Rachna Jain, Manish Kumar Bhadu, Keshave Swarnkar and Sumitesh Das
The purpose of this paper is to report on the use of phosphorylated polyphenol (PP)-coated galvanised iron (GI) surface to study the degradation of coating with different time…
Abstract
Purpose
The purpose of this paper is to report on the use of phosphorylated polyphenol (PP)-coated galvanised iron (GI) surface to study the degradation of coating with different time intervals and long-term exposure in different salty media.
Design/methodology/approach
The as-obtained PP complex on GI was evident by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), energy dispersive spectroscopy (EDS) and scanning electron microscopy (SEM). The coated coupons were exposed to different salty media such as 3.5 per cent NaCl, 1.5 per cent Na2SO4 and tap water at set time intervals. Electrochemical polarisation was performed to study the anodic and cathodic polarisation behaviour at each time interval.
Findings
The adherent foliolate nanopattern of iron zinc phosphate and zinc dihydrogen phosphate on GI surface was evident by SEM, FT-IR, EDS and XRD. The coated coupons exhibited good corrosion resistance. This coating performs as an alternative to time-consuming multistep operations of phosphating treatment.
Originality/value
The mode of the experiment treatment using modified PP coating especially on GI in different corrosive exposures at set time intervals is a novel approach in this research.
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Rachna Jain, Amit Sharma, Manish Kumar Bhadu and Keshave Swarnkar
The aim of this study was to evaluate the corrosion inhibition efficiency of steel samples in different environments before and after the treatment with rust metamorphose (RM)…
Abstract
Purpose
The aim of this study was to evaluate the corrosion inhibition efficiency of steel samples in different environments before and after the treatment with rust metamorphose (RM), which is formulated in this research study and shows excellent adherence over the rusted surface of substrate because of the presence of the P-O-Fe bond.
Design/methodology/approach
An RM solution (phosphorylated polyphenol) was synthesised and characterised using Fourier transform infrared spectroscopy (FT-IR), and then the degree of protection offered by it to steel surfaces with and without the treatment with the RM solution in different atmospheres was evaluated;. Before and after treating with the RM solution, the corroded steel samples were characterised using X-ray diffraction (XRD), FT-IR, scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The study of the passive behaviours of the corroded steel samples and RM-treated steel samples was done in different simulated atmospheres.
Findings
This RM solution is phosphorylated polyphenol solution (proved by FT-IR), which acts as a corrosion inhibitor on corroded steel surfaces because of the formation of a passive and symmetric adherent layer of phosphorylated polyphenol–iron complex (confirmed by FT-IR, XRD, EDS, SEM and adhesion X test). The significant improvement in corrosion resistance in splash conditions of 3.5 per cent NaCl, tap water and 1.5 per cent Na2SO4 was found with the treatment of phosphorylated polyphenol-based RM.
Originality/value
The development of RM and its characterisation with performance evaluation in different atmospheres is a novel approach in this research.
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Charul Agrawal and Taranjeet Duggal
The study aims to study the extent of research done in luxury marketing in an emerging economy like India by conducting a bibliometric analysis. A period of 21 years has been…
Abstract
The study aims to study the extent of research done in luxury marketing in an emerging economy like India by conducting a bibliometric analysis. A period of 21 years has been considered to present a comprehensive picture for results and analysis. Key findings indicate the gaps and scope of further research for academics in India and abroad. The findings indicate a dearth of research by scholars and academicians in luxury, counterfeit and masstige, especially when there is a surge of the upper middle class in India. More specifically, Indian-grown luxury brands also present a massive scope for future research.
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Shivinder Nijjer, Kumar Saurabh and Sahil Raj
The healthcare sector in India is witnessing phenomenal growth, such that by the year 2022, it will be a market worth trillions of INR. Increase in income levels, awareness…
Abstract
The healthcare sector in India is witnessing phenomenal growth, such that by the year 2022, it will be a market worth trillions of INR. Increase in income levels, awareness regarding personal health, the occurrence of lifestyle diseases, better insurance policies, low-cost healthcare services, and the emergence of newer technologies like telemedicine are driving this sector to new heights. Abundant quantities of healthcare data are being accumulated each day, which is difficult to analyze using traditional statistical and analytical tools, calling for the application of Big Data Analytics in the healthcare sector. Through provision of evidence-based decision-making and actions across healthcare networks, Big Data Analytics equips the sector with the ability to analyze a wide variety of data. Big Data Analytics includes both predictive and descriptive analytics. At present, about half of the healthcare organizations have adopted an analytical approach to decision-making, while a quarter of these firms are experienced in its application. This implies the lack of understanding prevalent in healthcare sector toward the value and the managerial, economic, and strategic impact of Big Data Analytics. In this context, this chapter on “Predictive Analytics in Healthcare” discusses sources, areas of application, possible future areas, advantages and limitations of the application of predictive Big Data Analytics in healthcare.
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Madhulika Bhatia, Shubham Sharma, Madhurima Hooda and Narayan C. Debnath
Recent research advances in artificial intelligence, machine learning, and neural networks are becoming essential tools for building a wide range of intelligent applications…
Abstract
Recent research advances in artificial intelligence, machine learning, and neural networks are becoming essential tools for building a wide range of intelligent applications. Moreover, machine learning helps to automate analytical model building. Machine learning based frameworks and approaches allow making well-informed and intelligent choices for improving daily eating habits and extension of healthy lifestyle. This book chapter presents a new machine learning approach for meal classification and assessment of nutrients values based on weather conditions along with new and innovative ideas for further study and research on health care-related applications.
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Anam and M. Israrul Haque
The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools to…
Abstract
The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools to store, maintain, and analyze large sets of data provided by different systems of health. It is essential to manage and analyze these data to get meaningful information. Pharmaceutical companies are accumulating their data in the medical databases, whereas the payers are digitalizing the records of patients. Biomedical research generates a significant amount of data. There has been a continuous improvement in the health sector for past decades. They have become more advanced by recording the patient’s data on the Internet of Things devices, Electronic Health Records efficiently. BD is undoubtedly going to enhance the productivity and performance of organizations in various fields. Still, there are several challenges associated with BD, such as storing, capturing, and analyzing data, and their subsequent application to a practical health sector.
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Tulsi Jayakumar, Aarti Punjabi and Jyotsnaa Shah
Part A – to identify the challenges of inducting and nurturing next-gen leaders, to outline the building blocks for the successful induction of the next generation into the family…
Abstract
Learning outcomes
Part A – to identify the challenges of inducting and nurturing next-gen leaders, to outline the building blocks for the successful induction of the next generation into the family business and to spell the importance of mentoring conversations as a tool for successful induction in the family business. Part B – to define the basic tenets of effective communication-goal setting, planning and action using the goals, plans and action framework, to build a “listening” environment through understanding the hearing, understanding, remembering, interpreting, evaluating, and responding mode and to relate the importance of “questioning” in diagnosing a problem and reading both verbal and non-verbal cues in communication.
Case overview/synopsis
The two-part case describes the role of communication amongst young family business scions and a mentor’s role in shaping such communication. Part A traces the induction of Aditya Gandhi, a fourth-generation scion of Gandhi Gems and Jewels, a 110-year old Indian family business dealing in precious gems and jewels. It deals with the challenges of mentoring and successful induction of the next-generation into family business Part B of the case describes the communication between Aditya Gandhi and the proprietor of Gandhi Gems and Jewels’ key client, Ghanshyam Das. It deals with the tenets of effective communication as should be understood by young next-generation family members.
Complexity academic level
The case can be used in an executive programme for owners of family businesses or in an undergraduate or post-graduate programme in general business administration or family business management.
Supplementary materials
Teaching Notes are available for educators only.
Subject code
CSS 11: Strategy.
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K. Kalaiselvi and A. Thirumurthi Raja
Big Data is one of the most promising area where it can be applied to make a change is health care. Healthcare analytics have the potential to reduce the treatment costs, forecast…
Abstract
Big Data is one of the most promising area where it can be applied to make a change is health care. Healthcare analytics have the potential to reduce the treatment costs, forecast outbreaks of epidemics, avoid preventable diseases, and improve the quality of life. In general, the lifetime of human is increasing along world population, which poses new experiments to today’s treatment delivery methods. Health professionals are skillful of gathering enormous volumes of data and look for best approaches to use these numbers. Big data analytics has helped the healthcare area by providing personalized medicine and prescriptive analytics, medical risk interference and predictive analytics, computerized external and internal reporting of patient data, homogeneous medical terms and patient registries, and fragmented point solutions. The data generated level within healthcare systems is significant. This includes electronic health record data, imaging data, patient-generated data, etc. While widespread information in health care is now mostly electronic and fits under the big data as most is unstructured and difficult to use. The use of big data in health care has raised substantial ethical challenges ranging from risks for specific rights, privacy and autonomy, to transparency and trust.