Impact of Voluntary Disclosure on Valuation of Firms: Evidence from Indian Companies
Financial Reporting; Firm Value; Panel Data Regression; Tobins Q Ratio; Voluntary Disclosures
This article investigates the effect of voluntary corporate disclosures on the firm value from the market value perspective. Financial reporting includes disclosures as prescribed by regulators, but few companies go beyond mandatory requirements and provide additional information voluntarily. This study empirically tests the extent of such voluntary disclosures using Corporate Voluntary Disclosure Index containing 81 items of both financial and non-financial information and panel data regression to test the hypotheses. The sample for this study is the non-financial companies in the BSE 100 Index and the period is five financial years from 20102011 to 20142015. This study finds a positive association between voluntary disclosures and firm value as measured by Tobins Q. Especially the market gives a higher valuation for companies disclosing optional information on social and environmental, corporate governance and financial information. This finding has a significant implication for emerging economies like India and it supports various disclosure theories such as agency, stakeholders and positive accounting theories. 2020 Management Development Institute.
Charumathi B., Department of Management Studies, School of Management, Pondicherry University, Puducherry, India; Ramesh L., Institute of Management, CHRIST (Deemed to be University), Bangalore, India
Enhancement of free convection from horizontal-base straight-fin heat sink by partial shrouding
Conduction; Electronic cooling; Extended surfaces/fins; Heat and mass transfer; Heat exchangers; Heat sink; Heat transfer enhancement; LED cooling; Natural and mixed convection; Natural convection; Rectangular fin; Shroud plate; Thermal systems
This work presents a simple method to improve natural convection heat transfer performance of horizontal-base straight-fin heat sink by adding partial shroud plates on top of the heat sink at both ends. Experiments are conducted in conjunction with a detailed three-dimensional (3D) computational study. The numerical model is validated using experimental results. With partial shrouding, the modification and effective utilization of airflow surrounding the heat sink leads to significant heat transfer enhancement. The installation of shroud plates effectively improves the mass flowrate of air admitted into the fin channel. Further, the airflow drawn above the heat sink dissipates heat from the upper surface of the shroud plate. There is also a significant heat dissipation from the lower surface of the shroud plate which is exposed to cold air drawn from the side-end of the heat sink. The heat transfer from the existing optimal conventional heat sink is improved by 17% with the introduction of shroud plates. An optimal width of the shroud plate is identified to exist for the maximum heat transfer. The percentage enhancement in heat transfer achieved by partial shrouding increases with a decrease in the fin height and with an increase in the fin spacing. The proposed compact heat sink design would be of application in enhancing passive heat dissipation from light-emitting diode (LED) lights and other electronic devices, especially when size constraints exist. Copyright 2020 by ASME
Journal of Thermal Science and Engineering Applications, Vol-12, No. 3
American Society of Mechanical Engineers (ASME)
https://doi.org/10.1115/1.4046021 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091516430&doi=10.1115%2f1.4046021&partnerID=40&md5=6426a6bc96e3d4577e85f70c7c99ce02
Nair D.V., Department of Mechanical and Automobile Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India
Augmented Reality-Enabled Education for Middle Schools
Augmented reality; Education; Mobile application
Augmented reality acts as an add-on to teachers while teaching students, and this helps the teachers and students to have an interactive session. Augmented realitys usage in education is cited as one of the major changes in the educational sector. Thus, the work carried out makes a positive impact in the educational industry. Augmented reality provides features like image recogntion, motion tracking, facial recognition, plane detection, etc., to provide interactive sessions. Simultaneous localization and mapping and concurrent odometry and mapping have proved to be efficient algorithms for augmented reality on mobile devices. The work carried out allows students to view interactive newspapers while reading a specific article. It also allows them to view a dynamic three-dimensional model of the solar system on their smartphone using augmented reality. 2020, Springer Nature Singapore Pte Ltd.
Kapoor V., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Naik P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India
Acetylcholine esterase inhibition activity of leaf extract of Saraca asoca using zebrafish as model organism
Acetylcholine esterase (AChE); Alzheimers disease; Molecular docking; Saraca asoca; Zebrafish
Alzheimers disease, also called as Senile Dementia, is a progressive neurogenerative disease that slowly destroys important mental functions like memory, reasoning and thinking. A plethora of factors including genetics, lifestyle, environment, age etc. play a part in determining its incidence. One of the commonly used techniques to slow down the progression of Alzheimers is to reduce the functioning of Acetylcholinesterase (AChE) enzyme which breaks down the neurotransmitter acetylcholine. Plants have been found to be natural sources of AChE inhibitors. Hence the present investigation was an attempt to screen Ashoka plant (Saraca asoca) for such inhibitors. Zebrafish (Danio rerio) was used as a model organism due to its genetic similarities with humans. Both in vivo and in vitro analyses using zebrafish indicated inhibitory action of the leaf extract on AChE. Gas Chromatography- Mass spectrometry (GCMS) analysis of the methanolic leaf extract and further docking studies of prominent phytochemicals revealed the AChE inhibitory potential of molecules like Stigmasterol, ?-sitosterol, Vitamin E etc. Hence these molecules can be thought of as targets in the therapy of Alzheimers disease. 2020 World Research Association. All rights reserved.
Rijo R.; Tilling B.R.; Mehul V.A.; Sumit P.; Suma S.
Research Journal of Chemistry and Environment, Vol-24, No. 6, pp. 88-94.
Rijo R., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Tilling B.R., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Mehul V.A., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Sumit P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Suma S., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India
Psychological health among armed forces doctors during COVID-19 pandemic in India
Anxiety; COVID-19; Depression HADS; Doctors
Background: A pandemic poses a significant challenge to the healthcare staff and infrastructure. We studied the prevalence of anxiety and depressive symptoms among armed forces doctors in India during the COVID-19 pandemic and the factors that contribute to these symptoms. Methods: The study was conducted from March 30, 2020, to April 2, 2020, using a self-administered questionnaire questionnaire using the hospital anxiety and depression scale (HADS), which was sent through Google Forms. Responses were received from 769 respondents. Data were analyzed for demographic details and HADS scores using the chi-square test and backward logistic regression. Results: Anxiety and depressive symptoms were seen in 35.2% and 28.2% of the doctors, respectively. In doctors with anxiety symptoms, significant associations were observed with age (2035 years, 39.4%, P = 0.01), gender (females, 44.6%, P < 0.001), duration of service (010 years, 38%, P = 0.03), and clinical versus non-clinical specialties (non-clinical, 41.3%, P < 0.001) as opposed to marital status, education level, and current department of work. In doctors with depressive symptoms, significant associations were observed with age (P = 0.04), clinical versus non-clinical specialties (P < 0.001), duration of service (010 years, 30.1%, P = 0.03), and doctoral degree (P = 0.04) as opposed to gender, marital status, education level, and current working department. Conclusion: The study revealed a high prevalence of anxiety and depressive symptoms among armed forces doctors. The main contributing factors are female gender, young age group, non-clinical specialties, and having a doctoral degree. Copyright 2020 Indian Psychiatric Society - South Zonal Branch.
Gupta S.; Kohli K.; Padmakumari P.; Dixit P.K.; Prasad A.S.; Chakravarthy B.S.; Shukla R.; Ghana P.; Mahapatra D.; Varadaraj G.
Indian Journal of Psychological Medicine, Vol-42, No. 4, pp. 374-378.
All Open Access; Gold Open Access; Green Open Access
Gupta S., Dept. of Psychology, CHRIST (Deemed to be University), Central Campus, Bengaluru, Karnataka, India; Kohli K., Medical Division, Command Hospital Airforce, Bengaluru, Karnataka, India; Padmakumari P., Dept. of Psychology, CHRIST (Deemed to be University), Central Campus, Bengaluru, Karnataka, India; Dixit P.K., Medical Division, Command Hospital Airforce, Bengaluru, Karnataka, India; Prasad A.S., Medical Division, Command Hospital Airforce, Bengaluru, Karnataka, India; Chakravarthy B.S., Dept. of Psychiatry, Command Hospital Airforce, Bengaluru, Karnataka, 560007, India; Shukla R., Medical Division, MH Namkum, Ranchi, Jharkhand, India; Ghana P., Medical Division, Command Hospital Airforce, Bengaluru, Karnataka, India; Mahapatra D., Medical Division, Command Hospital Airforce, Bengaluru, Karnataka, India; Varadaraj G., Medical Division, Command Hospital Airforce, Bengaluru, Karnataka, India
Long memory investigation during demonetization in India
Bubble; Demonetization; Herd behavior; Joseph Effect; Noah Effect
Long-range dependence (LRD) in financial markets remains a key factor in determining whether there is market memory, herding traces, or a bubble in the economy. Usually referred to as 'Long Memory', LRD has remained a key parameter even today since the mid-1970s. In November 2016, a sudden and drastic demonetization measure took place in the Indian market, aimed at curbing money laundering and terrorist funding. This study is an attempt to identify market behavior using long-range dependence during those few days in demonetization. Besides, it tries to identify nascent traces of bubble and embedded herding during that time. Auto Regressive Fractionally Integrated Moving Average (ARFIMA) is used for three consecutive days around the event. Tick-by-tick data from CNX Nifty High Frequency Trading (CNX Nifty HFT) is used for three consecutive days around demonetization (approximately, 5000 data points from morning trading sessions on each of the three days). The results show a clear and profound presence of herd behavior in all three data sets. The herd intensity remained similar, indicating a unique mixture of both 'Noah Effect' and 'Joseph Effect', proving a clear regime switch. However, the results on the event day show stable and prominent herding. Mandelbrot's specified effects were tested on an uncertain and sudden financial event in India and proved to function perfectly. Bikramaditya Ghosh, Saleema J. S., Aniruddha Oak, Manu K. S., Sangeetha R., 2020.
Ghosh B.; Saleema J.S.; Oak A.; Manu K.S.; Sangeetha R.
Investment Management and Financial Innovations, Vol-17, No. 2, pp. 297-307.
Ghosh B., Institute of Management, Christ University, India; Saleema J.S., Department of Computer Science, Christ University, India; Oak A., Institute of Management, Christ University, India; Manu K.S., Department of Management Studies, Christ University, India; Sangeetha R., Department of Management Studies, Christ University, India
An ancestral genomic locus in Mycobacterium tuberculosis clinical isolates from India hints the genetic link with Mycobacterium canettii
Ancestral strain; Genome sequencing; Mycobacterium tuberculosis; Smooth tubercle bacilli; Subtractive hybridization
Background: Tuberculosis remains a worldwide public health emergency. To better understand M. tuberculosis and to identify genomic variations characteristic to the Indian clinical isolates by a low-cost method, a genomic subtractive hybridization between M. tuberculosis H37Rv and a clinical isolate from South India was performed. Results: This revealed a novel 0.4-kb subtractive fragment which was used as a handle to pull out a 4.5-kb genomic region characteristic to the clinical isolate and was absent in H37Rv. On further studies, this 4.5-kb region was found to be present in 91% of the M. tuberculosis clinical isolates screened from Kerala, a state in South India. Interestingly, this novel region has 99% identity (with 100% query coverage) with genomic regions of M. canettii. Discussion: The present study hypothesizes that this locus was present in the recent common environmental ancestor of mycobacteria, retained to the maximum extent in M. canettii and ancestral isolates of M. tuberculosis, and later deleted in other modern lineages of M. tuberculosis. Thus, this region may serve as one of the links between the pathogenic mycobacteria and the environmental species. We also propose that the Indian isolates of M. tuberculosis might be closely related to the putative progenitor M. prototuberculosis with respect to this locus. More studies on other genomic loci from different strains of M. tuberculosis are required to establish more links in this direction. 2020, Springer Nature Switzerland AG.
International Microbiology, Vol-23, No. 3, pp. 397-404.
https://doi.org/10.1007/s10123-019-00113-0 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077586924&doi=10.1007%2fs10123-019-00113-0&partnerID=40&md5=313246f3c19fe94ecc9ad88fef0dbaaa
Sarojini S., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 29, India; Mundayoor S., Rajiv Gandhi Centre for Biotechnology, (RGCB), Trivandrum, India, Inter University Centre for Biomedical Research and Super Speciality Hospital (IUCBR & SSH), Kottayam, India
A New Series Solution Applicable to a Class of Boundary Layer Equations with Exponential Decay in Solution
Exponential decay; FalknerSkan-type equation; Series solution; Shooting method; Stretching sheet
A new series solution for the coupled nonlinear boundary value problem (BVP) of the FalknerSkan-type, resulting from the use of the boundary layer approximation to a mixed convective flow is obtained. The solution domain is transformed from the semi-infinite interval of physical interest to the unit interval by using the transformation z= 1 - e-?. The coupled nonlinear BVP is converted into an equivalent initial value problem (IVP) by supplying appropriate initial conditions. Series solution of the equivalent IVP is obtained in powers of 1 - e-? with assistance from the NewtonRaphson method. Convergence of the series is assured by the very design of the series as confirmed by the DombSykes plots and the plots of partial sums. The results of the series solution compare well with the numerical results obtained by the shooting method based on the RungeKuttaFehlberg45 and NewtonRaphson methods. The novelty of the methodology lies in the construction of a new series solution for a class of problems with exponential decay in their solution. Such a work has not been reported before. 2020, Springer Nature India Private Limited.
International Journal of Applied and Computational Mathematics, Vol-6, No. 4
Siddheshwar P.G., Department of Mathematics, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Narayana M., Department of Mathematics, The University of the West Indies, Mona Campus, Kingston 7, Jamaica; Bhatt B., Department of Mathematics and Statistics, The University of the West Indies, St. Augustine, Trinidad and Tobago
A Study on the Effect of Canny Edge Detection on Downscaled Images
Canny Edge detection; Gaussian blur; image interpolation; structural similarity index method
Abstract: Nowadays user devices such as phones, tablets etc. allows processing the images with help of high-end applications and softwares developed. Most of the times, the images are downscaled to make them compatible with these end devices. This leads to the loss of image quality. This loss of information on downscaling an image results in distortion of edges and while zoomed in results into a blurred image. As the edge detection is a basic step for many image processing applications such as object detection, object segmentation, object recognition, etc. It is necessary to know the impact of edge detection on downscaled image. In this paper, we are using Canny Edge detection method to detect the edges. The original images are downscaled using different interpolation methods. Canny Edge detection is applied on original images and downscaled images to compare the distortion in the edges. We used Structural Similarity Index Method for comparison. We are also comparing execution time taken by Canny Edge Detection on different interpolation methods to check for optimal interpolation method. We observed that the distortion in edges and time efficiency differ for different interpolation methods which are detailed below in the result section. As blurring is also a disadvantage of downscaling, we are applying Gaussian Blur on the images to compare the blurring due to Gaussian blur technique and blurring due to downscaling. 2020, Pleiades Publishing, Ltd.
Kim Y.W.; Innila Rose J.; Krishna A.V.N.
Pattern Recognition and Image Analysis, Vol-30, No. 3, pp. 372-381.
Kim Y.W., Centre for Digital Innovation, CHRIST (Deemed to be University), Mysore Road, Bangalore, Kumbalgodu, India; Innila Rose J., Centre for Digital Innovation, CHRIST (Deemed to be University), Mysore Road, Bangalore, Kumbalgodu, India; Krishna A.V.N., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Mysore Road, Bangalore, Kumbalgodu, India
Investigation of launch power and regenerator placement effect on the design of mixed-line-rate (MLR) optical WDM networks
Launch power; MILP; Mixed line rate; Optical WDM network design; Physical layer impairments; Regenerator
In recent years, owing to the consistent increase in volume and heterogeneity of the traffic, telecommunication networks have undergone significant innovations. Existing studies have shown that, by adopting a mixed-line-rate (MLR) strategy, wavelength division multiplexed (WDM) optical networks can cost-effectively respond to the diverse variety of traffic requirements which have heterogeneous service demands. However, due to the existence of physical layer impairments [specifically cross-phase modulation (XPM)], adjacent channels on different line rates may exhibit serious degradation of signal quality and optical reach. In such cases, launch power governs the bit-error rate as it affects both the signal and the noise power due to XPM. Therefore, an intelligent choice of launch power on different line rates can significantly reduce the network cost. Further, in MLR optical networks, trade-off between regenerator placement and the launch power attains importance and needs to be addressed. In this work, we investigate the launch power and regenerator placement effect on the design of a MLR WDM optical network. The obtained simulation results show that the network cost is (i) mainly controlled by power values of the 10/100/400 Gbps channels, and (ii) decreases for a cost model in which, compared to 10G transponders, high-bit-rate transponders have higher cost decay. Further, with a lower cost model, it is found that more numbers of regenerators can be deployed, simultaneously minimizing the network cost. 2017, Springer Science+Business Media New York.
Photonic Network Communications, Vol-40, No. 1, pp. 14-30.
https://doi.org/10.1007/s11107-017-0714-z https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020063715&doi=10.1007%2fs11107-017-0714-z&partnerID=40&md5=e233ea03e409ad503fea5d19d1ab1cd7
Iyer S., Department of Electronics and Communication Engineering, Christ University Faculty of Engineering, Mysore Road, Bangalore, 560060, India; Singh S.P., Division of ECE, Netaji Subhas Institute of Technology, Azad Hind Fauj Marg, Sector-3, Dwarka, New Delhi, 110078, India
Alkali-activated concrete paver blocks made with recycled asphalt pavement (RAP) aggregates
Alkali-activated; Concrete; Pavers; RAP; Strength
This study was conducted to evaluate the feasibility of using recycled asphalt pavement (RAP) aggregates in alkali-activated concrete paver blocks. Due to drastic growth in road expansion projects in India, there is tremendous amount of RAP generated by milling and digging of existing bituminous roads. Even though RAP gets recycled in new bituminous roads, there is still large volume of this material that gets downgraded, especially in urban areas. Therefore, there is a need to effectively utilize the unused RAP in paving industry. Alkali-activated paver blocks were synthesized with fly ash (FLA), ground granulated blast furnace slag (GGBS), NaOH sol., Na2SiO3 sol., RAP and natural aggregates. Natural aggregates were substituted with RAP aggregates at replacement rates of 0 %, 25 %, 50 %, and 75 % by weight. The developed paver blocks were tested for water absorption, compressive strength, and abrasion resistance according to IS 15658: 2006 standard. The results of the laboratory study showed that inclusion of RAP aggregates in alkali-activated concrete reduce the compressive strength and abrasion resistance of the paver blocks. Though there is reduction in strength, developed paver blocks classified for use in pedestrian and non-motorized facility. The study also found that the use of RAP aggregates in paver blocks incur economic benefits. A maximum reduction of 25.8 % in production cost was observed for RAP inclusive alkali-activated paver blocks. Furthermore, the proposed method provides environmental benefits by reducing consumption of Portland cement and natural aggregates from quarries, and thus makes paving industry more sustainable and environment friendly. 2019 The Authors
Hossiney N.; Sepuri H.K.; Mohan M.K.; H R A.; Govindaraju S.; Chyne J.
Case Studies in Construction Materials, Vol-12
https://doi.org/10.1016/j.cscm.2019.e00322 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076540071&doi=10.1016%2fj.cscm.2019.e00322&partnerID=40&md5=1c343306cd4240e48ba0dfb1dd8fd4a3
Hossiney N., Faculty of Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Sepuri H.K., Faculty of Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Mohan M.K., Faculty of Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; H R A., Department of Civil Engineering, R V College of Engineering, Visvesvaraya Technological University, India; Govindaraju S., Faculty of Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Chyne J., Faculty of Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India
A comprehensive novel model for network speech anomaly detection system using deep learning approach
Attack classification; Deep learning; Network intrusion detection system
Network Intrusion Detection System (NIDS) is the key technology for information security, and it plays significant role for classifying various attacks in the networks accurately. An NIDS gains an understanding of normal and anomalous behavior by examining the network traffic and can identify unknown and new attacks. Analyzing and Identifying unfamiliar attacks are one of the big challenges in Network IDS research. A huge response has been given to deep learning over the past several years and novelty in deep learning techniques are also improved regularly. Deep learning based Network Intrusion Detection approach is highly essential for improved performance. Nowadays, Machine learning algorithms made a revolution in the area of human computer interaction and achieved significant advancement in imitating human brain exactly. Convolutional Neural Network (CNN) is a powerful learning algorithm in deep learning model for improving the machine learning ability in order to achieve high attack classification accuracy and low false alarm rate. In this article, an overview of deep learning methodologies for commonly used NIDS such as Auto Encoder (AE), Deep Belief Network (DBN), Deep Neural Network (DNN), Restricted Boltzmann Machine (RBN). Moreover, the article introduces the most recent work on network anomaly detection using deep learning techniques for better understanding to choose appropriate method while implementing NIDS through widespread literature analysis. The experimental results designate that the accuracy, false alarm rate, and timeliness of the proposed CNN-NIDS model are superior than the traditional algorithms. 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Manimaran A.; Chandramohan D.; Shrinivas S.G.; Arulkumar N.
International Journal of Speech Technology, Vol-23, No. 2, pp. 305-313.
Manimaran A., Department of Computer Applications, Madanapalle Institute of Technology & Science, Madanapalle, India; Chandramohan D., Department of Computer Science & Engineering, Madanapalle Institute of Technology & Science, Madanapalle, India; Shrinivas S.G., Department of Computer Applications, Madanapalle Institute of Technology & Science, Madanapalle, India; Arulkumar N., Department of Computer Science, Christ (Deemed to be University), Bangalore, India
Phytochemical analysis and antioxidant activity of leaf extracts of some selected plants of the family acanthaceae
Antioxidant; DPPH; Ethnopharmacology; Phytochemistry; Quantitative analysis
The present era of scientific research has witnessed an enumerable amount of evidences to showcase the immense potential of medicinal plants. In the present investigation, the phytochemical analysis of Phlogacanthus pubinervius T. Anderson., Adhatoda vasica (L.) Nees,Phlogacanthus thyrsiflorus Nees, Phlogacanthus curviflorus (Wall.) Nees, and Ruellia tuberosa L. was carried out for the different plants extracted with methanol. Analysis was carried out to estimate the quantity of phenols, carbohydrates, tannins, flavonoids and proteins. The antioxidant property of these plants were analysed using DPPH method. The concentration of the plant samples required to decrease the DPPH concentration by 50% was calculated by interpolation from linear regression analysis and denoted IC50 value (g/ml). The qualitative analysis showed the presence of alkaloids, tannins, saponins, proteins, carbohydrate and phenols in all the sample extracts. The highest amount of tannins and phenols was observed in P. thyrsiflorus. P. pubinervius (77.83%), A. vasica (74.81%), P. curviflorus (94.20%), and R. tuberosa (70.78%) which showed highest antioxidant activity of DPPH-scavenging at 150 g/ml of methanol extract. The high percent of scavenging activities of those plants add value to their medicinal properties. The presence of the high amount of phytochemical compounds suggests that the plants have high amount of medicinal compounds and can be extensively used to extract the natural compounds. Kripasana & Xavier (2020). This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/).
Plant Science Today, Vol-7, No. 2, pp. 264-274.
https://doi.org/10.14719/PST.2020.7.2.717 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087460493&doi=10.14719%2fPST.2020.7.2.717&partnerID=40&md5=bb622789b022be6b8d3be88a2cc1ce77
Kripasana K., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560 029, India; Xavier J., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560 029, India
Attenuation parameters of polyvinyl alcohol-tungsten oxide composites at the photon energies 5.895, 6.490, 59.54 and 662 keV
mass attenuation coefficient; radiation shielding; tungsten filled polyvinyl alcohol composite
The growing demand for lightweight, non-toxic and effective X-A nd ?-ray shielding materials in various fields has led to the exploration of various polymer composites for shielding applications. In this study, tungsten filled polyvinyl alcohol (PVA) composites of varying WO3 concentrations (0-50 wt%) were prepared by solution cast technique. The structural, morphological, and thermal properties of the prepared composite films were studied using X-ray diffraction technique (XRD), Scanning electron microscopy (SEM) and Thermogravimetric analysis (TGA). The AC conductivity studies showed the low conductivity property of the composites. The X-ray (5.895 and 6.490 keV) and ?-ray (59.54 and 662 keV) attenuation studies performed using CdTe and NaI(Tl) detector spectrometers revealed a noticeable increase in shielding efficiency with increase in filler wt%. The effective atomic number (Zeff) calculated by the direct method agreed with the values obtained using Auto-Zeff software. The % heaviness showed that tungsten filled polyvinyl alcohol composites are lighter than traditional shielding materials. 2020 M V Muthamma et al., published by Sciendo 2020.
Muthamma M.V.; Gudennavar B.S.; Gudennavar S.B.
Polish Journal of Medical Physics and Engineering, Vol-26, No. 2, pp. 77-85.
https://doi.org/10.2478/pjmpe-2020-0009 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090297228&doi=10.2478%2fpjmpe-2020-0009&partnerID=40&md5=c12f9e39d6b38e0bd3b8d25a498d5766
Muthamma M.V., Department of Physics and Electronics, Christ, Deemed to Be University, Bangalore Central Campus, Karnataka, Bengaluru, 560029, India; Gudennavar B.S., Department of Physics and Electronics, Christ, Deemed to Be University, Bangalore Central Campus, Karnataka, Bengaluru, 560029, India; Gudennavar S.B., Department of Physics and Electronics, Christ, Deemed to Be University, Bangalore Central Campus, Karnataka, Bengaluru, 560029, India
Digital Marketing Strategies: Effectiveness on Generation Z
Content Marketing; Digital Marketing Strategies; Generation Z; Personalized Marketing; Push Notification; Social Media Marketing
The paper examines the constructs of digital marketing strategies on two aspects. Exploring the numerous digital marketing strategies related to Generation Z through a comprehensive desk review and archival research and confirming the explored factors to create a valid and measurable instrument.It is important to quantify and develop a scale to measure the effectiveness of digital marketing strategies on Generation Z. The first section of the study is exploratory factor analysis (EFA), establishing the effectiveness of digital marketing strategies on Generation Z. The second section deals with Confirmatory Factor Analysis (CFA), confirming the factors coined through exploratory factor analysis. The dimensions identified in the research can help marketers create exclusive digital marketing strategies to target Generation Z. 2020 SCMS Group of Educational Institutions. All rights reserved.
SCMS Journal of Indian Management, Vol-17, No. 2, pp. 54-69.
Anjum A., Department of Commerce, CHRIST (Deemed to be University), India; Thomas M.R., Department of Commerce, CHRIST (Deemed to be University), India; Prakash P.K., Department of Commerce, CHRIST (Deemed to be University), India
Relation between electricity consumption and economic growth in Karnataka, India: An aggregate and sector-wise analysis
Cross-subsidization; Economic growth; Electricity consumption; Granger causality; Holt-winter smoothening method; Karnataka, India; Per capita consumption
Karnataka is a highly progressive and rapidly growing state in India, with huge potential for industrial growth, however, it grapples with power deficits and other problems in electricity sector, which make it a good case study for Indian electricity sector. Given the importance of electricity in the urbanisation and growth process, the paper analyses the electricity consumption trend in Karnataka, examine its causality with economic growth at aggregate and sectoral levels using Granger causality test, and forecast the future electricity consumption applying Holt-Winters smoothening (no seasonality) technique. The general trend reflects higher consumption by the agricultural consumers, compared to the revenue-generating 'Industries' and 'Commercial' categories, mainly due to the policy of de-metering and providing 'free' power to agricultural consumers since late 1980s. The Granger causality tests reveal that there is no causality relation (neutrality hypothesis) between electricity consumption and economic growth in Karnataka, for total, agricultural and industrial consumption. This basically stems from the inaccurate measurements of agricultural consumption, higher dependence on captive generation, and poor quality grid supply. Finally, electricity consumption is predicted to be around 69,347 GW h by 2019?20. Future policies should focus on universal metering, reducing cross-subsidization, supplying good quality and reliable power to all sectors, and economical planning of resource-mix to achieve adequate, productive and efficient electricity consumption. 2020 Elsevier Inc.
https://doi.org/10.1016/j.tej.2020.106768 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083007279&doi=10.1016%2fj.tej.2020.106768&partnerID=40&md5=fcf13417a34685ff5d57027c4033638a
Rajkumari L., Christ (deemed to be University), Bangalore, 560029, India
A census of young stellar population associated with the Herbig Be star HD 200775
ISM: clouds; polarization; stars: distances; stars: pre-main-sequence; X-rays: stars
The region surrounding the well-known reflection nebula, NGC 7023, illuminated by a Herbig Be star, HD 200775, located in the dark cloud L1174 is studied in this work. Based on the distances and proper motion values from Gaia DR2 of 20 previously known young stellar object (YSO) candidates, we obtained a distance of 335 11 pc to the cloud complex L1172/1174. Using polarization measurements of the stars projected on the cloud complex, we show additional evidence for the cloud to be at ?335 pc distance. Using this distance and proper motion values of the YSO candidates, we searched for additional comoving sources in the vicinity of HD 200775 and found 20 new sources, which show low infrared excess emission and are of age ?1 Myr. Among these, 10 YSO candidates and 4 newly identified comoving sources are found to show X-ray emission. Three of the four new sources for which we have obtained optical spectra show H ? in emission. About 80 per cent of the total sources are found within ?1 pc distance from HD 200775. Spatial correlation of some of the YSO candidates with the Herschel dust column density peaks suggests that star formation is still active in the region and may have been triggered by HD 200775. 2020 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society.
Saha P.; Gopinathan M.; Kamath U.; Lee C.W.; Puravankara M.; Mathew B.; Sharma E.
Monthly Notices of the Royal Astronomical Society, Vol-494, No. 4, pp. 5851-5871.
https://doi.org/10.1093/mnras/staa1053 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096954636&doi=10.1093%2fmnras%2fstaa1053&partnerID=40&md5=2b7f174fef612b50fbefeb992b3eff5c
Saha P., Indian Institute of Astrophysics (IIA), Sarjapur Road, Koramangala, Bangalore, Karnataka, 560034, India, Pt. Ravishankar Shukla University, Amanaka G.E. Road, Raipur, Chhatisgarh, 492010, India; Gopinathan M., Indian Institute of Astrophysics (IIA), Sarjapur Road, Koramangala, Bangalore, Karnataka, 560034, India; Kamath U., Indian Institute of Astrophysics (IIA), Sarjapur Road, Koramangala, Bangalore, Karnataka, 560034, India; Lee C.W., Korea Astronomy and Space Science Institute (KASI), 776 Daedeok-daero, Yuseong-gu, Daejeon, South Chungcheong, 34055, South Korea, University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon, South Chungcheong, 34113, South Korea; Puravankara M., Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai, Maharashtra, 400005, India; Mathew B., Department of Physics and Electronics, CHRIST (deemed to be university), Bangalore, Karnataka, 560029, India; Sharma E., Indian Institute of Astrophysics (IIA), Sarjapur Road, Koramangala, Bangalore, Karnataka, 560034, India
Sectoral correlations and interlinkages: NSE
ADF Test; Granger causality; Intersectoral linkages; Portfolio Diversification
An efficient portfolio is a well-diversified portfolio that gives the investor opportunities to earn money and provide cover against risks. Understanding the intersectoral linkages and correlations among various sectors in a stock market will help an investor to diversify the portfolio and reduce risk efficiently. This study aims at examining the underlying linkages and correlations among eight sectors in the Indian National Stock Exchange (NSE) using a Granger causality test under VAR environment. The results of the study based on nine years' data from 2009 to 2018 show that an effective portfolio can have two classifications -stocks from Pharma and Media as group one (defensive stocks) and picks from IT, Bank, Financial Services, Realty, Auto and FMCG sector as group two (somewhat Cyclical). The study further proves that the usual definition for cyclical and defensive sectors have undergone some profound changes. 2020 SCMS Group of Educational Institutions. All rights reserved.
SCMS Journal of Indian Management, Vol-17, No. 3, pp. 94-102.
Florence M.A., Department of Economics, St. Michael's College, Cherthala, Alappuzha, India; Dibin K.K., Department of MBA, SCMS, School of Technology and Management, Kochi, India; Victor V., Department of Economics, CHRIST (Deemed to be University), Bangalore, Karnataka, India
The Consortium on Vulnerability to Externalizing Disorders and Addictions (c-VEDA): an accelerated longitudinal cohort of children and adolescents in India
The global burden of disease attributable to externalizing disorders such as alcohol misuse calls urgently for effective prevention and intervention. As our current knowledge is mainly derived from high-income countries such in Europe and North-America, it is difficult to address the wider socio-cultural, psychosocial context, and genetic factors in which risk and resilience are embedded in low- and medium-income countries. c-VEDA was established as the first and largest India-based multi-site cohort investigating the vulnerabilities for the development of externalizing disorders, addictions, and other mental health problems. Using a harmonised data collection plan coordinated with multiple cohorts in China, USA, and Europe, baseline data were collected from seven study sites between November 2016 and May 2019. Nine thousand and ten participants between the ages of 6 and 23 were assessed during this time, amongst which 1278 participants underwent more intensive assessments including MRI scans. Both waves of follow-ups have started according to the accelerated cohort structure with planned missingness design. Here, we present descriptive statistics on several key domains of assessments, and the full baseline dataset will be made accessible for researchers outside the consortium in September 2019. More details can be found on our website [cveda.org]. 2020, Springer Nature Limited.
Zhang Y.; Vaidya N.; Iyengar U.; Sharma E.; Holla B.; Ahuja C.K.; Barker G.J.; Basu D.; Bharath R.D.; Chakrabarti A.; Desrivies S.; Elliott P.; Fernandes G.; Gourisankar A.; Heron J.; Hickman M.; Jacob P.; Jain S.; Jayarajan D.; Kalyanram K.; Kartik K.; Krishna M.; Krishnaveni G.; Kumar K.; Kumaran K.; Kuriyan R.; Murthy P.; Orfanos D.P.; Purushottam M.; Rangaswamy M.; Kupard S.S.; Singh L.; Singh R.; Subodh B.N.; Thennarasu K.; Toledano M.; Varghese M.; Benegal V.; Schumann G.; Singh R.L.; Nanjayya S.B.; Kalyanram K.; Ghattu K.; Kurpad S.S.; Zhang Y.; Heron J.; Narayanan G.; Mehta U.M.; Girimaji S.C.; Khullar M.; Khandelwal N.; Joshi N.; Amit; Haque B.; Ghosh A.; Nagraj A.; Basu A.; Bhattacharya D.; Pandit M.M.; Das S.; Yadav A.; Das S.; Roy S.; Maurya P.K.; Chanu N.D.; Fujica M.C.; Ph V.; Phurailatpam C.; Rani G.; Sujatha B.; Fall C.; Kiran K.N.; Ramya M.C.; Urs C.; Santhosh N.; Somashekhara R.; Divyashree K.; Rao A.; Poornima R.; Tripathy S.; Parashar N.; Dhanalakshmi D.; Nayana K.B.; Seshadri A.K.; Kumar S.; Arumugam T.; Safai A.; Baligar S.K.; Cyril A.M.; Sharda A.; Rashmitha; Roy A.A.; Shivamma D.; Kiran L.; Bhavana B.R.
Molecular Psychiatry, Vol-25, No. 8, pp. 1618-1630.
ISSN: 13594184; PubMed ID: 32203154; CODEN: MOPSF
Zhang Y., Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom, Centre for Innovation in Mental Health, School of Psychology, University of Southampton, Southampton, United Kingdom; Vaidya N., Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom, Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, India, Centre for Population Neuroscience and Precision Medicine, MRC Social, Genetic, Developmental Psychiatry Centre, Institute of Psychology, Psychiatry & Neuroscience, Kings College London, London, United Kingdom; Iyengar U., Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom, Centre for Population Neuroscience and Precision Medicine, MRC Social, Genetic, Developmental Psychiatry Centre, Institute of Psychology, Psychiatry & Neuroscience, Kings College London, London, United Kingdom; Sharma E., Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Holla B., Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Ahuja C.K., Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh, India, Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education & Research, Chandigarh, India; Barker G.J., Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, London, Kings College, London, United Kingdom, Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, Kings College London, London, United Kingdom; Basu D., Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India, Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India; Bharath R.D., Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India; Chakrabarti A., ICMR-Regional Occupational Health Centre, Kolkata, India, ICMR-Regional Occupational Health Centre, Kolkata, India; Desrivies S., Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom, Centre for Population Neuroscience and Precision Medicine, MRC Social, Genetic, Developmental Psychiatry Centre, Institute of Psychology, Psychiatry & Neuroscience, Kings College London, London, United Kingdom; Elliott P., MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom, MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Fernandes G., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Gourisankar A., Rishi Valley Rural Health Centre, Rishi Valley, India, Rishi Valley, Rural Health Centre, Madanapalle, Andhra Pradesh, India; Heron J., Centre for Public Health, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Hickman M., Bristol Medical School, University of Bristol, Bristol, United Kingdom, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Jacob P., Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Jain S., Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Jayarajan D., Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Kalyanram K., Rishi Valley Rural Health Centre, Rishi Valley, India, Rishi Valley, Rural Health Centre, Madanapalle, Andhra Pradesh, India; Kartik K., Rishi Valley Rural Health Centre, Rishi Valley, India, Rishi Valley, Rural Health Centre, Madanapalle, Andhra Pradesh, India; Krishna M., Foundation for Research and Advocacy in Mental Health, Mysuru, India, Foundation for Research and Advocacy in Mental Health, Mysore, India; Krishnaveni G., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysuru, India; Kumar K., Department of Mental Health and Clinical Psychology, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Mental Health and Clinical Psychology, National Institute of Mental Health and Neurosciences, Bangalore, India; Kumaran K., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysuru, India, MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom; Kuriyan R., Division of Nutrition, St Johns Research Institute, Bengaluru, India, Division of Nutrition, St Johns Research Institute, Bangalore, India; Murthy P., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Orfanos D.P., NeuroSpin, CEA, UniversitParis-Saclay, Paris, France, NeuroSpin, CEA, UniversitParis-Saclay, Paris, France; Purushottam M., Molecular Genetics Laboratory, National Institute of Mental Health and Neurosciences, Bengaluru, India, Molecular Genetics Laboratory, National Institute of Mental Health and Neurosciences, Bangalore, India; Rangaswamy M., Department of Psychology, CHRIST (deemed to be university), Bengaluru, India, Department of Psychology, Christ University, Bangalore, India; Kupard S.S., Department of Psychiatry & Department of Medical Ethics, St. Johns Medical College & Hospital, Bengaluru, India; Singh L., Department of Psychiatry, Regional Institute of Medical Sciences, Imphal, Manipur, India; Singh R., Department of Psychiatry, Regional Institute of Medical Sciences, Imphal, Manipur, India, Regional Institute of Medical Sciences, Imphal, Manipur, India; Subodh B.N., Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India; Thennarasu K., Department of Biostatistics, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Biostatistics, National Institute of Mental Health and Neurosciences, Bangalore, India; Toledano M., MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom, MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Varghese M., Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Benegal V., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, India, Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Schumann G., Centre for Population Neuroscience and Precision Medicine (PONS), MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom, Population Neuroscience and Precision Medicine (PONS), LIN-Charite Research Group Department of Psychiatry and Psychotherapy, Charite, CCM, Humboldt University, Berlin, Germany, Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China, Centre for Population Neuroscience and Precision Medicine, MRC Social, Genetic, Developmental Psychiatry Centre, Institute of Psychology, Psychiatry & Neuroscience, Kings College London, London, United Kingdom; Singh R.L., Regional Institute of Medical Sciences, Imphal, Manipur, India; Nanjayya S.B., Department of Psychiatry, Postgraduate Institute of Medical Education & Research, Chandigarh, India; Kalyanram K., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Ghattu K., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Kurpad S.S., Department of Psychiatry & Department of Medical Ethics, St. Johns Medical College & Hospital, Bangalore, India; Zhang Y., Centre for Population Neuroscience and Precision Medicine, MRC Social, Genetic, Developmental Psychiatry Centre, Institute of Psychology, Psychiatry & Neuroscience, Kings College London, London, United Kingdom; Heron J., Centre for Public Health, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Narayanan G., Department of Clinical Psychology, National Institute of Mental Health and Neurosciences, Bangalore, India; Mehta U.M., Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Girimaji S.C., Department of Child & Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Khullar M., Department of Experimental Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh, India; Khandelwal N., Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Chandigarh, India; Joshi N., Department of Experimental Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh, India; Amit, Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Chandigarh, India; Haque B., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Ghosh A., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Nagraj A., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Basu A., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Bhattacharya D., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Pandit M.M., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Das S., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Yadav A., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Das S., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Roy S., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Maurya P.K., ICMR-Regional Occupational Health Centre, Eastern, Kolkata, India; Chanu N.D., Regional Institute of Medical Sciences, Imphal, Manipur, India; Fujica M.C., Regional Institute of Medical Sciences, Imphal, Manipur, India; Ph V., Regional Institute of Medical Sciences, Imphal, Manipur, India; Phurailatpam C., Regional Institute of Medical Sciences, Imphal, Manipur, India; Rani G., Rishi Valley, Rural Health Centre, Madanapalle, Andhra Pradesh, India; Sujatha B., Rishi Valley, Rural Health Centre, Madanapalle, Andhra Pradesh, India; Fall C., MRC Lifecourse Epidemiology Unit, University of Southamtpon, Southamtpon, United Kingdom; Kiran K.N., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Ramya M.C., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Urs C., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Santhosh N., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Somashekhara R., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Divyashree K., Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Rao A., Division of Nutrition, St Johns Research Institute, Bangalore, India; Poornima R., Division of Nutrition, St Johns Research Institute, Bangalore, India; Tripathy S., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Parashar N., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Dhanalakshmi D., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Nayana K.B., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Seshadri A.K., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Kumar S., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Arumugam T., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Safai A., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Baligar S.K., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Cyril A.M., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Sharda A., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Rashmitha, Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Roy A.A., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Shivamma D., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Kiran L., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India; Bhavana B.R., Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India
Synthesis of Quinoxalin-2(1 H)-ones and Hexahydroquinoxalin-2(1 H)-ones via Oxidative Amidation-Heterocycloannulation
2,2-dibromo-1-arylethanone; heterocycloannulation; oxidative amidation; quinoxalin-2(1 H)-one
A metal-catalyst-free synthesis of substituted quinoxalin-2-ones from 2,2-dibromo-1-arylethanone by employing an oxidative amidation-heterocycloannulation protocol is reported. The substrate scope of the reaction has been demonstrated and a possible mechanism for this reaction has also been proposed. 2020 GeorgThieme. All Rights Reserved.
Raghunadh A.; Tadiparthi K.; Meruva S.B.; Murthy V.N.; Rao L.V.; Kumar U.K.S.
Raghunadh A., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddy's Laboratories Ltd, Hyderabad, 560049, India; Tadiparthi K., Department of Chemistry, CHRIST (Deemed to Be University), Hosur Road, Bangalore, 560026, India; Meruva S.B., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddy's Laboratories Ltd, Hyderabad, 560049, India; Murthy V.N., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddy's Laboratories Ltd, Hyderabad, 560049, India; Rao L.V., Department of Chemistry, GIS, GITAM University, Visakhapatnam, 530045, India; Kumar U.K.S., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddy's Laboratories Ltd, Hyderabad, 560049, India