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The purpose of this paper is to identify coronavirus contact using internet of things. The disease is said to be highly contagious with the contact of infected persons. Feared to be air-borne, droplets of body fluids can transmit the disease in a matter of hours. The predominant symptoms of the COVID-19 are high fever, cough, breathing problem, etc. Recent studies have demonstrated the evolution of the disease to hide its symptoms. As it is highly transmissible, this disease might spread at an exponential rate costing the lives of thousands of people. The chain of transmission has to be detected with utmost priority through early detection and isolation of infected people. Automated internet of things (IoT) devices can be used in design and implementation of a prediction scheme for reporting the health-care risks of the patients with various parameters such as temperature, humidity and blood pressure.

IoT is a configuration of multiple autonomous and embedded wireless devices for serving a purpose. Every object possesses an individual identity and will serve to register critical events as entries for future learning and decisions. IoT plays an inevitable role in medical industries, detection of vital signs of diseases and monitoring. Among other life-threatening diseases, a new pandemic is on rise among world nations. COVID-19, a novel severe acute respiratory syndrome virus originated from animals in December 2019 and is becoming a serious menace to Governments, despite serious measures of lockdowns.

In this paper, the authors defined an architecture of an IoT system to predict the Covid-19 disease by getting the data from the human through sensors and send the data to the doctor using mobile, computer, etc. The main goal is early health surveillance by predicting COVID-19. Accordingly, the authors are able to identify both symptomatic and asymptomatic patients, which will help in the early prediction of disease.

Using the proposed method, the authors can save the time of both patient and doctor by ensuring timely medical treatment and contribute toward breaking the transmission chain. In so doing, the method also contributes toward avoiding unnecessary expenses and saving human lives.

The purpose of this study was to evaluate six different fruits from the Cerrado as to their chemical and bioactive properties.

Six different fruits from the Cerrado (araticum, baru, jatoba-do-cerrado, lobeira, macauba and pequi) were characterized regarding moisture, ash, lipids, proteins, carbohydrates, carotenoids, chlorophyll, ascorbic acid, flavonoids, phenolic compounds and their antioxidant activities.

The highest flavonoid content, which was found in araticum pulp, was significantly different from the ones of other fruit pulps. The carotenoid content of pequi pulp was 12-fold the one of lobeira pulp. The vitamin C content of baru pulp was five-fold the Reference Daily Intake (RDI). In relation to the antioxidant activity, araticum (5.7 µM/g) and jatoba (5.2 µM/g) pulps exhibited the highest values (p < 0.01). Both baru and araticum pulps were capable of capturing the radical with mean percentage of discoloration of 68.7 and 67.4%, respectively (p < 0.01).

Native fruits of the Cerrado have been poorly described in the literature, even though they are highly consumed in the region. Publicizing their nutritional characteristics can increase the commercial value of these fruits, which have been traditionally devalued. In addition, knowledge of new sources of nutrients contributes to their use by pharmaceutical and food industries.

This paper explores the role of Internet of things (IoT) enabling factors in adopting digital supply chain.

Analytical hierarchy process (AHP) was used to rank performance measures and prioritise the enabling factors. Semi-structured interviews were conducted to validate and support key research findings from the AHP analysis.

The results show that level of customer demand is the most important indicator in adopting IoT while the level of product/process flexibility is the least important. System integration and IoT infrastructure are the top two enabling factors in increasing the level of process stability, supply chain connectivity, and product/process flexibility, respectively. Furthermore, the study suggests that the enabling factors for IoT adoption are directly connected with organisational resources/technological capabilities that support the resource-based view theory. This research identified interdependencies between IoT enabling factors and key performance measures for IoT adoption success in managing the digital supply chain.

Supply chain managers can use the empirical findings of this study to prioritise IoT adoption, based on the relative importance of enabling factors and performance measures. The research findings are focused on broader supply chain practices of large companies rather than a specific industry and SMEs. Hence, any industry-specific adoption factors and SMEs were not evident from this study.

This research study empirically established priorities of enabling factors for IoT adoption, along with inter-dependencies among enabling factors as a basis for developing guidelines for IoT adoption.

The purpose of the research is to concentrate on the most important smart metropolitan applications which are smart living, smart security and smart maintainable. In that, Power management and security is a most important problem in the current metropolitan situation.

A smart metropolitan area utilizes recent innovative technologies to improve its living, security and maintainable. The aim of this study is to recognize and resolve the difficulties in metropolitan area applications.

The main aim of this study is to reduce the metropolitan foremost energy consumption, to recharge the electric vehicles and to increase the lifetime of smart street lights.

The hybrid renewable energy street light applies smart resolutions to substructure and facilities in rural and metropolitan areas to create them well. This study will be applying smart metropolitan solar and wind turbine street light using renewable energy for existing areas. In future, the smart street light work will be implemented everywhere else.

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.

In response to the growing demand for a polymer with improved chemical and thermal stability in the construction sector, this study aims to thoroughly explore the characteristics of silver nanoparticles (AgNP) and their various concentrations. The primary goal is to determine the effect of these nanoparticles on the chemical and thermal stability of unsaturated polyester (UPE) resin doped with dimethyl-para-toluidine (DMPT) when exposed to high temperatures.

Silver nanoparticles were first synthesized from the chemical reaction between silver nitrate and trisodium citrate before its addition to the resin. The nanocomposites were thoroughly examined using advanced analytical methods such as Fourier transform (FTIR), Raman spectroscopy and scanning electron microscope to determine chemical stability. Thermal stability tests were carried out using thermogravimetric analysis, differential thermal analysis and derivative thermogravimetry methods; viscosity and peak exotherm were also examined.

The data shows that increasing nanoparticle concentration improves resin chemical stability, reduces peak exotherm duration and increases viscosity. Clearly, only 1.5% AgNP concentration outperformed neat UPE resin, while 0.5% and 1% AgNP concentrations fall short in terms of thermal stability.

The enhanced resin highlights the subtle influence of nanoparticle addition, which has a greater impact on the chemical structure of the composite rather than its thermal properties.

Designing a sustainable bituminous concrete with long-term performance is a challenging problem. In addition, strength of the subgrade has a crucial impact on pavement design. This paper aims to concentrate on subgrade soil stabilization with granite dust powder (GDP) and crumb rubber powder (CRP) to improve the engineering properties of the soil. Further design of bituminous concrete pavement with cement-treated layers in base and subbase course layers was carried out with life cycle cost analysis and life cycle assessment for 1 km of a four-lane national highway.

Subgrade soil stabilized with GDP and CRP is characterized as per Indian Standards (IS)-2720 to determine the optimum dosage. Further, the mechanistic-empirical pavement design was carried out using Indian Road Congress-37 (2018), analyzed using IITPAVE software and validated with ANSYS software. The life cycle cost analysis is carried out using the net present value method, and the life cycle assessment is performed according to the cradle-to-grave approach.

A soil mix comprising 10% GDP and 2.5% CRP yielded a soaked California bearing ratio value of 6.58%. In addition, the design of bituminous concrete pavement with cement-treated granular layers showed a 26.9% reduction in life cycle cost and 59.4% reduction in total carbon footprint per kilometer compared to the pavement with traditional aggregate layers.

The research on subgrade stabilization with sustainable materials like GDP and CRP incorporating mechanistic empirical pavement design, life cycle cost analysis and life cycle assessment is limited. Overall, the study recommends the use of GDP and CRP to stabilize soil for subgrade application and incorporate cement-treated granular layers, which offer economic and environmental benefits compared to traditional pavement construction.

The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles from well-known databases revealed that earlier research in the field had not specifically addressed how the BRIC stock markets responded to the COVID-19 pandemic. The data regarding COVID-19 were collected from the World Health Organization (WHO) website, and the stock market data were collected from Yahoo Finance and the respective country’s stock exchange. A random forest regression algorithm takes the closing price of respective stock indices as target variables and COVID-19 variables as input variables. Using this algorithm, a model is fit to the data and is visualised using line plots. This study’s findings highlight a relationship between the COVID-19 variables and stock market indices. In addition, the stock market of BRIC countries showed a high correlation, especially with the Shanghai Composite Stock Index with a correlation value of 0.7 and above. Brazil took the worst hit in the studied duration by declining approximately 45.99%, followed by India by 37.76%. Finally, the data set’s model fit, which employed the random forest machine learning method, produced R² values of 0.972, 0.005, 0.997, and 0.983 and mean percentage errors of 1.4, 0.8, 0.9, and 0.8 for Brazil, Russia, India, and China (BRIC), respectively. Even now, two years after the coronavirus pandemic started, the Brazilian stock index has not yet returned to its pre-pandemic level.

The purpose of this work is to investigate the effect of oxide-coated steel in comparison with mild steel fibers on the tribological and corrosion performances of friction composites.

In this study, the friction composites were developed in the form of standard brake pads by using oxide-coated steel and compared with mild steel fibers-based one without varying the other ingredients. The brake pads were developed as per the industrial procedure. The physical, mechanical, thermal properties of the developed brake pads were analyzed as per the industrial standards. The tribological properties were analyzed using the Chase test. The worn surface analysis was done using scanning electron microscope. Corrosion behavior was also analyzed in both salt and normal water conditions.

The experimental results indicate that the oxide-coated steel-based friction composites brake pads possess good physical, chemical, thermal, corrosion resistance and mechanical properties with stable fade and recovery characteristics because of its oxide coating and flake morphology.

This paper explains the influence of oxide-coated steel in friction composites for enhancing the tribological performance and corrosion resistance by its oxide coating and flake morphology which could potentially replace mild steel fibers-based problems in friction composites.

3D food printing technology is an emerging smart technology, which because of its inbuilt capabilities, has the potential to support a sustainable supply chain and environmental quality management. This new technology needs a supportive ecosystem, and thus, this paper identifies and models the enablers for adopting 3D printing technology toward a sustainable food supply chain.

The enablers were identified through an extensive literature review and verified by domain experts. The identified enablers were modelled through the hybrid total interpretive structural modelling approach (TISM) and the decision-making trial and evaluation laboratory (DEMATEL) approach.

It emerged that stakeholders need technical know-how about the 3D printing technology, well supported by a legal framework for clear intellectual property rights ownership. Also, the industry players must have focused and clear strategic planning, considering the need for sustainable supply chains. Moreover, required product innovation as per customer needs may enhance the stakeholders' readiness to adopt this technology.

The framework proposed in this research provides managers with a hierarchy and categorization of adoption enablers which will help them adopt 3D food printing technology and improve environmental quality.

This research offers a framework for modelling the enablers for 3D food printing to develop a sustainable food supply chain using the TISM and DEMATEL techniques.