Stress Detection on Social Network: Public Mental Health Surveillance: Public mental health surveillance

Many nations of the world struggle with the COVID-19 pandemic, as the disease causes wide sweeping changes to society and the economy. One of the consequences of the pandemic is its effect on mental health stress. Gauging stress levels at scale is challenging to implement, as traditional methods require administrative labour and time. However, a combination of supervised Machine Learning (ML) and social media analytics could provide a faster and aggregated way to detect the stress levels of a population. This study investigates the potential clinical usage of ML practices for detecting stress in Twitter content, as a quantitative measure of stress at scale. The stress scores obtained by the models will be compared to the COVID-19 timeline of daily new cases. © 2023 ACM.

Recycling of Electrical and Electronic-Waste with the Help of Marx Power Pulse Generator

Electronic waste (E-wastes) includes obsolete electrical or electronic devices. With the expansion of telecommunications from the COVID-19 pandemic and the advancement of technology, it is expected that by 2025 the weight of this waste will increase to 4.3 billion tons per year. In addition to precious metals, E-waste contains hazardous substances such as mercury, lead, cadmium, barium, and lithium. Therefore, managing how to recycle them through healthy environmental processes is essential. In this paper, the removal of the CD-ROM cover with the help of the proposed device of Marx is investigated. The Marx generator is designed and manufactured with an input voltage of 50 volts, an output voltage of about 370 volts, and a pulse power of 24.5 J. The results indicate the possibility of short-term separation of the CD-ROM coating with the help of the proposed generator. © 2022 IEEE.

Twitter Sentiment Analysis in Covid-19 Pandemic

We have yet to realise the full capability of social media as an innovative information platform during emergencies and crisis response and management. Sentiment analysis can systematically identify, extract, and scrutinise emotional states and subjective information in social media data. Exploring reactions and perceptions to response messaging is invaluable and proved especially useful for a pandemic response as it can demonstrate general population reaction to the pandemic and governments response actions. This can be further analysed to identify the gap between government response actions and communications and citizens' perceptions. In this paper, an analysis of Twitter data explores population reaction towards COVID-19 health messaging. A Natural Language Processing Python tool is known as TextBlob was used to discover general data sentiment. Data were divided into three sentiments and text extraction of health messages was conducted to explore subsequent tweets in predefined categories. Our findings show the outcome of Tweets analysis could help us to identify the general population concerns and their reactions to COVID-19 to give a better understanding of the situation to governments and support them in implementing appropriate policies. © 2021 IEEE.

Remuneration Review: Risk, Planning, and Modelling beyond the Covid Crisis

Organisations that have survived Covid-19 jolts, uncertainties and lockdowns now require business intelligence and information system integration for decision support. Risks and market challenges have shifted as the pandemic progresses. Crisis management repositioning has left many firms cash-poor. Now, firms are facing labour shortages. Standard remuneration policies and practices need revision to keep core talent, stabilise teams from burn-out and to move forward strategically. This paper revises essential remuneration review considerations for crisis management in a new Covid-19 context. Current trends are discussed, as restrictions and pandemic uncertainties lift, allowing greater accuracy in risk scenario planning. Reliable data, fit for analytics and complex modelling, are making results more meaningful. The unique contribution of this research is the Covid-19 post-survival organisational perspective that can transform remuneration modelling. The scope extends beyond the governance level, and considers semantics and dynamic risk planning. Specific scenarios are updated from lessons learned from financial crisis management. Conclusions take a holistic view of how data can enhance remuneration practices to add value for organisations in the current Covid-19 climate. The paper advocates post crisis remuneration review that includes complex modelling with dynamic risk analysis for strategic planning in mid-term scenarios. © 2021 IEEE.

Contact-tracing applications: A review of technologies

Background: Using different technologies for healthcare-related purposes has been significantly accelerated since the beginning of the COVID-19 pandemic. This outbreak highlighted the need for digital contact-tracing applications to effectively manage the pandemic by identifying positive case close contacts that might be the virus carriers. Objective: The objective of this review is to examine design decisions related to COVID-19 contact-tracing applications and the implications of these decisions. This review can be a useful aid in navigating the existing approaches in COVID-19 digital contact tracing and their different aspects including the potential supported functions, privacy and security. Method: A narrative review was conducted using Google Scholar database from August to October 2020, limited to English language articles and reports published after 2010. Main outcome: Different technologies have been used for digital contact tracing. The choice of these technologies and their software architectures could influence different factors such as data collection accuracy and effectiveness of an application in identifying possible virus spread. Furthermore, different technologies require different levels of user interaction and have different security and privacy concerns which could potentially impact application adoption. Conclusion: Digital contact tracing has been introduced as one of the easy and efficient methods to trace people in close contact with infected COVID-19 cases. This tracing could be an effective strategy to break the chain of infection transmission among people. However, based on the used technology and the software architecture, different contact-tracing applications offer different possible trade-offs that should be taken into account based on government's objectives on contact tracing. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.