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Exploratory Architectures Analysis of Various Pre-trained Image Classification Models for Deep Learning
The image classification is one of the significant applications in the area of Deep Learning (DL) with respective to various sectors. Different types of neural network architectures are available to perform the image classification and each of which produces the different accuracy. The dataset and the features used are influence the outcome of the model. The research community is working towards the generalized model at least to the domain specific. On this gesture the contemporary survey of various Deep Learning models is identified using knowledge information management methods to move further to provide optimal architecture and also to generalized Deep Learning model to classify images narrow down to the sector specific. The study systematically presents the different types of architecture, its variants, layers and parameters used for each version of Deep Learning model. Domain specific applications and limitations of the type of architecture are detailed. It helps the researchers to select appropriate Deep Learning architecture for specific sector. 2024 by the authors. -
In silico analysis of NHP2 membrane protein, a novel vaccine candidate present in the RD7 region of Mycobacterium tuberculosis
Mycobacterium tuberculosis, the etiological agent of tuberculosis, is one of the trickiest pathogens. We have only a few protective shields, like the BCG vaccine against the pathogen, which itself has poor efficacy in preventing adult tuberculosis. Even though different vaccine trials for an alternative vaccine have been conducted, those studies have not shown much promising results. In the current study, advanced computational technology was used to study the potential of a novel hypothetical mycobacterial protein, identified by subtractive hybridization, to be a vaccine candidate. NHP2 (Novel Hypothetical Protein 2), housed in the RD7 region of the clinical strains of M. tuberculosis, was studied for its physical, chemical, immunological and structural properties using different computational tools. PFAM studies and Gene ontology studies depicted NHP2 protein to be functionally active with a possible antibiotic binding domain too. Different computational tools used to assess the toxicity, allergenicity and antigenicity of the protein indicated its antigenic nature. Immune Epitope Database (IEDB) tools were used to study the T and B cell determinants of the protein. The 3D structure of the protein was designed, refined and authenticated using bioinformatics tools. The validated tertiary structure of theprotein was docked against the TLR3 immune receptor to study the binding affinity and docking scores. Molecular dynamic simulation of the protein-protein complex formed were studied. NHP2 was found to activate host immune response against tubercle bacillus and could be explored as a potential vaccine in the fight against tuberculosis. 2023, The Author(s), under exclusive licence to Plant Science and Biodiversity Centre, Slovak Academy of Sciences (SAS), Institute of Zoology, Slovak Academy of Sciences (SAS), Institute of Molecular Biology, Slovak Academy of Sciences (SAS). -
Detecting Fake Information Dissemination using Leveraging Machine Learning and DRIMUX with B-LSTM
Information integrity and public confidence are seriously threatened by the rapid expansion of fake news and misinformation that has resulted from the online broadcast of information. This work focuses on the detection of fraudulent information propagation utilizing machine learning techniques and the Digital Reputation and Influence Measurement Unit (DRIMUX) in order to address this problem. The use of Bidirectional Long Short-Term Memory (B-LSTM) networks into the detection process is something we really advocate. B-LSTM enables the capture of contextual dependencies from both past and future time steps, enhancing the understanding of sequential data. Additionally, DRIMUX provides reputation and influence measurements to assess the credibility of information sources. Experimental analyses on various datasets reveal the promising performance of the suggested methodology, highlighting its potential in preventing the spread of false information and protecting the veracity of digital information. 2024, Ismail Saritas. All rights reserved. -
An analysis of factors associated with employee satisfaction in information technology companies
BACKGROUND AND OBJECTIVES: An employees satisfaction and performance are linked to the companys work discipline, personal factors, and organizational culture. This paper studies these three factors in the context of Information Technology companies and their connection to employee satisfaction. Job satisfaction is a significant issue in Information Technology Companies, leading to increased labour turnover in Information Technology Companies. The study highlights the relevance of Information Technology companies to understanding the reasons behind their employees satisfaction. Until now, little is known concerning the variants of job satisfaction among Information Technology employees, enriching the understanding in this particular professional area. The study was conducted to assess the job satisfaction needs of the employees in major Information Technology companies. The study helps to know the preferences and problems of the employees. METHODS: In this study, data was collected from employees from various Information Technology companies to uncover the factors that impact the satisfaction of employees. Considering the studys goal and the literature review, the technique was analytical and interpretive. Due to large populations random sampling method is convenient for the study. The studys objectives were achieved explicitly via the questionnaires design. To test the proposed hypotheses, all data were processed using the Structural Equation Modelling, Statistical Package for Social Science (SPSS) and Analysis of Moment Structures. FINDINGS: Information Technology companies need their employees to feel satisfied to achieve the overall objectives and remain loyal to the company to achieve company success. From the responses, we learned that 31% of the respondents were satisfied with their employer about the various allowances and benefits they receive. Also, we knew that around 50% of the respondents were happy with their choice of the company because of its future commitments. 102 of the respondents highly disagreed that they were satisfied with the attitude and nature of their employees. Also, 22.26% of the male respondents have said they are only sometimes motivated to go to work. The limitation of this study was that the collected data was only of the general employees of the Indian Information Technology companies and not to specific departments of those companies. Also, no categories of companies were defined as per turnover. CONCLUSION: By recognizing the importance of job satisfaction, managers can create an environment that motivates and engages employees, leading to better performance, increased productivity and reduced employee turnover 2024 Tehran Urban Research and Planning Center. All Rights Reserved. -
Impact of Globalization and Multinational Corporations on Farmer Suicides in India: An Overview, Effects, Strategies and Policies
The tragic rise of farmer suicides in India brought to light some of the high social and ecological costs associated with globalization and unsustainable agriculture. The study analyzes the impact of globalization and MNCs on farmer suicides and suggests strategies and policies. The crucial findings show regressive agricultural policies, output declines, insufficient credit support, private parties intervention, land fragmentation, and the high cost of cultivation due to the privatization of the seed sector that led to worst debt traps among other factors as major contributors to this turmoil. This research underlines the ongoing efforts in understanding and tackling these issues. 2023 Taylor & Francis Group, LLC. -
Facilitating Faculty Development for Training in Multicultural Competence in Health Service Psychology Graduate Programs Through an International Collaboration
A critical aspect of strengthening graduate-level clinical and counseling psychology training in cultural competence is to build capacity among faculty teaching in these programs to provide effective training. We addressed this need through an international collaboration between a university in India and another in the United States that included faculty travel to another country, peer mentoring groups, and review of curricula. This article describes faculty perceptions of this program and its perceived impact on their professional development and outlines curricular and research outcomes that resulted from the program. Across 4 years, a total of eight faculty visits took place with Indian faculty (n = 13) visiting the United States and US faculty (n = 11) visiting India. After each visit, faculty at both institutions responded to open-ended questions about the usefulness of these visits and completed a rating scale at the end of the program through an online survey. Faculty from both countries indicated that the visits contributed to enhanced cultural awareness and sensitivity by broadening their perspectives and learning about cultural similarities and differences. Indian faculty described learning about new pedagogical methods and enhanced motivation to engage in research and publish, along with new collaborative opportunities. US faculty described incorporating cultural competence more centrally in their teaching and clinical supervision through increased commitment, as well as inclusion of more global and diverse content and assignments aimed to increase students cultural competence. These responses provide preliminary support for the usefulness of cultural immersion experiences for faculty professional development. 2024 American Psychological Association Inc.. All rights reserved. -
A Novel Artificial Intelligence System for the Prediction of Interstitial Lung Diseases
Interstitial lung disease (ILD) encompasses a spectrum of more than 200 fatal lung disorders affecting the interstitium, contributing to substantial mortality rates. The intricate process of diagnosing ILDs is compounded by their diverse symptomatology and resemblance to other pulmonary conditions. High-resolution computed tomography (HRCT) assumes the role of the primary diagnostic tool for ILD, playing a pivotal role in the medical landscape. In response, this study introduces a computational framework powered by artificial intelligence (AI) to support medical professionals in the identification and classification of ILD from HRCT images. Our dataset comprises 3045 HRCT images sourced from distinct patient cases. The proposed framework presents a novel approach to predicting ILD categories using a two-tier ensemble strategy that integrates outcomes from convolutional neural networks (CNNs), transfer learning, and machine learning (ML) models. This approach outperforms existing methods when evaluated on previously unseen data. Initially, ML models, including Logistic Regression, BayesNet, Stochastic Gradient Descent (SGD), RandomForest, and J48, are deployed to detect ILD based on statistical measures derived from HRCT images. Notably, the J48 model achieves a notable accuracy of 93.08%, with the diagnostic significance of diagonal-wise standard deviation emphasized through feature analysis. Further refinement is achieved through the application of Marker-controlled Watershed Transformation Segmentation and Morphological Masking techniques to HRCT images, elevating accuracy to 95.73% with the J48 model. The computational framework also embraces deep learning techniques, introducing three innovative CNN models that achieve test accuracies of 94.08%, 92.04%, and 93.72%. Additionally, we evaluate five full-training and transfer learning models (InceptionV3, VGG16, MobileNetV2, VGG19, and ResNet50), with the InceptionV3 model achieving peak accuracy at 78.41% for full training and 92.48% for transfer learning. In the concluding phase, a soft-voting ensemble mechanism amplifies training outcomes, yielding ensemble test accuracies of 76.56% for full-training models and 92.81% for transfer learning models. Notably, the ensemble comprising the three newly introduced CNN models attains the pinnacle of test accuracy at 97.42%. This research is poised to drive advancements in ILD diagnosis, presenting a resilient computational framework that enhances accuracy and ultimately betters patient outcomes within the medical domain. 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
A Unified Approach to Two-Dimensional Brinkman-Bard Convection of Newtonian Liquids in Cylindrical and Rectangular Enclosures
A unified model for the analysis of two-dimensional BrinkmanBard/RayleighBard/ DarcyBard convection in cylindrical and rectangular enclosures ((Formula presented.)) saturated by a Newtonian liquid is presented by adopting the local thermal non-equilibrium ((Formula presented.)) model for the heat transfer between fluid and solid phases. The actual thermophysical properties of water and porous media are used. The range of permissible values for all the parameters is calculated and used in the analysis. The result of the local thermal equilibrium ((Formula presented.)) model is obtained as a particular case of the (Formula presented.) model through the use of asymptotic analyses. The critical value of the Rayleigh number at which the entropy generates in the system is reported in the study. The analytical expression for the number of Bard cells formed in the system at the onset of convection as a function of the aspect ratio, (Formula presented.), and parameters appearing in the problem is obtained. For a given value of (Formula presented.) it was found that in comparison with the case of (Formula presented.), more number of cells manifest in the case of (Formula presented.). Likewise, smaller cells form in the (Formula presented.) problem when compared with the corresponding problem of (Formula presented.). In the case of (Formula presented.), fewer cells form when compared to that in the case of (Formula presented.) and (Formula presented.). The above findings are true in both (Formula presented.) and (Formula presented.). In other words, the presence of a porous medium results in the production of less entropy in the system, or a more significant number of cells represents the case of less entropy production in the system. For small and finite (Formula presented.), the appearance of the first cell differs in the (Formula presented.) and (Formula presented.) problems. 2023 by the authors. -
Fabrication of biopolymeric sheets using cellulose extracted from water hyacinth and its application studies for reactive red dye removal
Driven by the imperative need for sustainable and biodegradable materials, this study focuses on two pivotal aspects: cellulose extraction and dye removal. The alarming repercussions of non-biodegradable food packaging materials on health and the environment necessitate the exploration of viable alternatives. Herein, we embark on creating easily degradable biopolymer substitutes, achieved through innovative crafting of a biodegradable cellulose sheet sourced from extracted cellulose. Concurrently, the significant environmental and health hazards posed by textile industry discharge of wastewater laden with persistent dyes demand innovative treatment strategies. This study extensively investigated four distinct methods of cellulose extraction from water hyacinth, a complex aquatic weed. The functional groups, crystallinity index, thermal stability, thermal effects, and morphology of the extracted cellulose were characterized by FTIR, XRD, TGA, DSC, and SEM. This exploration yielded a notable outcome, as the most promising yield (39.4 0.02% w/w) emerged using 2% sodium chlorite and 2% glacial acetic acid as bleaching agents, surpassing other methods. Building on this foundational cellulose extraction process, the extracted fibers were transformed into highly biodegradable cellulose sheets, outlining conventional packaging materials. Moreover, these cellulose sheets exhibit exceptional efficacy in adsorbing reactive red dye, with the adsorption capacity of 71.43 mg/g by following pseudo-second kinetics. This study establishes an economically viable avenue for repurposing challenging aquatic weeds into commercially valuable biopolymers. The potential of these sheets for dye removal, coupled with their innate biodegradability, opens auspicious avenues for broader applications encompassing commercial wastewater treatment procedures. 2023 Elsevier Inc. -
Impact of boundary conditions on Rayleigh-Bard convection: stability, heat transfer and chaos
The paper compares the results of Rayleigh-Bard convection problem for rigid-rigid-isothermal, rigid-free-isothermal and free-free isothermal boundaries. A minimal Fourier-Galerkin expansion yields the generalized-Lorenz-model whose scaled version is reduced to the Stuart-Landau-model using the multiscale-method. Nusselt number is estimated for both steady and unsteady regimes. Regular, chaotic, and periodic natures of the solution are studied using the Hopf-Rayleigh-number and by means of a bifurcation diagram. The linear and weakly-nonlinear-analyses reveal that the onset of regular and chaotic motions in the case of rigid-free-isothermal boundaries happens later than that of free-free isothermal boundaries but earlier than rigid-rigid-isothermal boundaries. It is shown that the scaled-Lorenz-model possesses all the features of the classical-Lorenz-model. Beyond the value of the Hopf-Rayleigh-number, we observe chaotic-motion between two consecutive spells of periodic motion. It is found that one can also have a window of periodicity for all three boundaries. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Efficacy of Psychosocial Care Training Programme for the Staff Working in Old Age Homes
Background: Training the old-age home staff is essential in raising geriatric mental health care standards in India. Inadequate knowledge on ageing and psychosocial interventions is a significant issue in old-age homes. Old-age home staff must know how to provide individualized psychosocial care and support for older adults. Hence this study aimed to test the feasibility of the psychosocial care training program for the staff working in old-age homes. Methods: A quasi-experimental research design (pre-post without a control group) was used. Forty-two staff members participated. Mary Starke Harper Aging Knowledge Exam (MSHAKE) and structured checklist to measure the staffs knowledge on ageing, psychosocial interventions, welfare legislations, schemes, and support services were administered before, immediately after, and two months after the program and the self-efficacy checklist was administered immediately and two months after the program, to examine the efficacy of the program. Results: Significant improvement was found in the ageing knowledge and the knowledge of psychosocial intervention and psychosocial care. These improvements continued for two months (p <.001). Similarly, their self-efficacy in managing such problems was also sustained across two post-measurements (p =.045). Conclusions: Face-to-face training programs would enhance the knowledge of the old age home staff. This Psychosocial Care Training module can be used for training old age home staff to address various psychosocial needs, concerns and other psychosocial problems of the residents. 2023 The Author(s). -
Classification and characterization using HCT/HFOSC spectra of carbon stars selected from the HES survey
We present results from the analysis of 88 carbon stars selected from Hamburg/ESO (HES) survey using low-resolution spectra (R ?1330 & 2190). The spectra were obtained with the Himalayan Faint Object Spectrograph Camera (HFOSC) attached to the 2-m Himalayan Chandra Telescope (HCT). Using well-defined spectral criteria based on the strength of carbon molecular bands, the stars are classified into different groups. In our sample, we have identified 53 CH stars, four C-R stars, and two C-N type stars. Twenty-nine stars could not be classified due to the absence of prominent C2 molecular bands in their spectra. We could derive the atmospheric parameters for 36 stars. The surface temperature was determined using photometric calibrations and synthesis of the H-alpha line profile. The surface gravity log g estimates are obtained using parallax estimates from the Gaia DR3 database whenever possible. Microturbulent velocity (?) was derived using calibration equation of log g & ? . We could determine metallicity for 48 objects from near-infrared Ca II triplet features using calibration equations. The derived metallicity ranges from ?0.43 ? [Fe/H] ? ?3.49. Nineteen objects were found to be metal-poor ([Fe/H] ? ?1), 14 very metal-poor ([Fe/H] ? ?2), and five extremely metal-poor ([Fe/H] ? ?3.0) stars. Eleven objects were found to have a metallicity in the range ?0.43 ? [Fe/H] ? ?0.97. We could derive the carbon abundance for 25 objects using the spectrum synthesis calculation of the C2 band around 5165 The most metal-poor objects found will make important targets for follow-up detailed chemical composition studies based on high-resolution spectroscopy, and are likely to provide insight into the Galactic chemical evolution. 2024, The Author(s), under exclusive licence to Springer Nature B.V. -
Impact of meme marketing on consumer purchase intention: Examining the mediating role of consumer engagement
This paper analyzes an emerging form of social media marketing, meme marketing, which has gained attention for its ability to entertain and engage users. Marketers and companies are recognizing the value of using memes as a tool to connect with consumers. To understand the effects of meme marketing activities, this paper aims to examine the impact of meme marketing activities on consumer purchase intentions and concurrently assess the mediating role of consumer engagement. The study encompassed 452 Indian social media users with active social media accounts and familiarity with memes and meme marketing concepts. It employed a quantitative methodology backed by robust statistical techniques. The method used for analysis was Structural Equation Modeling (SEM) through Analysis of Moment Structures (AMOS) software. The results found that meme marketing activities have a direct and significant positive impact (? = 0.257, p < 0.05) on consumer purchase intentions. It further shows that meme marketing has a direct and significant positive impact (? = 0.745, p < 0.05) on consumer engagement. It shows that consumer engagement has a direct and significant positive effect (? = 0.651, p < 0.05) on consumer purchase intention. However, the indirect impact of meme marketing activities on consumer purchase intentions is also significant, resulting in partial mediation. The study findings hold value for marketing managers, agencies, and companies that interact and engage consumers with memes and undertake meme marketing activities. Navrang Rathi, Pooja Jain, 2023. -
Framework for Sustainable Energy Management using Smart Grid Panels Integrated with Machine Learning and IOT based Approach.
Maintaining a consistent supply of power is essential for the well-being of the economy, the public, and one's own health. The generation of energy, as well as its distribution, monitoring, and management, are all undergoing fundamental changes as a result of the implementation of a smart grid (SG), which is authorised to include communication technology and sensors into power systems. There are a lot of problems that need to be fixed before the interoperability of the smart grid can be determined. The integration of renewable energy sources and smart grid technology market size and energy management is a sustainable solution to the problem of energy demand management. The importance work quickly toward the development of an efficient Energy Management Model (EMM) that integrates smart grids and renewable energy sources. When it comes to the modelling of complex and non-linear data, machine learning (ML), Internet of Things (IoT) approaches often perform better than statistical models. So, utilizing a machine learning approach for the EMM is a good option since it simplifies the EMM by generating a single trained model to anticipate its performance characteristics across all conditions. This may be accomplished via the use of an EMM created using an ML method. It was recommended that a certain flexibility sample be used as a control mechanism for incursion into the smart grid. The outcomes of the experiment indicate that the demand-side management (DSM) device is more resistant to infiltration and is enough to lower the energy usage of the smart grid. 2024, Ismail Saritas. All rights reserved. -
An Application of the Caputo Fractional Domain in the Analysis of a COVID-19 Mathematical Model
Vaccination programs aimed at preventing the spread of the coronavirus appear to have a significant global impact. In this research, we have investigated a mathematical model projecting COVID-19 disease spread by considering five groups of individuals viz. vulnerable, exposed, infected, unreported, recovered, and vaccinated. Looking at the current abnormal pattern of the virus spread in the projected model, we have implemented the fractional derivative in the Mittag-Leffler context. Using the existing theory of the fractional derivative, we have examined the theoretical aspects such as the existence and uniqueness of the solutions, the existence and stability of the disease-free and endemic equilibrium points, and the global stability of the disease-free equilibrium point. In computing the basic reproduction number, we have analyzed that the existence and stability of points of equilibrium are dependent on this number. The sensitivity of the basic reproduction number is also examined. The importance of the vaccination drive is highlighted by relating it to the basic reproduction number. Finally, we have presented the simulation of the numerical results by capturing the profile of each group under the influence of the fractional derivative and investigated the impact of vaccination rate and contact rate in controlling the disease by applying the Adams-Bashforth-Moultan (ABM) method. The present research study demonstrates the importance of the vaccination campaign and the curb on individual contact by featuring a novel fractional operator in the projected model and capturing the corresponding consequence. 2024 P. Veeresha, et al. -
Study of chaos in the Darcy-Bard convection problem with Robin boundary condition on the upper surface
Possibility of chaos is studied in Darcy-Bard convection using the Dirichlet and the Robin boundary condition at the lower and upper boundaries, respectively. Comparison is made with the results of Dirichlet (classical-Darcy-Bard convection, CDBC) and Neumann boundary condition (Barletta-Darcy-Bard convection, BDBC). It is found that the cell size at onset is bigger in the case of BDBC compared to the generalized-Darcy-Bard convection (GDBC) and much bigger compared to CDBC. The critical-Darcy-Rayleigh number of BDBC is found to be the least and that of CDBC is the largest. Nonlinear-stability-analysis is performed leading to the scaled-generalized-Vadasz-Lorenz model (SGVLM). In deriving this model, help is sought from a local-nonlinear-stability-analysis that yields the form of the convective-mode. The SGVLM is shown to be dissipative and conservative, with its bounded solution trapped within an ellipsoid. Onset of chaos and its characteristics are studied using the Hopf-Rayleigh-number, the Lorenz-butterfly-diagram, and the plot of the amplitude of the convective-mode vs the control-parameter, R, which is the eigenvalue. Chaos sets in earlier in CDBC and much later in BDBC when compared to that in GDBC. Beyond the onset of chaos is seen a sequence of chaotic and periodic motions, with the latter sometimes being present for an extended period. 2024 Author(s). -
Does environmental policy stringency improve nature's health in BRICS economies? Implications for sustainable development
In our groundbreaking exploration, we meticulously delve into the relationship between environmental policy stringency, international trade dynamics, and financial openness within the BRICS group (Brazil, Russia, India, China, and South Africa) spanning from 1996 to 2021. With a focus on critical variables such as economic growth and technological innovation, our empirical findings challenge conventional wisdom. Surprisingly, we found that those stringent environmental policies, when standing alone, do not invariably lead to reduce CO2 emissions. Equally interesting is our startling discovery that the anticipated moderating influence of environmental policy stringency, catalyzed by trade and foreign direct investment, on the well-being of our environment does not materialize; contrarily, both trade and foreign direct investment moderating channels exhibit unanticipated positive correlations with CO2 emissions. These revelations provoke us with the presence of a "pollution haven" phenomenon within the BRICS economies. Furthermore, our investigation reveals that, when examined individually, trade and foreign direct investment also appear to contribute to elevated emission levels. These findings provide a resolute solution to our research quandary, underlining the indispensable requirement for cutting-edge and robust environmental policies. These policies must possess the prowess to effectively counteract the adverse environmental consequences stemming from the amalgamation of global trade and financial integration. In doing so, they shall propel BRICS nations toward a future firmly grounded in principles of sustainability and ecological integrity. 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Generalized viscoelastic flow with thermal radiations and chemical reactions
Background: A generalized model of mathematical nature is considered to address the viscoelastic flow problem using fractional derivatives. Control/freedom of the flow mechanism is achieved with these derivatives. In simulations of industrial interest, more variations are available with fractional derivatives when compared with ordinary derivatives. Relaxation times are incorporated to handle the abrupt changes in the flow domain. Fluid flow is carried out under the influence of thermal radiations and when a heat source or sink is present. Chemical reactions of the first order are observed in the mathematical modeling of the flow. Methods: Flow is induced with the movement of the lower surface while applying force on the x-plane. Simulations of the governing mathematical problem are computed with the combination of finite element and finite difference algorithms. Significant Findings: It is noted that velocity, temperature, and concentration change with the variation of fractional order derivatives which was not possible with the classical derivatives. Moreover, with greater relaxation times, velocity, temperature, and concentration remained at a lower level. The modeled mechanism can be considered to avoid costly trials in chemical and polymer casting industries. 2023 Elsevier B.V. -
An ethnographic expose of Mithun-human interrelationship among the Kuki community of Northeast India
Unrestrained consumption and a lack of a proper breeding ecosystem have depleted the variety and species count of mithun (Bos frontalis). Indigenous Kuki tribes have a unique relationship with mithun, reared in the semi-domestic countryside. For the Kuki community, a mithun is used during community festivals, as a bride price in marriages, to settle disputes, in land-deed covenants, and at death ceremonies. Mithun-human interrelationship lessens poverty, empowers community survival, guarantees the completion of critical cultural obligations, and maintains marital bonds in the Kuki community. The head of a mithun signifies solemnity and celebration in many cultural underpinnings. A white cock, a dog, a goat, a pig, and a mithun were sacrificial elements to appease the unseen spirits for good health and prosperity. While some Indigenous practices have faded with the arrival of Christianity, the cultural involvement of mithun persists to this date. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Effects of global warming, time delay and chaos control on the dynamics of a chaotic atmospheric propagation model within the frame of Caputo fractional operator
The Lorenz-84 climate model is a simplified mathematical model that describes the chaotic behavior of atmospheric convection and its impact on global climate patterns. It captures the presence of chaotic behavior in the motion of westerly wind and helps understand the concept of sensitivity to initial conditions. But as observed over the years, the westerlies are gaining more strength due to the rise in atmospheric temperature. In this work, we have modified the old model to observe the changes in the behavior of the system due to global warming and time delay. The modified model has been generalized using Caputo fractional derivative to provide a more accurate representation of the system with memory effect and non-local behavior. The stability of the new model has been tested at all the equilibrium points. Using Picard's operator and Banach's Fixed Point theorem, it has been shown that there exists a unique and bounded solution for the new model. It has been observed that the sole effect of global warming makes the system gradually unstable from chaotic as the fractional order ? is decreased from 0.80 to 0.50. Also, a shift in the bifurcation point has been noticed for the new model. All three Lyapunov exponents have been calculated for different fractional orders to confirm the presence of chaos in the modified model as well. A chaos control law has been constructed for the modified chaotic model using the sliding mode control theory. Interestingly, the chaos disappears completely when the effect of time-delay is considered in the modified model. Since our proposed time-delayed modified model shows an asymptotically stable nature for all fractional orders ? less than 0.85, it is better suited to make more accurate predictions about the strength of the westerlies. 2023 Elsevier B.V.