Potential Roles of Phytochemicals in Combating Severe Acute Respiratory Syndrome Coronavirus Infection

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent of the current ongoing global pandemic COVID-19 is yet far away from the clutches of contemporary western medicines. With the lack of conventional drugs for this deadly disease the scope for the development of herbal formulations and Ayurvedic medication is finding a sound basis in the current scenario. The past two years has witnessed detailed and focused investigations on the biologically active constituents derived from a range of medicinal plants and their potential antiviral properties against SARS-CoV-2. The promising results of these investigations have intrigued the medical and plant experts in pharmacognosy enough to consider herbal medicines and plant-based products as they are more effective in combating the COVID-19 crisis. However, a large-scale application of the same would require more focused and thorough research on this matter. This review is an attempt to describe the current and future prospects of using medicinal plants and herbal compounds as natural and sustainable alternative for treating COVID-19. The current article evaluates the various strong evidences from biochemical and molecular studies that have been investigated so far in the development of herbal formulations to combat COVID-19 with detailed focus on the most potential phytochemicals of medicinal plants studied in this regard namely Withania somnifera (L.) Dunal, Cinchona officinalis L., Curcuma longa L., Ocimum sanctum L., Azadirachta indica A. Juss., and Tinospora cordifolia (Willd) Miers

IoT-Based System for Automated Accident Detection and Rescue

One of the most common causes of death is auto accidents. The worst thing that may happen to a road user is a traffic accident, despite the fact that they happen regularly. The worst part is that we fail to learn from our on-the-road errors. Most people who use roads regularly are extremely familiar with the fundamental guidelines and safety procedures that should be followed, but it is only their own negligence that results in accidents and wrecks. Accidents and crashes are primarily caused by human error. Here are some examples of normal human actions that result in accidents. 1. Driving too fast; 2. Driving while intoxicated; 3. Distracting the driver; 4. Running red lights; 5. Avoid utilizing safety equipment, such as seatbelts and helmets; 6. Driving erratically and overtaking improperly in order to save lives in a traffic collision, we’re going to construct an Arduino-based car accident alert system that combines GPS, GSM, and an accelerometer. If the accelerometer detects an abrupt shift in the vehicle’s axis, the GSM module alerts you and communicates the location of the accident to your cell phone. The GPS module’s latitude and longitude are utilized to pinpoint the accident’s location, which is provided as a Google Map link. The message also contains the vehicle’s speed in knots

Anesthesia for joint replacement surgery: Issues with coexisting diseases

The first joint replacement surgery was performed in 1919. Since then, joint replacement surgery has undergone tremendous development in terms of surgical technique and anesthetic management. In this era of nuclear family and independent survival, physical mobility is of paramount importance. In recent years, with an increase in life expectancy, advances in geriatric medicine and better insurance coverage, the scenario of joint replacement surgery has changed significantly. Increasing number of young patients are undergoing joint replacement for pathologies like rheumatoid arthritis and ankylosing spondylitis. The diverse pathologies and wide range of patient population brings unique challenges for the anesthesiologist. This article deals with anesthetic issues in joint replacement surgery in patients with comorbidities

Robotic invasion of operation theatre and associated anaesthetic issues: A review

A Robotic device is a powered, computer controlled manipulator with artificial sensing that can be reprogrammed to move and position tools to carry out a wide range of tasks. Robots and Telemanipulators were first developed by the National Aeronautics and Space Administration (NASA) for use in space exploration. Today’s medical robotic systems were the brainchild of the United States Department of Defence’s desire to decrease war casualties with the development of ‘telerobotic surgery’. The ‘master-slave’ telemanipulator concept was developed for medical use in the early 1990s where the surgeon’s (master) manual movements were transmitted to end-effector (slave) instruments at a remote site. Since then, the field of surgical robotics has undergone massive transformation and the future is even brighter. As expected, any new technique brings with it risks and the possibility of technical difficulties. The person who bears the brunt of complications or benefit from a new invention is the ‘Patient’. Anaesthesiologists as always must do their part to be the patient’s ‘best man’ in the perioperative period. We should be prepared for screening and selection of patients in a different perspective keeping in mind the steep learning curves of surgeons, long surgical hours, extreme patient positioning and other previously unknown anaesthetic challenges brought about by the surgical robot. In this article we have tried to track the development of surgical robots and consider the unique anaesthetic issues related to robot assisted surgeries

Study on Ductility of Ti Aluminide Using Artificial Neural Network

Improvement of ductility at room temperature has been a major concern on processing and application of Ti aluminides over the years. Modifications in alloy chemistry of binary alloy (Ti48 Al) and processing conditions were suggested through experimental studies with limited success. Using the reported data, the present paper aims to optimize the experimental conditions through computational modeling using artificial neural network (ANN). Ductility database were prepared, and three parameters, namely, alloy type, grain size, and heat treatment cycle were selected for modeling. Additionally, ductility data were generated from the literature for training and validation of models on the basis of linearity and considering the primary effect of these three parameters. Model was trained and tested for three different datasets drawn from the generated data. Possibility of improving ductility by more than 5% is observed for multicomponent alloy with grain size of 10–50 μm following a multistep heat treatment cycle