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UVIT view of Centaurus A: A detailed study on positive AGN feedback
Supermassive black holes at the centre of active galactic nuclei (AGNs) produce relativistic jets that can affect the star formation characteristics of the AGN hosts. Observations in the ultraviolet (UV) band can provide an excellent view of the effect of AGN jets on star formation. Here, we present a census of star formation properties in the Northern Star-forming Region (NSR) that spans about 20 kpc of the large radio source Centaurus A hosted by the giant elliptical galaxy NGC 5128. In this region, we identified 352 UV sources associated with Cen A using new observations at an angular resolution of <1.5 arcsec observed with the Ultra-Violet Imaging Telescope (UVIT) onboard AstroSat. These observations were carried out in one far-ultraviolet (FUV; ?mean = 1481 and three near-ultraviolet (NUV; with ?mean of 2196, 2447, and 2792 respectively) bands. The star-forming sources identified in UV tend to lie in the direction of the jet of Cen A, thereby suggesting jet triggering of star formation. Separating the NSR into Outer and Inner regions, we found the stars in the Inner region to have a relatively younger age than the Outer region, suggesting that the two regions may have different star formation histories. We also provide the UVIT source catalogue in the NSR. 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
UVIT observations of the star-forming ring in NGC 7252: Evidence of possible AGN feedback suppressing central star formation
Context. Some post-merger galaxies are known to undergo a starburst phase that quickly depletes the gas reservoir and turns it into a red-sequence galaxy, though the details are still unclear. Aims. Here we explore the pattern of recent star formation in the central region of the post-merger galaxy NGC 7252 using high-resolution ultraviolet (UV) images from the UVIT on ASTROSAT. Methods. The UVIT images with 1.2 and 1.4 arcsec resolution in the FUV and NUV are used to construct a FUV-NUV colour map of the central region. Results. The FUV-NUV pixel colour map for this canonical post-merger galaxy reveals a blue circumnuclear ring of diameter ?10?? (3.2 kpc) with bluer patches located over the ring. Based on a comparison to single stellar population models, we show that the ring is comprised of stellar populations with ages ? 300 Myr, with embedded star-forming clumps of younger age (? 150Myr). Conclusions. The suppressed star formation in the central region, along with the recent finding of a large amount of ionised gas, leads us to speculate that this ring may be connected to past feedback from a central super-massive black hole that has ionised the hydrogen gas in the central ?4?? ?1.3 kpc. ESO 2018. -
UVIT Observations of the Small Magellanic Cloud: Point-source Catalog
Three fields in the outskirts of the Small Magellanic Cloud were observed by the UltraViolet Imaging Telescope (UVIT) on board AstroSat, between 2017 December 31 and 2018 January 1. The observations were carried out on a total of seven filters, three in the far-ultraviolet (FUV; 1300-1800 band and four in the near-ultraviolet (NUV; 2000-3000 band. We carried out photometry of these observations that have a spatial resolution better than 1.?5. We present here the first results of this work, which is a matched catalog of 11,241 sources detected in three FUV and four NUV wavelengths. We make the catalog available online, which would be of use to the astronomical community to address a wide variety of astrophysical problems. We provide an expression to estimate the total count rate in the full point-spread function of UVIT that also incorporates the effect of saturation. 2023. The Author(s). Published by the American Astronomical Society. -
UV-Promoted Metal- and Photocatalyst-Free Direct Conversion of Aromatic Aldehydes to Nitriles
Abstract: An efficient, simple, and catalyst-free UV-induced functional group transformation of aromatic aldehydes to nitriles has been reported. The developed strategy delivers various functionalized aromatic nitriles with high yields and purity. The UV irradiation activates the carbonyl group of aldehydes and leads to the formation of aldoxime intermediate, further resulting in the generation of nitriles. The striking highlights of the reported methodology are simple reaction conditions, good yields, UV-promoted transformation, and catalyst-free synthesis. Due to the above-mentioned advantages, the methodology provides a whip hand toward environmentally friendly chemical synthesis. 2022, Pleiades Publishing, Ltd. -
UV-C and gamma radiation mediated L-DOPA production from in-vitro cultures of Mucuna pruriens (L.) DC
This is the first report on UV-C and gamma rays mediated in-vitro elicitation of L-DOPA from Mucuna pruriens (L.) DC. cell suspension cultures. Gamma and ultraviolet rays are used on plants to induce mutations which results in activation of defence cascades and production of secondary metabolites due to this abiotic stress. The in-vitro callus developed from 0.5mg/L picloram was suspended into liquid medium and exposed to different time intervals (0, 15, 30, 45 and 60min) of UV-C radiations. On the other hand, the seeds were directly exposed to different doses (25, 50, 100, 150 and 200Gy) of gamma radiations and these irradiated seeds were grown in-vitro from which callus and cell cultures were established. From all these in-vitro cultures, the anti-Parkinsons drug L-DOPA was quantified using HPLC. 60 and 30-minute exposure of UV-C radiations resulted in highest biomass (193.27g/L FW) and L-DOPA production (5.13mg/g DW) respectively both showing a 1.5-fold increase than the control. In gamma radiation studies, 100Gy (Gy) dose showed the highest (83%) seed germination rate, 150Gy increased the in-vitro root and shoot length, while 100Gy increased the biomass of the cell cultures. Also, 150Gy dose showed a 6.1, 2.6 and 2.4-fold increase in L-DOPA production in the in-vitro roots, in-vitro shoots, and cell suspension culture respectively when compared to the control. UV light exposure of 30min and 150Gy doses of gamma radiation showed a significant increase in L-DOPA production. The Author(s) under exclusive licence to Society for Plant Research 2024. -
Utilizing social psychology to drive financial policy solutions: Addressing female feticide and infanticide
Female feticide and infanticide, are two of the most serious problems confronting Indian society. This issue is largely caused by the identification of female fetuses through technology, which frequently results in the termination of a pregnancy. Despite the governments efforts to curb these practices, progress has been limited. There are facilities in cities for determining the gender of an unborn child. The financial difficulty of raising a girl child is a key element in the preference for male offspring. The aim of this study is to propose innovative financial solutions that the government can implement to address this longstanding and complex issue. By exploring various financial inclusion strategies, this study seeks to identify effective measures that can bring about social change and promote gender equality. 2024 by author(s). -
Utilizing Machine Learning for Sport Data Analytics in Cricket: Score Prediction and Player Categorization
Cricket is a popular sport with complex gameplay and numerous variables that contribute to team performance. In recent years, sports analytics has gained significant attention, aiming to extract valuable insights from large volumes of cricket data. Cricket has many fans in India. With a strong fan following, many try to use their cricket intuition to predict the outcome of a match. A set of rules and a points system govern the game. The venue and the performance of each player greatly affect the outcome of the match. The game is difficult to predict accurately as the various components are closely related. The CRR (Current Run Rate) approach is used to predict the final score of the first innings of a cricket match. Total points are calculated by multiplying the average number of runs scored in each over by the total number of overs. For ODI cricket, these methods are useless as the game can change very quickly regardless of the current run rate. The game may be decided by 1 or 2 overs. For more accurate score predictions, a system is needed that can more accurately predict the outcome of an inning. This research paper explores the application of machine learning techniques to predict scores and classify players based on their roles in the squad. The study utilizes a comprehensive dataset comprising various attributes of cricket matches, including player statistics, match conditions, and historical performance. Linear Regression, Logistic Regression, Naive Bayes, Support Vector Machines (SVM), Decision Tree, and Random Forest regression models are employed to predict scores. Additionally, player categorization is performed using a classification approach. The results demonstrate the effectiveness of machine learning techniques in enhancing performance analysis and decision-making in the game of cricket. 2023 IEEE. -
Utilizing Machine Learning for Advanced Natural Language Processing and Sentiment Analysis in Social Media Platforms
Social media is increasingly regarded as one of the most abundant online resources for information gathering and knowledge exchange. Among the most widely used social media sites is Twitter available today. When attempting to comprehend the information in any unknown word-based data (such as social media), natural language processing (NLP) techniques are crucial since they help remove noise from data, identify stem words, etc. It also helps with comprehension of the sentiment or semantic contents. Using social media, we apply machine learning techniques (clustering and classification) to determine the viewpoint's polarity in the information. Several classifiers and clusters, including SVM, RF, Naive Byes, and KNN, are used to detect content on social media. Sentiment analysis is the process of automatically classifying user-generated content as neutral, negative, or positive. It is possible to utilize the text, sentence, feature, or aspect as criteria to group feelings into distinct categories. This study demonstrates the application of machine learning techniques to the analysis of emotions expressed on the Twitter network. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Utilizing Deep Learning Techniques for Lung Cancer Detection
Deep learning can extract meaningful insights from complex biomedical statistics, which includes Radiographs and virtual tomosynthesis. Traits in contemporary deep studying architectures have enabled faster and more correct mastering of the functions gifted in clinical imagery, main to better accuracy and precision in medical analysis and imaging. Deep studying strategies may be used to pick out patterns within the pics which may be indicative of illnesses like lung cancer. Those ailment patterns, which include small lung nodules, can be used for early detection and prognosis of the sickness. Recent studies have employed deep learning strategies consisting of Convolutional Neural Networks (CNNs) and switch learning to come across most lung cancers in CT pictures. The first step in this manner is to generate datasets of pictures of the lungs, each from wholesome people and those with most lung cancers. Those datasets can then be used to teach a deep knowledge of a set of rules that may be optimized to it should locate those styles. Once educated, the version can be used to come across styles indicative of lung most cancers from new take a look at images with high accuracy. For further accuracy and reliability, extra up-processing techniques, along with segmentation and records augmentation, may be used. Segmentation can be used to detect a couple of lung nodules in a photo, and records augmentation can be used to lessen fake high quality outcomes. 2024 IEEE. -
Utilizing Artificial Intelligence-Powered Chatbots for Enhanced Customer Support in Online Retail
In many e-commerce contexts, live chat interfaces have become popular as a way to communicate with consumers and provide real-time customer support. Conversational software agents, commonly known as Chatbots, are systems created to converse with users in natural language and are often based on artificial intelligence (AI). These systems have replaced human chat service agents in many cases. Although AI -based Chatbots have been widely used due to their time and cost savings, they have not yet met consumer expectations, which may make users less likely to comply with chatbot requests. We empirically study, through a randomized online experiment, the impact of verbal humanoid design cues and a direct approach on compliance with user requirements, based on Social Reactions and Attachment Commitment Theory. Our results show that consumers are more likely to cooperate with chatbot service response requests when there is humanity and consistency. Furthermore, the results demonstrate that social presence plays a mediating role between humanoid design cues and user compliance. 2024 IEEE. -
Utilization of Iron Ore Tailings for the Production of Fly Ash - GGBS-Based Geopolymer Bricks
In India, million tons of manufacturing ravages such as ground-granulated blast furnace slag (GGBS), fly ash and mine tailings, are endangering. These ravages turn out to be injurious as they are landfilled close to the production sites and somewhere else. Since these manufacturing ravages include silica, alumina, calcium, etc., it is probable to formulate these as unprocessed resources to produce building substance which diminishes the carbon trace. In this circumstance, this analysis observes on utilizing iron ore tailings and slag sand as a substitution for clay or natural sand for the construction of steady geopolymer obstruct. Furthermore, in this analysis, geopolymer is utilized as a binder rather than cement. Expansion of geopolymer binder-oriented bricks with fly ash and GGBS has been implemented in this study. The analysis consists of automatic possessions of the geopolymer bricks. Sodium silicate (Na2SiO3) and sodium hydroxide (NaOH) resolution have been employed as alkaline activators. The proportion of alkaline liquid to aluminosilicate solid quotient and fraction of binder encompass foremost control on the force of brick. The bricks were casted and cured at ambient warmth. The compressive strength was tested at 7, 14 and 28 days. 2017 World Scientific Publishing Company. -
Utilization of IoT-Based Healthcare System and Vital Data Monitoring of patients
The next generation of technology, known as the Internet of Things (IoT), will provide a comprehensive system that connects different domains, functions, and innovations. With the increasing demand for elderly care due to the growing ageing population, health monitoring systems have become increasingly important. Continuous monitoring is required in ICU to monitor the health conditions of patients. In cases where patients are released from the hospital, they are advised to rest and observed for a certain period, and the IoT system is very helpful in such cases. This article primarily discusses the implementation of a precise autonomous medical facility management system using IoT. In the past, only current data was displayed, and the patients history could not be accessed. In this study, we propose an IoT-based healthcare system for continuous monitoring of a patients health conditions. The healthcare system focuses on measuring and monitoring various biological parameters of the patients body, such as heart rate, blood oxygen saturation level, and temperature, using a web server and an Android application. Doctors can continuously monitor the patients condition on their smart phones using the Android application. Moreover, the patients history will be stored on the web server, and doctors can access the information from anywhere without being physically present. RJPT All right reserved. -
Utilization of industrial and agricultural waste materials for the development of geopolymer concrete- A review
Concrete is a highly consumed construction material. Cement is the first and foremost ingredient in the manufacture of concrete. Manufacturing of cement results in emission of an equal amount of carbon dioxide. These greenhouse gases cause global warming. The utilization of environment-friendly construction materials has been identified to be most essential to overcome environmental issues. An ecofriendly concrete such as geopolymer concrete founds to be an alternative for cement concrete. Geopolymer concrete (GPC) is a sustainable construction material as it can reduce carbon dioxide emission by utilizing industrial and agricultural waste by-products. Hence in this context, to reduce global warming, usage of cement can be minimized by replacing it with other materials such as Fly ash, Silica fume, Red mud, Ground granulated blast furnace slag, Metakaolin, Rice husk ash, Corncob ash, Sugarcane bagasse ash etc. These materials have been utilized to prepare geopolymer concrete with good mechanical strength, durability and thermal resistivity. A lot of research has gone into the development of sustainable geopolymer concrete utilizing various industrial and agricultural waste. This review paper is on the research on the utilization of industrial and agricultural waste materials to produce sustainable geopolymer concrete. 2022 -
Utilization of CO2 for Electrocarboxylation of Benzophenone Using MXene-Based Electrodes: A Sustainable Approach
The significant rise in atmospheric carbon dioxide (CO2) levels has prompted the need to develop efficient methods for CO2 conversion and fixation methods. Electrocarboxylation reaction is a highly efficient and sustainable method for activating and utilizing CO2, yielding essential carboxylic acids and their analogues, which are important intermediates in the pharmaceutical and fuel industries. This research demonstrates the efficiency of 2D Ti3C2Tx and Ta2CTx MXene-modified carbon fiber paper electrodes (Ti3C2Tx/CFP and Ta2CTx/CFP) for CO2 fixation with benzophenone in a tetrabutylammonium bromide/acetonitrile (TBABr/CH3CN) medium, yielding benzilic acid. Ti3C2Tx/CFP exhibited superior electrocatalytic activity with a lower reduction potential for benzophenone at ?1.0 V and achieved a 72% yield of benzilic acid at an optimum current density of 50 mA cm-2. In comparison, Ta2CTx/CFP exhibited a cathodic peak at ?1.08 V, producing a 66% yield at 70 mA cm-2. The electron paramagnetic resonance spectrum substantiates the generation of reactive radical intermediates during the reaction. Ti3C2Tx/CFP showed robust structural stability with ?88% Faradaic efficiency and a turnover frequency of 1.90444 10-5 s-1, indicating its potential for CO2 fixation. 2024 American Chemical Society. -
Utilization of aluminum dross: Refractories from industrial waste
Aluminum oxide (Al2O3) and Magnesium-Aluminum oxides (MgAl2O4) are well known refractory materials used in engineering industries. They are built to withstand high temperatures and possess low thermal conductivities for greater energy efficiency. Dross, a product/byproduct of slag generated in aluminum metal production process is normally comprised of these two oxides in addition to aluminum nitride (AlN). Worldwide, thousands of tons of aluminum dross are generated as industrial wastes and are disposed of in landfills causing serious environmental hazard. This paper explores the potential to synergize the characteristics of the favourable contents of aluminum dross and its availability (in tons) via synthesis of refractories and thereby develop a value added product useful for the modern industries. In this work, Al-dross as-received from an aluminum industry which comprised of predominantly Al2O3, MgAl2O4 and AlN, was used to develop the refractories. AlN possesses high thermal conductivity values and therefore was leached out of the dross to protect the performance of the developed refractory. The washed dross was calcined at 700 and 1000C to facilitate gradual elimination of the undesired phases and finally sintered at 1500C. The dross refractory pellets were subjected to thermo-physical and structural properties analysis: XRD (structural phase), SEM (Microstructure), EDS (chemical constituents) and thermal shock cycling test by dipping in molten aluminum and exposing to ambient (laboratory). The findings include the favourable prospects of using aluminum dross as refractories in metal casting industries. Published under licence by IOP Publishing Ltd. -
Utilisation of Virtual Assistant and Its Impact on Retail Industry
Virtual assistant is nothing but an independent contractor, who offers administrative services to the clients of a particular organisation while operating outside of the office of the client. Generally, a virtual assistant operates from a home-based office. This virtual assistant application has the ability to access the required planning documents, such as shared calendars. The contemporary retail organisations like e-commerce companies in this competitive global business environment are using virtual assistant to enhance omnichannel experience, 24/7 customer service, order tracking, and product recommendations. Overall, virtual assistant helps the organisations in enhancing social media management activities. This concept of the use of virtual assistant has been significantly emerged after the increase in demands for e-commerce business activities in this decade. Research objectives related to the title of this research are developed and listed. Relevant theories on virtual assistant are applied in the literature review section of this study. The researcher has decided to adopt qualitative research methodology to achieve the objectives of the research. Moreover, the researcher has considered secondary data analysis approach to conduct this research. In terms of findings, it has been identified that virtual assistant has a positive impact on the business operation activities of retail organisations. Authentic secondary sources are considered to collect and analyse the data. Some challenges associated with the utilisation of virtual assistant also have been identified in the findings section. Some valuable recommendations are suggested for the future researchers to overcome those identified associated challenges. 2022 IEEE. -
Using Time series analysis, analyze the impact of the wholesale price index on the price escalation in the automotive industry
The automobile industry is a crucial sector of the economy, contributing significantly to employment and economic growth. One of the major challenges faced by this industry is the problem of price escalation, which can affect both consumers and manufacturers. In this project, we explore the impact of wholesale price index (WPI) on the price escalation of automobiles using time series analysis. We analyze the historical data of WPI and automobile prices in India from 2010 to 2022. We use statistical techniques like stationarity tests, autocorrelation analysis, and Granger causality tests to understand the relationship between WPI and automobile prices. Furthermore, we employ a SARIMA model in predicting WPI value and Vector Auto regression (VAR) model to analyze the dynamic interactions between WPI and CPI value. Our findings suggest that WPI has a significant impact on the price escalation of automobiles in India. The VAR model shows that there is a positive feedback loop between WPI, CPI and automobile prices, implying that an increase in WPI leads to a corresponding increase in automobile prices and vice versa. This feedback loop can create an inflationary spiral in the automobile industry, which can be detrimental to the economy. Our project highlights the importance of monitoring WPI and its impact on the automobile industry. Policymakers and industry experts can use our findings to develop effective strategies to manage price escalation in the automobile industry and mitigate its negative impact on the economy. 2023 ACM. -
Using service learning to fuel multi-disciplinary research in Indian HEIs: A novel approach
The current work proposes a novel approach that can allow Indian HEIs to offer service-learning-based curricula while enhancing the institutional research output. The proposed model suggests a unique linkage between existing volunteer and academic departments at institutions of higher education such that data already being generated through existing outreach programs can be utilised for meaningful social science research. The proposed model thus utilizes existing resources already available with an institution to bolster research output, enhances the institutional capacity to include a pedagogical approach with proven benefits, and facilitates institutional compliance with regulatory directives mandating the inclusion of Service-learning-based courses at UG and PG levels. 2024, IGI Global. All rights reserved. -
Using Sentiment Analysis to Identify Consumers Emotions in the Hotel Industry
This research attempted to present a more comprehensive overview of online user-generated data by extending far beyond quantitative analysis. We gathered a distinctive and substantial database of online user ratings for the hotel industry from numerous websites over a significant amount of time. To gauge the quality of hotel service, we divided customer reviews into two categories using the sentiment analysis technique. The impact of those factors in influencing users overall evaluation and content creation behavior is then investigated. The findings imply that different aspects of user evaluations have considerably diverse effects on how users evaluate products and what motivates them to create content. 2025 by Apple Academic Press, Inc. -
Using machine learning in an industrial control network to improve cybersecurity operations /
Patent Number: 202241052879, Applicant: Abhijit Das. A machine-learning service, which receives data related to a plurality of features related to internet traffic metrics, processes said data by performing operations selected from among an operation of ranking at least one feature, an operation of classifying at least one feature, an operation of predicting at least one feature, and an operation of clustering at least one feature, and as a result, the method monitors online security threats.