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The COVID-19 pandemic has put a strain on the entire global healthcare infrastructure. The pandemic has necessitated the re-invention, re-organization, and transformation of the healthcare system. The resurgence of new COVID-19 virus variants in several countries and the infection of a larger group of communities necessitate a rapid strategic shift. Governments, non-profit, and other healthcare organizations have all proposed various digital solutions. It's not clear whether these digital solutions are adaptable, functional, effective, or reliable. With the disease becoming more and more prevalent, many countries are looking for assistance and implementation of digital technologies to combat COVID-19. Digital health technologies for COVID-19 pandemic management, surveillance, contact tracing, diagnosis, treatment, and prevention will be discussed in this paper to ensure that healthcare is delivered effectively. Artificial Intelligence (AI), big data, telemedicine, robotic solutions, Internet of Things (IoT), digital platforms for communication (DC), computer vision, computer audition (CA), digital data management solutions (blockchain), digital imaging are premiering to assist healthcare workers (HCW's) with solutions that include case base surveillance, information dissemination, disinfection, and remote consultations, along with many other such interventions.

The paper seeks to address issues that arise during the drilling and fixation of bones in orthopedic, orthodontic and implant surgeries. Thermal necrosis is one of the widespread problems that occurs during bone/tooth drilling and which can lead to implant failures. The highest registered temperature during drilling is 86°C. However, when the temperature is increased beyond 47° C during the drilling process, it can often lead to osteonecrosis. The possibility of thermal necrosis can be minimized by controlling the drilling parameters. However, optimal parameter values identified by various researchers have not been complied so far, primarily because of the effects of multifactorial constraints. Overall, the drilling bore speed and the feed rate are found to be the most influential parameters in triggering thermal injuries in the course of time. The drilling speed is also more important to the feed rate. In addition, osteological location also increases the probability of necrosis by multiple means in terms of anatomy. A thermocouple is used to evaluate in vivo temperature conditions during the drilling process. However, given the uncertainty and the practical errors that occur during the experimental measurements, the finite-element analysis (FEA) is proposed in most studies. This paper explores the existing state of literature and summarizes various drilling methods and assess the related parameters using FEA. It also describes the impact of various constraints in detail to explore the optimum drilling parameters in order to minimize the danger of thermal necrosis.

Electric vehicles (EVs) are one of the near-term practical solutions in-vehicle technology, which can reduce emissions leading to the greenhouse effect and dependence on fossil fuels that are correlated with conventional vehiclesconventional vehicles (CVs). Several interferences are yet to be overcome for widespread adoption of EVs, despite many benefits provided to the consumers. The tendencies of customers to resist new technology is one of the major barriers in EV adoption. Hence, the policy-related decisions that showing grim concerns of EV have a greater level of success. This research aims to identify potential environmental and socio-technical barriers to purchase of EVs and it determines if governmental policies and awareness of individuals affect the customer decisions purchasing an EV. This research tries to convey valuable insights into perceptions and preferences of technology enthusiasts, individuals who are greatly connected to latest technology developments, and those who are well equipped to sort out the numerous differences between CVs and EVs. These results can provide direction to EV engineer’s decision in including customer preference into EV engineering design. It can also help policymakers in developing transportation and energy policies. A survey-based study was conducted with a sample of 1230 people from urban cities of emerging Asian markets, i.e. India and Srilanka. The data collected were analyzed, which found perception of economic benefits, functional characteristics of EVs, awareness, knowledge, and familiarity of EVs as significant parameters, which directly have an impact on the purchase behavior of fully EVs.

Drilling is a salient machining process employed in assembling the components and structures made from polymer composites. Influence of various drilling process parameters on the drilling process has been identified and controlled to maintain the integrity of the composite material and avoid material damage during drilling. The precision of drilling depends upon many process parameters like feed rate, tool material, cutting speed, drill diameter, fiber orientation in composite material and thrust forces developed. The present investigation deals with the study and evaluation of influence of drilling parameters such as material thickness, drill diameter, drill point angle, feed rate and spindle speed on thrust force developed during drilling of glass fiber reinforced plastic composite laminates using Taguchi method. The experimental results prove that drill angle and the spindle speed are the most significant parameters which influence the thrust force. The simulation of the drilling process was developed using a novel system dynamics (SD) modelling approach through a causal loop diagram. Design of experiments (DOE) was utilized to generate a number of experiments required. A full factorial design is used, and 243 holes were drilled to collect the experimental data. The required mathematical equation for modelling was developed by using DOE method. To validate the SD results, the results obtained through SD novel approach were compared with artificial neural network and response surface method which are recognised as the best simulation tools and noticed a good agreement between the values obtained. The novel SD approach of modelling showed an agreement of more than 93% acceptance level with the experimental results.