EMOTIONAL ANALYSIS OF SAFENESS AND RISK PERCEPTION OF DIFFERENT PAYMENT SYSTEMS IN ITALY AND THE UK DURING THE COVID-19 PANDEMIC

Public safety, security and risk perception is an important aspect considered in opinion mining and sentiment analysis typically carried out on social networks. This involves considering each individual's opinion and determining a sense of what the public feels about an incident, event or place. In that sense, social networks play an important role in capturing the emotions of people. Security and safety managers can employ opinion mining and sentiment analysis as a tool to discover any unforeseen vulnerabilities in a precise manner and thereby plan and manage any associated risks. Furthermore, a continuous evaluation of risk perception can be carried out for timely and planned interventions in a seamless, effective manner to reduce or avoid any panic amongst communities. Without such advance techniques, safety and security of people, infrastructures and specific contexts can be easily compromised. Recent work in this direction has shown promising results in managing risks, especially during the COVID-19 pandemic. The purpose of the present work is to investigate the perception of risk associated with different payment systems, in Italy and the UK, during the COVID-19 pandemic, from 10 November 2020 to 13 May 2021, by means of the semantic analysis of the textual contents existing in Twitter. © 2022 WIT Press.

Emotional analysis of safeness and risk perception of cybersecurity attacks during the COVID-19 pandemic

The assessment of perceived safeness and risk by persons is especially valuable for security and safety managing. Each person is founded on the opinion of other people to make a selection and the Internet embodies the place where these opinions are mostly pursued, taken, and estimated. From this point of view, social networks are characterized by a considerable influence. Due to this reason, Opinion Mining and Sentiment Analysis have found outstanding employs in diverse environments and one of the most remarkable is expressed by public security and safety.The purpose of the present work is to investigate the perception of safeness and risk of cybersecurity attacks during COVID-19 pandemic by means of the semantic analysis of the textual contents existing in Twitter. © 2022 IEEE.

Multiple, Eruptive and Generalised Lobular Capillary Haemangiomas- A Rare Morphological Variant

Lobular Capillary Haemangioma or Pyogenic Granuloma (PG) is a common benign, vascular proliferative lesion, usually occurring at sites of preceding trauma. It is known to occur more commonly in children and young females. The most common presentation is a solitary lesion. Multiple, eruptive PG have been reported after antecedent burns, trauma and following retinoid therapy and as satellite lesions after treatment of a primary lesion. A 14-year-old female, without any co-morbidities presented with spontaneous onset of multiple, eruptive and generalised skin coloured papules and nodules over face, neck, upper chest and upper back. The lesions were eruptive in nature, involved the back, face and upper trunk over duration of 4 months. There was intermittent bleeding from the lesions after trivial trauma. Clinical diagnosis of lobular capillary haemangioma was confirmed by histopathology which showed lobules of variably dilated network of blood filled capillaries in the papillary dermis surrounded by typical epithelial collarette. The lesions were removed by Radiofrequency (RF) in subsequent sittings. This case report features an interesting and unusual morphological presentation of generalised eruptive lobular capillary haemangioma, which occurred de novo in a young female without any associated skin or systemic disease.

Emotional analysis of safeness and risk perception of drones during the COVID-19 pandemic in Italy

The estimation of perceived safeness and risk by individuals is very significant for security and safety managing. Every person is based on the judgments of other persons to do a choosing and the Internet personifies the location where these judgments are mostly tracked, obtained, and assessed. From this point of view, social networks have a significant influence. For this reason, Opinion Mining and Sentiment Analysis have found remarkable utilizes in a multiplicity of circumstances and one of the most notable is represented by public safety and security. The purpose of the present work is to investigate the perception of safeness and risk of drones during COVID-19 pandemic in Italy. It was considered the period from Aprile 15 to December 10, 2020, properly divided into 4 significant phases, highlighting the emotional components using the semantic analysis of the textual contents present in Twitter. © 2021 IEEE.

Emotional analysis of safeness and risk perception of London and Rome railway stations during the COVID-19 pandemic

The evaluation of perceived safeness and risk by persons is particularly valuable for safety and security handling. Each individual is influenced by others’ opinions on safety and security and the Internet embodies the place where these opinions are mostly pursued, acquired, and estimated. From this point of view, social networks play a considerable influential role. For this reason, Opinion Mining and Sentiment Analysis have found noteworthy uses in a variety of situations and one of the most interesting is embodied by public safety and security. The goal of this work is to examine the perception of safety and risk within the railway stations of London (UK) and Rome (Italy) during COVID-19 pandemic. In particular, the railway stations of London Victoria and Waterloo and the railway stations of Rome Termini and Tiburtina were considered, from March 23 to July 9, 2020, highlighting the emotional components in three distinct pandemic phases of the considered period in the two countries, by means of the semantic analysis of the textual contents present in Twitter. © 2021 IEEE.

Emotional analysis of safeness and risk perception of London and Rome airports during the COVID-19 pandemic

The evaluation of perceived safeness and risk by individuals is really useful for security and safety managing. Every individual is founded on the opinion of other individuals to get a selection and the Internet personifies the location where these judgments are mainly sought, obtained, and evaluated. From this point of view, social networks are characterized by a significant effect. Due to this reason, Opinion Mining and Sentiment Analysis have found remarkable uses in various environments and one of the most interesting is embodied by public security and safety. The aim of this work is to study the perception of risk of aircraft passengers and users of airports of London (UK) and Rome (Italy) during COVID-19 pandemic. In particular, the airports of London Heathrow and Gatwick and the airports of Rome Fiumicino and Ciampino were studied, from March 23 to July 9, 2020, highlighting the emotional components in three distinct pandemic phases of the considered period in the two countries, by means of the semantic analysis of the textual contents existing in Twitter. © 2021 IEEE.

Emotional analysis of safeness and risk perception of transports and travels by car and motorcycle in London and Rome during the COVID-19 pandemic

The estimation of perceived safeness and risk by people is especially invaluable for security and safety managing. Everyone is based on the opinion of other persons to do selections of any kind and the Internet personifies the location where these opinions are primarily tracked, obtained, and assessed. From this point of view, social networks are considered of huge impact. For this reason, Opinion Mining and Sentiment Analysis reached remarkable applications in a diversity of circumstances and one of the most remarkable is expressed by public security and safety. The purpose of the present work is to investigate the perception of risk with transports and travels by car and motorcycles in London (UK) and Rome (Italy) during COVID-19 pandemic, from March 23 to July 9, 2020, underlighting the emotional components in three distinct pandemic phases of the considered period in the two countries, via the semantic analysis of the textual contents existing in Twitter. © 2021 IEEE.

The burden of COVID-19 infection in a rural Tamil Nadu community.

BACKGROUND: There have been over 30 million cases of COVID-19 in India and over 430,000 deaths. Transmission rates vary from region to region, and are influenced by many factors including population susceptibility, travel and uptake of preventive measures. To date there have been relatively few studies examining the impact of the pandemic in lower income, rural regions of India. We report on a study examining COVID-19 burden in a rural community in Tamil Nadu. METHODS: The study was undertaken in a population of approximately 130,000 people, served by the Rural Unit of Health and Social Affairs (RUHSA), a community health center of CMC, Vellore. We established and evaluated a COVID-19 PCR-testing programme for symptomatic patients-testing was offered to 350 individuals, and household members of test-positive cases were offered antibody testing. We also undertook two COVID-19 seroprevalence surveys in the same community, amongst 701 randomly-selected individuals. RESULTS: There were 182 positive tests in the symptomatic population (52.0%). Factors associated with test-positivity were older age, male gender, higher socioeconomic status (SES, as determined by occupation, education and housing), a history of diabetes, contact with a confirmed/suspected case and attending a gathering (such as a religious ceremony, festival or extended family gathering). Amongst test-positive cases, 3 (1.6%) died and 16 (8.8%) suffered a severe illness. Amongst 129 household contacts 40 (31.0%) tested positive. The two seroprevalence surveys showed positivity rates of 2.2% (July/Aug 2020) and 22.0% (Nov 2020). 40 tested positive (31.0%, 95% CI: 23.02 - 38.98). Our estimated infection-to-case ratio was 31.7. CONCLUSIONS: A simple approach using community health workers and a community-based testing clinic can readily identify significant numbers of COVID-19 infections in Indian rural population. There appear, however, to be low rates of death and severe illness, although vulnerable groups may be under-represented in our sample. It's vital these lower income, rural populations aren't overlooked in ongoing pandemic monitoring and vaccine roll-out in India.

Knowledge, Attitude and Practice of COVID 19 and the factors influencing them among a Rural Population in South India

Background: Mitigation measures to control the novel coronavirus disease 2019 (COVID-19) depends on the public adherence to preventive measures which is influenced by their knowledge and attitude. Aim: To find the knowledge, attitudes and practices (KAP) of the rural population toward COVID-19 and to establish its socio-demographic influencing factors. Material and methods: KAP study regarding Covid-19 was done among the rural population during August 2020 using a semi-structured questionnaire. Results: Among 500 participants, the mean knowledge, attitude and practice score was 21.55 +/- 2.9 ( Range 0- 30), 30.0 +/- 2.88 ( Range 12- 36) 9.4 +/- 1.25 ( Range 0-13) respectively. Higher knowledge was associated with higher education and employed individuals. Favourable attitude was among those aged <35 years and having higher education. Optimistic practices were exhibited by employed individuals and when children <12 years are present in their home. Conclusions: Study participants preceded good knowledge, positive attitude towards COVID-19 but practice is not sufficient enough to win the battle against the dreadful disease due to considerable knowledge- practice gap.