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Stiffness of a single layered cable assembly over a sheave with internal friction
The stiffness response of a single layered helical strand with a straight core surrounded by a layer of six helical wires has been made with improved relations of wire curvatures & twist and with internal friction considerations. The stranded cable undergoes a constant curvature bending over a sheave/pulley under static loading conditions and experiences the combinations of tension, torsion and bending loadings. A new analytical model has been developed for the cable in contact with the pulley/sheave using thin rod theory under linear elastic conditions. The stiffness coefficients of the cable are evaluated in free bending and constrained bending modes. The resulting wire strains are evaluated and compared with the experimental results. IAEME Publication -
Stigma among COVID-19 patients in South India-A cross-sectional study
Background: COVID-19 has a significant biopsychosocial impact on the lives of people who are infected, with the stigma associated with the illness being one of the major issues. However, the level of stigma based on demographics, gender differences, hospital-based or home-based care is yet to be explored. Hence, this study aimed to infer the level of stigma between these groups in the urban district of south India. Materials and Methods: This cross-sectional study recruited 50 participants who were recently infected with COVID-19 and were receiving either hospital or home-based care. The stigma was assessed using a standardized questionnaire which has four domains. MannWhitney U test was conducted to analyze the data. Results: Median age is 54 years and the majority of the participants are male (74%). The mean score of enacted stigma subscale was 4.48, disclosure fear was 2.34, internalized stigma was 2.82, perceived externalized stigma was 7.32 and the total stigma mean score was 17. The perceived externalized stigma subscale was higher in males (7.57 5.96) when compared to females 6.62 5.53. Total stigma scores were higher for males 17.2 10.1 when compared to females 16.2 10.5. The total stigma score was more (17 10.3) among home isolated COVID patients as compared to hospitalized patients (16.9 10.2). Conclusion: Increased levels of stigma among COVID-19 patients have various important psychosocial implications. This study highlights the need for larger prospective cohort studies to further understand stigma in the context of COVID-19. 2022 by the Author(s). -
Still Waters Run Deep: Groundwater Contamination and Education Outcomes in India
We investigate the impact of groundwater contamination on educational outcomes in India. Our study leverages variations in the geographical coverage and timing of construction of safe government piped water schemes to identify the effects of exposure to contaminants. Using self-collected survey data from public schools in Assam, one of the most groundwater-contaminated regions in India, we find that prolonged exposure to unsafe groundwater is associated with increased school absenteeism, grade retention, and decreased test scores and Cumulative Grade Point Average (CGPA). To complement our findings and to study the effect of one such contaminant, arsenic, we use a large nationally representative household survey. Using variations in soil textures across districts as an instrument for arsenic concentration levels we find that exposure to arsenic beyond safe threshold levels is negatively associated with school attendance. 2024 Elsevier Ltd -
Stirling number of the fourth kind and Lucky partitions of a finite set
The concept of Lucky k-polynomials and in particular Lucky ?polynomials was recently introduced. This paper introduces Stirling number of the fourth kind and Lucky partitions of a finite set in order to determine either the Lucky k- or Lucky ?-polynomial of a graph. The integer partitions influence Stirling partitions of the second kind. 2021 Azarbaijan Shahid Madani University. -
STOCHASTIC BEHAVIOUR OF AN ELECTRONIC SYSTEM SUBJECT TO MACHINE AND OPERATOR FAILURE
A stochastic model is developed by assuming the human (operator) redundancy in cold standby. For constructing this model, one unit is taken as electronic system which consists of hardware and software components and another unit is operator (human being). The system can be failed due to hardware failure, software failure and human failure. The failed hardware component goes under repair immediately and software goes for upgradation. The operator is subjected to failure during the manual operation. There are two separate service facilities in which one repairs/upgrades the hardware/software component of the electronic system and other gives the treatment to operator. The failure rates of components and operator are considered as constant. The repair rates of hardware/software components and human treatment rate follow arbitrary distributions with different pdfs. The state transition diagram and transition probabilities of the model are constructed by using the concepts of semi-Markov process (SMP) and regenerative point technique (RPT). These same concepts have been used for deriving the expressions (in steady state) for reliability measures or indices. The behavior of some important measures has been shown graphically by taking the particular values of the parameters. 2024, Gnedenko Forum. All rights reserved. -
Stochastic frontier analysis to measure technical efficiency: Evidence from skilled and unskilled agricultural labour in india
This paper comprises the stochastic frontier model which has been applied to measure the technical efficiency of skilled and unskilled labour. By considering the certain input variables listed in the cost of cultivation suggested by the Commission of Agricultural Costs and Prices (CACP) for Indian states during the main cropping season. Result of the study shows that the evaluated average technical efficiency estimates have been found between 71 to 84 % for both type of labour. Factors i.e. use of seeds (77 % efficient), fertilizers (29 % inefficient), manure (3 % efficient), land, human (9 % efficient), attached (10 % efficient) and casual (103 % efficient) labor, animal labor (is between 1 to 4 % efficient), hired machine (33 % inefficient), owned machine (7 % efficient), insecticides (20 % efficient), irrigational cost (31 % efficient), fixed cost (36 % inefficient) and operational cost (197 % inefficient) have a significant at 1, 5 and 10 % level of significance1. 2020 DAV College. All rights reserved. -
Stock Market Efficiency and COVID-19 with Multiple Structural Breaks: Evidence from India
The objective of the study is to investigate the influence of the coronavirus pandemic (endogenous crisis) on the stock market efficiency of India during the multiple break periods. The empirical analysis is performed using conditional heteroscedasticity and a small sample robust wild bootstrap automatic variance ratio test and automatic portmanteau test on a daily stock return data of two benchmark indices, that is, NIFTY and SENSEX. The empirical results demonstrate that the stock return of two indices deviates from market efficiency during some periods of the analysis, notably during the nationwide lockdown and peak periods of coronavirus cases in India. These findings indicate that changing stock market behaviour becomes more speculative and earns abnormal profits. To the best of the authors knowledge, this study provides the first evidence of investigating the variations in the stock market efficiency of India in response to this endogenous crisis. 2022 International Management Institute, New Delhi. -
Stock Market Linkages in Emerging Asia-Pacific Markets
Stock Market Linkages in Emerging Asia-Pacific Markets -
Stock market linkages in emerging Asia-Pacific markets
This study examines the stock market integration among major stock markets of emerging Asia-Pacific economies, viz. India, Malaysia, Hong Kong, Singapore, South Korea, Taiwan, Japan, China, and Indonesia. The Johansen and Juselius multivariate cointegration test, Granger causality/Block exogeneity Wald test based on the vector error correction model (VECM) approach, and variance decomposition analysis were used to investigate the dynamic linkages between markets. Cointegration test confirmed a well-defined long-run equilibrium relationship among the major stock markets, implying that there exists a common force, such as arbitrage activity, which brings these stock markets together in the long run. The results of Granger causality/Block exogeneity Wald test based on VECM and variance decomposition analysis revealed the stock market interdependencies and dynamic interactions among the selected emerging Asia-Pacific economies. This result implies that investors can gain feasible benefits from international portfolio diversification in the short run. On the whole, the study results suggest that although long-term diversification benefits from exposure to these markets might be limited, short-run benefits might exist due to substantial transitory fluctuations. The Author(s) 2013. -
Stock market prediction employing ensemble methods: the Nifty50 index
Accurately forecasting stock fluctuations can yield high investment returns while minimizing risk. However, market volatility makes these projections unlikely. As a result, stock market data analysis is significant for research. Analysts and researchers have developed various stock price prediction systems to help investors make informed judgments. Extensive studies show that machine learning can anticipate markets by examining stock data. This article proposed and evaluated different ensemble learning techniques such as max voting, bagging, boosting, and stacking to forecast the Nifty50 index efficiently. In addition, an embedded feature selection is performed to choose an optimal set of fundamental indicators as input to the model, and extensive hyperparameter tuning is applied using grid search to each base regressor to enhance performance. Our findings suggest the bagging and stacking ensemble models with random forest (RF) feature selection offer lower error rates. The bagging and stacking regressor model 2 outperformed all other models with the lowest root mean square error (RMSE) of 0.0084 and 0.0085, respectively, showing a better fit of ensemble regressors. Finally, the findings show that machine learning algorithms can help fundamental analyses make stock investment decisions. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Stock market prediction using subtractive clustering for a neuro fuzzy hybrid approach
Stock market prediction is the challenging area for the investors to yield profits in the financial markets. The investors need to understand the financial markets which are more volatile and affected by many external factors. This paper proposes a subtractive clustering based adaptive neuro fuzzy approach for predicting apple stock data prices. The research data used in this study is from 3rd Jan 2005 to 30th Jan 2015. Four technical indicators are proposed in this study. They are Simple moving average for 1week, simple moving average for 2weeks, 14days Disparity and Larry Williams R%. These variables are used as inputs to the neuro fuzzy system to predict the daily apple stock prices. Also, this study compares the proposed work with the ANFIS training method and subtractive clustering method etc. The performance of all these models is analyzed. The measures like training error, testing error, number of rules and number of parameters are calculated and compared for analysis. From the simulation results, the average performance of subtractive clustering based neuro fuzzy approach was found considerably better than the other networks. 2017, Springer Science+Business Media, LLC. -
Stock market prediction using subtractive clustering for a neuro fuzzy hybrid approach /
Cluster Computing (The Journal Of Networks, Software Tools And Applications), Vol.22, pp.13159–13166. -
Stock market sensitivity to macroeconomic factors: Evidence from China and India
The purpose of this study is to analyse the impact of Chinese macroeconomic factors on Shanghai Stock Exchange (SSE) Composite returns and Indian macroeconomic factors on Nifty returns based on monthly data from January 1998 to December 2018. This study adopts quantile regression approach. The QR allows examining the conditional dependence of specific quantile of SSE and Nifty returns with respect to the conditioning factors. The authors present results for two sample periods that are pre-recession and recession period from 1998 to 2008 and the post-recession period from 2009 to 2018. This paper also documents quite interesting and useful results for the entire period. From the results, It is concluded that Chinese consumer price index significantly affects the SSE returns only for lower quantiles. However, Indian consumer price index has a significant and positive impact on the Nifty returns for the upper quantiles. Further, Chinese interest rates and Indian interest rates have no impact on the SSE and Nifty returns respectively across the different quantiles. Moreover, the Chinese exchange rate influence the SSE returns at the extreme dataset. However, the Indian exchange rate is insignificant. It is important to note that the dependence structure of China shows a negligible change during the post-recession period. Conversely, the dependence structure has changed significantly for India post-recession. The implication of this paper would guide stock market participants. 2020 AESS Publications. All Rights Reserved. -
Stocks and throughput Accounting on Material Management and its Impact on Cost Management
Global Journal of Arts and Management, Vol. 2, No. 3, pp. 244-246, ISSN No. 2249-2658 -
Straightforward synthesis of mn3o4/zno/eu2o3-based ternary heterostructure nano-photocatalyst and its application for the photodegradation of methyl orange and methylene blue dyes
Zinc oxide-ternary heterostructure Mn3O4/ZnO/Eu2O3 nanocomposites were successfully prepared via waste curd as fuel by a facile one-pot combustion procedure. The fabricated heterostructures were characterized utilizing XRD, UVVisible, FT-IR, FE-SEM, HRTEM and EDX analysis. The photocatalytic degradation efficacy of the synthesized ternary nanocomposite was evaluated utilizing model organic pollutants of methylene blue (MB) and methyl orange (MO) in water as examples of cationic dyes and anionic dyes, respectively, under natural solar irradiation. The effect of various experimental factors, viz. the effect of a light source, catalyst dosage, irradiation time, pH of dye solution and dye concentration on the photodegradation activity, was systematically studied. The ternary Mn3O4/ZnO/Eu2O3 photocatalyst exhibited excellent MB and MO degradation activity of 98% and 96%, respectively, at 150 min under natural sunlight irradiation. Experiments further conclude that the fabricated nanocomposite exhibits pH-dependent photocatalytic efficacy, and for best results, concentrations of dye and catalysts have to be maintained in a specific range. The prepared photocatalysts are exemplary and could be employed for wastewater handling and several ecological applications. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Strain-Induced Tribocatalytic Activity of 2D ZnO Quantum Dots
The use of low-frequency vibration or high-frequency ultrasound waves to create polarization and an inherent electric field in piezo-tribocatalysts has recently been shown to be a novel advanced oxidation process. In this study, we have demonstrated the synthesis of two-dimensional (2D) ZnO quantum dots (QDs) and their strain-induced tribocatalytic effect, where the triboelectric charges generated under the influence of friction and strain are used to facilitate the decomposition of organic dye molecules. The catalytic performance of 2D QD catalysts can be tuned by modulation of the strain-induced band-gap variation, which are typically regarded as the active sites. The underlying mechanism for the strain-induced catalytic performance is due to the presence of defective dipole moments. Detailed theoretical investigations reveal strain-induced charge-transfer-dependent catalytic properties of the 2D ZnO QD-polymer interface. We believe that the present work provides a fundamental understanding of the design of high-performance catalysis applications for water cleaning and emerging technologies. 2024 American Chemical Society. -
Strategic design of MXene/CoFe2O4/g-C3N4 electrode for high-energy asymmetric supercapacitors
MXenes are emerging as the next-generation materials for energy storage due to their substantial surface area, exceptional conductivity, and abundant surface-terminating groups. However, the tortuous path for ion transfer within the restacked layers significantly limits the electrochemical performance of multilayered MXenes. To overcome this, interlayer spacers have been introduced. These spacers help mitigate ion diffusion barriers and enhance the accessibility of active sites, thereby improving the overall efficiency and longevity of MXene-based supercapacitors and related devices. In this study, a rational material is designed by incorporating CoFe2O4 and g-C3N4 into the layers of MXene through ultrasonication for supercapacitor application. The physicochemical properties of the synthesized materials have been comprehensively characterized using diverse techniques, revealing that MXene/CoFe2O4/g-C3N4 has successfully evolved into a multilayered structure possessing enhanced surface area, low restacking tendency, high pore diameter, and excellent pore volume. Leveraging these properties, it performs as a viable material for fabricating the working electrode with a specific capacitance (Csp) of 1506.2 F g?1 at a current density of 5 A g?1 in 3 M KOH. It shows good stability with 89 % capacitance retention over 7000 cycles. An asymmetric supercapacitor (ASC) constructed with MXene/CoFe2O4/g-C3N4 as positive electrode and activated carbon as negative electrode exhibits an energy density of 79.8 Wh Kg?1 and power density of 1343.3 W Kg?1. Furthermore, it shows a capacitive retention of 91 % over 10,000 cycles. This MXene based composite, with excellent capacitance and outstanding stability, offers an appreciable performance in the field of sustainable energy storage. 2024 Elsevier B.V. -
Strategic perspective of internal branding: A critical review /
European Journal of Business and Management, Vol.6, Issue 34, pp.98-105, ISSN No: 2222-1905 (Print), 2222-2839 (Online). -
Strategic positioning of tourist destinations- analyzing the role of perceived meaningfulness
This study analyzed the cognitive and affective components of destination image in the perception of foreign tourists visiting Indian destinations by exploring conceptual constructs, namely Post-visit Destination Image and Perceived Meaningfulness. The exploratory factor analysis of the responses of foreign tourists (n = 242) on items related to the major constructs significant in tourist behavior such as destination quality, perceived meaningfulness, and post-visit destination image confirmed the existence of multi-dimensional structure. Additionally, the empirical validation of the theoretical framework developed on the tenents of stimulus-organism-response paradigm with the constructs using structural equation modeling established significant relationships helpful to understand many new travel motivations. The study established that perceived meaningfulness has a significant mediating role in predicting tourist referral/revisit intentions from positive perceptions about destination quality and post-visit destination image. The observations from the study helped to identify six types of travel motivations useful in developing niche markets for positioning Indian destinations. The identified travel motivations, namely physical meaningfulness seeking, eternal meaningfulness seeking, social meaningfulness seeking, nature-loving, hospitality appreciating, and uniqueness exploring, offer directions to destination marketers to revamp destination attributes for destination marketing. 2021 The Authors -
Strategically designed multiwalled carbon nanotube/bismuth ferrite/polyaniline nanocomposites and unlocking their potential for advanced supercapacitors
Bismuth ferrite (BF) serves a potential electrode-active material due to its peculiar characteristics such as wide voltage window and high specific capacitance, excellent stability, facile synthesis routes, etc. to name a few. Herein we report the strategic design and facile synthesis of multiwalled carbon nanotubes (MWCNT)/BF/polyaniline (PANI) nanocomposites, particularly for application in advanced supercapacitors. The MWCNT/BF/PANI nanocomposite architecture is a strategic design in which the maximum available surface area is utilized for the electrode nanostructure with increased porosity that allows easy movement of electrolyte-ions through it. The uniform arrangement of BF on MWCNTs helps in mitigating the possible agglomeration, further augmenting the surface area for an enhanced charge storage. The strategic layout of PANI on BF-decorated MWCNTs has given a coral-like structure for the nanocomposite electrode which significantly increased the surface area, reduced ion pathways and facilitating better access to electrolytic K+ ions. The MWCNT/BF/PANI nanocomposite electrode exhibits a specific capacitance of 3640 F g?1 at a current density of 5 A g?1. The innovative design as well as the synergy between the individual components of the nanocomposite electrode play a pivotal role in attaining the enhanced electrochemical performance. 2024 Elsevier B.V.