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Predicting the financial behavior of Indian salaried-class individuals
COVID-19 has caused not only unprecedented health crises but also economic crises among individuals across the world. White-collar (salaried-class) employees with a fixed salary face financial insecurity due to job loss, pay cuts and uncertainty in retaining a job. This study examines the financial behavior of Indian white-collar salariedclass investors to their cognitive biases. In addition, the mediating effect of financial self-efficacy on cognitive biases and financial behavior is examined. Respondents were given structured questionnaires (google forms) through emails and WhatsApp for data collection. SPSS and R-PLS are used to analyze the data. Conservatism (r = -.603, p < 0.05) and herding bias (r = -.703, p < 0.05) have a significant negative correlation with financial behavior. Financial self-efficacy has a significant positive correlation (r =.621. p < 0.050). Conservatism and herding predicted 60.5% and 62.2% of the variance, respectively. The direct and indirect paths between conservatism bias, financial self-efficacy, and financial behavior are significant. The paths between herding, financial self-efficacy and financial behavior are also significant. Ankita Mulasi, Jain Mathew, Kavitha Desai, 2022. -
Exploring White Knight Syndrome in an Indian Setting: A Grounded Theory Approach
White knights are individuals who enter into romantic relationships with damaged and vulnerable partners, hoping that love will transform their partners behaviour or life. Existing literature on white knight is limited to a handful of studies, primarily based on Western population. The present research aimed at developing a substantive theory on white knight syndrome in an Indian setting. The study follows a qualitative paradigm and the research design is grounded theory approach to be specific. Participants for the study were screened using Lamias white knight checklist. Data has been collected from eighteen young adults aged 1825years through semi-structured interviews. The data was analyzed using Strauss and Corbin grounded theory analysis. The study identified six phasespre-relationship phase, needs exploration phase, shining white knight phase, drained white knight phase, golden realization phase, and finally delayed breakup. Along with the phases, the study identified factors, characteristics, and types of white knight. The study has implications in the clinical and counselling field in identifying and understanding white knight tendencies. Additionally, the theory is applicable in the Indian setting highlighting the intricate interaction between culture, norms, roles, and the recent social factors. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
High-affinity binding of celastrol to monomeric ?-synuclein mitigates invitro aggregation
?-Synuclein (?Syn) aggregation is associated with Parkinsons disease (PD). The region ?Syn36-42 acts as the nucleation 'master controller and ?Syn1-12 as a secondary nucleation site. They drive monomeric ?Syn to aggregation. Small molecules targeting these motifs are promising for disease-modifying therapy. Using computational techniques, we screened thirty phytochemicals for ?Syn binding. The top three compounds were experimentally validated for their binding affinity. Amongst them, celastrol showed high binding affinity. NMR analysis confirmed stable ?Syn-celastrol interactions involving several residues in the N-terminus and NAC regions but not in the C-terminal tail. Importantly, celastrol interacted extensively with the key motifs that drive ?Syn aggregation. Thioflavin-T assay indicated that celastrol reduced ?Syn aggregation. Thus, celastrol holds promise as a potent drug candidate for PD. Communicated by Ramaswamy H. Sarma. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Adoption of knowledge-graph best development practices for scalable and optimized manufacturing processes
Using data analytics to properly extracting insights that are in-line to the enterprises strategic goals is crucial for the business sustainability. Developing the most fitting context as a knowledge graph that answer related businesses questions and queries at scale. Data analytics is an integral main part of smart manufacturing for monitoring the production processes and identifying the potentials for automated operations for improved manufacturing performance. This paper reviews and investigates the best development practices to be followed for industrial enterprise knowledge-graph development that support smart manufacturing in the following aspects: Decision for intelligent business processes, data collection from multiple sources, competitive advantage graph ontology, ensuring data quality, improved data analytics, human-friendly interaction, rapid and scalable enterprise's architectures. Successful digital-transformation adoption for smart manufacturing as an enterprise knowledge-graph development with the capability to be transformed to data fabric supporting scalability of smart manufacturing processes in industrial enterprises. 2023 -
Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest Based FinTech Application for Hyper-automation
Hyper automation is the group of approaches and software companies utilised to automate manual procedures. Financial Technology (FinTech) was processed as a distinctive classification that highly inspects the financial technology sector from a broader group of functions for enterprises with utilise of Information Technology (IT) application. Financial crisis prediction (FCP) is the most essential FinTech technique, defining institutions financial status. This study proposes an Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest (ESAOA-ODCF) based FinTech Application for Hyperautomation. The ESAOA-ODCF technique has achieved exceptional performance with maximum accu y of 98.61%, and F score of 98.59%. Extensive experimental research revealed that the ESAOA-ODCF model beat more modern, cutting-edge approaches in terms of overall performance. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
A study on graph topology
The concept of topology defined on a set can be extended to the field of graph theory by defining the notion of graph topologies on graphs where we consider a collection of subgraphs of a graph G in such a way that this collection satisfies the three conditions stated similarly to that of the three axioms of point-set topology. This paper discusses an introduction and basic concepts to the graph topology. A subgraph of G is said to be open if it is in the graph topology TG. The paper also introduces the concept of the closed graph and the closure of graph topology in graph topological space using the ideas of decomposition-complement and neighborhood-complement. 2023 Azarbaijan Shahid Madani University. -
Winning battles with a joke: a qualitative inquiry of humour in the Indian Army
Humour in military organizations can be antithetical given the rigid hierarchy, high degrees of work formalization, and obedience to hierarchy. This paper explores how humour is initiated, propagated and maintained in the Indian Army. We conducted twelve in-depth interviews with retired army professionals and used Braun and Clarkes (2006) thematic analysis to capture the study's main findings. Three major themes emerged organizational humour, leader humour, and team humour. We found humour is essential in combating stress, increasing social cohesion, facilitating newcomer assimilation, and promoting a positive work environment. We also found evidence of subversive humour used in forms of resistance to challenge the hierarchical structure subtly. We have provided a three-part schema of workplace humour which sheds interesting insights on workplace humour. Our findings will contribute to understanding how military humour helps to maneuver challenges of a stressful work situation 2023,European Journal of Humour Research. All Rights Reserved. -
Corrosion studies on low-cost solid lubricant coated stainless steel specimen
AISI 304 stainless steel is widely used in industries owing to its many desirable qualities like excellent formability, drawability and resistance to corrosion. However, AISI 304 stainless steel corrodes when exposed to halide environment such as chloride and fluoride. This study is primarily focused to assess the anti-corrosion properties of AISI 304 steel when coated with CaF2 solid lubricant. CaF2 solid lubricant was synthesized from the discarded egg-shells by ion exchange method by treating the egg-shell powder with hydrogen fluoride solution. Thermal spray coating method was used to coat the synthesized CaF2 solid lubricant on the AISI 304 stainless steel specimen. Slurry erosion test and electrochemical impedance spectroscopy test were conducted on the coated and uncoated specimen to assess the corrosion resistance. From the experimental results, the corrosion rate of the coated specimen was found to be very effective compared to the uncoated specimen. 2023 Elsevier Ltd. All rights reserved. -
Analysing the market for digital payments in India using the predator-prey model
Technology has revolutionized the way transactions are carried out in economies across the world. India too has witnessed the introduction of numerous modes of electronic payment in the past couple of decades, including e-banking services, National Electronic Fund Transfer (NEFT), Real Time Gross Settlement (RTGS) and most recently the Unified Payments Interface (UPI). While other payment mechanisms have witnessed a gradual and consistent increase in the volume of transactions, UPI has witnessed an exponential increase in usage and is almost on par with pre-existing technologies in the volume of transactions. This study aims to employ a modified Lotka-Volterra (LV) equations (also known as the Predator-Prey Model) to study the competition among different payment mechanisms. The market share of each platform is estimated using the LV equations and combined with the estimates of the total market size obtained using the Auto-Regressive Integrated Moving Average (ARIMA) technique. The result of the model predicts that UPI will eventually overtake the conventional digital payment mechanism in terms of market share as well as volume. Thus, the model indicates a scenario where both payment mechanisms would coexist with UPI being the dominant (or more preferred) mode of payment. 2023 Balikesir University. All rights reserved. -
Roman domination in signed graphs
Let S = (G, ?) be a signed graph. A function f : V ? {0, 1, 2} is a Roman dominating function on S if (i) for each v ? V, f(N[v]) = f(v) + Pu?N(v) ?(uv)f(u) ? 1 and (ii) for each vertex v with f(v) = 0, there exists a vertex u ? N+(v) such that f(u) = 2. In this paper we initiate a study on Roman dominating function on signed graphs. We characterise the signed paths, cycles and stars that admit a Roman dominating function. 2023 Azarbaijan Shahid Madani University. -
Production of Boeravinone-B, total phenolic, flavonoid content and antioxidant activity from callus cultures of Punarnava (BoerhaviadiffusaL.)
Boerhavia diffusa L. (Punarnava) is a medicinal herb, rich in diversified plant secondary metabolites used in curing various health ailments. Boeravinone-B is one of the important phytochemicals reported in Punarnava, possessing various pharmacological activities. It belongs to the family of rotenoids, belonging to the isoflavone group. Production of Boeravinone-B from the Punarnava through conventional propagation is comparatively very low, and alternative interventions are of utmost importance to meet the growing demand. In view of this, the present study aims to develop biotechnological approaches like cell/tissue culture as a substitute strategy for the accumulation of biomass and Boeravinone-B biosynthesis. Callus was established from leaf explants of Boerhavia diffusa L. when cultured on MS semi solid medium fortified with varied concentrations and combinations of auxins and cytokinins. The callus induced on Murashige and Skoog medium (MS medium) supplemented with 5.0 ppm 2,4-Dichlorophenoxyacetic acid (2,4-D) favored the highest production of Boeravinone-B analyzed through High-performance Liquid chromatography (HPLC) and it was found to be 673.95 ?g g-1 Dry weight (DW). The total phenolic and flavonoid content were determined for the callus extracts and the results showed that callus induced on 5.0 ppm 2,4-D medium showed the highest phenolic and flavonoid content, which was 63.48 mg g-1 Gallic acid equivalent (GAE) Dry weight (DW), and 30.22 mg g-1 Quercetin equivalent (QE) DW. Similarly, antioxidant activities (radical scavenging, metal chelating, and reducing power) were performed, and it was found that callus induced on 5.0 ppm 2,4-D showed the highest anti-oxidant potential. Radical scavenging activity was found to be 91.1%, and 74% of metal chelating activity was recorded, and a similar trend was observed with respect to reducing power as well. The results of the present study lay foundation for optimization and subsequent large-scale production of Boeravinone-B from callus/cell suspension cultures. The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/ by/4.0/) -
Sprouting in Seeds Aided by Nitrogen Sourced from Ammonia Fumes Leached from Aluminum Dross
Nitrogen and water are nutrients essential for the sprouting of seeds and healthy growth of plants. The seeds derive nitrogen from ammonia (NH3), found in ammonium hydroxide commonly added as manure to the soil. In a materials synthesis process, NH3 gas was released when Aluminum-dross (Al-dross), a hazardous industrial foundry waste was beneficiated to extract useful materials (metallic Al, oxides of Al and Mg, etc.) from the waste. Chemical tests, SEM with EDS and XRD were used to characterize sieved black Al-dross (starting raw material) before and after the beneficiation process. Al-dross also contained significant quantities of aluminum nitride (AlN). When treated with an aqueous media (plain or carbonated water), the AlN reacted to release NH3 gas fumes. This work explored the potential of using this gas to act as a source of nitrogen to accelerate the sprouting of seeds and plant germination. Vegetable and fruit seeds were sown in the soil that was directly infused with the NH3 released from Al-dross for two hours, followed by several (8 to 12) hours of self-diffusion time for homogeneous distribution of the gas in the soil. Five pairs of soils (untreated regular and NH3 fumes treated soils) were prepared under similar conditions. 5 different vegetable and fruit seedlings were planted in these pairs of soils. The germination patterns and growth of the sprouts with time were observed. The seeds that preferred an alkaline environment for germination (e.g., ridge gourd and watermelon seeds) sprouted early and in good health in the NH3 treated soil. Seeds preferring acidic soils did not germinate well in NH3 fume-infused soils. The experiments confirmed the viability of the novel concept, where the waste ammonia fumes released from Al-dross could be favorably generated and used in a controlled manner to promote sprouting of certain agricultural seedlings. 2023 Elsevier Ltd. All rights reserved. -
COVID 19 fatalities burden in Asian countries: An analysis of pattern and determinants
Covid 19 pandemic has severe implications on health and life of people. Asia being the most populous region has higher fatalities burden. Health infrastructure, stringent preventive measures by the government and public participation through adhering to social distancing have influence to check on fatalities' burden. The level of Social capital as well as voters' participation in a particular country can have influence on containment of COVID cases and fatalities. In this context, the main objectives of this study are to analyse pattern and trend of death burden for 45 Asian countries and impact of stringency measures by government, and voters turnout ratio on death burden. However, for regression analysis only 32 countries are taken into account considering the availability of data for all variables. Multiple linear regression analysis is employed in a cross-sectional framework and Ordinary least square estimation technique with heteroscedastic adjusted standard errors have been used for estimation of coefficients. The results show that southern Asia contributes the highest share of fatality cases in total fatality cases of Asia with 71.43% share. It also has the highest share of confirmed cases in total confirmed cases of Asia with 71.72%. However, when we take the population into account, Western Asia leads in the share of confirmed COVID-19 cases and its associated fatality cases per million populations in Asia as compared to other Asian regions. The factors like health infrastructure and voters turnover ratio are found to be significant and potential in reducing the new deaths per million populations. Though the coefficient of Stringency index has been negative and it did not emerge to be significant in Asian countries. The COVID related fatalities in Asian region are urban centric and urbanization proxy is found to be positive and significant. Diabetes prevalence rate has some heterogeneous result and in the present study its coefficient is not in the hypothesized direction. The Countries should ramp up health infrastructure and necessary preparedness to deal with the subsequent waves and COVID related fatalities. Importance need to be given people's participation and their shared responsibilities in dealing with COVID cases and checking on fatalities. The realisation of social responsibility among the masses can lead to community participation and adhering to the protocols imposed by the government and helps in checking on spread of virus and associated death. 2022 The Author(s) -
Injective edge coloring of product graphs and some complexity results
Three edges e1, e2 and e3 in a graph G are consecutive if they form a cycle of length 3 or a path in this order. A k-injective edge coloring of a graph G is an edge coloring of G, (not necessarily proper), such that if edges e1, e2, e3 are consecutive, then e1 and e3 receive distinct colors. The minimum k for which G has a k-injective edge coloring is called the injective edge chromatic index, denoted by ?? (G) [4]. In this article, the i injective edge chromatic index of the resultant graphs by the operations union, join, Cartesian product and corona product of G and H are determined, where G and H are different classes of graphs. Also for any two arbitrary graphs G and H, bounds for ?? (G+H) andi?? (G? H) are obtained. Moreover the injective edge i coloring problem restricted to (2, 3, r)-triregular graph, (2, 4, r)-triregular graph and (2, r)-biregular graph, r ? 3 are also been demonstrated to be NP-complete. 2023, University of Nis. All rights reserved. -
Polymer-Carbon nanocomposite: Synthesis, optical and biocidal properties
Microorganism contamination of food storage, water treatment, pharmaceuticals, and especially biomedical equipment is a severe problem. Bacteria frequently contaminate permanent implantations after long-term usage. To successfully treat these infections, it is essential to monitor microbial activity and know how it interacts with antibodies in real-time. In this work, a nanocarbon-polymer nanocomposite (ARPD) is successfully developed, and its antibacterial activity against selected microorganisms is successfully validated. Obtained antibacterial results confirm that the photoluminescent ARPD demonstrated outstanding antibacterial action against the microorganism Escherichia coli from the selected group of bacteria. The fluorescent diagnostics and treatments offer exciting possibilities for the luminescence and biocidal activity of nanocomposite produced from ARH-PVDF nanomaterials. 2023 The Author(s) -
Green Bonds: A Propitious Financial Instrument of Climate Finance
Green bonds are a comparatively recent investment mechanism for green initiatives and are perceived as the first line of climate change protection. The aim of the article is to decide if the issuing of a green bond is perceived to be good news for market players, and also to ascertain whether developing markets, relative to established markets, are more inclined towards green bonds to tackle climate change. The study used an international sample of recent green bond issues and illustrated the possible effects of the issuing of a green bond for the issuer. A sample of 392 green bonds released from 2017 to 2020 is included. Event study methodology is used to analyse investor response to green bond issuance. Over the years, emerging markets have been found to be keen on greening projects by green bonds, much in line with established markets. The findings suggest that on the day of issuance of the green bonds the stock market responds adversely and reacts positively after the day. Hence statistical technique is applied on different event windows to obtain the cumulative abnormal returns (CAR). Statistical analysis concludes that the market responds adversely to the issuing of a green bond. This influence is particularly evident in the first issuing of green bonds and in developing markets. This research shows that proposals of green debt transmit unfavourable knowledge about the issuing companies. These results are relevant only in the case of green bonds issued by listed firms. 2023 MDI. -
A pharmacognostic approach, including phytochemical and GC-MS analysis, targeted towards the authentication of Strobilanthes jomyi P. Biju, Josekutty, Rekha & J.R.I.Wood
The genera Strobilanthes Blume have a rich history in therapeutic culture all over the world. Asian countries like India, China, Myanmar and Thailand still use Strobilanthes genus-based medicinal preparations for various diseases. Strobilanthes jomyi is a newly discovered species from Kerala, India. Some tribal communities of Kasaragod district still use S. jomyi leaf extract as a wound healing medication. The current study aims to investigate the pharmacognostic, phytochemical and GC-MS analysis of the leaves, stems and roots of S. jomyi. The microscopic, macroscopic, organoleptic, fluorescent, phytochemicals and GC-MS analysis of the leaves, stem, and root of S. jomyi were estimated using various standard protocols. The macroscopic and microscopic characters of leaves revealed the presence of non-glandular trichomes with paracytic stomata in the leaves. The transverse section of the stem and petiole showed the presence of raphides and the root showed the presence of tannin cells. Cystoliths were observed only in the petiole. Powder morphology of leaves, stems and roots revealed the presence of fibers, trichomes, palisade cells, spiral xylem vessels, bordered pit vessels and raphides. The vegetative part of S. jomyi powder exhibited various fluorescent coloration based on numerous chemical treatments along with different tastes, smells, colors and textures by organoleptic assays. Qualitative phytochemical analysis of different vegetative parts revealed the presence of flavonoids and other phytochemicals. GC-MS study revealed that lupeol a significant bioactive compound was present in all the vegetative parts of S. jomyi. The results acquired from this study can be used for the standardization, identification, quality and purity check of plant samples. The Author(s). -
A Novel Fuzzy-Based Thresholding Approach for Blood Vessel Segmentation from Fundus Image
Retinal vessel segmentation is a vital part of pathological analysis in Fundus imaging. The automatic detection of blood vessels resolves several issues in the manual segmentation process. Most unsupervised segmentation methods depend on conventional thresholding techniques for final vessel extraction. It may lead to the loss of some vessel pixels, leading to inaccurate analysis of retinal diseases. In this work, we incorporate fuzzy concepts into two threshold-based vessel detection methods, namely mean-c thresholding and Iso-Data thresholding, which results in a mask consisting of membership values rather than binary values. The two fuzzy-based thresholding algorithms are applied independently on each image, and the resultant membership image (mask) is fused to get a single membership mask. The fusion is performed using fuzzy union operation. Experiments are carried out with Fundus images from DRIVE, STARE and CHASE_DB1 databases.ses. The proposed fusion framework gives a 3%, 6%, and 5% increase in sensitivity compared to traditional thresholding methods when applied to the DRIVE, STARE, and CHASE_DB1 databases, respectively. The accuracy obtained for the datasets is 96.02%, 94.57%, and 94.34%, respectively. 2023 by the authors. -
Using machine learning architecture to optimize and model the treatment process for saline water level analysis
Water is a vital resource that makes it possible for human life forms to exist. The need for freshwater consumption has significantly increased in recent years. Seawater treatment facilities are less dependable and efficient. Deep learning systems have the potential to increase the efficiency as well as the accuracy of salt particle analysis in saltwater, which will benefit water treatment plant performance. This research proposed a novel method for optimization and modelling of the treatment process for saline water based on water level data analysis using machine learning (ML) techniques. Here, the optimization and modelling are carried out using molecular separation-based reverse osmosis Bayesian optimization. Then the modelled water saline particle analysis has been carried out using back propagation with Kernelized support swarm machine. Experimental analysis is carried out based on water salinity data in terms of accuracy, precision, recall, and specificity, computational cost, and Kappa coefficient. The proposed technique attained an accuracy of 92%, precision of 83%, recall of 78%, specificity of 81%, computational cost of 59%, and Kappa coefficient of 78%. 2023, IWA Publishing. All rights reserved. -
Comparative Performance of LSTM and ARIMA for the Short-Term Prediction of Bitcoin Prices
This research assesses the prediction of Bitcoin prices using the autoregressive integrated moving average (ARIMA) and long-short-term memory (LSTM) models. We forecast the price of Bitcoin for the following day using the static forecast method, with and without re-estimating the forecast model at each step. We take two different training and test samples into consideration for the cross-validation of forecast findings. In the first training sample, ARIMA outperforms LSTM, but in the second training sample, LSTM exceeds ARIMA. Additionally, in the two test-sample forecast periods, LSTM with model re-estimation at each step surpasses ARIMA. Comparing LSTM to ARIMA, the forecasts were much closer to the actual historical prices. As opposed to ARIMA, which could only track the trend of Bitcoin prices, the LSTM model was able to predict both the direction and the value during the specified time period. This research exhibits LSTM's persistent capacity for fluctuating Bitcoin price prediction despite the sophistication of ARIMA. 2023, University of Wollongong. All rights reserved.