ABSTRACT
In load frequency control (LFC) study of a large power system, the key concept is control area, which is the segment of the system consisting of strongly interconnected buses, generator buses thereof working in unison. For accurate linearization of load frequency control problem, proper determination of control area is important. In the present work, a novel deterministic method is proposed and formulated to calculate the sharing of load changes by the generators to determine the control areas for LFC study of multimachine systems. This method is applied on a weakly interconnected two-area system and then on the 10-Machine New England Test System for area segmentation of each of the two systems. Furthermore, LFC studies are carried out with proposed Fuzzy Rule-tuned PID controllers (FRT-PID Controllers) for both the systems incorporated with Dish-Stirling Solar thermal system (DSTS) in each area. The scaling factors and the controller gains are optimized using Coronavirus Herd Immunity Optimizer Algorithm (CHIOA). Performance of the proposed FRT-PID controllers is compared with that of the Conventional PID controllers for the LFC studies of the systems. To test effectiveness of the FRT-PID controllers, effect of random step load perturbation (SLP) in load buses located in different areas are considered. © 2023 Elsevier B.V.
ABSTRACT
Emissions of black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) from various anthropogenic activities are often reported, yet cultural practices such as the multi-day Diwali festival and its influences on the emissions of these compounds are often overlooked. Major activities during this festival include burning rows of oil-filled earthen lamps (diyas) and fireworks (bursting of crackers). A comprehensive field investigation was conducted to document the role of Diwali celebrations on the releases of BC and PAHs during the ongoing Covid pandemic. The results show that large-scale releases of BC and PAHs were observed on the first day of Diwali compared to the remaining four days. BC and PM2.5 mass concentrations throughout the monitoring period ranged from 3.24 to 27.64 µg m−3 and 83.33 to 288.13 µg m−3, respectively. The source apportionment was performed based on the calculated backward trajectories. The results show that the contribution of fossil fuel emission at Adityapur (ADP), Sakchi (SAK), and Gamharia (GMA) was approximately 36.1 %, 34.4 %, and 55.56 %, while biomass burning contribution was approx. 56.9 %, 59.9 %, 41.67 %, respectively. The result showed that fossil fuel emissions were lower compared to biomass combustion during Diwali. Simultaneously, PAHs diagnostic ratio showed that vehicular discharge and coal burning significantly contributed to PAHs at these study sites. © 2022 The Author(s)
ABSTRACT
Information and Communication Technology (ICT) in the realm of education is the mode of education that uses technology to improve the learning process and enhance interaction with the students. The Covid 19 pandemic has made the usage of technology in imparting knowledge more crucial in the last two years. There has been continuous investment in ICT in the higher education, however the adoption rates have not been very promising. On further investigation into poor technology adoption rates, it was revealed that even though teachers play a very crucial role in the ICT adoption in education, but there is a considerable gap between the expectations and how ICT is used in their daily teaching and learning processes. It has become the need of the hour to study and analyse why few teachers are more prone to adopting technology in their work area. The integration of technology into education is found to be significantly dependent on the attitude and personality traits of the teachers. The objective of the article is to understand why certain people in academics adopt technology more than others and the investigate on the possibility of a relationship between the individual personality trait and the adoption behavior of teachers in higher education. The paper concludes with hypothesis around the relationship between personality traits and ICT adoption in academics along with studying the impact of moderating elements that would influence the relationship. © 2022 University of Stockholm. All rights reserved.
ABSTRACT
The pandemic COVID-19 is an infectious respiratory illness caused by SARS CoV-2 (severe acute respiratory syndrome coronavirus-2) and it spreads human-to-human. Due to the COVID-19 outbreak, the world is facing an unprecedented loss of lives around the globe and highlighted an effective treatment to deal with the virus. Natural products have historically been utilized for respiratory disease and display promising toxicity. Natural products have been reported for several antiviral activities of viruses, like influenza, HIV and some coronaviruses SARS-CoV and MERS-CoV. Therefore, natural products could be a vital resource for developing efficient and safe antiviral drugs against COVID-19. This review summarized the inhibition of isolated compounds from medicinal plants against different coronaviruses which could lead to the development of effective antiviral drugs to counter COVID-19. © 2022, Rasayan Journal of Chemistry, c/o Dr. Pratima Sharma. All rights reserved.
ABSTRACT
In this study we draw a comparison between the trends in the growing cases of novel coronavirus after the administration of vaccine doses. We compare two scenarios where how the trends have changed after the vaccine has been administered and how the trend would have looked if there were no vaccines present. This study can be used to determine the early changes that the vaccines have brought about in the trends and how much reliability do they show in preventing the cases from rising further. The predictions are made using a Weibull based Long-Short-Term-Memory approach which is also being used by the National Health Service of the UK on a dataset that takes into account features like age groups, air traffic, developmental index of the country, average temperatures of a country, which are detrimental in determining the rate of infection and deaths accurately. The model is tested on data gathered from multiple countries and the results are drawn after analyzing the result for each country as an individual entity for the conclusion to be reliable. With an increasing market competition and not so long testing period given to these vaccines which have made it to the common masses we feel this study can help predict how effectively the vaccines will be able to improve immunity against this virus and is it a viable option to invest such large capital in development and purchase of these vaccines preferring it over the organically decreasing curve following the traditional methods and natural processes. © 2021 IEEE.
ABSTRACT
The present pregression of the highly contagious novel coronavirus [COVID-19] has been testing the healthcare system globally pressing the medical staff everywhere. Present and future healthcare workers’ updated knowledge, proper attitude towards the pandemic and adequate preventive practices are of paramount importance for the combat effectiveness of the healthcare burden.This study assessed the knowledge, practice and attitudes regarding COVID-19 among the nursing students of a tertiary care center in Eastern India. KAP scores were compared with their socio-demographic variables. Inter-relation between knowledge, attitude and practice was also assessed.Out of the 131 students participated in the study the KAP parameters were not significantly different based on the socio-demographic factors. Though knowledge and attitude parameters were positively correlated among them, it was found that practice was negatively correlated to both knowledge and attitude. This finding can be attributed to them being non-exposed and inexperienced in the regular healthcare activities as well to the fact that Indian population was to some extent unprepared to cope up with this type of epidemic for a long time. Training on the updated knowledge along with exposure to simulated environment with scheduled supervision to reflect the behavior of the students is of great importance so that in extreme situation, the trainee students can also come handy into utilization if needed.
ABSTRACT
With the rapid spread of COVID-19 since its inception a year back, the frontline healthcare workers, who underwent isolation and quarantine following possible exposure, faced multiple psychiatric problems like deterioration of sleep quality and anxiety manifestations. Different demographic variables were found to be associated with their occurrence, as well as inter-relation between them were found to be common. We tried to examine the role of social support system as well to the appearance of such problems in the present study. After getting the ethical clearance, willing healthcare workers during their isolation and quarantine were presented questionnaires consisting of Socio-demographic proforma, Self-rating Anxiety Scale (SAS), Personal Social Capital Scale 16 (PSCS) and Pittsburgh Sleep Quality Index (PSQI). Data taken were analysed with independent t test and Fishers exact chi square test, Pearson’s correlation analysis and linear regression analysis. Majority of the subjects were married Hindu female from urban background, mostly doctor and nurse by profession. Independent T test revealed significant association between gender and anxiety status as well as between marital status and sleep quality. Positive correlation between the PSCS scores and the SAS scores (r=0.652, P<0.01) and negative correlations between the PSCS and PSQI scores and between the SAS and PSQI score were found albeit being statistically insignificant. Significant association was found between the SAS score and social bridging component of PSCS (Fishers exact chi sq. value 0.54 and p = 0.003). Anxiety score was significantly affected when the socio-demographic factors like gender, religion, marital status and scores of sleep quality (PSQI) and social capital (PSCS) were considered together as seen in the linear regression analysis.
ABSTRACT
The outbreak of COVID 19 pandemic in India has started from the month of March when many cases were tested positive for novel coronavirus. The high infectivity of the disease led many governments to impose strict lockdown with the aim of limiting its spread. To restrict its spread and save the people of India our government has also imposed strict nationwide lockdown in a phase wise manner. Though the lockdown was imposed to restrict the spread of COVID 19 but it had severe undesirable impact on the socio-economical and psychological status of the people especially of low to medium income groups involved in private jobs. The aim of this study was to study the cases of autopsied unnatural deaths with special emphasis to find out the correlation between demographic pattern of deceased with the lockdown. In this study we have analysed the 961 cases of autopsied unnatural deathsin the mortuary of Department of Forensic Medicine, NBMCH, Darjeeling, West Bengal from the first day of lockdown up to the month of September (24th March 2020 to September 2020). All data were analysed by appropriate statistical tolls like SPSS software. In this study we found that male (66.4%) predominated over the females and most of the cases belongs to adult age group (44.27%). Persons involved in private jobs (44%) were more severely affected compared to the government jobs and cases of suicidal deaths (45.7%) rises but cases of deaths due to road traffic accidents (13.9%) drastically reduced during lockdown period.