Business Intelligence in Action: Way of Successful Implementation of Automated Systems
This chapter presents an overview of the role of automated systems in Business Intelligence (BI). BI has emerged as a critical element for modern organizations in decision-making processes by analyzing large volumes of data. Automated BI systems offer several advantages over traditional manual systems, including increased efficiency, accuracy, and customized insights. Despite these benefits, there are several limitations and challenges associated with the implementation of automated BI systems. This chapter examines the benefits and limitations of automated BI systems and identifies common success factors for successful implementation. The chapter also explores different types of automated systems, including predictive analytics, machine learning, natural language processing, and robotics process automation. These systems can help organizations analyze and interpret large amounts of data more quickly and accurately, enabling them to make informed decisions. However, despite the potential benefits of automated BI systems, there are several challenges associated with their implementation, including technical expertise and integration issues. To address these challenges, careful planning, collaboration, and ongoing monitoring are essential. In conclusion, this chapter highlights the importance of automated BI systems in modern businesses and provides valuable insights into their benefits and limitations. The chapter also emphasizes the need for careful planning, collaboration, and monitoring for the successful implementation of automated BI systems. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors.
Challa V.N.S.K.; Ramachandran K.K.; Rameshkumar P.M.; Cavaliere L.P.L.; Acharjee P.B.; Dornadula V.H.R.
Robotics and Automation in Industry 4.0: Smart Industries and Intelligent Technologies, Vol-45689, pp. 288-302.
Challa V.N.S.K., Department of BBA KL Business School, Koneru Lakshmaiah Education Foundation Green fields, Vaddeswaram, India; Ramachandran K.K., Department of ManagementCommerce/International Business, Dr. G R D College of Science, Coimbatore, India; Rameshkumar P.M., Department of Corporate Secretaryship Dwaraka Doss Goverdhan Doss, Vaishnav College (Autonomous), Chennai, India; Cavaliere L.P.L., Department of Economics University of Foggia, Foggia, Italy; Acharjee P.B., Christ University, Pune, India; Dornadula V.H.R., Sree Venkateswara College of Engineering, Nellore, India
Impact of Work from Home During COVID-19 Scenario
Coronavirus; COVID-19; Lockdown; SARS-CoV-2; Work from home (WFH)
In view of the recent situation, COVID-19 has spread across the world, and every country has to enforce a lockdown to prevent the virus from transmitting further. The worldwide COVID-19 outbreak has led to a large number of professionals work from their homes. Almost all the sectors like IT, academics, government, business, etc. are implementing work from home for safety of their employees and sincerely obeying the social distancing norms. Work from home can be beneficial and fruitful in terms of travel expenses, saving time commuting, working on ones own agenda, etc. But it can also be a pain and take a toll on mental well-being as you are living a quarantined life with little to no social life, which can also impact an individuals efficiency. There are so many barriers to work from home (WFH), like unavailability of resources, poor network connectivity, using digital platform and latest software for non-IT professionals, lack of proper infrastructure, etc. Our chapter focuses on every aspects of WFH during the COVID-19 lockdown period so that well-suited policies and practices can be designed to cope with the issues and hence transforming future of organizations by shifting the tradition of work from office to work from home. 2024 Apple Academic Press, Inc. All rights reserved.
Mahato S.; Pathak L.K.; Malik S.; Keo?lu N.
HR 4.0 Practices in the Post-covid-19 Scenario, pp. 47-69.
Mahato S., Indian Institute of Information Technology (IIIT), Jharkhand, Ranchi, India; Pathak L.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Malik S., Amity Institute of Biotechnology, Amity University Jharkhand, Jharkhand, Ranchi, India; Keo?lu N., Canakkale Onsekiz Mart University, Canakkale, Turkey
Bioactive Compounds and Biological Activities of Arrowroot (Maranta arundinacea L.)
Bioactive compounds; Biological activities; Maranta arundinacae; Rhizomes; Starch
Arrowroot is one of the most widely studied herbal species belonging to the family Marantaceae, which originated from South America and is mainly found in tropical areas. Species belonging to the Maranta genus attaining worldwide attention due to the bioactive compounds are present in their rhizomes. The nutritional values of the Maranta arundinacea plant parts were explored in traditional medicine and culinary practices. Maranta arundinacea flour is a good source of fiber, starch, and carbohydrate and is extensively utilized as a major ingredient in food products. It is also used as an alternative to wheat as the flour is gluten-free. Dietary fibers present in the Maranta arundinacea are beneficially used in the treatment of digestive disorders such as celiac disease and immune disorders. Its known to stimulate the production of IgM by immune cells. Maranta arundinacea is commonly used for weight management as it is protein-rich and has fewer calories. The rhizome contains substantial amounts of sodium, magnesium, phosphorus, potassium, calcium, iron, and zinc. The processed starch from the Maranta arundinacea rhizomes is broadly used in nutritional food products as well as in pharmacological applications. The bioactive compounds present in the Maranta arundinacea rhizome make it the subject of novel pharmaceutical studies. The current chapter tries to emphasize the general morphology, nutritional benefits and processing, bioactive compounds, and biological activities of the Maranta arundinacea. Springer Nature Switzerland AG 2024.
Jaison J.P.; Kurian J.T.; Scaria S.S.; Gangwar J.; Sebastian J.K.
Reference Series in Phytochemistry, Vol-Part F2504, pp. 523-540.
Springer Science and Business Media B.V.
Jaison J.P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Kurian J.T., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Scaria S.S., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Gangwar J., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Sebastian J.K., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India
Role of Leadership and Management of Higher Education Institutions (HEI) in Digitalization
24 learning; cultural transformation; digital transformational process; digitalization; higher education institutions; leadership; new education policy; technology-enhanced learning
Throughout this chapter, several updated concepts, terms, and theoretical constructs are proposed about leadership and management of Higher Education Institutions (HEIs) with respect to the current trends and demands. The digital learning (DL) ecosystem and the transformational stages are discussed to elaborate the process of digital transformation at the HEIs. The advantages and benefits of digital education are integrated in the chapter with a view to better understand the challenges and opportunities brought forth by these imperatives. The chiseling role of leadership in the entire process is presented in the context of the digital ecosystem in order to meet the expectations of all the stakeholders. The New Education Policy (NEP) presents itself as a shaping force in accordance with prevailing standards and/or voluntary commitment by the respective HEIs in India. Further to the elaboration of the drivers of digitalization in the HEIs, the key takeaway is introduced as a holistic approach to leadership and management in such an ecosystem. 2024 Apple Academic Press, Inc.
Digitalization of Higher Education: Opportunities and Threats, pp. 95-116.
Sao A., RICS School of Built Environment, Amity University, Uttar Pradesh, NOIDA, India; Kumar A., School of Business & Management, CHRIST (Deemed to be University), NCR Campus, Ghaziabad, India; Ashesh G., School of Business, AURO University, Gujarat, Surat, India
Securing Automated Systems with BT: Opportunities and Challenges
The use of automated systems is becoming increasingly prevalent in various industries; however, they pose significant security risks. In order to enhance the security of these systems, Blockchain Technology (BT) provides a promising solution. This chapter discusses the opportunities and challenges associated with using BT to secure automated systems. The role of BT in securing automated systems is discussed, emphasizing its ability to improve security and transparency. Additionally, BT-based systems with enhanced security are examined, such as decentralized data management, immutable and transparent ledgers, reduced cyber-attacks, and secure data sharing. Despite these opportunities, challenges such as high computational power requirements, integration challenges, BT scalability, and regulatory challenges must be addressed. Utilizing BT can create a more secure and transparent system that can help to prevent fraud, hacking, and other forms of cyber-attacks, ultimately enhancing the reliability and safety of automated systems. In conclusion, this paper highlights the potential of using BT for securing automated systems and the need for continued research and development to overcome the challenges associated with its implementation. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors.
Cavaliere L.P.L.; Rawat S.; Sidana N.; Acharjee P.B.; Kharb L.; Podile V.
Robotics and Automation in Industry 4.0: Smart Industries and Intelligent Technologies, Vol-45689, pp. 337-348.
Cavaliere L.P.L., Department of Economics University of Foggia, Foggia, Italy; Rawat S., MM Institute of Computer Technology and Business Management (MCA), Maharishi Markandeshwar (Christ Deemed to be University), Haryana, India; Sidana N., Amity School of Economics, Amity University, Noida, India; Acharjee P.B., Christ University, Pune, India; Kharb L., Department of IT, Jagan Institute of Management Studies, Delhi, India; Podile V., KL Business School, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India
Carbon-Based and TMDs-Based Materials as Catalyst Support for Fuel Cells
Global energy consumption and environmental pollution caused by the extensive use of fossil fuels have increased the need to look forward to more renewable energy sources. Fuel cell, one of the promising energy conversion devices, has the potential to outsmart the existing devices but has several setbacks to be employed on a larger scale. One of the hindrances is the sluggish oxygen reduction reaction kinetics at the cathode and hence requires electrocatalysts to improve its overall performance. This chapter provides a brief overview of graphene and transition metal dichalcogenides (TMDs)- based composites that have the potential to be used as a catalyst support. 2024 World Scientific Publishing Company.
Carbon and Tmds Nanomaterials for Energy Applications, pp. 107-131.
Nair A.S., Department of Physics and Electronics CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Joseph S., Department of Physics and Electronics CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Jafri R.I., Department of Physics and Electronics CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India
Data Analytics and ML for Optimized Performance in Industry 4.0
Industry 4.0, the fourth industrial revolution, has revolutionized manufacturing and production systems by integrating Data Analytics (DA) and Machine Learning (ML) techniques. Predictive maintenance, which predicts equipment malfunctions and schedules maintenance in advance, is a crucial application of DA and ML within Industry 4.0. It reduces downtime, improves productivity, and lowers costs. Demand forecasting, which uses historical data and ML algorithms to predict future product demand, and anomaly detection, which identifies abnormal patterns or events within large datasets, are also critical applications of DA and ML in Industry 4.0. They enhance operational efficiency and reduce costs. However, the adoption of DA and ML presents several challenges for organizations, including infrastructure, personnel, ethical, and privacy concerns. To realize the benefits of DA and ML, companies must invest in appropriate hardware and software and develop the necessary expertise. They must also handle data responsibly and transparently to ensure privacy and ethical standards. Despite these challenges, the integration of DA and ML in Industry 4.0 is critical for optimized performance, improved productivity, and cost savings. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors.
Daya Sagar K.V.; Ramachandran K.K.; Acharjee P.B.; Singh P.; Satyala H.; Singh B.
Robotics and Automation in Industry 4.0: Smart Industries and Intelligent Technologies, Vol-45689, pp. 275-287.
https://doi.org/10.1201/9781003317456-15 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191824754&doi=10.1201%2f9781003317456-15&partnerID=40&md5=ee2e7c5fd88fee6b4f0ebadbac00c861
Daya Sagar K.V., Department of Electronics and Computer Engineering, Koneru Lakshmaiah Education Foundation, Guntur, India; Ramachandran K.K., Department of ManagementCommerce/International Business, Dr. G R D College of Science, Coimbatore, India; Acharjee P.B., Christ University, Pune, India; Singh P., Department of CSE Guru Ghasidas Vishwavidyalaya, Bilaspur, India; Satyala H., Department of Operation Management, Indian Institute of Management, Ranchi, India; Singh B., Department of Food Science and Technology, IK Gujral Punjab Technical University, Punjab, India
Genetic Modification of Enzymes for Biomass Hydrolysis
Lignocellulose biomass is an economically viable and most abundant energy source. The synthesis of renewable energy-based fuel from lignocellulosic biomass is a replacement for fossil fuel. Cellulases are the biocatalysts that hydrolyze the ?-1,4-glycosidic bond in cellulose to release carbohydrate moieties that can be converted to ethanol, butanol, and other compounds. However, little enzymatic activity and product yield, and thermal stability are hurdles in the deconstruction of lignocellulose. Current progress in synthetic and omics technologies has resulted in several works in metabolic and genetic engineering that have paved the way for efficient conversion of lignocellulose to fuel in the last decades. Several works have attempted to apply genetic and metabolic engineering in the synthesis of stable and highly active cellulases at lower cost. This chapter reviews various genetic engineering technologies for enhancing cellulase synthesis and catalytic efficiency. 2024 selection and editorial matter, Reeta Rani Singhania, Anil Kumar Patel, Htor A. Ruiz, Ashok Pandey; individual chapters, the contributors.
Madhavan A.; Arun K.B.; Nair B.G.; Singhania R.R.; Raveendran S.; Awasthi M.K.; Pandey A.; Binod P.
Biomass Hydrolyzing Enzymes: Basics, Advancements, and Applications, pp. 101-111.
Madhavan A., School of Biotechnology, Amrita Vishwa Vidyapeetham, Kerala, Kollam, India; Arun K.B., Department of Life Sciences, Christ (Deemed to be University), Karnataka, Bengaluru, India; Nair B.G., School of Biotechnology, Amrita Vishwa Vidyapeetham, Kerala, Kollam, India; Singhania R.R., Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan, Centre for Energy and Environmental Sustainability, Uttar Pradesh, Lucknow, India; Raveendran S., Department of Food Technology, T K M Institute of Technology, Kerala, Kollam, India; Awasthi M.K., College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi Province, China; Pandey A., Centre for Energy and Environmental Sustainability, Uttar Pradesh, Lucknow, India, Centre for Innovation and Translational Research, CSIR-Indian Institute of Toxicology Research, Uttar Pradesh, Lucknow, India, Kyung Hee University, Seoul, South Korea, School of Engineering, University of Petroleum and Energy Studies, Dehradun, India; Binod P., Microbial Processes and Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology, Kerala, Thiruvananthapuram, India
AI applications at the scheduling and resource allocation schemes in web medium
Resources including business, informational, personal, and financial resources are required, with support from users, to maintain and implement the resource representations. Resource provisioning seeks to meet user needs by supplying the appropriate resources at the appropriate time at a lower cost. A service provider oversees supplying resources to all applications, and among the methods of resource management that they can employ are time-based, cost-based, on-demand, and bargain-based. These general approaches to resource provisioning and scheduling are based on recent developments in heterogeneity in 6G networks, including cloud computing, fog computing, and autonomic computing, to allocate and schedule resources while keeping an eye on service performance and adjusting as needed to meet the needs of cloud users. The proposed work increases resource allocation through cost reduction and, as a result, increases the availability of the services at the device levels without compromising performance parameters such as availability, efficiency, authentication, and authorization. The wide metropolitan area network (6G Networks) wireless heterogeneity is presented in this chapter's technological problems. Memory, network performance, and other factors were heterogeneous in fog nodes. Here, the Load balancing algorithm's Priority ordering is applied to make use of wireless model properties. This chapter focuses on various load balancing and scheduling strategies along with a few machine learning techniques applied to fog nodes and clustering techniques. 2024 selection and editorial matter, Dr. Abraham George and G. Ramana Murthy; individual chapters, the contributors.
Towards Wireless Heterogeneity in 6G Networks, pp. 107-126.
Shekhar R., Department of Computer Science and Engineering, Alliance University, Bangalore, India; Paul P.M., Department of Computer Science and Engineering, Alliance University, Bangalore, India; Jingle D.J., Department of Computer Science and Engineering, Christ University, Bangalore, India
Inkjet printing of MOx-based heterostructures for gas sensing and safety applicationsRecent trends, challenges, and future scope
Acetone; Acetylene; Doping; Ethanol; Formaldehyde; Heterostructures; Ink formulation; Inkjet printing; Metal oxide; Metal oxide semiconductor; Methanol; MOx; Nanocomposites; Nanostructures; Toluene; VOC
Volatile organic compounds (VOCs) are pollutants that affect air quality and human health. Detection of VOCs is important for environmental safety. Metal oxide semiconductor (MOS) is a promising product for gas sensors due to its advantages of easy fabrication, low cost, and good portability. Their performance is greatly affected by microstructure, defects, catalysts, heterojunctions, and moisture. Metal oxidebased nanomaterials serve as a platform to identify various VOCs with high sensitivity due to their wide bandgap, n-type transport, and excellent electrical properties. Gas detection devices based on doping, altered morphology, and heterostructure have been shown to be effective against VOCs. Inkjet printing (IJP) is a promising process for the room-temperature deposition of functional metal oxides for sensing applications. However, the development of metal oxide ink requires a careful selection of the precursors, solvents, and additives. This section will focus on the production of various metal oxide (MOx)-based sensors such as ZnO, SnO2, MoO3, CuO, Cu2O, Mn3O4, and WO3 for the detection of VOCs such as acetylene, toluene, ethanol, formaldehyde, and acetone. It will summarize recent research and advances in large-scale printing of MOx-based nanocomposites. This work illustrates the need to explore new composite materials, structures, and morphology as well as other methods for better and faster transformation. The role of solvents in ink stabilization and printing and the behavior of ink rheological parameters in the IJP spraying process will also be discussed. Ink formulations for the synthesis of functional nanocomposites will be analyzed and presented for future scope and challenges. 2024 Elsevier Inc. All rights reserved.
Complex and Composite Metal Oxides for Gas, VOC and Humidity Sensors, Volume 2: Technology and New Trends, pp. 133-157.
Murthy H., Department of Electronics and Communication Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Challenges and Issues in Health Care and Clinical Studies Using Deep Learning
Deep learning is a subset of machine learning, which has more than three layers of neural networks. Neural networks resemble the functioning of human behavior in nature. These neural networks are capable of producing results with single layers, but multiple layers help in producing accurate results with increased precision rate. Deep learning supports a number of artificial intelligence (AI)-based applications and services, which helps in increased automated devices, data analysis, and many more physical tasks in various fields. Deep learning technology has become part of human day-to-day life. It is involved in every aspect of daily routine like voice-based searches, operating a device, baking transactions, and many more. Deep learning allows the healthcare industry to examine data quickly without compromising accuracy. Deep learning uses mathematical models designed to work almost like the human brain. Multiple layers of networking and technology enable unmatched computing capability and the ability to traverse and analyze through vast sets of data that would have previously been lost, forgotten, or missed. 2024 Taylor & Francis Group, LLC.
Deep Learning for Smart Healthcare: Trends, Challenges and Applications, pp. 165-182.
Devi M.R., School of Information Science, Presidency University, Bangalore, India; Sindhu V., Department of Computer Science, Christ University, Yeshwanthpur campus, Bangalore, India; Devi S., Presidency University, Bangalore, India, School of Information Science, Presidency University, Bangalore, India
Leveraging Deep Learning in Hate Speech Analysis on Social Platform
The scope and usage of the Internet have surpassed the expected growth and have proven beyond the basic purpose of being used for networking and telecommunications. It serves as the backbone of the web, and one of the predominant domains that uses the Internet is social media. The concept was conceived in the early 1990s and went on to grow as a powerful medium of people networking along with the Internet. Social networking sites (SNS) acquired a predominant element of the Internet owing to their use and services they offer through the Internet. A few of the most used social networking sites include Twitter and Facebook, which are used synonymous to expressions of text. These SNS allow the users to post photos, videos, and other multimedia content along with text and voice messages that are shared among other users. As with any technology or application, these also have the risk of users posting offensive material and textual content. Hate is being spread through messages, which are in the form of text and also through other materials posted. There is no control to check for the message for the hate content as and when it is posted, and by the time it is deleted by admins, it could have already reached millions of users. This chapter proposes a technique for detecting hate texts in reviews from registered users in the Twitter dataset. The proposed work makes use of improved principle component analysis (IPCA) and modified convolution neural network (MCNN) for detecting hate texts. The advantage of natural language processing is used for building an automated system for the analysis of syntax and semantics of the words. The proposed methodology consists of phases like pre-processing, feature extraction, and process to classify the text. The white spaces in the text are removed through normalization in the pre-processing phase, and also remove special characters such as question marks, punctuations, and exclamatory symbols to remove stop words. The features that are pre-processed are then subjected to feature extraction using IPCA. A set of correlated features are made used for identifying more important features in the data set under consideration. Next, the classification is done for identifying the hate text or for any language abuse. MCNN is applied for the classification of the text into HATE and NON-HATE from the text with better accuracy. The experiments prove that the proposed method has a high level of accuracy even for a large dataset. The results show that the proposed method has better performance in terms of precision, recall, and F-measure when compared with other state-of-the-art methods. 2024 Taylor & Francis Group, LLC.
Manikandan R.; Hariharasitaraman S.; Ramkumar S.; Gobinath R.
Deep Learning for Smart Healthcare: Trends, Challenges and Applications, pp. 38-53.
Manikandan R., CHRIST (Deemed to be University), India, School of Business and Management, India; Hariharasitaraman S., Division of Cyber Security and Digital Forensics, Faculty of Computing Science and Engineering, VIT Bhopal University, India; Ramkumar S., Christ University, Bangalore, India; Gobinath R., Christ University, Bangalore, India
Bioactive Compounds and Biological Activities of Ensete Species
Antioxidants; Ensete; Pharmacological activities; Phytochemicals; Traditional medicine
Ensete, commonly known as the false banana, is a plant of the subtropical and tropical regions of Asia and Africa. Ensete has received global attention in the past decade. The various parts of the plant, such as the fruits, fruit peel, corm, pseudostem, seed, leaves, flowers, sap, and roots, have been used in traditional medicine to treat various ailments. Starch and other minor/trace components found in Ensete plants have been used as tablet binders, disintegrants, pharmaceutical gelling agents, and sustained release agents in pharmaceuticals and nutraceuticals. Ensete has been used as a staple and co-staple food by Ethiopians and has many ethnomedicinal uses. The present chapter validates the historic use of various parts of Ensete in treating ailments by providing detailed information on the phytochemicals present in the plant and discussing various biological properties such as antioxidant, antimicrobial, antidiabetic, immunomodulatory, hypolipidemic, cytotoxic, antiurolithiatic, antiestrogenic, nephroprotective, and hepatoprotective properties. Springer Nature Switzerland AG 2024.
Banadka A.; Toppo V.; Sudheer W.N.; Ramakrishnan R.; Lakshmaiah V.V.; Al-Khayri J.M.; Nagella P.
Reference Series in Phytochemistry, Vol-Part F2504, pp. 77-103.
Banadka A., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Toppo V., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Sudheer W.N., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Ramakrishnan R., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Lakshmaiah V.V., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Al-Khayri J.M., Department of Agricultural Biotechnology, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, Saudi Arabia; Nagella P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India
Polyoxometalates and redox-active molecular clusters for supercapacitors
electrochemical energy storage; molecular clusters; Polyoxometalates; rechargeable batteries; supercapacitors
Hybrid electric vehicles and portable electronic devices become inevitable part of our daily life and it is necessary to develop efficient energy storage devices to supply them power. Supercapacitors (SCs) are electrochemical energy storage devices with high power densities. The electrochemical performances of a SC depend mainly on the electrode-active material used in it. An efficient electrode-active material should have qualities such as large surface area, porous structure, uniform pore distribution, good chemical and electrochemical stabilities, and good mechanical strength, to name a few. Mesoporous electrode architecture is highly preferred to obtain maximum electrolyte-ion accessibility that can boost the electrochemical performance of the SC electrode. The various electrode-active materials developed to date are transition metal oxides, electronically conducting polymers, carbon nanomaterials, etc. Polyoxometalates (POMs) are comparatively novel electrode candidates that possess excellent structural stability during the reversible redox reactions. A unique characteristic such as higher oxidation state possessed by POMs makes them an ideal platform to accept and release electrons during the electrochemical charge storage. POMs are considered to be a polyatomic anion, which hold early transition metals like Mo, V, W, etc., and are linked to an oxygen atom in a three-dimensional cluster. The cluster formation of POMs enables higher stability and easy to prepare composites with other materials such as carbon nanomaterial, electronically conducting polymers, etc. The preparation of hybrid electrode architectures by anchoring of POMs helps in producing a large number of electroactive sites for the enhanced electrochemical reactions to occur. This chapter explains the salient features and functionalities of POMs and redox-active molecular clusters that affect the SC performance. 2024 Elsevier Inc. All rights reserved.
Thomas S.A.; Baby A.; Balakrishnan S.P.; Rajendran D.N.; Cherusseri J.
Supercapacitors: Materials, Design, and Commercialization, pp. 221-243.
Thomas S.A., Department of Physics, Government College for Women (Affiliated to University of Kerala), Kerala, Thiruvananthapuram, India; Baby A., Department of Chemistry, CHRIST (Deemed to be) University, Karnataka, Bengaluru, India; Balakrishnan S.P., Department of Chemistry, CHRIST (Deemed to be) University, Karnataka, Bengaluru, India; Rajendran D.N., Department of Physics, Government College for Women (Affiliated to University of Kerala), Kerala, Thiruvananthapuram, India; Cherusseri J., Research Centre for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University, No. 5 Jalan University, Selangor, Bandar Sunway, Subang Jaya, Malaysia
Exploring the Impact of Latent and Obscure Factors on Left-Censored Data: Bayesian Approaches and Case Study
Bayesian estimation; Frailty model; Left censoring; Reversed hazard rate; Survival distributions
In the realm of scientific investigation, traditional survival studies have historically focused on mitigating failures over time. However, when both observed and unobserved variables remain enigmatic, adverse consequences can arise. Frailty models offer a promising approach to understanding the effects of these latent factors. In this scholarly work, we hypothesize that frailty has a lasting impact on the reversed hazard rate. Notably, our research highlights the reliability of generalized Lindley frailty models, rooted in the generalized log-logistic type II distribution, as a robust framework for capturing the widespread influence of inherent variability. To estimate the associated parameters, we employ diverse loss functions such as SELF, MQSELF, and PLF within a Bayesian framework, forming the foundation for Markov Chain Monte Carlo methodology. We subsequently utilize Bayesian assessment strategies to assess the effectiveness of our proposed models. To illustrate their superiority, we employ data from renowned Australian twins as a demonstrative case study, establishing the innovative models advantages over those relying on inverse Gaussian and gamma frailty distributions. This study delves into the impact of hidden and obscure factors on left-censored data, utilizing Bayesian methodologies, with a specific emphasis on the application of generalized Lindley frailty models. Our findings contribute to a deeper understanding of survival analysis, particularly when dealing with complex and unobservable covariates. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Gupta P.; Pandey A.; Hanagal D.D.; Tyagi S.
Springer Series in Reliability Engineering, Vol-Part F2569, pp. 293-320.
Springer Science and Business Media Deutschland GmbH
Gupta P., Department of Statistics, Central University of Rajasthan, Rajasthan, India; Pandey A., Department of Statistics, Central University of Rajasthan, Rajasthan, India; Hanagal D.D., Department of Statistics, Savitri Bai Phule Pune University, Pune, India; Tyagi S., Department of Statistics, Central University of Rajasthan, Rajasthan, India, Department of Statistics and Data Science, Christ Deemed to Be University, Bangalore, India
Translation of supercapacitor technology from laboratory scale to commercialization
commercial supercapacitors; electrochemical energy storage; low-cost supercapacitors; rechargeable batteries; Supercapacitors
This overview chapter discusses the critical process of transforming supercapacitor technology from the laboratory scale to successful commercialization. Supercapacitors possess remarkable energy storage capacity and fast discharge cycles, making them highly promising for diverse applications, including electric vehicles and renewable energy systems. However, transitioning from small-scale prototyping to mass production presents significant challenges, such as scalability, cost-effectiveness, and maintaining consistent performance. The primary objective of this study is to conduct a comprehensive analysis of the main obstacles in the commercialization process and propose strategies and solutions to expedite the market introduction of supercapacitors. By identifying and addressing these hurdles, this research aims to facilitate the rapid and efficient transition of supercapacitor technology into commercial applications. To achieve this goal, the present chapter examines several aspects, including increasing production output, optimizing manufacturing processes, and reducing costs while upholding performance standards. Additionally, this chapter explores methods to ensure the scalability and reliability of supercapacitors, enabling seamless integration into existing energy storage systems. By bridging the gap between laboratory innovation and large-scale production, this study seeks to make a significant contribution to the realization of efficient and sustainable energy storage technologies across various industries. The successful commercialization of supercapacitors holds the potential to revolutionize the field of energy storage and provide viable solutions to global challenges, such as climate change and the transition to cleaner and more sustainable energy sources. In summary, this chapter addresses the challenges involved in transitioning supercapacitor technology from the laboratory scale to commercialization. 2024 Elsevier Inc. All rights reserved.
Thomas S.A.; Mishra R.K.; Baby A.; Balakrishnan S.P.; Rajendran D.N.; Cherusseri J.
Supercapacitors: Materials, Design, and Commercialization, pp. 371-395.
Thomas S.A., Department of Physics, Government College for Women (Affiliated to University of Kerala), Kerala, Thiruvananthapuram, India; Mishra R.K., Enhanced Composites and Structures Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, United Kingdom; Baby A., Department of Chemistry, CHRIST (Deemed to be) University, Karnataka, Bengaluru, India; Balakrishnan S.P., Department of Chemistry, CHRIST (Deemed to be) University, Karnataka, Bengaluru, India; Rajendran D.N., Department of Physics, Government College for Women (Affiliated to University of Kerala), Kerala, Thiruvananthapuram, India; Cherusseri J., Research Centre for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University, No. 5 Jalan University, Bandar Sunway, Selangor, Subang Jaya, Malaysia
Bioactive Compounds and Biological Activities of Cassava (Manihot esculenta Crantz)
Biological activities; Cassava; Food products; Manihot esculenta; Nutrients
The most significant tropical tuberous crop, cassava (Manihot esculenta Crantz), is grown extensively around the world. It has a lot of minerals that have been linked to health benefits, is high in calories, and contains vitamin C, an antioxidant that supports the creation of collagen and boosts immunity. It is known to be the biggest generator of carbohydrates among stable crops, with its roots serving as the main source of starch and dietary energy. Currently, cassava flour is being used in gluten-free or gluten-reduced foods as a novel food application. The cassava plant extract is a rich source of major phytochemicals consisting of flavonoids, tannins, cardiac glycosides, anthraquinone, phlobatannins, saponins, and anthrocyanosides along with other antinutritive factors that contribute to its diverse pharmacological activities like antibacterial activity, in vitro ovicidal and larvicidal activity, antioxidant activity, anti-inflammatory activity, and analgesic and antipyretic activities. This chapter provides a comprehensive overview of the botanical features, production statistics, nutritional composition and benefits, phytochemicals present and their biological activities present in different parts of cassava plants, toxicity, food applications, and various strategies of breeding for crop improvement. Springer Nature Switzerland AG 2024.
Scaria S.S.; Gangwar J.; Kurian J.T.; Jaison J.P.; Sebastian J.K.
Reference Series in Phytochemistry, Vol-Part F2504, pp. 901-935.
Scaria S.S., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Gangwar J., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Kurian J.T., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Jaison J.P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Sebastian J.K., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India
Bioactive Compounds and Biological Activities of Lotus (Nelumbo nucifera Gaertn.)
Bioactive compounds; Lotus; Nelumbo; Nutrition; Pharmaceutical activities
Nelumbo nucifera Gaertn.Nelumbo nucifera Gaertn.Lotus (Nelumbonaceae A. Rich.) is a beautiful aquatic flowering plant with a subterranean rhizome. With a vast array of culinary applications and a storehouse of bioactive compounds in its plant parts, N. nucifera functions as both an underground food crop and a valuable medicinal plant. With a more than 7,000-year history of cultivation, this plant is one of the few aquatic plants used as a vegetable. N. nucifera possesses copious amounts of alkaloids and flavonoids as phytochemicals, along with various other derivatives. The rhizome is consumed as a vegetable since it has more carbohydrates, proteins, and vitamins, and it also possesses phytocompounds that exhibit immunomodulatory, antiviral, and antioxidant properties. Many countries in Asia use N. nucifera starch as a major culinary ingredient. To date, many phytochemicals isolated from this plant are used in many medicinal systems, including traditional, Ayurvedic, herbal, and oriental medicine. The extracts of various organs of this plant are used to treat numerous types of cancers, cardiac diseases, liver ailments, diabetes, and nervous disorders. The flower extracts are effective against fever, adipsia, cholera, and diarrhea. Eaten raw or puffed, lotus seeds are high in protein and contain minerals like calcium, phosphorus, iron, and potassium. The seeds are used as antibiotics to cure skin diseases like leprosy. Chinese medicine uses lotus seeds to treat renal and cardiac problems. Accordingly, N. nucifera is employed in food, medicine, culture, and religion. Furthermore, N. nucifera is an excellent environmental adapter and has the capacity to modify its resistance to environmental stress in order to adapt to a variety of abiotic stresses including flooding, extremely high temperatures, salt, low light, and heavy metals. It can therefore be grown in a variety of environments. Although this aquatic crop is restricted to an extensive geographical region and has a huge variety of cultivars, many parts of the world are still uninformed about this crop. Therefore, it is crucial to comprehend the medicinal and nutritional benefits of this tuberous crop in order to investigate it as a potential replacement for present-day food crops as well as a source of medicine. In order to effectively utilize this aquatic underground crop, this chapter aims to embody the nutritional advantages, traditional uses, phytochemistry, and bioactivity of the phytocompounds from the various parts of N. nucifera. It also emphasizes lotus breeding to date, applications as food, cultural aspects, and future production of potential N. nucifera underground crops of the highest quality. Springer Nature Switzerland AG 2024.
Dandin V.S.; Sebastian J.K.; Dalavi J.V.; Nagella P.; Madhav N.A.; Khot V.V.
Reference Series in Phytochemistry, Vol-Part F2504, pp. 541-587.
Dandin V.S., Department of Biology, JSS RSH PU College, Vidyagiri, Karnataka, Dharwad, India; Sebastian J.K., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Dalavi J.V., Department of Botany, Balwant College, Maharashtra, Vita, India; Nagella P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Madhav N.A., Department of Botany, HPT Arts & RYK Science College, Maharashtra, Nashik, India; Khot V.V., Department of Botany, Balwant College, Maharashtra, Vita, India
Redefining Organizational Sustainability Through Revamping Digital Capital
Technical and Vocational Education and Training, Vol-38, pp. 447-455.
Thomas J.V., Christ (Deemed to be University), Karnataka, Bengaluru, India; Sankar M.M., Christ (Deemed to be University), Karnataka, Bengaluru, India
CRISPR-Cas9 genome editing of crops: Food and nutritional security
CRISPR-Cas9; Crop improvement; Food safety; Food security; Genome editing; Molecular breeding; Nutritional security
The United Nations established the goal of achieving global food security by 2030 as one of its top sustainable development goals in 2015. The current agricultural harvest is insufficient to accomplish the zero-hunger objective and feed the world's growing population. It would require more extensive and consistent crop production. Gene-editing technologies have recently emerged as viable alternatives to permit precise modifications in genomes with increased efficiency and yield higher agricultural productivity. Due to their simplicity, adaptability, and reproducibility across a diverse variety of species, genetic engineering techniques like CRISPR-Cas9 have become quite prominent. CRISPR-Cas9 gene-editing technology can improve crop yields, quality, stress resistance, food safety, nutritional security, and shelf-life, reduce antibiotic resistance, and hasten plant domestication. Cutting-edge techniques like genome editing (GE) allow for the precise introduction or mutation of specified genes into plant genomes. The advent of programmable nucleases like CRISPR-Cas9 has improved gene editing and potentially improved food production and nutritional security. Knock-out, knock-in, gene activation, gene repression, nuclear rearrangements, base editing, molecular breeding, and epigenome engineering are just a few ways that CRISPR systems can target and change genes. For novel applications in plant genetic engineering, CRISPR-Cas systems can be repurposed for GE toward de-novo speciation; mitochondrial and plastid genome engineering toward enhancing photosynthesis, submergence, and drought tolerance. The versatility of CRISPR-associated systems broadens the scope of crop development applications that they can be used for, especially in improving food and nutritional security, which is the focus of this chapter. 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
R Krishnan R.; Sivakumar B.; Jagannath N.; Rao N.R.; Suresh N.; Nagella P.; Al-Khayri J.M.; Jain S.M.
CRISPRized Horticulture Crops: Genome Modified Plants and Microbes in Food and Agriculture, pp. 161-190.
R Krishnan R., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Sivakumar B., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Jagannath N., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Rao N.R., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Suresh N., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Nagella P., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Al-Khayri J.M., Department of Agricultural Biotechnology, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, Saudi Arabia; Jain S.M., Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland