Revisiting India’s Amended Citizenship Act 2019 in Light of Constitutional Ethos

The Citizenship Amendment Act 2019 and the National Register of Citizens in India are perceived as reflective of a religious classification in grant and continuance of Indian citizenship. The study aimed to discuss the future effects of the amended Citizenship Act 2019 and suggest alternatives to accommodate India's constitutional ethos. A considerable fraction of the Indian citizenry was discorded with this Act because Article 14 of the Indian Constitution prohibits discrimination based on religion, among other grounds. On the other hand, the state's stance asserted that the law aims to protect the persecuted religious minorities from other states. This study dealt with the nuances and intricacies of the problem to explicate viable solutions by an in-depth analysis of the issue in an unprejudiced manner where it used a combined doctrinal and empirical research to assess the perspectives on the policy in the Global South from the Indian experience. The findings reflected that while a majority of the provisions in the Act can be justified based on constitutional parameters, its few provisions are unconstitutional. In summary, even after juxtaposing all the justifications of the Act against the allegations, a considerable portion of the Act remains unconstitutional, and it needs to be revisited based on constitutional parameters

The technological growth in eHealth services

The infusion of information communication technology (ICT) into health services is emerging as an active area of research. It has several advantages but perhaps the most important one is providing medical benefits to one and all irrespective of geographic boundaries in a cost effective manner, providing global expertise and holistic services, in a time bound manner. This paper provides a systematic review of technological growth in eHealth services. The present study reviews and analyzes the role of four important technologies, namely, satellite, internet, mobile, and cloud for providing health services.Web of Scienceart. no. 89417

Implementation of Clean Coal Technologies to comply with “New Emission Norms” for Thermal Power Plants - Way forward for Southern Region Summary Report of NITI Aayog-DST-NIAS Workshop 17th September 2019 (NIAS/NSE/EEP/U/WR/13/2019)

Coal based Thermal Power Plants (TPP) are the backbone of the power generation utilities in the country. Coal based TPPs constitute to around 56.1% of the total installed capacity and generates around 74.2% of the electricity generated in India. Considering the high pollution and resource impacts, of TPPs the Ministry of Environment, Forest and Climate Change (MoEF&CC) notified the Environment Protection (Amendment) Rules (EPAR) on December 5, 2015 with a two-year window for TPPs to meet these standards.  When implemented, these norms are expected to have positive environmental and health benefits by leading to lower pollution levels from TPPs. However, compliance with the new emission norms would require retrofitting existing thermal power plants with various Pollution Control Technologies (PCT) in the form of auxiliary systems to control SO2, NOX and PM emissions. In order to ensure 24x7 supply of electricity, CPCB (in consultation with CEA) finalized the revised timelines for all TPPs to comply with the new emission norms by December 2022. The team at Energy and Environment Programme (EEP) in NIAS, Bangalore interacted with various Power Plant Generation companies (GENCOs) in Southern Region to understand their challenges and way forward with respect to the huge capital investment and schedules for implementation. This team developed and a “Concept Paper” for a workshop with the theme, “Strategies and Action Plans needed for transition to an environment friendly and sustainable Electricity Source mix for the Southern Region”. This Workshop was held at NIAS on 17th September 2019 to enable key stakeholders - Power Plant Owners (Central & Southern States), Pollution Control Equipment Suppliers, Regulators and Policymakers to share their experience and deliberate on the challenges to develop a road map for implementation.  This report presents the gist of each talk by the invited participants, and also consolidates the key findings and recommendations of the Workshop.  This summary report will form the basis for further research as well as for policy advocacy with GOI through NITI Aayog

Implementation of clean coal technologies to comply with "New Emission Norms" for thermal power plants - way forward for the Southern region. Summary Report of NITI Aayog-DST-NIAS Workshop, 17th September 2019

Coal based Thermal Power Plants (TPP) are the backbone of the power generation utilities in the country. Coal based TPPs constitute to around 56.1% of the total installed capacity and generates around 74.2% of the electricity generated in India. Considering the high pollution and resource impacts, of TPPs the Ministry of Environment, Forest and Climate Change (MoEF&CC) notified the Environment Protection (Amendment) Rules (EPAR) on December 5, 2015 with a two-year window for TPPs to meet these standards. When implemented, these norms are expected to have positive environmental and health benefits by leading to lower pollution levels from TPPs. However, compliance with the new emission norms would require retrofitting existing thermal power plants with various Pollution Control Technologies (PCT) in the form of auxiliary systems to control SO2, NOX and PM emissions. In order to ensure 24x7 supply of electricity, CPCB (in consultation with CEA) finalized the revised timelines for all TPPs to comply with the new emission norms by December 2022. The team at Energy and Environment Programme (EEP) in NIAS, Bangalore interacted with various Power Plant Generation companies (GENCOs) in Southern Region to understand their challenges and way forward with respect to the huge capital investment and schedules for implementation. This team developed and a “Concept Paper” for a workshop with the theme, “Strategies and Action Plans needed for transition to an environment friendly and sustainable Electricity Source mix for the Southern Region”. This Workshop was held at NIAS on 17th September 2019 to enable key stakeholders - Power Plant Owners (Central & Southern States), Pollution Control Equipment Suppliers, Regulators and Policymakers to share their experience and deliberate on the challenges to develop a road map for implementation. This report presents the gist of each talk by the invited participants, and also consolidates the key findings and recommendations of the Workshop. This summary report will form the basis for further research as well as for policy advocacy with GOI through NITI Aayog. A.V. Krishnan, Shyam Sundar R, Shilpa Srivastava and R. Srikant

Multi-Objective ANT Lion Optimization Algorithm Based Mutant Test Case Selection for Regression Testing

582-592The regression testing is principally carried out on modified parts of the programs. The quality of programs is the only concern of regression testing in the case of produced software. Main challenges to select mutant test cases are related to the affected classes. In software regression testing, the identification of optimal mutant test case is another challenge. In this research work, an evolutionary approach multi objective ant-lion optimization (MOALO) is proposed to identify optimal mutant test cases. The selection of mutant test cases is processed as multi objective enhancement problem and these will solve through MOALO algorithm. Optimal identification of mutant test cases is carried out by using the above algorithm which also enhances the regression testing efficiency. The proposed MOALO methods are implemented and tested using the Mat Lab software platform. On considering the populace size of 100, at that point the fitness estimation of the proposed framework, NSGA, MPSO, and GA are 3, 2.4, 1, and 0.3 respectively. The benefits and efficiencies of proposed methods are compared with random testing and existing works utilizing NSGA-II, MPSO, genetic algorithms in considerations of test effort, mutation score, fitness value, and time of execution. It is found that the execution times of MOALO, NSGA, MPSO, and GA are 2.8, 5, 6.5, and 7.8 respectively. Finally, it is observed that MOALO has higher fitness estimation with least execution time which indicates that MOALO methods provide better results in regression testing

Analyzing the Prospects of Blockchain in Healthcare Industry

Deployment of a secured healthcare information is a major challenge in a web based environment. Ehealth services are subjected to same security threats as other services. The purpose of blockchain is to provide a structure and security to the organization data. Healthcare data deals with confidential information. The medical records can be well organized and empower their propagation in a secured manner through the usage of blockchain technology. The study throws light on providing security of health services through blockchain technology. The authors have analysed the various aspects of role of blockchain in healthcare through an extensive literature review. The application of blockchain in covid-19 has also been analysed and discussed in the study. Further application of blockchain in Indian healthcare has been highlighted in the paper. The study provides suggestions for strengthening the healthcare system by blending machine learning, artificial intelligence, big data, IoT with blockchain

Multi-Objective ANT Lion Optimization Algorithm Based Mutant Test CaseSelection for Regression Testing

The regression testing is principally carried out on modified parts of the programs. The quality of programs is the only concern of regression testing in the case of produced software. Main challenges to select mutant test cases are related to the affected classes. In software regression testing, the identification of optimal mutant test case is another challenge. In this research work, an evolutionary approach multi objective ant-lion optimization (MOALO) is proposed to identify optimal mutant test cases. The selection of mutant test cases is processed as multi objective enhancement problem and these willsolve through MOALO algorithm. Optimal identification of mutant test cases is carried out by using the above algorithm which also enhances the regression testing efficiency. The proposed MOALO methods are implemented and tested using the Mat Lab software platform. On considering the populace size of 100, at that point the fitness estimation of the proposed framework, NSGA, MPSO, and GA are 3, 2.4, 1, and 0.3 respectively. The benefits and efficiencies of proposed methods are compared with random testing and existing works utilizing NSGA-II, MPSO, genetic algorithms in considerations of test effort, mutation score, fitness value, and time of execution. It is found that the execution times of MOALO, NSGA, MPSO, and GA are 2.8, 5, 6.5, and 7.8 respectively. Finally, it is observed that MOALO has higher fitness estimation with least execution time which indicates that MOALO methods provide better results in regression testing

MOLECULAR DETECTION OF HUMAN RHINOVIRUS IN RESPIRATORY SAMPLES OF SWINE FLU NEGATIVE NORTH INDIAN CHILDREN WITH FLU-LIKE ILLNESS

Objectives: Flu-like illness may also be caused by different respiratory viruses other than influenza. Human rhinovirus (HRV) shows almost flu-likesymptoms. The purpose of this study is the molecular detection of HRV in throat swab of swine flu negative North Indian children during the years2012 and 2013. Reverse transcriptase (RT) - polymerase chain reaction (PCR) amplification of 5'non-coding region (NCR) was used for HRV detectionfollowed by cell culture isolation of HRV.Methods: PCR confirmed swine flu negative throat swab samples were collected from the Department of Microbiology, Sanjay Gandhi Post GraduateInstitute of Medical Sciences, Lucknow, Uttar Pradesh, India. The RNA isolation of samples was done using the QIAampViral RNA Mini Kit (Qiagen),followed by single step RT-PCR amplification (AgPath-ID, Life Technologies). All PCR positive HRV samples were cell cultured in HeLa and HEp-2 celllines for viral isolation.®Results: 135 swine flu negative throat swab samples were examined. Out of which 34 samples (25.2%) were found HRV positive by RT-PCR, while onlyfour samples (11.8%) were culture positive on HeLa cell line. Younger children (0-4 year) were found more susceptible to HRV infection. This studyindicated the highest prevalence of HRV (37.0%) during the months (September-October) of the Autumn season in 2012 and 57% in Winter-springseason (February-March) during 2013.Conclusion: HRV may be a cause of flu-like symptoms in swine flu suspected North Indian children with a higher rate during Autumn and Springseason. Molecular detection of HRV using RT-PCR is more sensitive than cell culture assay.Keywords: Human rhinovirus, Swine flu, Influenza-like illness, Lower respiratory tract infections