Early diagnosis of COVID-19 patients using deep learning-based deep forest model
CNN; COVID-19; deep forest; deep learning; ResNet101; testing
Coronavirus disease-19 (COVID-19) has rapidly spread all over the world. It is found that the low sensitivity of reverse transcription-polymerase chain reaction (RT-PCR) examinations during the early stage of COVID-19 disease. Thus, efficient models are desirable for early-stage testing of COVID-19 infected patients. Chest X-ray (CXR) images of COVID-19 infected patients have shown some bilateral changes. In this paper, deep transfer learning and a deep forest-based model are proposed to diagnose COVID-19 infection from CXR images. Initially, features of X-ray images are extracted using the well-known deep transfer learning model (i.e., ResNet101), which does not require tuning many parameters compared to the deep convolutional neural network (CNN). After that, the deep forest model is utilised to predict COVID-19 infected patients. The deep forest is based upon ensemble learning and requires a small number of hyper-parameters. Additionally, the proposed model is trained on a multi-class dataset that contains four different classes as COVID-19 (+), pneumonia, tuberculosis, and healthy patients. The comparisons are drawn among the proposed deep transfer learning and deep forest-based models, the competitive models. The obtained results show that the proposed model effectively diagnoses COVID-19 infection with an accuracy of 99.4%. 2022 Informa UK Limited, trading as Taylor & Francis Group.
Journal of Experimental and Theoretical Artificial Intelligence, Vol-35, No. 3, pp. 365-375.
Singh D., School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea; Kumar V., Department of Computer Science & Engineering, National Institute of Technology Hamirpur, Hamirpur, India; Kaur M., School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea; Kumari R., Department of Computer Science, Christ (Deemed to Be University), Bangalore, India
Flat Unglazed Transpired Solar Collector: Performance Probability Prediction Approach Using Monte Carlo Simulation Technique
Monte Carlo simulation; probability prediction; solar energy; unglazed transpired solar collector (UTC)
Engineering applications including food processing, wastewater treatment, home heating, commercial heating, and institutional heating successfully use unglazed transpired solar collectors (UTCs). Trapping of solar energy is the prime goal of developing an unglazed transpired solar collector. The UTC is usually developed in and around the walls of the building and absorbs the solar energy to heat the air. One of the key challenges faced by the UTC designer is the prediction of performance and its warranty under uncertain operating conditions of flow variables. Some of the flow features are the velocity distribution, plate temperature, exit temperature and perforation location. The objective of the present study was to establish correlations among these flow features and demonstrate a method of predicting the performance of the UTC. Hence, a correlation matrix was generated from the dataset prepared after solving the airflow over a perforated flat UTC. Further, both strong and weak correlations of flow features were captured through Pearsons correlation coefficient. A comparison between the outcomes from a linear regression model and that of computational simulation was showcased. The performance probability for the UTC was interlinked with correlation matrix data. The Monte Carlo simulation was used to predict the performance from random values of the flow parameters. The study showed that the difference between the free stream value of temperature and the value of temperature inside the UTCs chamber varied between 15 and 20 C. The probability of achieving system efficiency greater than 35% was 55.2%. This has raised the hope of recommending the UTC for drying and heating where the required temperature differential is within 20 C. 2022 by the authors.
Parimita Panigrahi S.; Kumar Maharana S.; Rajashekaraiah T.; Gopalashetty R.; Sharifpur M.; Ahmadi M.H.; Saleel C.A.; Abbas M.
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.3390/en15238843 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143800353&doi=10.3390%2fen15238843&partnerID=40&md5=67f70b318a0104182317ee56f4d99c4d
Parimita Panigrahi S., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Kumar Maharana S., Department of Aeronautical Engineering, Acharya Institute of Technology, Karnataka, Bangalore, 560107, India; Rajashekaraiah T., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Gopalashetty R., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Sharifpur M., Department of Mechanical and Aeronautical Engineering, University of Pretoria, Hatfield, 0028, South Africa, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404327, Taiwan; Ahmadi M.H., Faculty of Mechanical Engineering, Shahrood University of Technology, Shahrood, 3619995161, Iran; Saleel C.A., Department of Mechanical Engineering, College of Engineering, King Khalid University, P.O. Box 394, Abha, 61421, Saudi Arabia; Abbas M., Electrical Engineering Department, College of Engineering, King Khalid University, P.O. Box 394, Abha, 61421, Saudi Arabia, Electronics and Communications Department, College of Engineering, Delta University for Science and Technology, Gamasa, 35712, Egypt
Presence or absence of Dunning-Kruger effect: Differences in narcissism, general self-efficacy and decision-making styles in young adults
Decision-making styles; Dunning-Kruger effect; General self-efficacy; Narcissism; Overestimation; Performance
The Dunning-Kruger effect is a cognitive bias in which individuals who are unskilled in certain domains overestimate their ability and are unaware of it. Past studies have focused on establishing the effect but have not looked into associated factors. This study aimed to see if the Dunning-Kruger effect has any influence on an individuals narcissism, general self-efficacy and decision making styles especially in young adults in the Indian population. The Dunning- Kruger effect was established using scores from the Cognitive Reflection Task and the Rationality scale from Rational Experiential Inventory, keeping the Unskilled and Unaware phrase under consideration, while establishing cut-offs. The participants were also divided into three groups - the group that was able to estimate their performance, the group that over-estimated their performance and the group that underestimated their performance. The dependent variables were measured using the NPI-16, General Self-Efficacy Scale and Flinders Decision-Making Styles Questionnaire. The Kruskal-Wallis H results showed that there is a significant difference between the group with Dunning-Kruger effect, without Dunning-Kruger effect and the group that underestimated their performance with reference to Narcissism, General Self-Efficacy, Vigilance and Hypervigilance decision-making styles. The Mann-Whitney U results further indicated a significant difference in Narcissism and Vigilance, between the groups that overestimated their performance and the group that accurately estimated their performance. However, there was no correlation between the CRT discrepancy scores of the individuals with Dunning-Kruger effect and the dependent variables. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
Current Psychology, Vol-42, No. 2, pp. 1444-1455.
Christopher K.I., Department of Psychology, Christ (Deemed to be University), Bengaluru, India; P P., Department of Psychology, Christ (Deemed to be University), Bengaluru, India; Herbert H.S., Department of Psychology, Christ (Deemed to be University), Bengaluru, India
A Simple and Efficient Ligand-Free Copper-Catalyzed C-N Bond Formation of Aryl (Hetero) Halides and N-Heteroaryl Amines
CuI; ligand free; N-heteroaryl amines; pyrimidines and pyrazines; Ullman coupling
In this protocol, we report a simple, inexpensive, and user-friendly conventional method for C-N cross coupling between aryl/heteroaryl halides and hetero aryl amines using copper iodide as a catalyst in DMSO as a solvent to prepare pyrimidines and pyrazines derivatives. The reaction conditions were optimized by screening in various copper catalysts and bases. The substrate scope of the reaction was also carried out to prepare novel functionalized N-arylated compounds in good yields. 2021 Taylor & Francis Group, LLC.
Kommuri V.C.; Tadiparthi K.; Pawar L.; Arunachalampillai A.
Polycyclic Aromatic Compounds, Vol-43, No. 1, pp. 665-673.
Kommuri V.C., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Tadiparthi K., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Pawar L., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Arunachalampillai A., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India
Stability Testing and Restoration of a DEIG-Based Wind Power Plant with Indirect Grid Control Strategies
DEIG; Indirect grid control; Resilience; Stability; Wind turbine
In the current scenario, because of government policies, environmental factors, and technological improvements, there is a rapid growth in renewable energy sector. The emphasis is to obtain better system performance by effective resource utilization and providing security and reliability. This paper discusses the design and implementation of indirect grid control of a wind power plant by controlling the parameters in both grid and rotor side converters. The proposed system consists of Doubly Excited Induction Generator (DEIG) with Wind turbine system (WTS) and Mechanical and Electrical Power Controlling Systems (MPCS-EPCS). Various transmission line faults (symmetrical and asymmetrical faults) incur power imbalances in power grid. The developed MPCS and EPCS are helpful to perform grid monitoring and controlling under different types of faulty conditions. The MPCS monitors the effective source utilization and EPCS helpful for matching the grid energy levels under normal and faulty conditions. Modification in the converter topologies to minimize the impact of adverse effects of faults on the DEIG-WTS and to improve resiliency in the power grid is also discussed. To improve the stability and enhancing resource utilization to improve the efficiency of the overall system with the enhancement of fault voltage ride-through capability in DEIG-WTS under fault conditions are also considered. The stability of the system is tested under steady-state and dynamic-state conditions by applying faulty conditions in MATLAB/Simulink environment. 2023 IETE.
Venkatesh A.; Nalinakshan S.; Jayasankar V.N.; Aneesh V.; Kiran S.S.; Sivasubramanian V.
IETE Journal of Research, Vol-69, No. 6, pp. 3928-3942.
Venkatesh A., Department of Electrical and Electronics Engineering, The National Institute of Engineering, Karnataka, Mysuru, India; Nalinakshan S., Department of Electrical and Electronics Engineering, The National Institute of Engineering, Karnataka, Mysuru, India; Jayasankar V.N., Department of Electrical and Electronics Engineering, The National Institute of Engineering, Karnataka, Mysuru, India; Aneesh V., Department of Electronics and Communication Engineering, Christ (Deemed to be University), Karnataka, Bengaluru, India; Kiran S.S., Department of Electronics and Communication Engineering, Lendi Institute of Engineering and Technology, Andhra Pradesh, Vizianagaram, India; Sivasubramanian V., Department of Chemical Engineering, National Institute of Technology Calicut, Kerala, Kozhikode, India
Study of multilayer flow of a bi-viscous Bingham fluid sandwiched between hybrid nanofluid in a vertical slab with nonlinear Boussinesq approximation
Bi-viscosity Bingham plastic fluids are used to understand the rheological characteristics of pigment-oil suspensions, polymeric gels, emulsions, heavy oil, etc. In many industrial and engineering problems involving high-temperature situation, a linear density-temperature variation is inadequate to describe the convective heat transport. Therefore, the characteristics of the nonlinear convective flow of a bi-viscous Bingham fluid (BVBF) through three layers in a vertical slab are studied. The two outer layers of the oil-based hybrid nanofluid and the intermediate layer of BVBF are considered. The thermal buoyancy force is governed by the nonlinear Boussinesq approximation. Continuity of heat flux, velocity, shear stress, and temperature are imposed on the interfaces. The governing equations are derived from the Navier-Stokes equation, conservation of energy, and conservation of mass for three layers. The nonlinear multi-point (four-point) boundary value problem is solved using the differential transform method (DTM). Converging DTM solutions are obtained, and they are validated. The entropy equation and Bejan number were also derived and analyzed. It is established that the nonlinear density-temperature variation leads to a significant improvement in the magnitude of the velocity and temperature profiles due to the increased buoyancy force, and as a result, the drag force on the walls gets reduced. The drag force on the slab gets reduced by decreasing the volume fraction of nanoparticles. Furthermore, nonlinear convection and mixed convection give rise to an advanced rate of heat transport on the walls and thereby to an enhanced heat transport situation. 2022 Author(s).
Basavarajappa M.; Myson S.; Vajravelu K.
https://doi.org/10.1063/5.0123131 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144389172&doi=10.1063%2f5.0123131&partnerID=40&md5=21c3921081bc9b69521decc293607a21
Basavarajappa M., School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, Edinburg, 78531, TX, United States; Myson S., Center for Mathematical Needs, Department of Mathematics, Christ (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Vajravelu K., Department of Mathematics, University of Central Florida, Orlando, 32816, FL, United States
Effect of face sheet on the flexural and tensile characteristics in GLARE laminates
flexural; GLARE laminates; mechanical properties; mechanical testing; SEM; tensile
The present study is carried out to study Glass Fibre Reinforced Aluminium Laminate (GLARE) structures and to evaluate their flexural and tensile properties. The GLARE specimens were fabricated using hand layup with vacuum bag moulding process wherein the aluminium sheets and E-Glass fibre woven mats of fixed thickness are bonded together by application of epoxy resins. Three different thicknesses of aluminium alloy (0.2 mm, 0.3 mm and 0.4 mm) Al-2024 T3 are used for the purpose of the study. The aluminium sheets are stacked together by application of epoxy resin between the sheets and are cured under a compression moulding machine under constant pressure. The overall thickness of the specimen is maintained constant for 2 mm. The samples were subjected to a three-point bending and tensile test as per ASTM D790 and ASTM D3039 standards, respectively, to evaluate their mechanical properties. The results indicate that the tensile strength of the composites is maximum for the specimen with aluminium 2024 T3 face sheet with a minimum thickness of 0.2 mm; however, with the increase in the thickness, the tensile strength is found to be decreasing. 2021 Engineers Australia.
Australian Journal of Mechanical Engineering, Vol-21, No. 3, pp. 872-884.
Harish Kumar M., Department of Mechanical and Automobile Engineering, CHRIST (Deemed to be University), Bangalore, India; Rajesh Mathivanan N., Department of Mechanical Engineering, PES University, Bangalore, India
Facial emotion recognition using convolutional neural networks
CNN; Emotion recognition; Facial expression
Emotional expressivity has always been a simple job for people, but computer programming is much harder to accomplish. Image emotions may be recognised by recent developments in computer vision and machine learning. In this article, we present a new method to detect face emotion. Use neural networks convolutionary (FERC). The FERC is based on a CNN network of two parts: the first portion removed the backdrop of the image, the second part removed the face vector. The expressional vector (EV) is utilised in the FERC model to detect the fve different kinds of regular facial expressions. The double-level CNN is continuous and the weights and exponent values of the final perception layer vary with each iteration. In that it improves accuracy, FERC varies from widely utilised CNN single-level technology. Moreover, EV generation prevents the development of a number of issues before a new background removal process is used (for example distance from the camera). 2021
Sarvakar K.; Senkamalavalli R.; Raghavendra S.; Santosh Kumar J.; Manjunath R.; Jaiswal S.
Materials Today: Proceedings, Vol-80, pp. 3560-3564.
https://doi.org/10.1016/j.matpr.2021.07.297 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130147305&doi=10.1016%2fj.matpr.2021.07.297&partnerID=40&md5=e4a42bc434d14197ebc4c9a55f4c1044
Sarvakar K., Information Technology Department, U.V. Patel College of Engineering, Ganpat University, Gujarat, Mehsana, 384012, India; Senkamalavalli R., CSE Department, East Point College of Engineering, Bangalore, India; Raghavendra S., Department of Computer Science and Engineering, School of Engineering and Technology, Christ Deemed to be University, Bengaluru, 560074, India; Santosh Kumar J., Department of Computer Science and Engineering, K S School of Engineering and Management, Bengaluru, 56019, India; Manjunath R., Department of Computer Science and Engineering, R R Institute of Technology, Bengaluru, 560090, India; Jaiswal S., Department of Computer Science & Information Technology (CSIT), Guru Ghasidas Vishwavidyalaya, (A Central University)Koni, (C.G.), Bilaspur, 495009, India
Religions, Women and Discourse of Modernity in Colonial South India
Christianity; colonialism; gender; Hinduism; missionary modernity; Nadars; Nairs; tradition
Colonial education and missionary discourse of modernity intensified struggles for continuity and change among the followers of Hinduism and Christianity in nineteenth century India. While missionary modernity was characterised by an emphasis on sociocultural changes among the marginalized women through Christian norms of decency, orthodox Hindus used traditional cultural practices to confront missionary modernization endeavours. This article posits that the discourse of missionary modernity needs to be understood through the principles of Western secular modernity that impelled missionaries to employ decent clothing as a symbol of Christian femininity. It argues that missionary modernity not only emboldened the marginalized women to challenge their ascribed sociocultural standing but also solidified communitarian consciousness among the followers of Hinduism and Christianity substantially. Even though Travancore state defended the entrenched customary practices, including womens attire patterns, with all its potency through authoritative proclamations, it could not dissuade missionaries from converting the marginalized women to missionary modernity. 2022 by the author.
https://doi.org/10.3390/rel13121225 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144404453&doi=10.3390%2frel13121225&partnerID=40&md5=13fc8bad2c940fd5f62be49324cdd7ef
Doss M.C., School of Social Sciences, Christ University, Bengaluru, 560029, India
Predicting Intention to Buy Organic Food during the COVID-19 Pandemic: A multi-group analysis based on the Health Belief Model
consumer behavior; COVID-19; food choice; health belief model; moderation; Organic food
The ongoing COVID-19 pandemic has deeply affected physical and psychological health of people. It also had a huge impact on their dietary choices. This study specifically attempts to determine the impact of the constructs of health belief model on consumer purchase intention of organic food in the pandemic scenario. A survey was conducted among 413 Indian organic food consumers. The proposed hypotheses are tested by employing structural equation modeling. The findings highlight those perceived benefits is an important predictor of consumers behavioral intention to buy organic food, followed by cues to action and perceived threats. It is also found that consumers age moderates the impact of perceived threat and perceived barrier on consumers purchase intention, with a 22% difference in model prediction. In conclusion, the health belief model is found to be one of the most suitable models to predict consumer intention toward organic food purchase during the COVID-19 pandemic. 2022 Taylor & Francis Group, LLC.
Alagarsamy S.; Mehrolia S.; Vasudevan M.; Jeevananda S.
Journal of International Food and Agribusiness Marketing, Vol-35, No. 4, pp. 508-534.
Alagarsamy S., School of Business, Manipal Academy of Higher Education, Dubai Campus, Dubai, United Arab Emirates; Mehrolia S., School of Business and Management, Christ University, Bangalore, India; Vasudevan M., School of Business and Management, Christ University, Bangalore, India; Jeevananda S., School of Business and Management, Christ University, Bangalore, India
Iodine Mediated Oxidative Cross-Coupling of Benzo[d]Imidazo[2,1-b]Thiazoles with Ethylbenzene: An Unprecedented Approach of C3-Dicarbonylation
Benzo[d]imidazo[2,1-b]thiazoles; dicarbonylation; iodine
A versatile approach of iodine mediated C3-dicarbonylation of benzo[d]imidazo[2,1-b]thiazoles (IBTs) with ethylbenzene has been reported. The reaction conditions were optimized by screening in various solvents, catalysts, and oxidants. The reaction is compatible with various substrates and was successfully demonstrated to offer moderate to good yields. 2022 Taylor & Francis Group, LLC.
Jinkala R.; Tadiparthi K.; Raghunadh A.; Shiva Kumar K.B.; Venkateshwarlu R.; Siddaiah V.; Ramamohan H.
Polycyclic Aromatic Compounds, Vol-43, No. 5, pp. 4045-4054.
Jinkala R., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddys Laboratories Ltd, Hyderabad, India, Department of Organic Chemistry and FDW, Andhra University, Visakhapatnam, India; Tadiparthi K., Department of Chemistry, CHRIST (Deemed to Be University), Bangalore, India; Raghunadh A., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddys Laboratories Ltd, Hyderabad, India; Shiva Kumar K.B., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddys Laboratories Ltd, Hyderabad, India; Venkateshwarlu R., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddys Laboratories Ltd, Hyderabad, India; Siddaiah V., Department of Organic Chemistry and FDW, Andhra University, Visakhapatnam, India; Ramamohan H., Technology Development Centre, Custom Pharmaceutical Services, Dr. Reddys Laboratories Ltd, Hyderabad, India
Effect of alkyl chain length on the corrosion inhibition of mild steel in a simulated hydrochloric acid medium by a phosphonium based inhibitor
adsorption isotherm; corrosion inhibitor; ionic liquids; Mild steel; SEM
The corrosion inhibiting effect of three synthesised phosphonium containing ionic liquids of varying alkyl chain length, namely, butyltriphenyl phosphonium bromide (BTPPB), hexyltriphenyl phosphonium bromide (HTPPB) and hexadecyltriphenyl phosphonium bromide (HDTPPB) on mild steel, was evaluated in 1 M HCl medium. The corrosion inhibition performance was studied by gravimetric method, potentiodynamic polarization studies, electrochemical impedance spectroscopy and quantum chemical studies (DFT). However, the results of the SEM, AFM and contact angle tests confirmed that the protective layer formed on the mild steel. Furthermore, assessed the theoretical calculations for exploring the inhibition mechanism. A maximum of 95.77% inhibition efficiency was achieved using 250 ppm of HDTPPB. The obtained results showed that HDTPPB has greater inhibition ability than BTPPB and HTPPB. Adsorption studies obeyed the Langmuir adsorption isotherm. Moreover, the increased alkyl chain length of ionic liquids did increase their inhibition efficiency. 2021 Informa UK Limited, trading as Taylor & Francis Group.
Subasree N.; Arockia Selvi J.; Pillai R.S.
Journal of Adhesion Science and Technology, Vol-37, No. 1, pp. 83-104.
Subasree N., Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, India; Arockia Selvi J., Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, India; Pillai R.S., Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, India, Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, India
An empirical study on the clients perspective in decision making with regard to lawyer selection for trial courts: Does grey hair matter?
Age; Clients lawyer selection; Junior lawyers; Seniority; Trial court
In higher courts, statutory interpretation and persuasion of the court with new perspectives on legal principles are critical. Whereas, the main focus of the subordinate courts is on evidential underpinnings. Hence, the lawyers in all courts are an indispensable part of the judicial process and play a seminal role in the dispensation of justice. The existing literature demonstrates that engaging a senior lawyer increases the chances of winning cases. However, young lawyers today make their mark by establishing their own offices, succeeding in the profession, while some remain the dark horses of their incumbent seniors. Against this backdrop, the authors explore the clients perception of the lawyer selection process and the significance of lawyers age using a mixed methods approach. The data for this study was gathered from trial court clients using a convenient sampling method. The qualitative data were collected by conducting semi-structured interviews with clients. Interviews were analysed at a thematic level and broad themes were identified and used as constructs for a quantitative survey questionnaire. The quantitative data were analysed through Pearson correlation, regression analysis, and factor analysis. The study determined that lawyers efficiency is a key factor considered by trial court clients in selecting their lawyers. The results also revealed that there exists a significant positive correlation between the age of the lawyer and the clients decision making when choosing their lawyers. In the end, the implications of the findings are discussed. 2022, The Author(s), under exclusive licence to O.P. Jindal Global University (JGU).
Jindal Global Law Review, Vol-13, No. 2, pp. 277-305.
Springer Science and Business Media B.V.
Sharmila H.S., CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Jain S.A., CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Covert Conditioning for Persistent Aggressive Behaviors: A Case Illustration
anger management; emotion dysregulation; Psychotherapy; resistant symptoms; self-management
In psychotherapy practice and training, single case study design plays an indispensable role by effectively articulating the application of textbook knowledge, thereby bridging the gap between theory and practice. This article, on similar lines, illustrates one such successful example of the application of the classical behavioral technique of covert conditioning modified with a component of verbal challenging. A woman in her late-thirties reported with long-standing seemingly-resistant-to-treat symptoms of aggressive behavior of beating children. The client had a total of 10 daily sessions of 6090 minutes each. By the end of one week, she reported not beating children in this period. She felt extremely relieved because it had happened for the first time in 10 years. The intensity of anger had decreased drastically, and she was not shouting any longer. She had to discontinue sessions abruptly due to unavoidable circumstances. Although she was suggested to follow up the intensive sessions again, she was not able to do it due to feasibility issues. The improvement was maintained on follow-up visits after two weeks, four weeks, and three months. 2021 The Author(s).
Indian Journal of Psychological Medicine, Vol-45, No. 1, pp. 85-88.
Kavan, School of Humanities and Social Sciences (Psychology), Christ University Delhi-NCR, Uttar Pradesh, Ghaziabad, India; Grover N., Dept. of Clinical Psychology, Institute of Human Behaviour and Allied Sciences, IHBAS, Delhi, New Delhi, India; Jain N., Private Practice, Delhi, India; Dhiman V., Dept. of Psychiatry, All India Institute of Medical Sciences, AIIMS, Uttarakhand, Rishikesh, India
Synthesis, DFT and In Silico Anti-COVID Evaluation of Novel Tetrazole Analogues
ADMET; anti-COVID; click chemistry; DFT; one-pot synthesis; Tetrazole
A new series of 3-aryl/heteroaryl-2-(1H-tetrazol-5-yl) acrylamides have been synthesized through catalyst-free, one-pot cascade reactions, utilizing click chemistry approach and evaluated for their anti-COVID activities against two proteins in silico. The structural properties of the synthesized molecules were evaluated based on DFT calculations. Total energy of the synthesized tetrazole compounds were obtained through computational analysis which indicate the high stability of the synthesized compounds. The Frontier Molecular Orbitals (FMO) and associated energies and molecular electrostatic potential (MEP) surfaces were generated for the compounds. Spectral analysis by DFT gave additional evidence to the structural properties of the synthesized molecules. All tetrazole analogues come under good ADMET data as they followed the standard value for ADMET parameters. Docking studies offered evidence of the molecules displaying excellent biological properties as an anti-Covid drug. Compound 4 g exhibited excellent anti-COVID-19 properties with four hydrogen binding interactions with amino acids GLN 2.486 GLN 2.436 THR 2.186 and HSD 2.468 with good full-fitness score (1189.12) and DeltaG (7.19). Similarly, compound 4d shown potent activity against anti-COVID-19 mutant protein (PDB: 3K7H) with three hydrogen binding interactions, i.e., SER 2.274 GLU 1.758 and GLU 1.853 with full-fitness score of 786.60) and DeltaG (6.85). The result of these studies revealed that the compounds have the potential to become lead molecules in the drug discovery process. 2022 Taylor & Francis Group, LLC.
Devasia J.; Chinnam S.; Khatana K.; Shakya S.; Joy F.; Rudrapal M.; Nizam A.
Polycyclic Aromatic Compounds, Vol-43, No. 3, pp. 1941-1956.
Devasia J., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Chinnam S., Department of Chemistry, M. S. Ramaiah Institute of Technology (Visvesvaraya Technological University, Belgaum), Karnataka, Bengaluru, India; Khatana K., Department of Applied Sciences (Chemistry), IIMT College of Polytechnic, Uttar Pradesh, Greater Noida, India; Shakya S., Department of Chemistry, Aligarh Muslim University, Uttar Pradesh, Aligarh, India; Joy F., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Rudrapal M., Department of Pharmaceutical Chemistry, Rasiklal M. Dhariwal Institute of Pharmaceutical Education and Research, Maharashtra, Pune, India; Nizam A., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Enhancing the energy efficiency for prolonging the network life time in multi-conditional multi-sensor based wireless sensor network
clustering; energy efficiency; signal strength verification; Wireless sensor networks
A wireless sensor network is one of the networks that is highly demanding by various real-time networking applications nowadays. A huge amount of sensor nodes is deployed in the network randomly and distributed. Most of the applications using wireless sensor network (WSN) are surveillance monitoring applications like a forest, home, healthcare, environment, and remote monitoring systems. Based on the application usage, the type of sensor, a number of sensor nodes are deployed in such a manner where the sensors can be used effectively. But the sensor nodes are restricted in the battery and sensing region. Thus, the battery of the sensor nodes is decreased based on the nodes function. The energy level of the sensor nodes highly affects the network lifetime. Improving the energy efficiency in WSN is one of the most important challenging tasks. Most of the earlier research works have proposed various methods, techniques, and routing protocols, but they are application dependent and as a common method. So, this paper is motivated to propose a Multi-Conditional Network Analysis (MCNA) framework for saving the energy level of the sensor nodes by reducing energy consumption. The MCNA framework involves two different clustering processes with cluster head selection, choosing the best nodes based on the signal strength, and the best route for data transmission. The data transmission is done by cluster based on source-destination based. The simulation results proved that the proposed MCNA framework outperforms the other existing methods. 2022 Northeastern University, China.
Kocherla R.; Chandra Sekhar M.; Vatambeti R.
Journal of Control and Decision, Vol-10, No. 1, pp. 72-81.
Kocherla R., Research scholar, Department of CSE, Presidency University, Bangalore, India; Chandra Sekhar M., Department of CSE, Presidency University, Bangalore, India; Vatambeti R., Department of CSE, CHRIST (Deemed to be University), Bangalore, India
Heat transfer enhancement using temperature-dependent effective properties of alumina-water nanoliquid with thermo-solutal Marangoni convection: A sensitivity analysis
Marangoni boundary layer flow; Modified Buongiorno model; Nanofluid; Response surface methodology (RSM); Sensitivity analysis
The sensitivity of the heat transport rate in the thermo-solutal Marangoni convection of Al 2O 3- H 2O nanoliquid at 300K is analyzed. The nanoliquid is modeled using the modified Buongiorno model which incorporates the Brownian motion, effective nanoliquid properties, and thermophoresis effects. The thermophysical models proposed by Khanafer and Vafai are chosen in this analysis as these correlations are in good agreement with the experimental values. External constraining factors like thermal radiation and variable magnetic field are also considered. The basic equations are solved using apposite transformation variables and Finite Difference Method (FDM). The impacts of the effectual parameters on all the profiles are analyzed. Furthermore, the heat transport is analyzed by executing a Response Surface Methodology (RSM) model with the Brownian motion parameter (0.1 ? Nb ? 0.5), thermophoretic parameter (0.1 ? Nt ? 0.5), and nanoparticle volume fraction (1 % ? ?? 3 %). The modified Buongiorno model yields lower temperature and concentration profiles when compared to the conventional Buongiorno model. The heat transfer rate is the most sensitive to the Brownian motion parameter than thermophoresis and nanoparticle (NP) volume fraction parameters. The results of this study would be instrumental in improving the efficiency of the welding process, crystal growth, and coating technologies. 2021, King Abdulaziz City for Science and Technology.
Applied Nanoscience (Switzerland), Vol-13, No. 1, pp. 255-266.
Springer Science and Business Media Deutschland GmbH
Mackolil J., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Mahanthesh B., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India
P-ROCK: A Sustainable Clustering Algorithm for Large Categorical Datasets
Clustering approaches; K-histogram; K-means algorithm; ROCK; Unsupervised learning
Data clustering is crucial when it comes to data processing and analytics. The new clustering method overcomes the challenge of evaluating and extracting data from big data. Numerical or categorical data can be grouped. Existing clustering methods favor numerical data clustering and ignore categorical data clustering. Until recently, the only way to cluster categorical data was to convert it to a numeric representation and then cluster it using current numeric clustering methods. However, these algorithms could not use the concept of categorical data for clustering. Following that, suggestions for expanding traditional categorical data processing methods were made. In addition to expansions, several new clustering methods and extensions have been proposed in recent years. ROCK is an adaptable and straightforward algorithm for calculating the similarity between data sets to cluster them. This paper aims to modify the algorithm by creating a parameterized version that takes specific algorithm parameters as input and outputs satisfactory cluster structures. The parameterized ROCK algorithm is the name given to the modified algorithm (P-ROCK). The proposed modification makes the original algorithm more flexible by using user-defined parameters. A detailed hypothesis was developed later validated with experimental results on real-world datasets using our proposed P-ROCK algorithm. A comparison with the original ROCK algorithm is also provided. Experiment results show that the proposed algorithm is on par with the original ROCK algorithm with an accuracy of 97.9%. The proposed P-ROCK algorithm has improved the runtime and is more flexible and scalable. 2023, Tech Science Press. All rights reserved.
Altameem A.; Poonia R.C.; Kumar A.; Raja L.; Saudagar A.K.J.
Intelligent Automation and Soft Computing, Vol-35, No. 1, pp. 553-566.
All Open Access; Hybrid Gold Open Access
Altameem A., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, 11533, Saudi Arabia; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Kumar A., Department of Computer Engineering and Applications, GLA University, Mathura UP, India; Raja L., Department of Computer Application, Manipal University Jaipur, Rajasthan, 303007, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
Kitchen Waste Derived Porous Nanocarbon Spheres for Metal Free Degradation of Azo Dyes: An Environmental Friendly, Cost Effective Method
Azo degradation; Metal free; Oxidant free; Porous nanocarbon spheres
A porous nanocarbon spheres (PNCSs) were prepared from kitchen waste and successfully used for the metal and oxidant free degradation of azo compounds. The PNCSs obtained by the pyrolysis of onion peel, at 1000C, were found to be effective catalysts for the reductive degradation of azo dyes in presence of hydrazine hydrate. The reductive cleavage of azo bonds (N=N) was achieved under microwave irradiation. The degradation process was completed in a span of 1040min; the process was monitored by ultravioletvisible spectroscopy. Fourier transform infrared spectroscopy was also used for the illustration of azo degradation. Interestingly, the reductive degradation of azo dyes produced corresponding amines and they were successfully reused for the preparation of fresh azo compounds. The work, therefore, highlights the valorization of largely produced kitchen-wastes to the sustainable PNCSs and it also provides a platform to demonstrate their applicability as highly cost-effective catalysts for bulk scale chemical transformations. Graphical Abstract: [Figure not available: see fulltext.]. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Supriya S.; Ananthnag G.S.; Maiyalagan T.; Hegde G.
Journal of Cluster Science, Vol-34, No. 1, pp. 243-254.
Supriya S., Centre for Nano-Materials & Displays, B.M.S. College of Engineering, Bull Temple Road, Karnataka, Bengaluru, 560 019, India, Department of Chemistry, B.M.S. College of Engineering, Bull Temple Road, Karnataka, Bengaluru, 560 019, India; Ananthnag G.S., Department of Chemistry, B.M.S. College of Engineering, Bull Temple Road, Karnataka, Bengaluru, 560 019, India; Maiyalagan T., Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, 603 203, India; Hegde G., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bengaluru, 560029, India, Department of Chemistry, CHRIST (Deemed to be University), Hosur Rd, Bengaluru, 560029, India
Drivers of Mandatory and Non-Mandatory Internet Corporate Reporting in Public and Private Sector Indian Companies
disclosure; Internet corporate reporting; regulation; SEBI
The papers objective was to measure the drivers of mandatory and non-mandatory internet corporate reporting by public and private sector companies following the internet disclosure compliance of listing and obligation requirement of SEBI under Clause 46. Several drivers, namely firm size, profitability, leverage, liquidity, board size, independence of board, and CEO duality, were used to measure the effectiveness of mandatory and non-mandatory disclosure. A multiple regression model was applied to test the present papers hypotheses. The results of multiple regression revealed that the firms size was exceptionally important for both sectors. In contrast, public sector disclosure was largely impacted by leverage, liquidity, board size, and board independence. In comparison, the private sector disclosure scores were mainly impacted by leverage and board size, although there is no relationship between ICR and firm profitability and CEO duality. In performing separate multivariate regression between the two sectors, many disparities emerged. This disparity showed that public and private sector corporations had quite different firm and governance characteristics of the disclosure. As the first exploratory research to assess the mandate internet disclosure of public and private sector companies in India, it is very informational, specifically for those working on Indian companies regulation, compliance, and research. 2022, Associated Management Consultants Pvt. Ltd. All rights reserved.
Prabandhan: Indian Journal of Management, Vol-15, No. 12, pp. 39-53.
Associated Management Consultants Pvt. Ltd.
https://doi.org/10.17010/pijom/2022/v15i12/172600 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144122501&doi=10.17010%2fpijom%2f2022%2fv15i12%2f172600&partnerID=40&md5=352178e1aae6d3613df6367bcadc359c
Singh H., Department of Commerce, School of Commerce, Finance and Accountancy, Christ (Deemed to be University), Bangalore, 560 029, India