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Tracking the transmission channels of fiscal deficit and food inflation linkages: A structural var approach
This empirical analysis aspired to unearth the transmission channels of fiscal deficit and food inflation linkages in the Indian perspective by reasonably exerting the data for 1991 to 2017. The precise results of structural vector autoregressive (SVAR) analysis proffered that there were three different mechanisms of transmission such as consumption, general inflation, and import channels that led to food inflation in response to the high fiscal deficit. The first channel revealed that government deficit spending had a positive impact on income which further led to food inflation through surging the household consumption expenditure. It was concluded that fiscal deficit passed through general inflation finally leading to a food price surge in the economy and seemed to work as cost-push inflation for the food and agricultural industry. The outcome also revealed that the impact of fiscal deficit passed to food inflation through external linkages such as import and export. 2020 The Society of Economics and Development, except certain content provided by third parties. -
Tracking Sigmoid Regression with Multicollinearity in Phase I: An Approach Incorporating Control Charts
Regression and quality control are two crucial techniques that data analysis employs in improving the decision-making process. We use the sigmoid function to model the connection between independent factors and the dependent variable in sigmoid regression. When there is a significant correlation among the independent variables in a regression model, multicollinearity a statistical phenomenon exists. Multicollinearity presents problems with higher uncertainty when estimating individual coefficients possibly making it harder to identify each variable's distinct contribution to the model. By suggesting a control chart specifically designed for the sigmoid regression model, this research presents a strategy to address the impact of influential observations using regression control charts, by making use of principal component regression class estimators. Principal component regression merges from the principal component analysis and linear regression methodologies, aiming to alleviate multicollinearity issues and enhances the stability of regression models. The performance of the model is evaluated using Pearson's residuals, Deviance residuals, and residuals. This strategy is proven to be useful in real world situations demonstrated through an application in the field of sleep wellness disorder. In conclusion, this study introduces a unique control chart to manage multicollinearity in sigmoid regression, providing a new perspective on the topic to spot differences in the underlying process by highlighting trends in the residuals. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Tracking Greenfield FDI During the COVID-19 Pandemic: Analysis by Sectors
We study the trends and fluctuations in greenfield foreign direct investment (GFDI) during the first wave of the COVID-19 pandemic crisis on a global scale. We analyse the data of a data set of GFDI provided by fDi Markets (Financial Times) to understand the contraction of GFDI during the first three quarters of the year 2020, taking into account the sector of the investment and the host and home country. We analyse both the long-run trends and the quarter-over-quarter changes in GFDI to capture its fluctuations before and during the first wave of the COVID-19 crisis and the 2008 global financial crisis. Our findings cast light on which countries and industries GFDIs were most affected by the pandemic crisis and draw a comparison to the global financial crisis. To our surprise, many services industries have shown unexpected resilience of GFDI due to the flexibility for remote work. On the contrary, GFDI in the manufacturing industries, as well as the extractives and the utility industries, has shown a dramatic decline during the pandemic. These contractions raise questions of stability and resilience of the global supply chains these industries are a part of. JEL Codes: F21. 2021 Indian Institute of Foreign Trade. -
Tracking and Localization of Devices - An IoT Review
S everal IoT applications have immediate impacts on daily lives. The notion of "connected life, which includes IoT has been discussed. Apps that rely on localization are also featured. IoT is originally used to determine the precise position of things, animals, and people. The second tracks everyone and everything that's on the move, including pets, kids, and the elderly people. Localization and tracking are integral parts of security and surveillance systems in interconnected homes. This study reviews the state-of-the-art IoT-based localization and tracking approaches and outlines the key technical aspects, and contrast localization initiatives based on Internet of Things (IoT) with those that do not show how they might be used in a variety of contexts. It is now well established that localization and tracking methods based on the Internet of Things (IoT) are more pervasive and accurate than their predecessors. 2023 IEEE. -
Tracing the outer disk of NGC300: An ultraviolet view
We present an ultra-violet (UV) study of the galaxy NGC300 using GALEX far-UV (FUV) and near-UV (NUV) observations. We studied the nature of UV emission in the galaxy and correlated it with optical, HI and mid-infrared (3.6 ?m) wavelengths. Our study identified extended features in the outer disk, with the UV disk extending up to a radius of 12 kpc (> 2 R25). We estimated the FUV and NUV disk scale-length as 3.05 0.27 kpc and 2.66 0.20 kpc respectively. The scale-length in FUV is 2.3 times larger than that at 3.6 ?m, and we also find the disk to gradually become flatter from longer to shorter wavelengths. We performed a statistical source subtraction to eliminate the background contaminants and identified 261 unresolved UV sources between the radii 5.3 kpc and 10 kpc (1 ? 2 R25). The identified UV sources show an age range between 1300 Myr with a peak at 25 Myr and a mass range between 10 3M? to 10 6M?, estimated using Starburst99 models. The north-eastern spiral arm is found to be populated by young low mass sources suggesting that the star formation in this spiral arm is a recent phenomenon. The UV emission beyond the R25 radius has contribution from these low mass sources and is extended up to ? 2 R25 radius. We conclude that NGC300 has an extended UV disk, mainly populated by young low mass sources. The star formation rate is measured to be ?0.46M?/yr which is comparable to its near optical twin M33. 2019, Indian Academy of Sciences. -
Tracing the impact of social media on social cognition: Bibliometric analysis
The words "misinformation, " "fake news, " and "post-truth" have filled social media posts. It is a serious social threat, especially post COVID-19. In this chapter, the authors provide bibliometric analysis of research on social media and its impact on social cognition. This can be useful for identifying gaps for future research in the field. Publication data was obtained from the Web of Science database using a search algorithm. A total of 22,935 articles were extracted, and 22,909 eligible articles were included for analysis. Document co-citation analysis revealed that themes on social engagement, fake news, problematic social media use, and healthcare emerged as trends on shaping the social cognition through social media. Further, India achieved 9th position on the list based on citations and 8th on centrality and did not appear on any of the top-10 lists based on Burst value and Sigma. This indicates that neither sudden trend-setting articles nor scientific novelty-based articles have been published in this domain thus far. There is a considerable research gap in India to counter misinformation. 2024, IGI Global. -
Tracing narcissism in the digital era - A study on the selfie phenomenon /
With the advent of mobile camera technology, there stepped in a new concept of photography popularly known as ‘selfie’. Selfie eliminated all the trouble and embarrassment of requesting others to click the picture of one’s own self. Selfie’s rise in popularity can be primarily attributed to social media sites and platforms where they are shared, liked and commented the most. Sensing selfie’s phenomenal popularity, it was soon commercialized by marketers, one form of it being the introduction of selfie stick. -
Toy telephone /
Patent Number: 346943-001, Applicant: Ritwika Das Gupta. -
Toxicological Profiling of Onion-Peel-Derived Mesoporous Carbon Nanospheres Using In Vivo Drosophila melanogaster Model
Toxicological profiling of the novel carbon materials has become imperative, owing to their wide applicability and potential health risks on exposure. In the current study, the toxicity of mesoporous carbon nanospheres synthesized from waste onion peel was investigated using the genetic animal model Drosophila melanogaster. The survival assays at different doses of carbon nanoparticles suggested their non-toxic effect for exposure for 25 days. Developmental and behavioral defects were not observed. The biochemical and metabolic parameters, such as total antioxidant capacity (TAC), protein level, triglyceride level, and glucose, were not significantly altered. The neurological toxicity as analyzed using acetylcholinesterase activity was also not altered significantly. Survival, behavior, and biochemical assays suggested that oral feeding of mesoporous carbon nanoparticles for 25 days did not elicit any significant toxicity effect in Drosophila melanogaster. Thus, mesoporous carbon nanoparticles synthesized from waste onion peel can be used as beneficial drug carriers in different disease models. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Toxicity analysis of endocrine disrupting pesticides on non-target organisms: A critical analysis on toxicity mechanisms
Endocrine disrupting compounds are the chemicals which mimics the natural endocrine hormones and bind to the receptors made for the hormones. Upon binding they activate the cascade of reaction which leads to permanent activating of the signalling cycle and ultimately leads to uncontrolled growth. Pesticides are one of the endocrine disrupting chemicals which cause cancer, congenital birth defects, and reproductive defects in non-target organisms. Non-target organisms are keen on exposing to these pesticides. Although several studies have reported about the pesticide toxicity. But a critical analysis of pesticide toxicity and its role as endocrine disruptor is lacking. Therefore, the presented review literature is an endeavour to understand the role of the pesticides as endocrine disruptors. In addition, it discusses about the endocrine disruption, neurological disruption, genotoxicity, and ROS induced pesticide toxicity. Moreover, biochemical mechanisms of pesticide toxicity on non-target organisms have been presented. An insight on the chlorpyrifos toxicity on non-target organisms along with species names have been presented. 2023 Elsevier Inc. -
Toxic waste colonialism : A re-evaluation of global management of transboundary hazardous waste /
Journal On Environment Law Policy And Development, Vol.3, pp.85-119, ISSN: 2348-7046. -
Toxic text classification
The users of the Internet increase every moment with increasing population and accessibility of the Internet. With the increase in the number of users of the Internet, the number of controversies, arguments and abuses of all kinds increases. It becomes necessary for social media and other sites to identify toxic content amongst a large number of content being posted by the users of the sites every second. The traditional algorithms that depend on users reporting toxic content for it to be deleted and necessary actions to be taken against the users posting the content would take a long time, within which it would have gained media attention and would have lead to huge fights over the content. Thus, it becomes important for the content to be evaluated for toxicity at the time it is posted in order to stop it from being posted. Therefore, we have designed and trained a deep learning model that can be read through the textual content given through it and determine if it is toxic or not. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Toxic heavy metal ion detection by fluorescent nanocarbon sensor derived from a medicinal plant
In the twenty-first century, the importance of environmental pollution sensing cannot be overstated. Cadmium is a well-known poisonous heavy metal that seriously endangers human health. In terms of screening for poisons and diagnosing illnesses, the sensitive and focused detection of cadmium in cells is crucial. In this work, we developed Green fluorescent Carbon nanomaterial (Carbon nanomaterial) synthesized from a novel precursor, Justicia Wynaadensis, by the most eco-friendly, cost-effective hydrothermal method, which acts as a fluorescent probe for Cadmium fluorescence sensing technique with the concentration range of 1 nM1 M. The sensor displays remarkable linear detection with a 5.235 nM detection limit. 2022 The Author(s) -
Toxic Effects of Nanoparticles on Fish Embryos
Nanoparticles are used widely in the in-drug delivery, diagnostics, cosmetics, paints, electronics, fabrics, solar cells, medicines etc. Their wide application is due to their special properties which include minute size, high reaction rate, increased surface area and quantum effect. Despite their multiple applications, nanoparticles have harmful effects too due to their improper disposal causing their entry into the aquatic environment greatly threatening the ecological security as well as our health. Zebra fishes (Danio rerio) are used more commonly for the evaluation of toxicity and are considered a promising animal model. Studies on Salmon and Labeo rohita have also been used for toxicity evaluation. Nanoparticles affect the embryo more easily than the adult since the embryo are more sensitive. Hence it becomes important for us to study the effect of the nanoparticles on the embryo of the fishes. These nanoparticles have the ability to cross the chorion layer and affect the developing embryo. Since the fishes are a part of the food chain, when these organisms get affected they will eventually harm the humans too. This review focuses on the effect of metal nanoparticles (NPs) like gold(Au), silver(Ag), copper(Cu), platinum and metal oxides nanoparticles like titanium dioxide, aluminium oxide, copper oxide, nickel oxide zinc oxide on the embryonic development of fish embryos. When compared to the other nanoparticles (NPs) like silver, copper and platinum, it has been observed that the gold nanoparticles (Au NPs) showed no toxicity to embryos of zebrafish though few studies contradict this. Aluminium nanoparticles showed no toxicity and role of reactive oxygen species (ROS) in enhancing the toxicity of nanoparticles have also been discussed. 2021 World Research Association. All rights reserved. -
Towards Visibility: Subaltern Counterpublics in Paul Chirakkarodes Pulayathara
Christianity has always been celebrated as a catalyst towards modernity for the Dalits of Kerala. Though missionary accounts and ethnographic studies confirm the progress of the community, there was rampant casteism and separatism too. This is succinctly revealed in Dalit Christian texts. Pulayathara by Paul Chirakkarode stands as a testimony to the Dalit Christian dilemma and traces the history of the Kuttanadan Pulaya community in the pre- and post-conversion scenarios. Conversions could not change the existing public sphere of Kerala, where upper castes were the dominant party. They (Dalits) continued to be marginalized and subordinated and lacked a class consciousness. The article highlights the limitations in the public sphere that emerged in Kerala as part of the missionary endeavours in accommodating the converted Dalits. The article attempts to trace the emergence of subaltern counterpublics among the Dalit Christians to oppose the continued oppression and casteism by situating Pulayathara at the centre of the analysis. 2022 Indian Institute of Management, Ahmedabad. -
Towards various applications of Big Data and related issues and challenges
A new trend in feature abstraction is Big Data Analysis combined with computational techniques. This includes gathering knowledge from reputable data sources, analyzing information quickly, and forecasting the future. Big data entails vast amounts of data that are challenging to analyze using typical database and software approaches. When using big data applications, a technological hurdle arises when transporting data across several locations, which is quite expensive and necessitates a huge primary memory for storing data for processing. Big data refers to the transaction and interaction of datasets whose size and complexity transcend the usual technical capabilities of acquiring, organizing, and processing data in a cloud environment. This article provides an in depth study of various applications of big data. It also provides a detailed view on various problems and challenges in Big Data. 2021 IEEE. -
Towards sustainable resource management: A short and long-run dynamics of mineral production on ecological footprint
The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the Dynamic Autoregressive Distributed Lag (DYNARDL) simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional Environmental Kuznets Curve, implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, trade openness can exacerbate environmental degradation due to economic priorities often taking precedence over environmental concerns. 2024 Elsevier Ltd -
Towards Sustainable Living through Sentiment Analysis during Covid19
Artificial intelligence is the process of the machine to perform with the simulation of human intelligence. Computing within the field of emotions paves the recognitions to sentiment analysis. Sentiment analysis is the method of capturing the emotions behind a text whether or not it's positive, negative or neutral. Sentiment Analysis (SA) or Opinion Mining (OA) is the process to provide computational treatment to unstructured data to categorize and identify the sentiments or emotions expressed in a piece of text. It combines Natural Language Processing Techniques and Machine Learning Techniques. This technology is additionally referred to as opinion mining or feeling computing. Sentiment Analysis uses the ideas of machine learning alongside an AI based process called NLP to extract and analyse the data, emotions, information from the text. This work explores the impact of social media during covid 19 and possible link between sustainable living and health care with the usage of sentiments. This paper address the sustainable development goal 3 (good health and wellbeing) of SDG 2030 and a possible way towards sustainable living through sentiment analysis. The Electrochemical Society -
Towards sustainable business: Review of sentiment analysis to promote business and well-being
Sustainability in business is expected considering the growth in the long run. Sustainable development goals are important for our sustainability on this planet. In case of a business, it is essential to ensure sustainable processes and sustainability of the existing customers. Sustainable customers can in turn contribute to improving the process by providing constructive suggestions to the business. This paper is an attempt to review sentiment analysis techniques to improve the customer experience of a business. 2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad. -
Towards reading song in performance as aural narrative : Reading a sense of spatiality in select albums of mark knopfler using henri lefebver's notions of space
One of the chief objectives of this study is to explore and offer a strategy to read song in performance as Aural Narratives. This was necessary because verbal texts can be read in multiple ways. Perhaps the chief claim of a text s possibility to be literary lies in its inherent potential to be discursive. Therefore sound texts require a way of understanding sound as an element of storytelling. Shifts in Humanities necessitate an expanding notion of textuality. One of the chief concerns and burdens of the writer of literature is the evocation of a sense of spatiality which can be perceived as an outcome of spatial practice. Spatial practice in turn is defined by social codes and practices. Spaces can be read therefore through the life experiences of the inhabitants of a space as spatial practices are dependent on particular spaces. This study explores the use of Sound in creating a sense of Spatiality. Singer, songwriter and guitarist, Mark Knopfler creates songs that are arranged around a central character s lived experience. Thus the perception and conception of a sense of space that is thus evoked can be negotiated using Henri Lefebvre s triadic notions of newlinespatiality as a reading strategy.