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The importance of Mindshare branding (MB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13-point four-factor multidimensional scale which could be used to measure MB formally. Dimensions measuring MB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale.</text>
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The importance of Viral branding (VB) strategy in building long-term and sustainable psychological links with consumers had been sufficiently highlighted in literature. However, very few research attempted to provide a structured tool for its measurement. This study proposed a 13- point four-factor multidimensional scale which could be used to measure VB formally. Dimensions measuring VB were derived from literature and then examined on different brands in order to achieve a reliable and valid scale.</text>
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                <text>Photonuclear reactions play an important role in nuclear physics, astrophysics and in various applications such as non-destructive measurement of nuclear materials (NDT). The study of (?, n) reactions using deuterium targets i.e., photodisintegration of deuterons in addition to all the other (?, n) reactions, is of considerable interest to these fields. In this contribution, we have studied the photodisintegration of deuterons with unpolarized photons. The angular dependence of the differential cross section is studied by expressing it in terms of Legendre polynomials. The analysis of differential cross-section is presented using the model-independent irreducible tensor formalism.  2021</text>
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                <text>Materials Today: Proceedings, Vol-54, pp. 818-819.</text>
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                <text>S P S., School of Engineering and Technology, Christ University, Bengaluru, 560074, India; M K., School of Engineering and Technology, Christ University, Bengaluru, 560074, India, K S School of Engineering and Management, Bengaluru, 560109, India</text>
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                <text>One of the elements that was synthesized primordially in the standard Big Bang Nucleosynthesis is lithium. Lithium, being fragile gets easily destroyed at relatively low temperatures in the mixing process between stellar surface and hot internal layers. So that, at the end of the stellar lifetime the lithium content is believed to be depleted. Series of experimental measurements on lithium isotopes were carried out at High Intensity Gamma Ray Source (HIGS) at Duke Free Electron Laser Laboratory. More recently experiments [1]-[2] were performed, to measure the differential cross section of the photo-neutron reaction channel in photodisintegration of 7Li, where the progeny nuclei is in the ground state as well as in excited states. The purpose of present contribution is to study the reaction channel 7Li + ? ? 6Li + n using linearly polarized photons.The model independent irreducible tensor formalism [3]-[5] will be used to study the differential cross section of the reaction. We study the angular dependence of differential cross section by expressing differential cross section in terms of legendre polynomials. In view of the several theoretical and ongoing experimental studies, a detailed theoretical study of the spin structure of the amplitudes in 7Li+ ? ? 6Li+ n and their expansion in terms of'electric' and 'magnetic' amplitudes is needed to analyze the measurements of spin observables as well as differential cross section, which leads to a better understanding of the problem at astrophysical energies.  2022 Institute of Physics Publishing. All rights reserved.</text>
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                <text>Aswathi V.; Shastri V.; Shilpashree S.P.</text>
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                <text>Journal of Physics: Conference Series, Vol-2156, No. 1</text>
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                <text>Institute of Physics</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>In addition to other photonuclear reactions, the study of photonuclear reactions on deuterium targets is important for laser physics, nuclear physics, astrophysics, and a number of applications, including nondestructive testing of nuclear materials. In this paper, we have carried out a model independent analysis of proton polarization in photodisintegration of deuterons with initially unpolarized beam and unpolarized target. The angular dependence of the polarization is studied by expressing it in terms of multipole amplitudes.  2023 Elsevier Ltd. All rights reserved.</text>
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                <text>Kusuma M., K S School of Engineering and Management, Karnataka, Bengaluru, 560109, India, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India; Shastri V., School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India; Shilpashree S.P., School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India</text>
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                <text>In the globalized economy, it is necessary to consider expatriates cross-cultural adjustment, which is affected by their spouses, whose cross-cultural adjustment should not be neglected. We examined a model of cross-cultural adjustment among Japanese spouses in India. We hypothesized that demands (e.g., cultural differences, language immaturity) and resources (e.g., spouses personality/agreeableness, perceived social support) negatively and positively affect cross-cultural adjustment, respectively. In turn, cross-cultural adjustment positively affects subjective happiness and intent to stay. In addition, cross-cultural adjustment consists a part of life-career perspective for expatriate spouses who quit their job when go to abroad. To examine the hypotheses, we use a mixed methods approach (QUAN?QUAL) that uses multiple variables and sampling to collect quantitative and qualitative data over two phases sequentially. First, from August to October 2018, a survey using a web-based questionnaire was conducted in four areas in India: New Delhi, Mumbai, Chennai, and Bengaluru. Responses from 105 participants, who are parents of Japanese school children or members of a parenting support group were received. Second, from October to December 2018, the interview data for 17 participants were collected at Bengaluru. To confirm the hypothesized model, we tested a structural equations modeling (SEM) analysis. Additionally, the interview transcript data were analyzed with a modified version of the Grounded Theory approach (M-GTA). The Results demonstrated that Japanese expatriate spouses who had difficulties in communicating in English and felt large cultural differences, decreased their adjustment, their subjective happiness was lowered, and they wanted to return to their home country early. However, the more the personality was cooperative and compassionate, and the more they worked to adjust to their international life; their subjective happiness increased. Additionally, expatriate spouses obtained the concept of view of life-career. The view of life-career included cross-cultural adjustment. Cross-cultural adjustment affects positive view of life-career that will lead to smooth re-employment after returning to Japan.  2020, Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>Current Psychology, Vol-41, No. 9, pp. 5935-5947.</text>
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                <text>Matsumoto M., Department of Psychology, CHRIST(Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India, Aichi Mizuho Junior College, 13, 2, Shunko, Mizuho, Aichi, Nagoya, 467-0867, Japan; Gopal B., Department of Psychology, CHRIST(Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India</text>
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                <text>Samanta, Debabrata.</text>
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                <text>Energy is present in various forms in and around us. Capturing and storing energy from various sources have diverse challenges. Designing and developing energy storage systems are challenging, as various techniques are used to distribute energy from sources and to store for diverse use cases. Identifying the optimal and effective energy storage system requires the application of various model selection strategies. The success and adoption of effective energy storage systems can be identified with numerous factors, which include the systems efficiency, reliability, cost-effectiveness, and scalability. Various model selection strategies are available to compute and determine the effective energy storage mechanisms. Various researchers are planning and designing energy storage systems based on the insights from the data with the support of optimisation algorithms, mathematical models, and Artificial Intelligence (AI) and Machine Learning (ML) technologies. The chapter discusses the various model selection strategies for identifying effective models for energy storage systems.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.</text>
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                <text>Kavya N.S., Centre for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Mishra S.S., Department of Mathematics, School of Computer Science and Artificial Intelligence, SR University, Telangana, Warangal, 506371, India, Department of Mathematics, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, Telangana, 500078, India; Sahoo P.K., Department of Mathematics, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, Telangana, 500078, India</text>
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                <text>The accelerated expansion of the Universe remains a fundamental challenge in cosmology, motivating model-independent methods to reconstruct its expansion history without relying on specific dark energy models. Cosmography, which employs series expansions of cosmological observables around the present epoch, provides a powerful kinematic framework rooted in the cosmological principle. However, standard Taylor expansions suffer from limited convergence at high redshift, prompting the exploration of alternative expansions. In this work, logarithmic polynomial cosmography is investigated, which expands observables in powers of the logarithm of redshift, thereby enhancing convergence over a broad redshift range while maintaining physical insight. The logarithmic polynomial parameters are constrained using recent datasets, including gravitational-wave standard sirens, DESI DR2, cosmic chronometers, and multiple Type Ia supernova compilations (DES-SN5YR, Union3, Pantheon+SH0ES). The analysis demonstrates the efficacy of the logarithmic approach in accurately modeling the cosmic expansion history, providing an interpretable alternative to traditional cosmographic techniques.  2026 Wiley-VCH GmbH.</text>
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                <text>This assessment and treatment of cancer may be done using logistic regression. To properly forecast whether a tumour is malignant or benign, the likelihood of binary outcomes may be simulated based on input variables and taken into account for factors like volume, topology and texture. It aids in risk assessment by estimating an individual's likelihood of developing cancer using factors like age-group, relatives past data, life choices and gene based markers. Logistic regression plays an important role in early cancer detection and creating screening tools that identify high-risk individuals through patent characteristics, biomarkers, and medical imaging data. Prediction of the probability of survival based on age, tumor characteristics, treatment options and comorbidities is useful for survival analysis. In a comparative study, logistic regression achieved a high accuracy of 97.4%, along with random forest, in cancer detection and diagnosis.   2023 IEEE.</text>
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                <text>International Conference for Technological Engineering and its Applications in Sustainable Development, ICTEASD 2023, pp. 262-267.</text>
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                <text>Pattanaik A., KIIT Deemed to Be University, School of Computer Engineering, Odisha, Bhubaneswar, 751024, India; Gour P., KIIT Deemed to Be University, School of Computer Engineering, Odisha, Bhubaneswar, 751024, India; Mishra S., KIIT Deemed to Be University, School of Computer Engineering, Odisha, Bhubaneswar, 751024, India; Sharma V., CHRIST (Deemed to Be University), Computer Science Department, Delhi NCR, India; Alabdeli H., The Islamic University, College of Technical Engineering, Najaf, Iraq</text>
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                <text>Modeling and analysis of the bioconvective flow of nanofluid over a stretching sheet with ThompsonTroian slip condition</text>
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                <text>Journal of Thermal Analysis and Calorimetry;Volume;150;Issue;26;pp.21763-21778</text>
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                <text>Kamath A.V., Centre for Mathematical Needs, Department of Mathematics, CHRIST University, Karnataka, Bengaluru, 560029, India; Puneeth V., Centre for Mathematical Needs, Department of Mathematics, CHRIST University, Karnataka, Bengaluru, 560029, India; Nisar K.S., Department of Mathematics, College of Science and Humanities, Al Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan</text>
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                <text>In the present study, the flow, heat, and mass transfer characteristics of a bioconvective nanofluid over a stretching plate subjected to an external magnetic field are analyzed. The nonlinear slip at the surface is modeled using the ThompsonTroian velocity slip condition, while convective boundary conditions are applied to account for heat and mass transfer in the thermal and concentration fields. To ensure uniform nanoparticle distribution, motile microorganisms are incorporated into the fluid. These microorganisms help counteract particle aggregation and prevent solidification within the medium. Their motion gives rise to the bioconvection phenomenon, enhancing overall fluid transport. The governing equations for momentum, energy, and species concentration are formulated as partial differential equations (PDEs), incorporating key effects such as viscous dissipation, magnetic field influence, and heat sources. Using similarity transformations, the PDEs are reduced to a system of ordinary differential equations (ODEs). This system is then numerically solved via Python solve_bvp function, which employs a collocation method for boundary value problems. The computed solutions are validated against existing literature, and residual analysis is conducted to ensure accuracy. The results reveal that an increase in magnetic field strength suppresses fluid velocity while simultaneously raising the nanofluid temperature. Additionally, higher critical shear stress associated with the ThompsonTroian slip model further reduces the flow velocity near the surface.  Akadiai KiadZrt 2025.</text>
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                <text>Modeling and computational fluid dynamic analysis on a non-AC bus coach system</text>
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                <text>CFD analysis; drag force; Hypermesh; non-AC bus coach; solidworks</text>
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                <text>The main objective of this paper is to reduce the drag force and enhance the uniform airflow inside an existing non-air-conditioning bus coach system. The redesigning of an existing bus carried out by considering the forces that reduce the moment of the bus. Modeling and meshing was carried out using solid works and Hypermesh software, respectively. Finally, the problem is simulated using Ansys fluent software and analysis is carried out for different bus models. The noteworthy findings state that the air resistance of the vehicle is found to be 812.74 N and coefficient of drag is 0.67 are less as compared to existing bus model.  2020 Wiley Periodicals LLC</text>
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                <text>Shravanabelagola Jinachandra N.; Sadashivappa Kubsad S.; Sarpabhushana M.; Siddaramaiah S.; Rajashekaraiah T.</text>
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                <text>Heat Transfer, Vol-49, No. 8, pp. 4870-4877.</text>
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                <text>Shravanabelagola Jinachandra N., Department of Mechanical Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, Karnataka, India, Department of Mechanical Engineering, Atria Institute of Technology, Bengaluru, Karnataka, India; Sadashivappa Kubsad S., Department of Mechanical Engineering, Atria Institute of Technology, Bengaluru, Karnataka, India; Sarpabhushana M., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Siddaramaiah S., Department of Mechanical Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Rajashekaraiah T., Department of Mechanical Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, Karnataka, India</text>
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                <text>Modeling Consumer Price Index: A Machine Learning Approach</text>
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                <text>The change in price of a group of goods and services is reflected in terms of consumer price index (CPI), making it one of the most important economic indicators. This is also the mostly used measure of inflation. Forecasted CPI values help the Government to take corrective measures to control the economic conditions of the country. This paper implements and examines two machine learning models such as artificial neural network (ANN) and ANN model optimized with particle swarm optimization (PSO) known as ANN-PSO to assess the accuracy in predictability of CPI. The data set for four groups such as food and beverages, housing, clothing, and footwear used for the calculation of all India CPI has been taken from the official website of the Government of India. The mean absolute percentage error (MAPE) has been used as the validator for model accuracy. The MAPE calculated for all experiments are less than 10% which indicates that the ANN-PSO models used are highly accurate for prediction of CPI of India.  2022 Wiley-VCH GmbH</text>
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                <text>Sarangi P.K.; Sahoo A.K.; Sinha S.</text>
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                <text>Sarangi P.K., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, 140401, India; Sahoo A.K., Graphic Era Hill University, Dehradun, 248002, India; Sinha S., Christ (Deemed to be University), Delhi, 201003, India</text>
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                <text>Modeling destination competitiveness: The unfamiliar shift for destination rebranding, restructuring, and repositioning with DMOs</text>
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                <text>Tourism is a tactical economic practice across the globe, but the urban and provincial transformations in the industry are strongly contemplated in the light of an unfamiliar shift in tourism business. This chapter discusses an integrated concept with a framework relating systematic approach of managing the destination and its competitiveness. An investigation on the impact on tourism and the recent narrative of national, regional, and local planning approach directs towards efficient destination management organizations (DMO) in practice for future development. This has proceeded by the formation of a competitive approach, emphasizing on the DMO roles and responsibilities helpful for a destination management during an unfamiliar business trend. Modeling destination competitiveness demands an absolute mechanism through destination rebranding, restructuring, and repositioning with DMOs for enabling competency.  2018, IGI Global.</text>
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                <text>Varghese B.; Aboobacker S.</text>
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                <text>Strategies for Promoting Sustainable Hospitality and Tourism Services, pp. 171-190.</text>
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                <text>Varghese B., Christ University, India; Aboobacker S., Christ University, India</text>
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                <text>Modeling Environmentally Conscious Purchase Behavior: Examining the Role of Ethical Obligation and Green Self-Identity</text>
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              <elementText elementTextId="96409">
                <text>environment-friendly products; ethical obligation; green products; green purchase behavior; green self-identity; theory of planned behavior</text>
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                <text>Due to environmental degradation, using environment-friendly products has become necessary to reduce carbon emissions. However, the consumption of such products is still below expectations because these products are usually costlier than their traditional counterparts. The current study aims to investigate consumer behavior towards environment-friendly products using Ajzens theory of planned behavior as a theoretical model. The study seeks to examine the role of the key determinates of environmentally conscious purchase behavior, such as ethical obligation and green self-identity. A total of 386 responses were collected from consumers living in a few major cities of northern India using purposive sampling. The data were analyzed using structural equation modeling in Amos 22.0. The results demonstrated that attitudes towards environment-friendly products perceived behavioral control and green self-identity as the major determinants of green purchase intentions. In addition, attitude was reported to mediate the effect of ethical obligation on green purchase intentions and green self-identity was found to moderate the effect of attitude on green purchase intentions. Additionally, green self-identity was also reported to moderate the relationship between ethical obligation and attitude. The study adds value to the existing literature by signifying the role of green self-identity and ethical obligation in stimulating consumers green purchase intentions. The findings of the study are also meaningful for marketers and policymakers.  2023 by the authors.</text>
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                <text>Kumar R.; Kumar K.; Singh R.; SJ.C.; Carvalho S.; Santos G.</text>
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                <text>Sustainability (Switzerland), Vol-15, No. 8</text>
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                <text>&lt;a href="https://doi.org/10.3390/su15086426" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.3390/su15086426&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156179635&amp;amp;doi=10.3390%2Fsu15086426&amp;amp;partnerID=40&amp;amp;md5=3aafb4801cdc41034f735a4b9a9b4d4e" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156179635&amp;amp;doi=10.3390%2fsu15086426&amp;amp;partnerID=40&amp;amp;md5=3aafb4801cdc41034f735a4b9a9b4d4e&lt;/a&gt;</text>
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              <elementText elementTextId="96416">
                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>ISSN: 20711050</text>
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                <text>Kumar R., School of Management Studies, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, 211004, India; Kumar K., School of Business and Management, Christ (Deemed to be University), NCR Campus, Ghaziabad, 201003, India; Singh R., Institute of Business Management, GLA University, Mathura, 281406, India; SJ.C., School of Engineering (ISEP), Polytechnic of Porto, Rua Dr. Antio Bernardino de Almeida 431, Porto, 4200-072, Portugal; Carvalho S., Technological School, 2AiApplied Artificial Intelligence Laboratory Polytechnic Institute of Cavado and Ave, Barcelos, 4750-810, Portugal; Santos G., Design School, Polytechnic Institute Cavado Ave, Campus do IPCA, Barcelos, 4750-810, Portugal</text>
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                <text>Orupalli, Surendra; Sayama, Hiroki</text>
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                <text>Modeling Flood-Induced Cascading Disruptions in the Indian Electronics Supply Chain Using Influence Network Analysis</text>
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                <text>Northeast Journal of Complex Systems;Volume;8;Issue;1;Article No.;11;</text>
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                <text>&lt;a href="https://doi.org/10.63562/2577-8439.1164" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.63562/2577-8439.1164&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105038288557?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105038288557?origin=resultslist&lt;/a&gt;</text>
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                <text>Orupalli S., School of Systems Science and Industrial Engineering, Binghamton University, NY, United States; Sayama H., School of Systems Science and Industrial Engineering, Binghamton University, NY, United States, Waseda Innovation Lab, Waseda University, Japan, School of Sciences, Christ University, Lavasa, Pune, India</text>
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                <text>This study investigates flood induced disruptions in the Indian electronics supply chain using influence network analysis. Monsoon floods are recurring hazards that significantly impact economic activities, logistics, and industrial productivity. This study integrates district-level rainfall data (2020 to 2025) with supply chain network models to quantify cascading failures. The methodology applies rainfall thresholds (? 300 mm/month) to identify flood-prone districts and constructs a stochastic influence matrix representing inter-firm dependencies. Flood propagation dynamics are modeled iteratively with a propagation coefficient (? = 0.6) and convergence threshold (? = 10-4). The resulting disruption profiles are mapped onto company-level revenues calibrated to India-specific scales, adjusted for disruption durations (two months per year). This approach produces district and company-level economic loss estimates consistent with observed flood impacts (e.g., Chennai 2015 flood losses of USD 3 to 5 billion). Key contributions include linking meteorological hazards to systemic supply chain failures, demonstrating economic vulnerabilities at district and sectoral scales, and providing a framework for resilience planning.  2026 Binghamton University Libraries. All rights reserved.</text>
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                <text>Thomas A., Department of Statistics &amp;amp; Data Science, CHRIST(Deemed to be University), Bengaluru, India; John N., Department of Statistics &amp;amp; Data Science, CHRIST(Deemed to be University), Bengaluru, India</text>
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                <text>Measurement error in time series refers to inaccuracies or deviations in recorded data that can distort the true underlying patterns, potentially leading to biased estimates and misleading conclusions in statistical analysis. AR models with non-Gaussian errors are crucial for accurately capturing real-world time series data with skewness, heavy tails, or outliers, leading to better forecasts and more reliable statistical inferences. Our focus in this study is on an optimal estimating function (EF) method that accounts for measurement error while estimating the parameters of AR(1) with logistic innovation. The asymptotic properties of the obtained optimal EF are also proved. The simulation study shows that incorporating measurement error into the model yields better estimates compared to ignoring its presence when measurement error exists. This shows that ignoring the measurement error leads to biased estimates.  2026 Taylor &amp;amp; Francis Group, LLC.</text>
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