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An Empirical Evaluation of the Relationship Between Economic Growth, Population and Solid Waste Generation in India
Municipal solid waste (MSW) poses a hazard to the environment, human health and well-being and economic growth, if not managed correctly.It is essential to study the determinants of municipal solid waste generation for efficient waste management planning and achieving sustainable growth.The main objective of this paper is to establish a relationship between economic growth, population and MSW generation.Secondly, it aims to verify whether the environmental Kuznets curve (EKC) hypothesis is valid in the Indian context with MSW generation as the proxy variable for environmental degradation.Panel regression has been run using statewise data of MSW generation, state net domestic product (SNDP) per capita and population for the years 2000-2019.The results show a significant positive relationship between the selected variables.Least square regression was applied to verify the validity of the environmental Kuznets curve (EKC) hypothesis in India using nationwide data for MSW generation and GDP per capita for the years mentioned above.The results depicted inverted U-shaped curve with MSW as the dependent variable and GDP per capita as the independent variable and confirmed the validity of the EKC hypothesis. 2022 Scientific Publishers. All rights reserved. -
Structure-based virtual screening, pharmacokinetic prediction, molecular dynamics studies for the identification of novel EGFR inhibitors in breast cancer
Breast cancer is one of the most prevalent malignancy cancer types especially affecting women globally. EGFR is a proto onco gene as well as the first identified tyrosine kinase receptor. It plays a dynamic role in many biological tasks such as apoptosis, cell cycle progression, differentiation, development and transcription. Somatic mutation in the EGFR kinase domain derails the normal kinase activity and over expression leads to the progression of cancer especially breast cancer. EGFR is one of the well-known therapeutic targets for breast cancer. In this scenario, we attempt to identify novel potent inhibitors of EGFR. Initially, we performed structure-based virtual screening and identified four potential compounds effective against EGFR. Further, the compounds were subjected to ADME prediction as part of evaluation of the druggability and all the four compounds found to fall under satisfactory range with predicted pharmacokinetic properties. Eventually, the conformational stability of proteinligand complex was analyzed at different time scale by using Gromacs software. Molecular dynamics simulation run of 20 ns is carried out and results were analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF) to signify the stability of proteinigand complex. The stability of the proteinligand complex is more stable throughout entire simulation. From the results obtained from in silico studies, we propose that these compounds are exceptionally useful for further lead optimization and drug development. Communicated by Ramaswamy H. Sarma. 2020 Informa UK Limited, trading as Taylor & Francis Group. -
An efficient nonlinear access policy based on quadratic residue for ciphertext policy attribute based encryption
Ciphertext Policy Attribute Based Encryption (CP-ABE) is an efficient encryption scheme as data owner is making decision about the attributes that can access his data and adding that attributes to access structure while encrypting that message. Most existing CP-ABE scheme are based traditional access structure such as linear secret sharing scheme which incur large ciphertext size and linearly increases according to the number of attributes. And those schemes have more computational overhead for calculating share for each attribute and when recalculating secret in data user side. In this paper, we propose a different secret sharing scheme that can be used in access policy for CP-ABE which will reduce the size of ciphertext and there by communication overhead. Furthermore, the proposed scheme reduced computational overhead of secret sharing scheme and improved overall efficiency of the scheme. 2021 Little Lion Scientific -
Machine Learning Techniques for Resource-Constrained Devices in IoT Applications with CP-ABE Scheme
Ciphertext-policy attribute-based encryption (CP-ABE) is one of the promising schemes which provides security and fine-grain access control for outsourced data. The emergence of cloud computing allows many organizations to store their data, even sensitive data, in cloud storage. This raises the concern of security and access control of stored data in a third-party service provider. To solve this problem, CP-ABE can be used. CP-ABE cannot only be used in cloud computing but can also be used in other areas such as machine learning (ML) and the Internet of things (IoT). In this paper, the main focus is discussing the use of the CP-ABE scheme in different areas mainly ML and IoT. In ML, data sets are trained, and they can be used for decision-making in the CP-ABE scheme in several scenarios. IoT devices are mostly resource-constrained and has to process huge amounts of data so these kinds of resource-constrained devices cannot use the CP-ABE scheme. So, some solutions for these problems are discussed in this paper. Two security schemes used in resource-constrained devices are discussed. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AN EFFICIENT ACCESS POLICY WITH MULTI-LINEAR SECRET-SHARING SCHEME IN CIPHERTEXT-POLICY ATTRIBUTE-BASED ENCRYPTION
Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is a system in which attribute are used for user's identity and data owner determine the access policy to the data to be encrypt. Here access policy are attached with the ciphertext. In the form of a monotone Boolean formula monotone access structure, an access policy can be interpreted and a linear secret-sharing scheme (LSSS) can be implemented. In recent CP-ABE schemes, LSSS is a matrix whose row represent attributes and there exist a general algorithm which is proposed by Lewko and Waters it transforms a Boolean formula into corresponding LSSS matrix. But we may want to transform the monotone Boolean formula to an analogous but compressed formula first before applying the algorithm. This is a very complex procedure and require efficient optimization algorithm for obtaining equivalent but smaller size Boolean formula. So in this paper we are introducing an extended LSSS called multi-linear secret-sharing scheme where we can eliminate above optimization algorithm and directly convert any Boolean formula to multi-linear secret-sharing scheme. 2022 Little Lion Scientific. All rights reserved. -
A Machine Learning Model for Augmenting the Media Accessibility for the Disabled People
In an era characterized by the proliferation of digital media, the need to efficiently use multimedia content has become paramount. This article discusses an innovative technique called 'Fast Captioning (FC)' to improve media accessibility, especially for people with disabilities and others with time restrictions. Modern Machine Learning (ML) algorithms are incorporated into the framework, which speeds up video consumption while maintaining content coherence. The procedure includes extracting complex features like Word2Vec embeddings, part-of-speech tags, named entities, and syntactic relationships. Using annotated data, a ML model is trained to forecast semantic similarity scores between words and frames. The predicted scores seamlessly integrate into equations that calculate similarity, thus enhancing content comprehension. Through this all-encompassing approach, the article offers a comprehensive solution that balances the requirements of contemporary media with the accessibility requirements of people with disabilities, producing a more inclusive digital environment. Machine Learning-based Media Augmentation (ML-MA) has achieved the highest accuracy of 96%, and the captioning is accurate. 2023 IEEE. -
Quality of Drinking Water and Sanitation in India
Wide disparity exists in access to drinking water across social groups in rural and urban India. This article shows that the economically weaker sections or the lower quintile class does not have access to water within the premises both in rural and urban areas. This indicates that low income or wealth would mean poor access to basic amenities for households. Similarly, access to toilets and incidence of open defaecation reflect social disparities. The regression results show that an increase in the household income increases the predicted probability of maintaining an exclusive latrine. Further, compared to the General Category, the Scheduled Castes and Other Backward Classes have a lower probability of constructing an exclusive latrine facility, in the rural and urban areas. 2021 Institute for Human Development. -
Changes in Wage Trends and Earnings Differences in Kerala
In this article, the weekly earnings gap between men and women in Kerala is examined by a number of inequality indices such as the percentile ratio and the Gini coefficient. The entropy measures of inequality are used to decompose wage inequality into within-group and between-group inequalities. The earnings inequality between men and women has been increasing, even though their wage grows faster than mens wage. The indices of inequality suggest the growing wage disparity in the regular and casual labour market. The result reveals that the levels of education and earnings are positively correlated, but women with the same level of education earn much less than men in regular salaried work. The rising wage inequality of men and women during 20042009 were associated with the growth rate of wages in the same period. That is, the wage rates of both regular and casual workers have increased more than four per cent during the period that experienced the highest inequality. 2019, Indian Society of Labour Economics. -
Education Inequality in India: An Empirical Analysis Using National Sample Survey Data
This research examines the ruralurban differences in educational inequality of major states in India. Using National Sample Survey Office (NSSO) data and decomposition methods, this study finds that overall educational inequality has come down but still very high in rural areas. We found that factors such as limited access to higher education, financial constraints and social factors are responsible for the high inequality in rural areas. This study highlights the need for government intervention to enhance educational access by increasing institutions and providing financial aid. It also notes that non-financial barriers like English proficiency further exclude lower socio-economic groups. Hence, we argue for inclusive education policies to improve the existing situation. 2024 Institute for Human Development. -
Does the green finance initiatives transform the world into a green economy? A study of green bond issuing countries
Green finance initiatives have received global support in modern times, relatively in response to safeguard the environment and preserve natural resources through channelizing the investments to create a green economy. This paper attempts to evaluate and compare the green finance growth in green bond issuing nations across the world. This study also assesses the effect of green finance growth on the dependence of non-renewable energy resources especially fossil fuels that have been creating several environmental issues for the past years. This study develops a pressure-state-response framework to evaluate the comprehensive system of green finance growth that depicts the interaction of sub-aspects. We employ the entropy technique to calculate the weights at each level within the evaluation system. We also constructed empirical models to assess the relationship between green finance growth and dependence on fossil fuel consumption and found that there exists a negative relationship between the two. The results convey that proliferation of green finance instruments can reduce the dependence on fossil fuels and smoothen the transition towards a carbon negative world. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Malicious URL Detection Using Machine Learning Techniques
Cyber security is a very important requirement for users. With the rise in Internet usage in recent years, cyber security has become a serious concern for computer systems. When a user accesses a malicious Web site, it initiates a malicious behavior that has been pre-programmed. As a result, there are numerous methods for locating potentially hazardous URLs on the Internet. Traditionally, detection was based heavily on the usage of blacklists. Blacklists, on the other hand, are not exhaustive and cannot detect newly created harmful URLs. Recently, machine learning methods have received a lot of importance as a way to improve the majority of malicious URL detectors. The main goal of this research is to compile a list of significant features that can be utilized to detect and classify the majority of malicious URLs. To increase the effectiveness of classifiers for detecting malicious URLs, this study recommends utilizing host-based and lexical aspects of the URLs. Malicious and benign URLs were classified using machine learning classifiers such as AdaBoost and Random Forest algorithms. The experiment shows that Random Forest performs really well when checked using voting classifier on AdaBoost and Random Forest Algorithms. The Random Forest achieves about 99% accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Synthesis of ZnO and NiO nano ceramics composite high-performance supercapacitor and its catalytic capabilities
NiO and ZnO mixed nanocomposites were manufactured using the solution combustion process. As-prepared samples were analyzed using XRD. The XRD shows an average crystallite size of 3540 nm. The elemental composition determined by EDS indicates a nearly equal proportion of Ni and Zn, with an atomic ratio of Ni/Zn = 0.96. The specific capacitances of NiO is 295.5 Fg-1, ZnO is 117.3 Fg-1 and ZnO/NiO nanocomposites is 561.75 Fg-1 which are more than NiO and ZnO alone. This study shows that constructing binary oxide nanocomposites is an approach for developing high-performance supercapacitor electrode materials. Experimental observations on catalytic activity revealed that NiO/ZnO increased catalytic activity. Furthermore, adding NiO to ZnO in the composite increased the overall amount of oxygen vacancies in the samples. Our research lays the door for a simple, inexpensive, nontoxic, and quick technique to synthesize binary transition metal oxide-based electrode materials for high-performance supercapacitors. 2024 Elsevier Ltd and Techna Group S.r.l. -
Enhanced supercapacitors and LPG sensing performance of reduced graphene oxide/cobalt chromate pigments for energy storage applications
It is imperative that an initial inquiry be conducted as soon as possible since the production of monolayer of carbon atoms (rGO) composites is the root cause of their poor performance in supercapacitor and LPG sensors. Here, an effort is undertaken to construct a cobalt chromate pigments-reduced graphene oxide (CoCr2O4/rGO) by solution combustion method for the supercapacitor and LPG sensor. The proposed method is efficient and easy in terms of its application to the production of CoCr2O4/rGO polycrystalline composite on a wide scale. Within the scope of this work is an investigation into the improved supercapacitor and LPG sensing behaviour of CoCr2O4/rGO polycrystalline composite. We have implemented a simple method that has been identified for mass-producing reduced graphene oxide. The Solution combustion technique was used, and it was successful in achieving this goal for the very first time. X-ray diffraction technique is used analyse crystallinity, phase, and structural investigation. The nature of gas sensing behaviour with a step function of LPG gas at 500 ppb was studied at room temperature for rGO, The CoCr2O4 pigments and 0.5CoCr2O4+0.5rGo polycrystalline composite samples. The gas response is maximum for 0.5CoCr2O4+0.5rGo polycrystalline composite in the order of 97% in compare with the reduced graphene oxide sample which shows the lowest sensitivity in the order of 26% on exposure of liquified petroleum gas (LPG). The recorded response and recovery times of 0.5CoCr2O4+0.5rGo polycrystalline composite is found to be 40 s and 52 s respectively in comparison to the rGO sample about 58 and 74 s respectively. By adding rGo to the material, the cyclic voltammetry (CV) findings demonstrate improved current density and area of CV loop with increased scan rate. In three-electrode reveals the system, a CoCr2O4-rGo material exhibits a specific capacitance of 226 F/g. Thus, the results reveals that rGo is contributing significantly to the enhancement of a supercapacitor's performance of CoCr2O4. 2023 Elsevier Ltd and Techna Group S.r.l. -
Fintech Innovations in the Financial Service Industry
Digital transformation underscored by the fourth industrial revolution has led to the emergence of sophisticated technology-enabled financial services known as fintech, that has swiftly altered traditional financial services space. Global adoption of fintech is rapidly increasing due to its disruptive nature and is largely embraced by participants who are underserved by traditional financial service providers. Global investments in fintech are growing rapidly year by year owing to increased interconnectivity with the digital revolution. Fintech is expansive, engulfing a plethora of innovative applications in various services including payments, financing, asset management, insurance, etc. There exists a gap in the literature and visualization research on impact and future pathway of fintech innovations in payments and financial services and role of financial regulations. This study aims to enrich the understanding of fintech innovations in payments and financing and investigate the correlation and significance of regulatory framework in maintaining a fair ecosystem. With this objective, an extant systematic review was performed using research articles published in peer-reviewed journals for the period 20142022 when there has been a burgeoning of interest in fintech globally. The findings of this study contribute to the theoretical constructs of fintech innovations in the financial services industry and show that such innovations play a crucial role in shaping the nature of future of business. The results of this study have implications for researchers who could deploy this research as a reference point to get a holistic insight and a detailed mapping of innovations in fintech. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Intelligent Optimized Delay Algorithm for Improved Quality of Service in Healthcare Social Internet of Things
Internet of Things (IoT) interconnects billions of devices by establishing a network that adheres to International Organization of Standardization (ISO) standards. These devices communicate with each other by sharing data regulated by the application. This is performed to accomplish a task or service that the application demands. The social or human-like behaviors are adapted in the IoT environment forming the Social IoT (SIoT). The SIoT integrates social networks in IoT-connected devices, making them unique and identifiable. Recent advancements in networking, intelligent network management, battery management, remote sensing, sensors, and other related technologies convinced users and designers to adopt IoT even for large-scale applications where the data involved is enormous. Leveraging the advancements in medical IoT, which focuses on healthcare to patients, can improve its service by removing redundant manual processes, long wait times, and providing other automated services. The advancements in real-time healthcare IoT devices and wearables make a strong case for implementing SIoT in the healthcare domain. SIoT in the healthcare domain has the potential to benefit users on a large scale. This chapter comprehends the challenges and solutions of using SIoT in medical and healthcare solutions from a networking quality of service (QoS) perspective. In addition, this chapter compares the intelligent algorithm, which can be used to improve the QoS of SIoT. Achieving higher QoS is necessary for healthcare services, especially while handling data from emergency and intensive care units. These data cannot tolerate errors and delays. Intelligent network management has become unavoidable in the health and medical services to achieve a higher degree of QoS system, which indirectly decreases data transfer time. The data from the sensor devices sent across the network leads to data loss and delay in data transmission due to congestion in the network and gateway devices. The optimized algorithms incorporated with the delay-based algorithm improves the QoS predominantly and reduces the delay in data transfer. Similarly, the particle swarm optimization algorithm allocates resources over the network and dynamically makes the network adapt to increased and reduced data flow, which reduces the delay and improves the QoS. Intelligent optimized delay algorithm (IODA) is proposed to improve the network performance by reducing the delay and using available bandwidth for data transfer in SIoT. 2023 selection and editorial matter, Gururaj H L, Pramod H B, and Gowtham M; individual chapters, the contributors. -
ChIPSeq Analysis with Bayesian Machine Learning
ChIP-sequencing, otherwise called ChIP-seq, is a technique used to identify protein co-operations with DNA. A crucial advancement to the field of bio-informatics, ChIP sequencing is conducted in research labs around the world to get a better understanding of the way transcription factors and other associated proteins influence the gene in many biological processes and in tackling disease states. ChIP-seq is predominantly a field under the domain of biotechnology, however recent advancements and development of tools to process ChIP data have turned the study into one involving bio-informatics, allowing computer scientists and lab technicians to work on an otherwise scholarly field of biochemistry, molecular biology, microbiology and biomedicine. This report illustrates the predominant work-flow undertaken to sequence chromatin from a cell and to gain insights on the gene/protein of interest. Another aspect added is to use Machine Learning with Bayesian statistical techniques for Peak Calling. The different stages enumerated in this paper have been completed either with the R language or on a Web Server titled Galaxy.org. 2019 IEEE. -
Alzheimer's disease : A challenge in the face of modern era /
Mapana Journal of Sciences, Vol.12, Issue 2, pp.19-36, ISSN No: 0975-3303. -
Will the antioxidant supplements impact the mitigation of oxidative stress in Parkinsons disease?
Parkinsons disease is a frequent neurodegenerative condition marked by both non-motor and motor symptoms. It is brought on by the selective depletion of dopamine neurons from the substantia nigra region of the midbrain. Numerous variables, including lifestyle, environment, age, smoking, and underlying medical disorders, affect the occurrence of Parkinsons disease. The free radicals created by oxidative stress have an impact on the morphology and function of neuronal cells and are a factor in many neurodegenerative disorders, including Parkinsons and Alzheimers, disorder. Although the pathophysiological mechanism causing neuronal degeneration is still unknown, oxidative stress plays a critical role in the pathogenesis of idiopathic Parkinsons disease. It also has an association with numerous proteins, including ?-synuclein, amyloid, DJ-1 protein and several signalling pathways like extracellular regulated protein kinases. Reactive oxygen species also contribute to complex Is mitochondrial respiratory activity. The naturally occurring antioxidants are the phenols, anthocyanins, carotenoids, flavonoids, vitamins, and lignans. These antioxidants retain the reactive oxygen species generation and plays a role in several biological effects. As a result, natural plant antioxidants may have an impact on Parkinsons disease and offer an alternative therapy that minimises oxidative stress and slows down the evolution of the disease. 2024 Visagaa Publishing House. -
Harnessing the Power of Simulation Games for Effective Teaching in Business Schools
This research delves into the effectiveness of simulation games, in business education specifically focusing on how they improve decision making skills, critical thinking, real world business applications, student engagement and problem-solving abilities. While simulation games are widely recognized as cutting edge tools that provide learning experiences beyond traditional methods there remains a gap in empirical research assessing their overall impact on educational outcomes. Using a combination of analysis and qualitative case studies this study seeks to address this gap by examining how simulation games influence factors in business education. The methodology involves using a one-way ANOVA to compare learning outcomes across business disciplines and conducting detailed case studies for context. The results reveal effects of integrating simulation games into curricula on the mentioned learning outcomes. These findings highlight the importance of incorporating simulation games into business education to enhance students learning experiences effectively. By offering insights on optimizing and tailoring the use of simulation games in education settings this study contributes to improving teaching practices in business schools and encourages research into the interaction, between educational technology and learning efficacy. 2024 IEEE. -
Chandra X-ray analysis of Herbig Ae/Be stars
Herbig Ae/Be (HAeBe) stars are intermediate-mass pre-main-sequence stars, characterized by infrared (IR) excess and emission lines. They are observed to emit X-rays, whose origin is a matter of discussion and not settled yet. X-ray emission is not expected in HAeBe stars, as they lack the subsurface convective zone. In this study, we retrieved observations from the Chandra archive for 62 HAeBe stars, among which 44 sources (detection fraction ?71 per cent) were detected in X-rays, with 7 being new detections. We use this sample as a test bed to conduct a comparative analysis of the X-ray properties of HAeBe stars and their low-mass counterparts, T Tauri stars (TTSs). Further, we compare the X-ray properties of HAeBe stars and TTSs with optical and IR properties to constrain the X-ray emission mechanism in HAeBe stars. We found no correlation between X-ray emission and disc properties of HAeBe stars, confirming that X-rays are not related to accretion shocks. About 56 per cent of HAeBe stars without any known subarcsec companions have lower plasma temperatures (kT ? 2 keV). We observe flaring/variability in HAeBe stars with confirmed low-mass companions. These stars show plasma temperatures > 2 keV, similar to TTSs. Guided by this information, we discuss the role of a T Tauri companion for X-ray emission seen in our sample of HAeBe stars. From the results obtained in this paper, we suggest that X-ray emission from HAeBe stars may not be related to accretion shocks or hidden TTS, but rather can be due to magnetically driven coronal emission. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society.