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Improving crop production using an agro-deep learning framework in precision agriculture
Background: The study focuses on enhancing the effectiveness of precision agriculture through the application of deep learning technologies. Precision agriculture, which aims to optimize farming practices by monitoring and adjusting various factors influencing crop growth, can greatly benefit from artificial intelligence (AI) methods like deep learning. The Agro Deep Learning Framework (ADLF) was developed to tackle critical issues in crop cultivation by processing vast datasets. These datasets include variables such as soil moisture, temperature, and humidity, all of which are essential to understanding and predicting crop behavior. By leveraging deep learning models, the framework seeks to improve decision-making processes, detect potential crop problems early, and boost agricultural productivity. Results: The study found that the Agro Deep Learning Framework (ADLF) achieved an accuracy of 85.41%, precision of 84.87%, recall of 84.24%, and an F1-Score of 88.91%, indicating strong predictive capabilities for improving crop management. The false negative rate was 91.17% and the false positive rate was 89.82%, highlighting the framework's ability to correctly detect issues while minimizing errors. These results suggest that ADLF can significantly enhance decision-making in precision agriculture, leading to improved crop yield and reduced agricultural losses. Conclusions: The ADLF can significantly improve precision agriculture by leveraging deep learning to process complex datasets and provide valuable insights into crop management. The framework allows farmers to detect issues early, optimize resource use, and improve yields. The study demonstrates that AI-driven agriculture has the potential to revolutionize farming, making it more efficient and sustainable. Future research could focus on further refining the model and exploring its applicability across different types of crops and farming environments. The Author(s) 2024. -
Death-worlds, Necropolitics and Decoloniality Colonial Negotiations in Mah
The boundaries of sovereignty are mostly relegated to modern and late modern political thoughts that focus on biopolitical and democratic theories. This paper marks a shift of sovereign subjectivity to the interstitial spaces of life and death of the colonial subjects. Through the study of the necropolitics of colonial control in the erstwhile French colony of Mah as narrated in the novel On the Banks of the Mayyazhi, this paper argues that colonial subjectivity and the idea of sovereignty have decentred itself from the traditional notions of political control and violence to newer avenues of life and death. The perusal of the decolonial approach to necropolitics will examine how colonial logic has shaped the idea of sovereignty. 2024 Economic and Political Weekly. All rights reserved. -
Optimising lead qualification through machine learning: A customer data-driven approach
Lead generation is the process of turning an outside person or business into a customer of the business. Traditionally, marketing personnel must conduct significant follow-ups in order to convert even one potential consumer. Converting bad client leads can cause businesses to burn through cash reserves. As a result of this, it is now necessary to develop an automated system that can correctly anticipate whether or not a lead should be explored (converted to a customer or not). In this study, an attempt is made to evaluate historical data for leads produced by other businesses in order to train and validate a machine learning (ML)/deep learning (DL) model and test it against real-world characteristics to categorise them as hot leads (convert to customers) or cold leads (failed leads). This can be achieved by employing ML algorithms, low codeno code libraries, such as PyCaret in Python, and can be used to make predictions regarding probable lead creation, propensity to convert generated leads and optimal actions on the leads by communications teams. Supervised ML algorithms such as logistic regression, decision trees, random forests and other models using a Python library were built to score leads for identifying potential conversions. With good and broad lead-scoring models in place, businesses can optimise their CTI actions on the basis of lead prioritisation and let go of non-prospect leads at the right time to cut costs and enable efficiency. The result of this study reveals that 52 per cent of the sample of 74,779 leads are cold leads and 48 per cent are hot leads that are sales qualified. The leads are qualified using the lead score matrix. This method can aid digital businesses to remove unqualified leads and manage leads better, and therefore improve the quality of the leads sent to clients. This, in turn, will improve conversion rates for individual customers. These increased conversion rates will enhance the business strategy of digital marketing firms. Henry Stewart Publications. -
Investigating MnSe@Y2O3 nanocomposite as an electrode for asymmetric hybrid supercapacitor
In this research work, manganese selenide (MnSe) and yttrium oxide (Y2O3) nanoparticles have been synthesized by facile melt diffusion and hydrothermal technique which are then composited by ultrasonication. The composite MnSe@Y2O3 has been analyzed as a supercapacitor electrode. The growth structure of the composite was scrutinized systematically by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), high resolution transmission electron microscopy (HRTEM), and selected area diffraction pattern (SAED). The Trasatti and Dunn's plots have been also plotted to calculate the capacitive and diffusive contribution. The device is fabricated with PVA-KOH gel electrolyte. Also, the fabricated device MnSe@Y2O3||AC has exhibited a specific capacity of 48.39 C/g at 1 A/g through the potential window of 01.7 V. The wide potential window is evidence for high energy density. This also provides elevated energy density of 19 Wh/kg, at high power density of 1445 W/kg, and has shown brilliant cyclic stability of 70.16 % even after 5000 charge/discharge cycles. 2024 Elsevier B.V. -
Effectual Energy Optimization Stratagems for Wireless Sensor Network Collections Through Fuzzy-Based Inadequate Clustering
Wireless Sensor Networks (WSNs) are crucial in the burgeoning Internet of Things (IoT) landscape, serving as a backbone technology that enables myriad applications across various industries. Originating as a simple methodology, WSNs have evolved significantly, propelled by rapid advancements in sensor technology and hardware capabilities. These networks play a pivotal role in collecting and transmitting data, which is essential for the infrastructure of most IoT systems. WSNs operate by deploying sensor nodes across diverse locations to gather environmental data. This scalability and adaptability of WSNs were demonstrated in studies where network coverage was expanded to include 100 and 200 nodes. Notably, the implementation of the innovative FLECH (Fuzzy Logic Energy-efficient Clustering Hierarchy) protocol significantly enhanced energy efficiency, reducing consumption by 12.69% in networks with 100 nodes and by 36.85% in those with 200 nodes, compared to the traditional LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol. This work innovatively combines fuzzy logic and Particle Swarm Optimization (PSO) for efficient Cluster Head selection in Wireless Sensor Networks. The evaluation of these protocols involved numerous simulations and communication tests to ascertain the First Node Die (FND) pointindicative of when a network begins to lose efficacy due to energy depletion. Results indicated that the LEACH protocol reached the FND point faster than FLECH, suggesting that FLECH may offer better longevity and durability for IoT applications, aligning with the needs for sustainable and efficient operation in expanding technological ecosystems. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. -
Mechanical and Wear Behavior of Aluminium Metal Matrix Composites Reinforced Ceramics Materials for Light Structures
Aluminium Alloy based Metal Matrix Composites (AAMMCs) has widely used in defense, aircraft and automobile applications because of their enhanced engineering properties with light weight metals. Nano sized silicon nitride (80 ?m) is used as a reinforcement in this study, whereas aluminium alloy 8011 is selected as the matrix material. Using the stir casting method, metal matrix composites made of aluminium alloy 8011 with varying weight percentages of Si3N4(0, 4, 8, 12, and 16) are created. The stir casted AL 8011/Si3N4composites further heated under T6 condition. The AL 8011/Si3N4 T6 composites are further subjected to Energy Dispersive X ray Analysis (EDAX) and Scanning Electron Microscope (SEM) to identify by the presence of elements and study the microstructure characterization, respectively. The density, microhardness and wear test are conducted by employing Archimedes principle, Vickers hardness tested and pin on disc equipment, respectively. The wear test is done at different sliding distances like (500, 1000, 1500 and 2000 m), applied load like (10, 20, 30 and 40 N) and kept sliding at a speed of 1 m/s. The increasing weight percentage of silicon nitride expands the increasing of density and Vickers hardness up to 12 wt % of silicon nitride and decreasing by 16 wt % addition. The wear resistances of AL 8011/12 wt % Si3N4T6 composite exhibits higher wear resistance than other Al8011 based composites. 2024, Informatics Publishing Limited. All rights reserved. -
Synthesis and characterization of biowaste-derived porous carbon supported palladium: a systematic study as a heterogeneous catalyst for the reduction of nitroarenes
In this study, we present a green synthesis approach for the fabrication of porous carbon supported palladium catalysts derived from Caesalpinia pods. The synthesis involves self-activation of Caesalpinia pods in a nitrogen atmosphere at various temperatures (600C, 800C, and 1000C) to produce porous carbon nanoparticles. Among the synthesized carbon materials, the sample CP-CNS/10 synthesized at 1000C exhibited the highest surface area of 793 m2/g with an average pore size diameter of 1.8nm. The resulting porous carbon material served as an efficient support for palladium nanoparticles, with a low metal loading of about 0.2mol% Pd for the reaction. This catalyst demonstrated excellent performance in the reduction of nitroarenes to their corresponding aromatic amines. The successful incorporation of approximately 4.5% Pd during the deposition process highlights the potential of the porous carbon supported palladium catalyst synthesized at 1000C for a sustainable and efficient heterogeneous catalyst for the reduction of nitroarenes. Graphical Abstract: (Figure presented.) Akadiai Kiad Budapest, Hungary 2024. -
Design and implementation of a universal converter for microgrid applications using approximate dynamic programming and artificial neural networks
This paper introduces a novel design for a universal DC-DC and DC-AC converter tailored for DC/AC microgrid applications using Approximate Dynamic Programming and Artificial Neural Networks (ADP-ANN). The proposed converter is engineered to operate efficiently with both low-power battery and single-phase AC supply, utilizing identical side terminals and switches for both chopper and inverter configurations. This innovation reduces component redundancy and enhances operational versatility. The converter's design emphasizes minimal switch usage while ensuring efficient conversion to meet diverse load requirements from battery or AC sources. A conceptual example illustrates the design's principles, and comprehensive analyses compare the converter's performance across various operational modes. A test bench model, rated at 3000W, demonstrates the converter's efficacy in all five operational modes with AC/DC inputs. Experimental results confirm the system's robustness and adaptability, leveraging ADP-ANN for optimal performance. The paper concludes by outlining potential applications, including microgrids, electric vehicles, and renewable energy systems, highlighting the converter's key advantages such as reduced complexity, increased efficiency, and broad applicability. The Author(s) 2024. -
A high-efficiency poly-input boost DCDC converter for energy storage and electric vehicle applications
This research paper introduces an avant-garde poly-input DCDC converter (PIDC) meticulously engineered for cutting-edge energy storage and electric vehicle (EV) applications. The pioneering converter synergizes two primary power sourcessolar energy and fuel cellswith an auxiliary backup source, an energy storage device battery (ESDB). The PIDC showcases a remarkable enhancement in conversion efficiency, achieving up to 96% compared to the conventional 8590% efficiency of traditional converters. This substantial improvement is attained through an advanced control strategy, rigorously validated via MATLAB/Simulink simulations and real-time experimentation on a 100 W test bench model. Simulation results reveal that the PIDC sustains stable operation and superior efficiency across diverse load conditions, with a peak efficiency of 96% when the ESDB is disengaged and an efficiency spectrum of 9195% during battery charging and discharging phases. Additionally, the integration of solar power curtails dependence on fuel cells by up to 40%, thereby augmenting overall system efficiency and sustainability. The PIDCs adaptability and enhanced performance render it highly suitable for a wide array of applications, including poly-input DCDC conversion, energy storage management, and EV power systems. This innovative paradigm in power conversion and management is poised to significantly elevate the efficiency and reliability of energy storage and utilization in contemporary electric vehicles and renewable energy infrastructures. The Author(s) 2024. -
Automated lung cancer T-Stage detection and classification using improved U-Net model
Lung cancer results from the uncontrolled growth of abnormal cells. This research proposes an automated, improved U-Net model for lung cancer detection and tumor staging using the TNM system. A novel mask-generation process using thresholding and morphological operations is developed for the U-Net segmentation process. In the pre-processing stage, an advanced augmentation technique and contrast limited adaptive histogram equalization (CLAHE) are implemented for image enhancement. The improved U-Net model, enhanced with an advanced residual network (ARESNET) and batch normalization, is trained to accurately segment the tumor region from lung computed tomography (CT) images. Geometrical parameters, including perimeter, area, convex area, solidity, roundness, and eccentricity, are used to find precise T-stage of lung cancer. Validation using performance metrics such as accuracy, specificity, sensitivity, precision, and recall shows the proposed hybrid method is more accurate than existing approaches, achieving a staging accuracy of 94%. This model addresses the need for a highly accurate automated technique for lung cancer staging, essential for effective detection and treatment. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Convergence of Health Expenditure and Health Outcomes in Central Europe and the Baltic Region
This research work examines the convergence of health expenditure in Central Europe and the Baltic region. The study reveals the absolute convergence in per capita health expenditures, indicating similar health outcomes for all eleven countries of the region. However, there is a divergence in health expenditure and outcomes across the eleven countries. Notably, public health expenditure diverges in Denmark, Estonia, Finland, and Norway, while, private health expenditure converges in Poland, Russia, and Sweden. Despite an overall convergence in life expectancy at birth across the countries, mortality rates due to non-communicable diseases only converge in Estonia. 2024 Taylor & Francis Group, LLC. -
Developing a global sustainable electricity use index using the pressure-state-response framework
This study analyse and compare the sustainable electricity usage in 60 countries listed on the official websites of World Energy Consumption Statistics and Climate Bond Initiative. The study also analyses the impact of increased usage of sustainable electricity on the economies' dependence on non-renewable energy sources in the evaluation system. We used a standard index system based on the Pressure-State Response (PSR) model to measure global sustainable electricity usage. Model results convey that Norway is the best performer in sustainable electricity usage, while several European countries display commendable scores, confirming their commitment to sustainable electricity practices. On the other hand, despite being the leading economies in terms of GDP, major economies such as the United States, China, Japan, and India have underperformed compared to others in the evaluation system. The study employs regression techniques to explain the relationship between sustainable electricity usage and non-renewable energy dependence. Results confirm a negative relationship between the variables, indicating the role of sustainable energy practices in reducing fossil fuel consumption. It emphasizes the urgency of a balanced approach to economic growth and natural resource usage to support a green future. 2024 Elsevier Ltd -
Exploring the Photocatalytic and Cytotoxic Potential of Quassia indica-Derived Bimetallic Silver-Zinc Oxide Nanocomposites
In response to the escalating need for nanomaterials characterized by enhanced properties and reduced environmental impact, this study addresses critical challenges associated with conventional nanomaterial synthesis methods, particularly focusing on concerns related to environmental toxicity and economic feasibility. In this study, we report the eco-friendly synthesis of silver-zinc oxide nanocomposites using leaf extracts of Quassia indica (QI- Ag: ZnO NC). The synthesized QI- Ag: ZnO nanocomposites were characterized using various techniques including UV-visible spectroscopy, X-ray diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FTIR), Dynamic Light Scattering (DLS), Field-Emission Scanning Electron Microscopy (FE-SEM) with Energy Dispersive X-ray Spectroscopy (EDX), High Resolution Transmission Electron Microscopy (HR-TEM), and Selected Area Electron Diffraction (SAED). The photocatalytic activity of the biosynthesized QI- Ag: ZnO NC was evaluated against several textile dyes. Reactive Blue-220 exhibited the highest percentage of degradation (99.97%), closely followed by Reactive Blue-222 (99.37%), while Reactive Red-120 displayed significant degradation (94.62%). Remarkably, these nanocomposites exhibited significant photocatalytic degradation of the tested dyes, suggesting their potential application in wastewater treatment for dye removal. Furthermore, phytotoxicity studies were conducted to assess the impact of the nanocomposites on plant growth and brine shrimp mortality. To evaluate their cytotoxicity, the nanocomposites synthesized were assessed using the MTT assay on MCF-7 and MDA-MB-231 cancer cells. These findings suggest that QI- Ag: ZnO NCs have promising applications in environmental remediation and cancer therapy, opening avenues for further advancements in the arena of nanomaterial synthesis and utilization. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Ultraviolet Flux and Spectral Variability Study of Blazars Observed with UVIT/AstroSat
Blazars, the peculiar class of active galactic nuclei, are known to show flux variations across the accessible electromagnetic spectrum. Though they have been studied extensively for their flux variability characteristics across wavelengths, information on their ultraviolet (UV) flux variations on timescales of hours is very limited. Here, we present the first UV flux variability study on intraday timescales of a sample of ten blazars comprising two flat-spectrum radio quasars (FSRQs) and eight BL Lacertae objects (BL Lacs). These objects, spanning a redshift (z) range of 0.034 ? z ? 1.003, were observed in the far-UV (1300?1800 and near-UV (2000?3000 wavebands using the ultraviolet imaging telescope on board AstroSat. UV flux variations on timescales of hours were detected in nine sources out of the observed ten blazars. The spectral variability analysis showed a bluer-when-brighter trend with no difference in the UV spectral variability behavior between the studied sample of FSRQs and BL Lacs. The observed UV flux and spectral variability in our sample of both FSRQs and BL Lacs revealed that the observed UV emission in them is dominated by jet synchrotron process. 2024. The Author(s). Published by the American Astronomical Society. -
Biotic elicitors influence boeravinone B production from cell suspension cultures of Boerhavia diffusa Linn.
Boerhavia diffusa L., (punarnava) is known for its rich, secondary metabolite content and potential pharmacological properties. Boeravinone B, a flavonoid, is a significant plant secondary metabolite found in punarnava, exhibiting various pharmacological properties that translate into anticancer, antioxidant, anti-inflammatory, immunomodulatory and nephroprotective activities. However, the limited production of boeravinone B within the plant poses challenges in meeting market demands. In this study, various biotic components, including filtrates and supernatants of algae, fungi, and bacteria, are employed as elicitors to enhance the production of boeravinone B from the cell suspension cultures of punarnava. Fungal components like yeast extract, Aspergillus niger and Cordyceps militaris, bacteria like Escherichia coli and Bacillus subtilis, as well as Algae such as Valonia utricularis and Spirulina platensis, are utilised to assess their efficiency as elicitors at different day intervals. Results indicate that among all the elicitor treatments, fungal components like yeast extract, C. militaris and A. niger at 100 mg/L, 1 % and 5 % concentrations, administered 6, 6 and 2, days before harvesting, exhibit increased production of boeravinone B by 1.13, 1.14 and 2.63 folds, respectively, when compared to control cultures. Similarly, algae V. utricularis and S. platensis, at 2.5 % concentration and treated before harvesting on Day 6, demonstrate enhanced production of boeravinone B by 1.74 and 4.40 folds compared to control cultures. In addition, the efficiency of various biotic elicitors is examined by quantifying total phenolics and flavonoids in treated cell suspension cultures. These findings have the potential to enhance production strategies and meet the growing demand for this valuable compound with medicinal properties, leveraging easily accessible biotic elicitors. 2024 SAAB -
Ceramic-Polymer-Carbon Composite Coating on the Truncated Octahedron-Shaped LNMO Cathode for High Capacity and Extended Cycling in High-Voltage Lithium-Ion Batteries
Long-term electrochemical cycle life of the LiNi0.5Mn1.5O4 (LNMO) cathode with liquid electrolytes (LEs) and the inadequate knowledge of the cell failure mechanism are the eloquent Achilles heel to practical applications despite their large promise to lower the cost of lithium-ion batteries (LIBs). Herein, a strategy for engineering the cathode-LE interface is presented to enhance the cycle life of LIBs. The direct contact between cathode-active particles and LE is controlled by encasing sol-gel-synthesized truncated octahedron-shaped LNMO particles by an ion-electron-conductive (ambipolar) hybrid ceramic-polymer electrolyte (IECHP) via a simple slot-die coating. The IECHP-coated LNMO cathode demonstrated negligible capacity fading in 250 cycles and a capacity retention of ?90% after 1000 charge-discharge cycles, significantly exceeding that of the uncoated LNMO cathode (a capacity retention of ?57% after 980 cycles) in 1 M LiPF6 in EC:DMC at 1 C rate. The difference in stability between the two types of cathodes after cycling is examined by focused ion beam scanning electron microscopy and time-of-flight secondary ion mass spectrometry. These studies revealed that the pristine LNMO produces an inactive layer on the cathode surface, reducing ionic transport between the cathode and the electrolyte and increasing the interface resistance. The IECHP coating successfully overcomes these limitations. Therefore, the present work underlines the adaptability of IECHP-coated LNMO as a high-voltage cathode material in a 1 M LiPF6 electrolyte for prolonged use. The proposed strategy is simple and affordable for commercial applications. 2024 The Authors. Published by American Chemical Society. -
Exploring the role of plant oils in aquaculture practices: an overview
As the global demand for seafood surges, the expanding aquaculture industry faces a pressing need for viable aquafeed ingredients. The raw material for fish oil is limited and expensive due to unpredictable fishery resources in the fishing zones and the overexploitation of wild fisheries, underscoring the urgency of finding alternatives. This review explores diverse plant oil sources, including soybean, rapeseed, linseed, and algal oils, emphasizing their crucial role in nutritionally balanced aquafeeds. These oils support aquatic animals growth, health, and development, influencing membrane structure, energy storage, and hormone production. Genetically modified oilseeds (GM), such as camelina and canola, offer a controlled nutrient content, enabling customized nutrient profiles. This comprehensive review provides an overview of different plant oil sources, elucidates their nutrient profiles, and assesses their potential applications in aquaculture. The discussion encompasses their impact on growth, feed efficiency, lipid profile, health, immunological status, disease resistance, and overall performance of both freshwater and marine fish. Furthermore, the review compiles relevant data on the current status of genetically modified plant oils and explores their potential integration into aquaculture practices. In summary, substituting plant oils for fish oil in aquafeed presents a promising solution to aquaculture industry challenges to meet nutritional requirements for fish. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Exploring the Role of structurally modified Molybdenum disulfide composites with Prussian blue analogues as counter electrode catalysts for bifacial Dye-Sensitized solar cells
The present study aims to utilize Mn, Ni, and MnNi Prussian Blue Analogue (PBA) embedded MoS2 composites as Pt-free Counter Electrode (CE) in Dye Sensitized Solar Cells (DSSCs). Therefore, Ni-PBA, Mn-PBA, and MnNi-PBA were synthesized using a simple ageing procedure followed by a Hydrothermal method to prepare modified MoS2 composites. The crystalline structure, shape, surface area, and elemental oxidation state were analyzed using various studies. Also, the nanosheets formation around cubic structure further shows large numbers of active sites resulting in the high catalytic behaviour of the composites. Among the various composites, the Modified MoS2 based on MnNi-PBA, which was coated using a simple spin-coating procedure, exhibited the smallest ?EPP separation and the highest JRED value due to the rapid redox reaction at the CE/electrolyte interface and catalytic current. The maximum efficiency of 8.25 % was achieved for MnNi-PBA based composites, surpassing pristine MoS2 (6.72 %) and Pt (7.58 %) under front illumination (100 mW/cm2). Under rear illumination, the cell demonstrated a higher efficiency of 4.96 %, attributed to the high transmittance of the material-coated CE, making it suitable for bifacial applications. 2024 International Solar Energy Society -
Nano Zinc Oxide Particle Synthesis from Bio-Waste Selaginella willdenowii Leaf Extract: A Multi-Faceted Approach for Environmental and Biomedical Applications
Selaginella willdenowii, a commonly used greenhouse fern, was often used as a biowaste to synthesize zinc oxide nanoparticles (ZnO NPs) in an eco-friendly and cost-effective way. UV-Visible spectra studies were carried out to confirm the synthesis of S. willdenowii-mediated ZnO NPs (SW-ZnO NPs), and a peak at 367nm with a sharp band gap of 3.415eV was observed. The X-ray diffraction analysis indicated that the crystalline size of the synthesized SW-ZnO NPs was 11.971nm. The phytochemicals present in the extracts and the compounds involved in the reduction of metal to nanoparticles were determined by Fourier Transform Infrared analysis. Scanning electron microscopy was utilized to analyze the surface morphology and size of the obtained SW-ZnO NPs. The examination revealed that they exhibited a hexagonal shape, with an average size falling within the range of 17-23nm. Under ultra-violet light, reactive blue 220 and reactive yellow 145 dyes showed 78.06% and 60.14% degradation, showing potential photocatalytic degradation activity. The synthesized SW-ZnO NPs also exhibited antimicrobial activity against bacterial strains (Escherichia coli and Bacillus subtilis) and fungal cultures (Candida tropicalis and Candida albicans) showed cytotoxic activity against Hep-G2 cell lines. Our results suggest the green synthesized SW-ZnO NPs have potential photocatalytic, antimicrobial and cytotoxic potential. 2024 World Scientific Publishing Company. -
The Evolving Prospects of Bharatanatyam: An Enquiry on Changing Religious Landscape
As cultural boundaries expand, symbols of cultural identity, like dance forms, evolve in terms of content and practice. Bharatanatyam, originally a temple dance, originated in the Hindu culture and had long been considered a religious art. However, the art form has gradually expanded its scope beyond its religious context. Contemporary evidence suggests that artists increasingly engage in performances addressing themes that are secular and even compositions based on other religious beliefs, but not without challenges. This article brings to light the evolving religious aspects of Bharatanatyam and investigates novel elements being introduced by cross-religious practices, such as thematic innovations, choreographic patterns and symbolic representations. By analysing data from in-depth interviews with twenty artists from diverse religious backgrounds, the authors argue that religious conservatism in society hinders the evolution of art forms such as Bharatanatyam that have the potential to adapt across and beyond religions. Edinburgh University Press.