Christ University, Bangalore
  • Bengaluru, Karnataka, India
Recent publications
We investigate the asymmetric nonlinear link between foreign direct investment, oil prices, and CO2 emissions for the Gulf Cooperation Council nations, using foreign direct investment and oil price data. As foreign direct investment is positively associated with carbon emissions in the long run and oil prices have positive, significant effects on CO2 emissions, our findings support the pollution haven hypothesis. Furthermore, these variables have an asymmetric nonlinear relationship, which corresponds to the theoretical expectations of the pollution haven hypothesis. We also find that negative changes in foreign direct investment have positive, significant impacts on carbon emissions in the short run, implying that foreign enterprises utilize green technologies in their manufacturing processes in the short run. In the long run, however, negative changes in oil prices are positively associated with carbon emissions. These findings should help Gulf Cooperation Council economies focus on policies that encourage foreign direct investment in green rather than dirty industries in order to ensure environmental sustainability.
Internal heat modulation has several applications in nuclear reactor design and safety, as well as meteorology. In this paper, the influence of internal heat modulation on Rayleigh–Bénard convection in a Boussinesq–Stokes ferromagnetic fluid is explored using linear and nonlinear analyses. The impact of the square, sine, triangular, and sawtooth wave type of internal heat modulation on the onset of convection and heat transport is considered. Using a Venezian method, linear stability analysis is performed to derive the correction Rayleigh number and the critical Rayleigh number for all four waveforms. A nonautonomous Lorenz model is derived and solved for the amplitude to obtain the Nusselt number, which quantifies the heat transport. The impact of the nondimensional parameter on the convective onset and heat transfer under heat source/sink modulation is analyzed. The study shows that all four types of internal heat modulation destabilize the system. It is also found that the presence of a heat source/sink modulation affects the impact of all four types of internal heat modulation on heat transport.
Concerns about the health effects of frequent exposure to electromagnetic fields (EMF) emitted from mobile towers and handsets have been raised because of the gradual increase in usage of cell phones and frequent setting up of mobile towers. Present study is targeted to detrimental effects of EMF radiation on various biological systems mainly due to online teaching and learning process by suppressing the immune system. During COVID-19 pandemic the increased usage of internet due to online education and online office leads to more detrimental effects of EMF radiation. Further inculcation of soft computing techniques in EMF radiation has been presented. A literature review focusing on the usage of soft computing techniques in the domain of EMF radiation has been presented in the article. An online survey has been conducted targeting Indian academic stakeholders’ (Specially Teachers, Students and Parents termed as population in paper) for analyzing the awareness towards the bio hazards of EMF exposure.
Carbonized Polymer Nanomaterials (CPNs) have acquired substantial research interest in recent years due to their budding applications in various optical and electrochemical studies like electrocatalysis, solar cells, biosensing, etc. Due to their stability and toxicity, the enhancement of CPNs' properties was the primary cause of concern. Herein, we synthesized Nitrogen-doped (N-doped) N-CPNs using the one-step hydrothermal approach of PVA and PVDF polymers with Nitric acid (HNO3) as the nitrogen source. The luminescence intensity was observed to be enhanced by increasing nitrogen doping concentration. The synthesized fluorescent samples exhibited significant antibacterial properties, making them useful in biomarkers, sensing strategies, drug delivery, etc. Doped PVA samples exhibited negligible antibacterial activity, but nitrogen-doped PVDF samples displayed considerable biocidal activity against gram-positive bacteria, according to antibacterial research. Each sample's growth inhibition was distinct and species-specific.
Secular and environmental effects play a significant role in regulating the star formation rate and hence the evolution of the galaxies. Since UV flux is a direct tracer of the star formation in galaxies, the UltraViolet Imaging Telescope (UVIT) onboard ASTROSAT enables us to characterize the star forming regions in a galaxy with its remarkable spatial resolution. In this study, we focus on the secular evolution of NGC 628, a spiral galaxy in the local universe. We exploit the resolution of UVIT to resolve up to ∼ 63 pc in NGC 628 for identification and characterization of the star forming regions. We identify 300 star forming regions in the UVIT FUV image of NGC 628 using ProFound and the identified regions are characterized using Starburst99 models. The age and mass distribution of the star forming regions across the galaxy supports the inside-out growth of the disk. We find that there is no significant difference in the star formation properties between the two arms of NGC 628. We also quantify the azimuthal offset of the star forming regions of different ages. Since we do not find an age gradient, we suggest that the spiral density waves might not be the possible formation scenario of the spiral arms of NGC 628. The headlight cloud present in the disk of the galaxy is found to be having the highest star formation rate density (0.23M⊙yr−1kpc−2) compared to other star forming regions on spiral arms and the rest of the galaxy.
The COVID-19 pandemic and lockdowns potentially severely impact adolescents’ mental well-being. This research aims to study students’ subjective well-being during the covid-19 pandemic in Iran and investigate the role of loneliness, resilience, and parental involvement. For this study, 629 students (female = 345) were recruited by purposive sampling. Students were assessed on the Student’s Subjective Well-Being, Loneliness Scale, Resilience Scale, and Parental Involvement. The results confirm our hypothesis that the relationship between parental involvement and students’ subjective well-being is mediated by loneliness. Furthermore, the results indicated a partial mediation of resilience in the relationship between parental involvement and students’ subjective well-being. This study theoretically contributes to a better understanding of the factors determining the impact of traumatic events such as a pandemic on adolescents’ mental health. The implications of this study indicate interventions that can be carried out to minimize the negative psychological consequences of the pandemic.
The paper explores how the experiences of the present pandemic are shaped by the memories of popular religious piety during past pandemics and epidemics. Taking insights from the works of Astrid Erll and Reinhart Koselleck, the process ‘remembering-imagining system’ within the context of the pandemic is discussed by tracing the reemergence of pandemic deities and narratives of piety in India. Using digitally documented and disseminated narratives on piety emerging during COVID-19, an attempt is made to understand how these narratives shape the experiences, responses, and collective memory of the pandemic. Through a discussion of the shift in the imagination of political leadership and the moral responsibilities of the community, an attempt is made to highlight the mode in which the narratives on piety shape the contours of a time that is otherwise unimaginable. The mediated memories of popular religious piety make it possible to remember similar crisis times and to imagine and reinstate the social order that is threatened by this sudden unimaginable crisis. The paper thus argues that within the context of India, popular religious piety, though often overlooked, becomes a significant part of making sense and shaping the experiences of the pandemic time.
In this paper, we describe the green synthesis of silver nanoparticles (AgNPs) using plant extracts, as well as their structural, optical, and antibacterial activities against Escherichia coli and Bacillus velezensis bacteria. For the study, several sections (root, leaves, and seed) of Mucuna pruriens, an immense medicinal herbal used to treat Parkinson's disease, were evaluated. Also, the seeds were grown in-vitro in the modified Murashige and Skoog's medium and the leaf derived callus supplemented by different phytohormones like picloram (pic), thidiazuron (TDZ), 6-benzylaminopurine (BAP) and 2-isopentenyl adenine (2-iP) were selected for this study. This is the first report of distinct callus obtained from M. pruriens and used for green nanoparticle synthesis. The prepared materials were thoroughly evaluated for structural and optical properties using XRD, FTIR, and UV-Visible spectroscopy. During synthesis, the colour changes from colourless to reddish brown, and the existence of an SPR peak in the absorption spectra confirms the formation of AgNPs. The FTIR spectra reveals the presence of phenolic group and alkyl ether groups, which were responsible for the reduction of silver ions during the green synthesis. The aqueous extracts of plant parts and callus obtained from different hormones showed very poor antibacterial activity. However, the green synthesized nanoparticles fabricated by different plant extracts showed good antimicrobial activity towards E. coli and B. velezensis bacteria. amongst the investigated results, highest antimicrobial activity against E. coli (84.8%) and B. velezensis (78.1%) was shown by AgNPs mediated by leaf extracts respectively followed by 0.5 mg/L pic and 2.0 mg/L BAP callus mediated silver nanoparticle solution. According to the findings, green produced AgNPs are promising candidates for antibacterial applications against E. coli and B. velezensis.
Diabetic Retinopathy (DR) is one the most important problems of diabetics and it directs to the main cause of blindness. When proper treatment is afforded for DR patients, almost 90% of patients are protected from visual damage. DR does not produce any symptoms at the initial phase of the disease, thus various physical assessments, namely pupil dilation, visual acuity test, and so on are needed for DR disease detection. It is more complex to detect the DR during manual testing, because of the variations and complications of DR. The early detection and appropriate treatment assist to prevent vision loss for DR patients. Thus, it is very indispensable to categorize the levels and severity of DR for recommendation of essential treatment. In this paper, Autoregressive-Henry Gas Sailfish Optimization (Ar-HGSO)-based deep learning technique is proposed for DR detection and severity level classification of DR and Macular Edema (ME) based on color fundus images. The segmentation process is more essential for proper detection and classification process, which segments the image into various subgroups. The Deep Learning approach is utilized for effective identification of DR and severity classification of DR and ME. Moreover, the deep learning technique is trained by the designed Ar-HGSO scheme for obtaining better performance. The performance of the devised technique is evaluated using the IDRID dataset and DDR dataset. The introduced Ar-HGSO-based deep learning approach obtained better performance than other existing DR detection and classification techniques with regards to testing accuracy, sensitivity, and specificity of 0.9142, 0.9254, and 0.9142 using the IDRID dataset.
Nanocomposite MoS2/ZnO was prepared by an exfoliation process and characterized. A flower-like morphology was obtained for the hybrid where uniformly spread ZnO is stacked over thin layers of MoS2. A tight interface between the two components coupled with the energy band bending at the junction has resulted in a high activity of the composite towards the reduction of 4-nitrophenol. A complete reduction to 4-aminophenol from 4-nitrophenol took place within 15 min under the optimized conditions. The catalyst has a recyclability of six times without any perceptible decrease in the catalytic activity.
Excellence in transmission can be assessed in optical transport networks before providing any additional connections or upgrading the connections. Generally, the Physical Layer Model (PLM) is used to assess the transmission quality which has high probability in uncertainty and inaccuracy due to the circumstances of physical layer. The network efficiency is directly proportional to the margins. If the margins getting increases in the PLM, the efficiency of the network decreases. Maintaining the excellence in transmission is the biggest challenge when the margins getting increased. Other significant factors for excellence in transmission is scalable, minimum latency with maximum speed and energy efficient. Photonic switching is a hopeful solution for handling these challenges. Machine learning technique is proposed to assess the excellence of transmission and flow detection. ML-E and Precedence based scheduling algorithms are proposed for excellence of transmission and flow detection respectively. The proposed techniques justify variations, uncertainties in kits like fiber dilution, dispersion and optimizes PSON (packet switched optical network). Simulation results are demonstrated and the proposed work results indicates that it can outperform a benchmark in all aspects.
Sericulture is the process of cultivating silkworms for the production of silk. High-quality production of silk without mixing with low quality is a great challenge faced in the silk production centers. One of the possibilities to overcome this issue is by separating male and female cocoons before extracting silk fibers from the cocoons as male cocoon silk fibers are finer than females. This study proposes a method for the classification of male and female cocoons with the help of X-ray images without destructing the cocoon. The study used popular single hybrid varieties FC1 and FC2 mulberry silkworm cocoons. The shape features of the pupa are considered for the classification process and were obtained without cutting the cocoon. A novel point interpolation method is used for the computation of the width and height of the cocoon. Different dimensionality reduction methods are employed to enhance the performance of the model. The preprocessed features are fed to the powerful ensemble learning method AdaBoost and used logistic regression as the base learner. This model attained a mean accuracy of 96.3% for FC1 and FC2 in cross-validation and 95.3% in FC1 and 95.1% in FC2 for external validation.
Zero forcing is one of the dynamic vertex coloring problem. Zero forcing number is the minimum cardinality of the zero forcing sets. This parameter is the upper bound for the maximum nullity. A new class of graph where the maximum nullity is equal to the zero forcing number of the graph is defined as closed global shadow graph. Basic properties and zero forcing number of this graph class is analysed.
The Depression Anxiety Stress Scales-21 (DASS-21) is a well-established scale designed to measure the negative emotional states of depression, anxiety, and stress. DASS-21 has been translated into various languages, and findings conclude that it is psychometrically sound, with good reliability and validity. This study adapts and validates the psychometric properties of DASS-21 in the Tamil language. The instrument was administered to 511 Tamil speaking students ranging between 18 and 35 of age with an average age of 21 years. Results reaffirm that DASS-21 three-factor model shows excellent validity and reliability on the entire sample and groups based on age, gender, and residential area. They also find support in different hierarchical variance measurement models (metric, scalar, strict models). This study concludes that Tamil DASS-21 can be used as a universal measure to map symptoms and screen for depression, anxiety, and stress in any circumstances. Our findings provide roadmap for future research on the Tamil version of DASS-21 with specific focus on its clinical use.
With the amount of data being transferred on a daily basis, it is becoming increasingly dangerous to save data on the Internet in the face of intruders or hackers. This study paper is one of the most effective ways to transmit information in a secure and confidential manner. The authors previously disclosed a way for embedding a secret video inside a cover video in their prior work. The writers have implemented a number of techniques to incorporate the secret video. The current work improves on the existing approach by including encryption and decryption concepts into the video embedding process. The secret data for either a large or little amount of information is put on the cover video utilising the embedding technique. Our proposed method combines compression, encryption, decryption, and secret information embedding to provide a more secure data transfer.
The cellular activities of the endothelium layer between lumen and intima are significantly linked to the origin of the disease atherosclerosis. Three stages of atherosclerosis were investigated in this study (40%-mild, 50%-modest, and 60%-acute) concerning the coronary arterial segment. The essence of the hemodynamic factors like flow velocity, pressure, and wall shear stress has been investigated, as well as the interrelationships between them. At all degrees of stenosis, the biophysical relationship between convection-diffusion of low-density lipoproteins (LDL) and convection-diffusion of oxygen in the bloodstream is investigated. The Finite Element Methods (FEM) are used to solve the modeled partial differential equation systems. The method adopted is numerical in nature providing accurate graphical solutions to the framed systems. The physical effects of the deposition of LDL on the arterial wall, like a decrease in the diameter of the lumen, and toughening of the walls, are analyzed through the evaluation of the physical parameters. The study revealed that the deposition of LDL molecules in the post stenotic region leads to the depletion of oxygen in the region leading to the rapid dysfunctioning of the endothelial layer of the lumen-intima boundary.
The induced \(nK_2\) decomposition of infinite square grids and hexagonal grids are described here. We use the multi-level distance edge labeling as an effective technique in the decomposition of square grids. If the edges are adjacent, then their color difference is at least 2 and if they are separated by exactly a single edge, then their colors must be distinct. Only non-negative integers are used for labeling. The proposed partitioning technique per the edge labels to get the induced \(nK_2\) decomposition of the ladder graph is the square grid and the hexagonal grid.
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18,677 members
Santhosh Kareepadath Rajan
  • Department of Psychology
Subbarama Pranesh
  • Department of Mathematics
Dr. M. Nidhin
  • Department of Chemistry
Arun Kenath
  • Department of Physics
Lakshmi Shankar Iyer
  • School of Business and Management
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