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The purpose of the study is to examine the influence of the corn biofuel on the Jet engine. Each tests were carried out in a small gas turbine setup. The performance characteristics of thrust, thrust-specific fuel consumption, exhaust gas temperature and emission characteristics of Carbon monoxide(CO), Carbon dioxide (CO₂), Oxygen (O₂), Unburned hydrocarbons (UHC) and Nitrogen of oxides (NO) emissions were measured and compared with Jet-A fuel to find the suitability of the biofuel used.

Upgrading and using biofuels in aviation sector have been emerging as a fruitful method to diminish the CO emission into the atmosphere. This research paper explores the possibility of using nanoparticles-enriched bio-oil as a fuel for jet engines. The biofuel taken is corn oil and the added nanoparticles are Al₂O₃.

The biofuel blends used are B0 (100% Jet-A fuel), B10 (10 % corn oil biofuel + 90% Jet-A fuel), B20 (20% corn oil biofuel + 80% Jet-A fuel) and B30 (30% corn oil biofuel + 70% Jet-A fuel). All fuel blends were mixed with the moderate dosage level of 30 ppm. All tests were conducted at different rpm as 50,000, 60,000, 70,000 and 80,000 rpm.

The results proved that within the lower limit, use of biofuel increased the performance characteristics and reduced the emission characteristics except the emission of NO. The moderate-level biofuel with Jet-A fuel showed the equally better performance to the neat Jet-A fuel.

The food organisations are pushing to adopt circular economy initiatives to enhance economic–ecological–social sustainability of supply chains. The adoption of circular economy and sustainability aspects is complex from the point of view of developing nations compared to the developed nations. In this sense, the purpose of this paper is to develop a model of the challenges for implementing the successful circular economy-led sustainability concepts in food supply chains in emerging economies, especially in the Indian context.

The authors recognised 11 circular economy-led sustainability-related challenges and analysed appropriate interactions among the identified challenges. The Delphi method was used for the confirmation of identified challenges. The challenges were identified initially with the help of literature. Interpretive structural modelling method was used for modelling the challenges. In addition, MICMAC analysis was used for classifying the challenges based on their dependence and driving power. A case study of diary food processing company in India was conducted.

According to the findings, poor government policies, lack of technology and techniques and lack of farmers’ knowledge and awareness come under the driving challenges.

Understanding of circular economy-led sustainability-related challenges would help managers and policy makers in the sustainable management of natural resources in food value chains.

This is one of the initial works conducted on identifying and evaluating the challenges to circular economy-based sustainability aspects in food value chains.

Sustainable consumption and production (SCP) assist managers to improve their operational efficiency while aiming at reducing the generation of waste. The purpose of this paper is to construct a structural model of the SCP practices in a supply chain context.

The work is based on the experience of supply chain professionals, a case study and literature review related to SCP. The present work recommends an assessment framework by prioritizing the SCP oriented practices using best-worst method.

The current work is an effort to understand the significance of SCP practices and to reveal their level of influence in developing a sustainable culture in value chains. Data for this work are derived from an automotive company operating in India. Findings reveal that the “resource efficiency” acquires the highest rank and “sharing assets” acquires the last lank among all SCP practices.

It is difficult to finalize the SCP practices. This work uses the expert’s approach for this. In this way, the process needs to be conducted very carefully.

This research can assist automotive managers and practitioners in efficiently utilizing their companies’ resources, which would result in superior business effectiveness by generating higher employment opportunities in value chains.

Efforts have been made to contribute in the identification and analysis of SCP oriented practices. The developed structural model will help in understanding the ranking of practices.

The purpose of this study is to identify the accelerators of sharing economy that lead to sustainability by adopting green consumption. Nostalgia is studied as a mediator along with social connectedness and past orientation. Specifically, the study is based upon a framework to explore the outcomes of sharing economy through an individual's green consumption behavior from the perspective of mortality anxiety.

Quantitative research technique was employed by collecting data from 537 households through snowball sampling. The model was tested using partial least squares (SEM-VB). The validity of the theoretical and measurement model was assessed.

The results revealed that nostalgia positively influences social connectedness and past orientation, whereas social connectedness and past orientation accelerate green consumption. However, it was confirmed that nostalgia decreases green consumption.

The drivers of sharing economy lead toward environmentally friendly consumer behavior by providing opportunities for different agents to increase the usage of shared consumption. The model can be improved by introducing other mediating variables to enrich understanding.

The study may provide opportunities for practitioners and the government to identify the key factors in a sharing economy, specifically with reference to green consumption and social connectedness. It is predicted that it will help reduce environmental deterioration.

This study identifies the role of mortality anxiety and nostalgia toward green consumption, predominantly in the context of a sharing economy. It is a forward to collaborative consumption.

The present study aims to summarize different non-invasive techniques for continuous glucose monitoring (CGM) in diabetic patients using glucose-oxidase biosensors. In diabetic patients, the self-monitoring of blood glucose (BG) levels through minimally invasive techniques provides a quick method of measuring their BG concentration, unlike conventional laboratory measurements. The drawbacks of minimally invasive techniques include physical pain, anxiety and reduced patient compliance. To overcome these limitations, researchers shifted their attention towards the development of a pain-free and non-invasive glucose monitoring system, which showed encouraging results.

This study reviews the development of minimally and non-invasive method for continuous glucose level monitoring in diabetic or hyperglycemic patients. Specifically, glucose monitoring using non-invasive techniques, such as spectroscopy-based methods, polarimetry, fluorescence, electromagnetic variations, transdermal extraction-based methods and using body fluids, has been discussed. The various strategies adopted for improving the overall specificity and performance of biosensors are discussed.

In conclusion, the technology of glucose oxidase-based biosensors for glucose level monitoring is becoming a strong competitor, probably because of high specificity and selectivity, low cost and increased patient compliance. Many industries currently working in this field include Google, Novartis and Microsoft, which demonstrates the significance and strong market potential of self-monitored glucose-oxidase-based biosensors in the near future.

This review paper summarizes comprehensive strategies for continuous glucose monitoring (CGM) in diabetic patients using non-invasive glucose-oxidase biosensors. Non-invasive techniques received significant research interest because of high sensitivity and better patient compliance, unlike invasive ones. Although the results from these innovative devices require frequent calibration against direct BG data, they might be a preferable candidate for future CGM. However, the challenges associated with designing accurate level sensors to biomonitor BG data easily and painlessly needs to be addressed.

“Fake news” or misinformation sharing using social media sites into public discourse or politics has increased dramatically, over the last few years, especially in the current COVID-19 pandemic causing concern. However, this phenomenon is inadequately researched. This study examines fake news sharing with the lens of stimulus-organism-response (SOR) theory, uses and gratification theory (UGT) and big five personality traits (BFPT) theory to understand the motivations for sharing fake news and the personality traits that do so. The stimuli in the model comprise gratifications (pass time, entertainment, socialization, information sharing and information seeking) and personality traits (agreeableness, conscientiousness, extraversion, openness and neuroticism). The feeling of authenticating or instantly sharing news is the organism leading to sharing fake news, which forms the response in the study.

The conceptual model was tested by the data collected from a sample of 221 social media users in India. The data were analyzed with partial least squares structural equation modeling to determine the effects of UGT and personality traits on fake news sharing. The moderating role of the platform WhatsApp or Facebook was studied.

The results suggest that pass time, information sharing and socialization gratifications lead to instant sharing news on social media platforms. Individuals who exhibit extraversion, neuroticism and openness share news on social media platforms instantly. In contrast, agreeableness and conscientiousness personality traits lead to authentication news before sharing on the social media platform.

This study contributes to social media literature by identifying the user gratifications and personality traits that lead to sharing fake news on social media platforms. Furthermore, the study also sheds light on the moderating influence of the choice of the social media platform for fake news sharing.