeneration due to the LACF, which enhances efficiency. A novel luminous control algorithm is presented to improve the converter performance. The proposed circuits performance and feasibility are compared with existing converter parameters, such as the number of components in the circuit, voltage rating, and regeneration. 2023 by the authors. -
Soil classification using active contour model for efficient texture feature extraction
Precision farming is a systematic approach in agriculture that aims in improving economic and environment status of the farmers. It is achieved by having prior knowledge on soil texture, nutrient, pH and other climatic conditions. Hence this paper proposes a soil classification for crop prediction approach that uses an active contour algorithm for band estimation in Fourier domain for efficient texture feature extraction. This approach initially segments the soil sample and extracts into the color and texture features. The approach proposes a texture feature extraction where the image is initially transformed to Fourier domain of a 2D-discrete Fourier transform. The image in the Fourier domain is classified into high and low-frequency bands. The cut off frequency is decided by final contour of active contour method, where initial circular contour is used for estimating final contours on Fourier coefficients. This leads to the estimation of an irregular-shaped cut off frequency along with the 2D Fourier coefficients, instead of using a circular-shaped cut off frequency. A local binary pattern (LBP) from the high-frequency band image extracts texture feature. The extracted texture and color features are trained using a fully connected network. Active contour-based proposed model was evaluated by metrics F1-score, accuracy, specificity, sensitivity, and precision on soil datasets of Kaggle and IRSID. The accuracy, F1-score, specificity, precision, and sensitivity of proposed approach active contour-based were estimated as 97.89%, 97.87%, 99.46%, 98.11 and 97.94% respectively when evaluated in the Kaggle dataset. The evaluation results of proposed active contour model based soil classification outperform other traditional approaches. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
The Evolution of Interindustry Technology Linkage Topics and Its Analysis Framework in Three-Dimensional Printing Technology
The mutual influence and complementarity of technologies between different industries are becoming increasingly prominent. Revealing the topic evolution of technology linkages between industries is the foundation for understanding the technological development trend of the industry. Although numerous works have focused on technology topic mining and its evolution characteristics, these works have not accurately represented the interindustry technology linkage, analyze the related topics and even ignored the technological development characteristics hidden in the topic evolution pathway. Since the Lingo algorithm fully considers the time-series characteristics of the topics, and the knowledge evolution theory can reveal three inherent characteristics in the evolution of knowledge topics, namely, 'stability, heredity, and variability,' this article aims to combine the Lingo algorithm and the knowledge evolution theory to analyze the topic evolution of interindustry technology linkages. Additionally, because three-dimensional (3-D) printing technology has significant interdisciplinary and cross-industry characteristics, a wide range of application fields, and various interindustry technology linkages, 3-D printing technology is used for empirical analysis. The empirical results show that the key topics of interindustry technology linkages in 3-D printing include model design, manufacturing methods, manufacturing equipment, manufacturing material, and application. In addition, all these topics have the development feature of heredity. However, the topic of manufacturing materials presents significant variability, the topic of manufacturing methods has the strongest stability, and multiple subtopics of the five topics show variability and genetic intersection. 2023 IEEE. -
Computer modelling of trace SO2 and NO2 removal from flue gases by utilizing Zn(ii) MOF catalysts
SO2 and NO2 capture and conversion have been investigated via density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations using a novel hydrogen-bonded 3D metal-organic framework (MOF) containing a Zn(ii) centre and a partially fluorinated (polar -CF3) long-chain dicarboxylate ligand with a melamine (basic -NH2) co-ligand. Initially, computational single-component isotherms have been determined for SO2 and NO2 gases. These simulations have shown exothermic adsorption enthalpies of ?36.4 and ?28.6 kJ mol?1 for SO2 and NO2, respectively. They have also indicated that SO2 has a high affinity for polar -CF3 and basic -NH2 binding sites of the ligand in the framework pore walls. The lower adsorption capacity of NO2 compared with SO2 is due to weaker electrostatic interactions with the framework. Furthermore, MOF adsorbent selectivity for removing trace amounts of SO2 and NO2 in flue gases has been estimated through the co-adsorption of ternary gas mixtures (SO2/CO2/N2 and NO2/CO2/N2). Together with DFT, the climbing image nudged elastic band (CI-NEB) method has been used for investigating the plausible mechanisms for HbMOF1 catalyzed cycloadditions of SO2 and NO2 with epoxides leading to the formation of cyclic sulphites and nitrates, respectively. 2023 The Royal Society of Chemistry. -
Spectroscopic study of Herbig Ae/Be stars in the Galactic anti-centre region from LAMOST DR5
We study a sample of 119 Herbig Ae/Be stars in the Galactic anti-centre direction using the spectroscopic data from large sky area multi-object fiber spectroscopic telescope survey program. Emission lines of hydrogen belonging to the Balmer and Paschen series, and metallic lines of species such as Fe ii, O i, Ca ii triplet are identified. A moderate correlation is observed between the emission strengths of H? and Fe ii 5169 suggesting a possible common emission region for Fe ii lines and one of the components of H?. We explored a technique for the extinction correction of the HAeBe stars using diffuse interstellar bands present in the spectrum. We estimated the stellar parameters such as age and mass of these HAeBe stars, which are found to be in the range 0.1-10 Myr and 1.5-10 M, respectively. We found that the mass accretion rate of the HAeBe stars in the Galactic anti-centre direction follows the relation ?acc ? M?3.12-0.34+0.21, which is similar to the relation derived for HAeBe stars in other regions of the Galaxy. The mass accretion rate of HAeBe stars is found to have a functional form of ?acc ? t-1.10.02 with age, in agreement with previous studies. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Blockchain-Based Service Oriented Privacy-Preserving Data Sharing over Distributed Data Streams in Asynchronous Environment
Innovative city applications use information and communication technologies to function various operations efficiently. The widespread use of the Internet of Things (IoT) can be viewed in several applications like smart cars, smart cities, e-commerce, and cyber-physical systems. The huge amount of data produced and transmitted by these systems is handled by cloud-based storage services, which are vulnerable to multiple threats risking the privacy and security features of the application. Cloud storage services employ encryption algorithms to ensure data confidentiality, but it fails to address the privacy issues. Apart from the privacy risks, in these systems, the identity of a user who shares and accesses the data is traceable, as it is required to verify user eligibility before providing access. Also, a vast amount of daily data is stored on a centralized system that processes service requests from multiple users, posing considerable risks to the system's stability during peak periods. To address these challenges faced during the data sharing process in a centralized system, Service Oriented Privacy-Preserving Data Sharing (SOPPDS) platform based on a blockchain framework is proposed. The modified Key Policy-Attribute-based Encryption (MKP-ABE) technique is applied to securely share the data between the service owners and the service consumers. It was evident from the performance evaluation of the proposed SOPPDS platform that the encryption process takes lesser time than the decryption process. Also, the cryptographic operations performed on the prime order sets exhibited increased latency and computational cost. It was observed that comparatively, cryptographic operations performed on composite order sets could overcome the issues in prime order sets. SOPPDS platform works well in preserving the users' privacy, ensuring anonymity in the data sharing process, and maintaining the confidentiality of the data shared in the system. 2023, Ismail Saritas. All rights reserved. -
Probing the soft state evolution of 4U 1543-47 during its 2021 outburst using AstroSat
4U 1543-47 underwent its brightest outburst in 2021 after two decades of inactivity. During its decay phase, AstroSat conducted nine observations of the source spanning from 2021 July 1 to September 26. The first three observations were performed with an offset of 40 arcmin with AstroSat/LAXPC, while the remaining six were on-axis observations. In this report, we present a comprehensive spectral analysis of the source as it was in the High/Soft state during the entire observation period. The source exhibited a disc-dominated spectra with a weak high-energy tail (power-law index ?2.5) and a high inner disc temperature (?0.84 keV). Modelling the disc continuum with non-relativistic and relativistic models, we find inner radius to be significantly truncated at >10 Rg. Alternatively, to model the spectral evolution with the assumption that the inner disc is at the innermost stable circular orbit, it is necessary to introduce variation in the spectral hardening in the range ?1.5-1.9. 2023 The Author(s). -
A Scoping Review on Integration of Electroencephalogram Neurofeedback Training for Alcohol Use Disorder: Clinical and Neurocognitive Outcomes
Background. The conventional treatment for alcohol use disorder (AUD) consists of dual treatment encompassing pharmacotherapy and psychotherapy. Nonetheless, the impact of these treatments on clinical and neurocognitive outcomes is only low to medium efficacy. Research studies substantiate the integration of electroencephalogram neurofeedback training (EEG-NFT) as an add-on tool with significant improvements in clinical and neurocognitive outcomes. Methods. A scoping review of the existing literature on EEG-NFT and AUD, which are open access, including review papers and empirical studies in the English language, and with human subjects are deemed worthy of the scope of this study. The keywords electroencephalogram neurofeedback training, alcohol use disorder, stress, neurocognition, and relapse were used. The primary sources of the literature search were Science Direct, Scopus, PubMed, and Google Scholar. A total of 35 articles have been included in the scoping review. Studies from the last 15 years were considered for the same. Results. This review revealed that EEG-NFT is a promising tool with significant improvements in stress levels, cognitive deficits, and relapse rates for individuals with AUD when used in integration with conventional treatments. Conclusion. Chronic alcohol use affects cognitive functions, escalates relapse rate, and increases stress experienced by the individual. The present study highlights the significance of NFT as a potent add-on treatment modality to improve clinical and cognitive outcomes, thereby facilitating abstinence and reducing relapse rates in individuals with AUD. Copyright: 2023. -
Molecular architecture of PANI/V2O5/MnO2 composite designed for hydrogen evolution reaction
An ever increasing demand for energy has mandated scientists towards exploring innovative and environmentally friendly energy production techniques that can meet the needs of human beings and the world at large. Among the various techniques, hydrogen evolution reaction (HER) is a cost-effective and efficient method that produces hydrogen, a better fuel, for meeting our energy requirements. The large surface area, good redox capacity, high electroactivity, and tunable bandgap of polyaniline (PANI) makes it a preferred candidate for various energy-related applications. Incorporating mixed metal oxides into a polymer enhances its catalytic activities and can be used as an electrocatalyst for HER. In situ chemical oxidative polymerization method has been carried out to synthesize PANI/V2O5/MnO2 composite. The characterization studies of PANI/V2O5/MnO2 composite are done using XRD, FT-IR, BET, XPS, and FE-SEM analysis. The PANI/V2O5/MnO2 composite is used for linear sweep voltammetry studies and shows that it acts as an efficient electrocatalyst which gives an overpotential of 130 mV at 10 mA/cm2. The high electrocatalytic activity of the composite is due to the better surface phenomenon that is enhanced by the high porosity and surface area. The electrochemical impedance spectroscopy also shows lower charge transfer resistance for the PANI/V2O5/MnO2, confirming its excellent electroactivity. 90% of the current density is retained even after 7200 seconds, validating its stability. 2023 Elsevier B.V. -
Why is the size of discouraged labour force increasing in India?
The Indian economy is currently passing through a critical phase of economic development as its structural transformation in employment has stalled, whilst both the youth unemployment rate and the number of youths Not in Employment, Education, and Training (NEET) have increased to an unprecedentedly high level. In the context in which the share of the youth population is continuing to rise despite the declining fertility rate to below the replacement rate, increased educated youth unemployment has caused an upsurge in the Discouraged Labour Force (DLF). This paper explores the trends, composition, and determinants of rising DLF in India using national level employment-unemployment surveys and macro-level panel data. Based on Multinomial logit and System GMM regression results, it is argued that policies aiming to enhance human capabilities through an improved base of technical education and the promotion of industry are necessary to enhance the growth of quality jobs in order to combat the problem of rising educated youth unemployment and DLF. Moreover, these measures could help in the process of harnessing the demographic dividend in India through an increased level of labour productivity in the long run. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.