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1.
Adversity And Resilience Science ; : 1-15, 2022.
Article in English | MEDLINE | ID: covidwho-1827652

ABSTRACT

The COVID-19 pandemic and associated restrictions have had a negative impact on the mental health and wellbeing of many people worldwide, but this may have been particularly challenging for adolescents. However, there is a paucity of research examining the factors associated with good mental health during this time. The aim of the current study was to identify the protective factors amongst early adolescents in the UK that were associated with better mental health outcomes (internalising and externalising difficulties, and wellbeing) during the first national COVID-19 lockdown. Between September and December 2020, 290 11-14 year olds across North West England completed an online survey consisting of several measures pertaining to experiences of lockdown, and mental health and wellbeing. Hierarchical multiple regression was used to analyse the data. Results indicated that higher participant-rated lockdown experience (the extent to which it was fun, easy, and good) and higher levels of optimism were protective factors for all three outcomes of interest. Greater adherence to government guidance was a protective factor for internalising difficulties and wellbeing only, while family keyworker status was protective for externalising difficulties and wellbeing only. Community and school connection were protective factors for internalising difficulties;family connection and number of parents at home were protective factors for externalising difficulties;and peer support and family knowledge of COVID-19 were protective factors for wellbeing. In summary, the 'ordinary magic' of supportive relationships and positive experiences appear to be some of the key factors needed to maintain adolescents' mental health and wellbeing, and to help them overcome difficulties posed by the COVID-19 pandemic.

2.
5th World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2021 ; 334:785-800, 2022.
Article in English | Scopus | ID: covidwho-1611372

ABSTRACT

The COVID pandemic has opened the eyes of numerous nations about their medical services framework. The short blast and uncontrolled overall spread of COVID-19 show the constraints of existing medical services frameworks to handle general wellbeing crises conveniently. The disease and demise numbers detailed by World Health Organization (WHO) about this pandemic is an expanding danger to the lives of individuals and the financial matters of nations. The greatest challenge that most governments are experiencing is the absence of a precise mechanism to recognize obscure contaminated cases and anticipate the disease danger of COVID-19 infection. Numerous countries have been utilizing a scope of devices to battle the pandemic, looking for data about development, checking just as the releasing the private data of the occupants. This research paper plans to help tainted individuals with care utilizing the Internet of Things (IoT) and blockchain innovations. From one viewpoint, blockchain can battle pandemics by empowering early discovery of the cases, securing client protection, and guaranteeing a compacted clinical flexibly chain during the pandemic attack. Then again, IoT-based medical services accumulate valuable data, give advanced knowledge through indications and practices, permit far-off checking, and essentially give individuals better self-assurance and medical services. A proposed layer consists of four-layer architecture utilizing IoT and blockchain to identify and predict people to be COVID-19. This idea provides a framework for patients with COVID-19 irresistible infection and perceives medical problems and determinations. The proposed approach is anticipated to deliver a robust framework ready to help governments, healthcare specialists, and residents make basic choices concerning disease recognition, disease forecast, and disease avoidance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

3.
Indian Journal of Forensic Medicine and Toxicology ; 15(4):124-126, 2021.
Article in English | EMBASE | ID: covidwho-1472560

ABSTRACT

Fogging of protective eyewear is commonly encountered by healthcare workers and there exists a number of ways to combat this. This article presents a comparison various anti-fogging measures of protective eyewear in terms of their mechanism of action, advantages and disadvantages.

4.
Congress on Advances in Materials Science and Engineering, CAMSE 2020 ; : 629-637, 2021.
Article in English | Scopus | ID: covidwho-1366328

ABSTRACT

In the present era of pool of technologies, the technical world is drastically shifting to artificial intelligence and all its application areas. One among such unprecedented areas of artificial intelligence is machine learning. Machine learning techniques are way useful for predicting the futuristic results as well as visualizing the data into different form which help the keen researchers and business analysts in determining their study gaps and can achieve the desired outcomes with an ease. With a necessity of well-organized dataset, machine learning algorithms can be implemented on any real-life data such as COVID-19 as it is the most popular topic for researchers today. COVID-19, as per the recent publications, is a pandemic declared by World Health Organization and spreading across the globe at an alarming pace. This has become a threat to human lives due to the reason that no medicine till date has proven its effectiveness to cure the infection spread by COVID-19. The paper is a work on the dataset for COVID-19 in which predictions have been made on the basis of cases emerging in an area and the expected date rate so that the situation can be tackled with all the medical emergency services. Regression is a machine learning technique that has been used for the prediction purpose. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

5.
IEEE Int. Conf. Power Electron., Drives Energy Syst., PEDES ; 2020.
Article in English | Scopus | ID: covidwho-1189594

ABSTRACT

In recent one decade, application of battery energy storage system (BESS) increased not only for integration of renewable energy sources to grid but also it plays a vital role for energy storage at user end side. Energy storage system application not only limited to renewable energy integration with grid but also its vital application in rural micro-grid electric mobility. A new era of energy transformation through battery energy storage begins, recently crude oil demand decreased that result results price plummets into negative zone for the first time in history during COVID-19. World's most countries utilize energy storage system to reduce CO2 emission and achieve their decarbonization target up to 2030. It is predicted that in near term worlds mobality market and other sector would dependent either BESS or other Energy storage system (ESS) with integration of PV generation as a cost-effective means of reducing pollution and greenhouse effect. The paper presents a comprehensive review of energy storage system techniques, comparison, benefits and brief tabulated summary of research done on ESS allocation in distribution system. © 2020 IEEE.

6.
Research Journal of Pharmacy and Technology ; 13(5):2530-2532, 2020.
Article in English | EMBASE | ID: covidwho-809338

ABSTRACT

This narrative review aims to know the association of the novel corona virus disease (COVID-19) in patients with diabetes mellitus and other co-morbidities. COVID 19 has reached the number 2.5 million of cases according to the situation report of World Health Organization on 21st, April 2020, affecting nearly 210 countries worldwide. It's highly virulent, involves ‘flu-like symptoms’, which are mild in most cases, in severe condition, results into acute respiratory distress syndrome, multiple organ failure leading to the blockage in lower respiratory tract/pathways and difficulty in breathing, it increases the risk for hospitalization and sometimes, leads to death in COVID-19 patients. Most of the patients are asymptomatic, but they can be a carrier to those who have less immunity. Patient with other co-morbidities like diabetes, cardiac problems, and older ages fails to survive as they are more prone to virus infections. The additional burden of disease can be one of the factors to the mortality in these cases.

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