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The purpose of this paper is to study the effect of mean stress and stress amplitude on the asymmetric cyclic deformation behavior of SA333 Gr-6 C-Mn steel. Such type of loading may arise during the service period because of the load fluctuations, thermal gradients and sudden loading like seismic events. Tests were also carried out at different temperatures to understand the effect of it on sensitiveness of the materials deformation behavior.

Cylindrical specimen of 8-mm gauge diameter and 15-mm gauge length was fabricated from the pipe section along its axis. Stress controlled ratcheting tests were carried out by using triangular waveform for cyclic loading. The strain accumulations were measured using 12.5-mm gauge length extensometer. Ratcheting tests were carried out at fixed stress amplitude of 400 MPa and mean stress varying from 0 to 75 MPa, whereas at the fixed mean stress of 100 MPa and stress amplitude varies from 300 to 400 MPa at 300°C. To study the effect of temperature on ratcheting behavior, tests were carried out at a load of 100 MPa mean stress and 350 MPa stress amplitude, with a varying temperature between room temperature and 350°C. The stress rate of 115 MPas-1 was kept constant for all the tests.

Increase in mean stress and stress amplitude, ratcheting strain and plastic strain amplitude increases, whereas ratcheting life decreases. With an increase in temperature, ratcheting life increases and strain accumulation decreases up to 300°C, whereas on further increase in temperature, strain accumulation increases with reduction in ratcheting life. Minimum ratcheting rate was observed at 250°C and 300°C. The dynamic strain aging (DSA) phenomena lead to the hardening of the material. The investigated steel shows DSA temperature regime lies between 250°C and 300°C. The failure modes at 250°C and 300°C temperature was transgranular, whereas at 350°C complete ductile.

The stress rate and loading condition may vary to study the ratcheting behavior.

From this study, the critical cyclic load may be determined. The DSA temperature regime of this material is determined at this stress rate. This could help to evaluate the cyclic deformation behavior of the material with temperature changes.

In this investigation, the DSA temperature regime has been determined where maximum ratcheting life, minimum strain accumulation and ratcheting rate were observed. The critical load where the minimum life of the material occurred at elevated temperature is 100 MPa mean stress and 400 MPa stress amplitude.

The COVID-19 pandemic disrupted organizations, bringing in unforeseen situations and highlighting the need for organizational leaders to develop a capacity for resilience, i.e. the ability to recuperate, exhibit agility and rebound. Hence, this paper aims to explore leaders’ views on what resilience capabilities are needed to manage themselves, the team and the organization.

This qualitative research study uses an in-depth interview tool and adopts a reflexive thematic analysis. The capabilities approach and resilience theory framework were applied to view resilience capabilities. The sample comprises 19 middle and senior leaders, both men and women, from the information technology Industry in India.

This study unravelled different capabilities to manage individuals, teams and organizations. The three key themes of resilience capabilities observed were as follows: self-leadership capabilities – where leaders focussed on capabilities that developed themselves; people leadership capabilities – which focussed on leading people and the team; and organisation-focussed leadership capabilities – which focussed on the macro level.

The findings of the study benefit organizations, leaders, human resource professionals, talent management strategists and academic leadership scholars to identify, train, conceive and deliver resilience capabilities.

In today’s digital world, real-time health monitoring is becoming a most important challenge in the field of medical research. Body signals such as electrocardiogram (ECG), electromyogram and electroencephalogram (EEG) are produced in human body. This continuous monitoring generates huge count of data and thus an efficient method is required to shrink the size of the obtained large data. Compressed sensing (CS) is one of the techniques used to compress the data size. This technique is most used in certain applications, where the size of data is huge or the data acquisition process is too expensive to gather data from vast count of samples at Nyquist rate. This paper aims to propose Lion Mutated Crow search Algorithm (LM-CSA), to improve the performance of the LMCSA model.

A new CS algorithm is exploited in this paper, where the compression process undergoes three stages: designing of stable measurement matrix, signal compression and signal reconstruction. Here, the compression process falls under certain working principle, and is as follows: signal transformation, computation of Θ and normalization. As the main contribution, the theta value evaluation is proceeded by a new “Enhanced bi-orthogonal wavelet filter.” The enhancement is given under the scaling coefficients, where they are optimally tuned for processing the compression. However, the way of tuning seems to be the great crisis, and hence this work seeks the strategy of meta-heuristic algorithms. Moreover, a new hybrid algorithm is introduced that solves the above mentioned optimization inconsistency. The proposed algorithm is named as “Lion Mutated Crow search Algorithm (LM-CSA),” which is the hybridization of crow search algorithm (CSA) and lion algorithm (LA) to enhance the performance of the LM-CSA model.

Finally, the proposed LM-CSA model is compared over the traditional models in terms of certain error measures such as mean error percentage (MEP), symmetric mean absolute percentage error (SMAPE), mean absolute scaled error, mean absolute error (MAE), root mean square error, L1-norm and L2-normand infinity-norm. For ECG analysis, under bior 3.1, LM-CSA is 56.6, 62.5 and 81.5% better than bi-orthogonal wavelet in terms of MEP, SMAPE and MAE, respectively. Under bior 3.7 for ECG analysis, LM-CSA is 0.15% better than genetic algorithm (GA), 0.10% superior to particle search optimization (PSO), 0.22% superior to firefly (FF), 0.22% superior to CSA and 0.14% superior to LA, respectively, in terms of L1-norm. Further, for EEG analysis, LM-CSA is 86.9 and 91.2% better than the traditional bi-orthogonal wavelet under bior 3.1. Under bior 3.3, LM-CSA is 91.7 and 73.12% better than the bi-orthogonal wavelet in terms of MAE and MEP, respectively. Under bior 3.5 for EEG, L1-norm of LM-CSA is 0.64% superior to GA, 0.43% superior to PSO, 0.62% superior to FF, 0.84% superior to CSA and 0.60% better than LA, respectively.

This paper presents a novel CS framework using LM-CSA algorithm for EEG and ECG signal compression. To the best of the authors’ knowledge, this is the first work to use LM-CSA with enhanced bi-orthogonal wavelet filter for enhancing the CS capability as well reducing the errors.

The purpose of this paper is to illustrate the use of a post hoc predictive segmentation procedure to find out the variables that are the most important predictors of investor's preference for specific financial investment products.

The study considers various demographic, socio‐economic and psychographic variables for the purpose of understanding the investor's preferences. Using a sample of individual investors (n=377), a classification and regression tree (CART) methodology was used to determine whether psychographic variables were better predictors than demographic and socio‐economic variables for understanding an individual investor's preference for the investment alternatives.

The results showed that psychographic variables emerged as the most important predictors in the case of investment products with greater degree of risk, and the demographic and socio‐economic variables emerged as the most important for the investment instruments with lesser degree of risk. However, when the sample was divided based on occupation profile (government and non‐government), for both the fixed returns based instruments and the non‐fixed instruments, psychographic variables emerged as the most important predictors.

These results show the need for financial service providers to consider the psychographic variables along with demographic and socio‐economic variables, so as to better understand and advise the financial consumers. This would enable the financial service institutions to target their audience more sharply, so as to develop appropriate marketing strategies and further build the investor's trust.

This paper is a first of its kind to empirically identify the most important variable that determines the financial consumer's preference for investment products in India, using CART technique. This study contributes to furthering the understanding of investor behavior.

In the last 10 years, India has amended its laws dealing with sexual offences against women with the changes ranging from increasing terms of imprisonment for the offence of rape to state-funded compensation schemes for women and child victims. In this regard, challenges persist for the agencies of the criminal justice system in India especially the courts to realise the vision of restorative justice as these forums have to navigate the relevant statutory provisions and binding precedents. This chapter seeks to analyse the challenges faced by courts in proper reintegration of victims and offenders of sexual offences, the institutional responses of the courts and suggests reforms to the criminal justice system in India in consonance with the principles of restorative justice acknowledged in the restorative justice movement in the international discourse.

Investigates the application of the Internet marketing and information exchange strategies in the Biotechnology sector. The Internet is particularly valuable in this context because not only does it offer instant information about products and services, but it also allows an interactive medium for value added activities such as “virtual” molecular modeling. This type of activity can foster important joint research operations between companies on a worldwide basis.

Indian investors have been exposed to a plethora of investment opportunities in the past decade and a half, after the liberalization process which commenced in 1991. Over the years, the increased competition has brought a wind of change, not just in the economic environment within the country, but also a radical change in the choices and preferences of the financial consumers. In the endeavor to provide more personalized advice to the financial consumers, financial service providers need more insights into the minds of the consumers. However, little work has been done to understand the Indian individual investor. The purpose of this paper is to study the Individual investor in India: to segment the investor into distinct behavioural groups based on their biases; to understand the investment preferences and profile of the identified segments; and to understand the implications for financial services providers.

Exploratory research, using In‐depth interviews, was undertaken to explore the manifestations of the biases among the individual investors. The initial inventory of 97 items pertaining to biases was assessed for content and face validity and subject to pilot test and subsequent rounds of modification. The final data were collected on a sample of 377 respondents, using a questionnaire that captured eight biases: Reliance on experts; Overconfidence bias; Self‐control bias; Categorisation tendency; Budgeting tendency; Adaptive tendency; Socially responsible investing bias; and Spouse effect. The segments of investor biases were identified using cluster analysis.

A cluster analysis of data, collected from individual investors was conducted in India (n=377), yielded four main segments of individual investors biases, which have been termed as the Novice Learner, the Competent Confirmer, the Cautious Anticipator and the Efficient Planner. This typology has predictive validity with regard to financial satisfaction and perceived financial market knowledge.

The paper presents a very important practical tool which can help financial service providers define their target audience more sharply and understand how people in these segments differ, behaviorally. Better understanding of investor's perceptions would help in designing more attractive financial products and development of marketing strategies that would impact the customer's financial satisfaction levels and create trust and customer loyalty.

This paper is a first of its kind to empirically identify the segments of biased behavior among investors and contributes to furthering the understanding on investor behavior.

Physicians who are primary care providers in rural communities form an essential stakeholder group in rural mobile health (mHealth) delivery. This study was exploratory in nature and was conducted in Udupi district of Karnataka, India. The purpose of this study is to examine the perceptions of rural medical officers (MOs) (rural physicians) regarding the benefits and challenges of mobile phone use by community health workers (CHWs).

In-depth interviews were conducted among 15 MOs belonging to different primary health centers of the district. Only MOs with a minimum five years of experience were recruited in the study using purposive and snowball sampling. This was followed by thematic analysis of the data collected.

The perceptions of MOs regarding the CHWs' use of mobile phones were largely positive. However, they reported the existence of some challenges that limits the potential of its full use. The findings were categorized under four themes namely, benefits of mobile phone use to CHWs, benefits of mobile phone-equipped CHWs, current mobile phone use by CHWs and barriers to CHWs' mobile phone use. The significant barriers reported in the CHWs' mobile phone use were poor mobile network coverage, technical illiteracy, lack of consistent technical training and call and data expense of the CHWs. The participants recommend an increased number of mobile towers, frequent training in mobile phone use and basic English language for the CHWs as possible solutions to the barriers.

Studies examining the perceptions of doctors who are a primary stakeholder group in mHealth as well as in the public health system scenario are limited. To the authors’ knowledge, this is one of the first studies to examine the perception of rural doctors regarding CHWs' mobile phone use for work in India.