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National cinema in India: exploring myths and realities
[No abstract available] -
National Development through women empowerment
International Journal of Physical and Social Sciences Vol.3, Issue 3, pp.77-89 -
National Education Policy 2020: Equity and inclusion in India's education system
The term "equity" in education refers to justice and fairness in the allocation of educational resources and opportunities. In order to achieve educational equity, it is necessary to remove the structural obstacles that prevent students from realizing their full potential. Obstacles like socioeconomic inequalities, prejudice, and unequal resource distribution often act as barriers to quality education. In this background, the present chapter will critically analyze a few significant opportunities offered by the New Education Policy 2020, such as three language formulas, privatization, NEP financing, special education zones policy implications, and challenges in implementation. Even though the opportunities and milestones offered by NEP 2020 are irrefutable, apprehensions pertaining to its scope and usefulness also exist, questioning the sanguinity of the policy. 2024, IGI Global. All rights reserved. -
Natural biotic polymer bombyx mori silk fibroin for gold nanoparticles: Fabrication, characterisations and application as colorimetric ammonia detection
Gold nanoparticles (AuNPs) were fabricated using a cost-effective and environmentally benign method, using silk fibroin (SF) as a stabilizing and reducing agent. As a natural, renewable protein polymer, silk fibroin can reduce and stabilize material as well as provide shape-tailoring agent. This resulted bio-polymer with gold nanoparticles was biodegradable, biocompatible, and very stable. Au ions are proficiently reduced to neutral Au atoms by silk fibroin, which governs the size, shape, and distribution of the nanoparticles and, consequently, their optical characteristics. The fabricated nanoparticles are very well characterized using a set of advanced analytical techniques that include UV-Vis Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and Fluorescence Spectroscopy (FL). The sensing performance of ammonia in aqueous ammonia using the SF-AuNPs is presented herein based on an optical sensing approach utilizing surface plasmon resonance (SPR). It is obvious from the results that the materials synthesized have exhibited some unique plasmonic properties due to the interaction between silk fibroin and gold surfaces, hence enhanced sensitivity in colorimetric detection. The AuNPs acted as an ammonia optical sensor with a detected limit of about 1 parts per billion (ppb), very outstanding performance. Ammonia and AuNPs interact to cause a change in their surface plasmon resonance simple rapid and low-cost to realize, eco-friendly, and can find applications towards environmental monitoring and biomedical research fields for ammonia detection. 2026 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Natural convection of a binary liquid in cylindrical porous annuli/rectangular porous enclosures with cross-diffusion effects under local thermal non-equilibrium state
The present article reports an analytical study of the double diffusive natural convection (DDNC) in cylindrical porous annuli (CPA) and rectangular porous enclosures (RPE), which are handled in a unified way using the curvature parameter, saturated by a binary liquid under the assumption of local thermal non-equilibrium (LTNE) state. The buoyancy forces (thermal and solutal) driving the flow are assumed to be induced by the maintenance of constant and uniform heat and mass fluxes applied along the vertical (radial) walls and insulation of both horizontal walls of the annuli/rectangular enclosures. The Darcy-Boussinesq equations with LTNE assumption between the fluid and solid phases are employed to model the problem of DDNC in a binary liquid-saturated porous medium with cross-diffusion effects. The analytical results are obtained by employing the Oseen-linearization transformation technique in the study. The influence of various dimensionless parameters on heat and mass transports of the system are depicted using the Nusselt and Sherwood numbers and isotherms plots, and the obtained results are analysed with the physical explanation. Special attention is given to understand the effect of LTNE parameter and cross-diffusion parameters on heat and mass transports of the system. Different aspect ratio values are chosen to obtain the results of three types of CPA/RPE (shallow, square and tall). Among these CPA/RPE, maximum and minimum heat and mass transports are achieved in the cases of shallow and tall CPA/RPE, respectively. The results of the pure thermal convection problem is obtained at the zero value of buoyancy ratio and solute Rayleigh number. The increasing value of N magnifies the heat and mass transports in the system due to the augmented buoyancy effect resulted from the thermal and solutal gradients. The increase of solid inner cylinder radius, by fixing its volume, makes the annulus slender which yields to decrease the heat and mass transports in the system. The effects of LTNE parameter and cross-diffusion parameters on heat and mass transports of the system are clearly brought out. The results of LTE model are obtained at the infinite value of ratio of porosity modified thermal conductivities, ?, as a particular case of the present model. From the study, we conclude that the shallow porous annulus and tall rectangular enclosure are best suited in the design of heat removal and heat storage systems, respectively. 2021 -
Natural convection of water-copper nanoliquids confined in low-porosity cylindrical annuli
Natural convection in cylindrical porous annuli saturated by a nanoliquid whose inner and outer vertical radial walls are respectively subjected to uniform heat and mass influxes and out fluxes is studied analytically using the modified Buongiorno-Darcy model (MBDM) and the Oseen-linearization technique. Nanoliquid-saturated porous medium made up of water as base liquid, copper nanoparticles of five different shapes, viz., spheres, bricks, cylinders, platelets and blades, and glass balls porous material is considered as working medium for investigation. The thermophysical properties of nanoliquid -saturated porous medium is modeled using phenomenological laws and mixture theory. The effect of various parameters and individual effects of five different shapes of copper nanoparticles on velocity, temperature and heat transport are found. From the study, it is clear that the addition of a dilute concentration of nanoparticles increases the effective thermal conductivity of the system and thereby increases the velocity and the heat transport, and decreases the temperature. In other words, the heat transport is more in the case of heat and mass driven convection compared to purely heat-driven convection. Among the five different shapes of nanoparticles, blade-shaped nanoparticles facilitate the transport of maximum temperature compared to all other shapes. Maximum heat transport is achieved in a shallow cylindrical annulus compared to square and tall circular annuli. The increase of the inner solid cylinder's radius is to decrease heat transport. The results of the KVL single-phase model are obtained from the present study by setting to zero the value of the nanoparticles concentration Rayleigh number. Also, neglecting the curvature effect in the present problem, we obtain the results of the rectangular enclosure problem. 2020 The Physical Society of the Republic of China (Taiwan) -
Natural Disaster Prediction by Using Image Based Deep Learning and Machine Learning
In recent years, diseases and disaster have become more unpredictable. The advent of technology has not only making our lives easier but also technology-dependent. Nevertheless, the natural disasters cause great adversity by disrupting considerable human lives. Also, the disasters obstruct and affect many industries and services either directly or indirectly. Hence, it is necessary to study and observe data patterns and warning signs that lead to a natural disaster, its potential risk and its ability to resolve management strategies, which can be implemented immediately to minimize the socio-economic loss. This article reviews the state-of-the-art research works and findings through a technological perspective on data analysis, natural disaster prediction, and the utilization of technology for deploying management strategy. Also, this paper focuses on investigating the today's Industry 4.0 that utilizes cognitive computing. The primary aim of this article is to review the research ideas that leverage big data and data mining to observe and track patterns, which can impelment predictive analysis to anticipate the forthcoming disasters. Furthermore, this research work analyzed the posed predictive models by specifically using ANN (Artificial Neural Networks), sentiment model, and smart disaster prediction application (SDPA) to predict the flash flood. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Natural Language Processing (NLP) in chatbot design: NLP's impact on chatbot architecture
The creation and development of chatbots, which are the prevalent manifestations of artificial intelligence (AI) and machine learning (ML) technologies in today's digital world, are built on Natural Language Processing (NLP), which serves as a cornerstone in the process. This chapter investigates the significant part that natural language processing (NLP) plays in determining the development and effectiveness of chatbots, beginning with their beginnings as personal virtual assistants and continuing through their seamless incorporation into messaging platforms and smart home gadgets. The study delves into the technological complexities and emphasizes the problems and improvements in natural language processing (NLP) algorithms and understanding (NLU) systems. These systems are essential in enabling chatbots to grasp context, decode user intent, and provide replies that are contextually appropriate in real time. In spite of the substantial progress that has been made, chatbots continue to struggle with constraints. 2024, IGI Global. All rights reserved. -
Natural Language Processing and Information Retrieval: Principles and Applications
This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation. Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data. Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining. Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing. Covers latest datasets for natural language processing and information retrieval for social media like Twitter. The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. 2024 selection and editorial matter, Muskan Garg, Sandeep Kumar and Abdul Khader Jilani Saudagar chapters. -
Natural Language Processing in Medical Applications
Medical applications of machine learning are very new, and there are still several obstacles that limit their widespread use. There is still a need to address issues like high dimensionality data and a lack of a standard data schema. An intriguing way to explore the possibilities of machine learning in healthcare is to apply it to the difficult problem of cardiovascular disease diagnosis. At the present day, cardiovascular disorders account for the majority of deaths worldwide. It is often too late to adopt appropriate treatment for many of them because they progress for a long time without showing any symptoms. Because of this, its crucial to get checked up on routinely so that any developing diseases can be caught early. If the sickness is caught early enough, effective therapy can be put into place to stop the progression of the illness. This is done with the intention of analysing data from many sources and making use of NLP to overcome data heterogeneity. This paper evaluates the usefulness of several machine learning methods (such as the Naive Bayes (NB), Transductive Neuro-Fuzzy Inference, and Terminated Ramp-Support Vector Machine (TR-SVM)) for healthcare applications and suggests using Natural Language Processing (NLP) to address issues of data heterogeneity and the transformation of plain text. The implementation, testing, comparison of performance and analysis of the parameters of the algorithms used for diagnosis have simplified the process of selecting an algorithm better suited to a certain instance. TWNFI is particularly effective on larger datasets, while Terminated Ramp-Support Vector Machine is well suited to lesser datasets with a lower number of magnitudes due to performance difficulties. 2024 Scrivener Publishing LLC. -
Natural Language Processing on Diverse Data Layers through Microservice Architecture
With the rapid growth in Natural Language Processing (NLP), all types of industries find a need for analyzing a massive amount of data. Sentiment analysis is becoming a more exciting area for the businessmen and researchers in Text mining NLP. This process includes the calculation of various sentiments with the help of text mining. Supplementary to this, the world is connected through Information Technology and, businesses are moving toward the next step of the development to make their system more intelligent. Microservices have fulfilled the need for development platforms which help the developers to use various development tools (Languages and applications) efficiently. With the consideration of data analysis for business growth, data security becomes a major concern in front of developers. This paper gives a solution to keep the data secured by providing required access to data scientists without disturbing the base system software. This paper has discussed data storage and exchange policies of microservices through common JavaScript Object Notation (JSON) response which performs the sentiment analysis of customer's data fetched from various microservices through secured APIs. 2020 IEEE. -
Natural polymer-based hydrogels as prospective tissue equivalent materials for radiation therapy and dosimetry
Natural polymer-based hydrogels have been extensively employed in tissue engineering and biomedical applications, owing to their biodegradability and biocompatibility. In the present work, we have investigated the efficacy of hydrogels such as agarose, hyaluronan, gelatin, carrageenan, chitosan, sodium alginate and collagen as tissue equivalent materials with respect to photon and charged particle (electron, proton and alpha particle) interactions, for use in radiation therapy and dosimetry. Tissue equivalence has been investigated by computing photon mass energy absorption coefficient (?en/?), kinetic energy released per unit mass (KERMA), equivalent atomic number (Zeq) and energy absorption build-up factors (EABF) relative to human tissues (soft tissue, cortical bone, skeletal muscle, breast tissue, lung tissue, adipose tissue, skin tissue, brain) in the energy range of 0.01515MeV. Ratio of effective atomic numbers (Zeff) have been examined for tissue-equivalence in the energy range of 10keV1GeV for charged particle interactions. Analysis using standard theoretical formulations revealed that all the selected natural polymers can serve as good tissue equivalent materials with respect to all human tissues except cortical bone. Notably, sodium alginate, collagen and hyaluronan are found to have radiation interaction characteristics close to that of human tissues. These results would be useful in deciding on the suitability of a natural polymer hydrogel as tissue substitute in the desired energy range. 2021, Australasian College of Physical Scientists and Engineers in Medicine. -
Natural processing language: Business strategy in marketing intelligence
Customer Perception (CP) plays a crucial role for linking business strategy to success, with companies using multichannel data like social media and surveys to gather valuable unstructured information. Accurate analysis of this data uncovers purchasing trends, product flaws, and customer interests, thus guiding product improvements and marketing strategies. This chapter highlights the importance of prioritizing pricing and product usefulness over aesthetic appeal in catalogues by understanding consumer behaviour, and leveraging multichannel marketing for global reach and cost-effectiveness. This chapter explores how Deep Learning and NLP technologies enhance data analysis, customer feedback capture, and marketing strategies along with emphasizing ethical considerations. It aims to provide insights into developing competitive, intelligent marketing strategies (IMS) focussing on CRM, ultimately guiding companies to navigate the evolving marketing landscape effectively. 2025 Kankhita Mukherjee, Sriram Ananthan, Raghunandan G. and Thirupathi Manickam. Published under exclusive licence by Emerald Publishing Limited. All rights reserved. -
Natural template-assisted green synthesis of cobalt oxide and its surface functionalization using ?-alanine for biological applications
The incorporation of nanotechnology into material science has brought great advancements in diverse fields like medicine, electronics, energy, and the environment. Metal oxides gained notable attention from various nanomaterials due to their unique structure and properties. Cobalt oxide nanoparticles (Co3O4) stand out especially due to their diverse properties and applications. Synthesis of metal oxides through the traditional method faces many drawbacks, such as the use of toxic chemicals, a complex procedure, and environmental and health impacts. Whereas the green method of synthesis using natural resources, followed by surface modification with amino acids, acts as a better option for metal oxide synthesis. This paper focuses on developing a green, sustainable, and scalable method for synthesising Co3O4 nanoparticles, using a natural template, gum Arabic, followed by surface functionalization of ?-alanine. Various physico-chemical characterisation techniques such as DLS, TEM, FTIR and XRD were used to study nanoparticle composition and properties. Biocompatibility studies, cell viability assays and fibroblast cell lines from human skin by Alamar Blue assay, were carried out to test the effects of synthesised nanoparticles, and optimised protocols were also used to enhance performance for particular biomedical applications. Incorporating green synthesis and advanced techniques, ?-alanine functionalized Co3O4 nanoparticles, this research points toward developing more stable, biocompatible, and reactive nanoparticles under biological conditions. and multifunctional Co3O4 nanomaterials. Overall, the current study aims at sustainability with innovation towards transformative various biological applications in healthcare, biomedicine, diagnostics, MRI, biosensors, photo-sensing agents and energy technologies while addressing significant gaps in present methodologies. 2025 Elsevier B.V. -
Nature inspired algorithm approach for the development of an energy aware model for sensor network
The unique and strong characteristics of Wireless Sensor Network (WSN) have paved a way to many real time applications. Nevertheless, the WSN has their own set of challenges likewise data redundancy, resource constraints, security, packet errors and variable-link capacity etc. Among all, management of energy resource is of high importance as the efficient energy mechanism increases the lifespan of the network. Thereby providing good Quality of Service (QoS) demanded by the application. In WSN even though the energy is required for data acquisition (sensing), processing and communication, more energy are consumed during communication where transmission and retransmission of packets are quite often. In WSN data is transmitted from source to destination where at the destination site the data are analyzed using appropriate data mining techniques to convert data into useful information, and knowledge is extracted from that information to aid the user in efficient decision making. The transmission of data can be either through a single hop or via multiple hops. In single hop, a node is just a router where as in multi hop the node acts as both data originator and router. Thus, consuming more amount of energy and in a multi hop if any of the nodes fails it leads to many large retransmissions thus making a system highly susceptible for energy consumption. Many researchers have dedicated and devoted their time, energy and resources in order to come up with better solutions to answer this problem. This chapter is one such effort to provide a better solution to reduce the energy consumption of sensors. Here, the beauty of DBSCAN clustering technique has been fully exploited in order to develop a spatiotemporal relational model of sensor nodes, followed by the selection of representative subset using measure trend strategy and finally meeting the criteria for identifying the best optimal path for transmission of data using few nature inspired algorithms like Ant Colony Optimization (ACO), Bees Colony Optimization (BCO), and Simulated Annealing (SA). 2019, Springer-Verlag GmbH Germany, part of Springer Nature. -
Nature metaphors in Kalyanikutty Ammas Mohiniyattam body aesthetics
Mohiniyattam is a classical dance tradition from the state of Kerala in India, which is bestowed with a feminine identity. Scholars have theorised this feminine identity as self-enforced, constructed and regional. Unique to Mohiniyattam is the inherent relationship with nature. Nature association can be observed in the tradition of Kalamandalam Kalyanikutty Amma, one of the revivalists of Mohiniyattam. This paper will closely read the dance manual Mohiniyattam: Charithravum Aattaprakaaravum by Kalyanikutty Amma, focussing on Ammas use of nature metaphor for body movement. Dance theorist Sondra Fraleighs ideation of the lived and poetic body will be used to understand the experience and expression of nature as a movement quality. Further, Kavya Krishnas theorisation of gender performativity in Mohiniyattam and the discussions on regionality and naturality in movement will bring into effect an ecofeminist reading of Ammas dance aesthetics. This paper will also examine the metaphorical nomenclature that constructs nature as a feminine quality in the body movements and aesthetics of Mohiniyattam. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Nature metaphors in Kalyanikutty Ammas Mohiniyattam body aesthetics
Mohiniyattam is a classical dance tradition from the state of Kerala in India, which is bestowed with a feminine identity. Scholars have theorised this feminine identity as self-enforced, constructed and regional. Unique to Mohiniyattam is the inherent relationship with nature. Nature association can be observed in the tradition of Kalamandalam Kalyanikutty Amma, one of the revivalists of Mohiniyattam. This paper will closely read the dance manual Mohiniyattam: Charithravum Aattaprakaaravum by Kalyanikutty Amma, focussing on Ammas use of nature metaphor for body movement. Dance theorist Sondra Fraleighs ideation of the lived and poetic body will be used to understand the experience and expression of nature as a movement quality. Further, Kavya Krishnas theorisation of gender performativity in Mohiniyattam and the discussions on regionality and naturality in movement will bring into effect an ecofeminist reading of Ammas dance aesthetics. This paper will also examine the metaphorical nomenclature that constructs nature as a feminine quality in the body movements and aesthetics of Mohiniyattam. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Nature of music engagement and its relation to resilient coping, optimism and fear of COVID-19
The COVID-19 pandemic has resulted in unprecedented lockdowns, a work from home culture, social distancing and other measures which badly affected the world populace.Individuals over the globe reported experiencing several psychosocial and psychosomatic problems.Nevertheless, this pandemic allowed us to be with ourselves, to understand the importance of healthy lifestyles and to devote time to our passions and hobbies when we were socially isolated.Against this background, the present study was undertaken to explore the nature of peoples everyday musical engagement and to examine how the experience and functions of music were related to resilient coping, life orientation and fear from COVID-19.In an online survey, a total of 197 participants responded to a questionnaire designed to assess the nature of musical engagement (level of musical training, functional niche of music, listening habits and involvement in musical activities), functions of music (FMS), resilient coping (BRCS), life orientation (LOT-R), and fear of COVID-19 (FCV-19S).Results indicate that for most of the respondents, music listening was a preferred activity during the pandemic which resulted in positive effects on their mood, heart rate and respiratory rates.More than 80 per cent of respondents reported music as a source of pleasure and enjoyment and claimed that it helped to calm them, release their stress, and help them relax.Significant positive correlations were found between the functions of music (memory-based and mood-based), optimism and resilient coping and mood-based functions of music and optimism were found to predict resilient coping among individuals.These results suggest that meaningful and active music engagement may lead to optimism which may result in effective resilient coping during the crisis.Moreover, reflecting upon our everyday musical engagements can promote music as a coping skill. 2025 selection and editorial matter, Asma Parveen and Rajesh Verma; individual chapters, the contributors. -
Nature-inspired ?-MnMoO4nanocubes from Arachis hypogaea for next-generation wastewater treatment and organic pollutant catalysis
In this study, bimetallic ?-MnMoO4 nanoparticles (NPs) were successfully synthesized via a one-step solution combustion method using Arachis hypogaea (peanut) seed powder as a green fuel. This eco-friendly route was adopted to explore the adsorption, photocatalytic, and catalytic properties of the resulting NPs. The structural, morphological, and optical characteristics of ?-MnMoO4 NPs were systematically characterized using XRD, FTIR, UV-vis, and PL spectroscopy, SEM, and EDX techniques. Notably, ?-MnMoO4 NPs demonstrated excellent adsorption capability toward methylene blue (MB) dye, achieving a removal efficiency of 86.70%, which was primarily attributed to their negatively charged surface. Moreover, the nanoparticles demonstrated a remarkable photocatalytic activity, achieving 81.55% degradation of MB through the photo-oxidation of water into hydroxyl (?H) radicals by photogenerated holes. Beyond dye remediation, the study further explored the catalytic capabilities of o-phenylenediamine via oxidative condensation with substituted aromatic aldehydes to synthesize benzimidazole derivatives, achieving yields ranging from 35% to 85%, depending on the substituents used. This integrated approach highlights the potential of ?-MnMoO4 NPs not only in pollutant removal but also in facilitating the green synthesis of high-value chemical products, demonstrating promising applications in environmental remediation and fine chemical industries. This journal is The Royal Society of Chemistry, 2026