The COVID-19 Pandemic and Its Influence on Coworking Spaces in Slovakia: West–East Division

Operation of the coworking spaces (CSs) all over the world was strongly impacted by the COVID-19 pandemic, including those in Slovakia. The capital city's CSs and coworking spaces localised in non-metropolitan eastern part confirmed decline in co-worker presence that have also influenced financial aspect of the coworking spaces stability and resilience. Even though there have been several possibilities of national and local grants from public authorities, this support was not widely used and no CSs decided to contact the owners of premises in order to get rent deferrals and/or rent discounts. The pandemic also caused switch of physical events into online activities and activate those spaces located in the eastern part of the country as the number of the events in these spaces overall increased. Even the community spirit inside the CSs transformed to community events decreased due to the adaptation of government measures, cooperation outside individual CSs have strengthen and lead to establishing of formalised coworking association in Slovakia. In spite of the difficult situation the CSs have to face, many of them realised the need of adaptation and invested in ICT devices, change of already not sufficient marketing strategies but also see business opportunities as several new coworking spaces have started to operate. All these aspects point at the fact that flexible work arrangement coworking spaces offer could help to solve global economic crisis. © 2023, The Author(s).

Deep Crowd Analysis to Spot Social Distancing Violations in Post-COVID 19 Lifestyle

Crowd analysis is a new field of study that involves processing a large group of people to examine one or more of their behaviors. Deep learning is an appropriate technique for crowd analysis using a convolutional neural network. To calculate the distance between crowd members and to identify social distance violations, a deep crowd analysis is proposed in this study. Pre-trained in a single class To discover the region of interest, CNN is utilised to classify people (RoI). The people in the picture are then localized using a density map. The reference point used to calculate the distance between the people is the centroid of the isolated areas in the density map. A social distance violation is reported if the estimated distance is less than the specified threshold distance (3 meters). Between the two ROIs, a distance measured in pixels is determined. © 2022 IEEE.

A cohort analysis of patients receiving neoadjuvant androgen deprivation therapy prior to robot-assisted laparoscopic prostatectomy during the Covid-19 pandemic.

Objectives: The purpose of this study was to investigate localised prostate cancer treated with or without neoadjuvant androgen deprivation therapy prior to robot-assisted laparoscopic prostatectomy, and the impact of Covid-19 treatment disruption, on clinico-pathologic outcomes. Patients and methods: Data was retrospectively collected from 124 consecutive patients treated with robot-assisted laparoscopic prostatectomy between November 2019-September 2020. Sixty-two patients were treated before 13 March 2020 (historic cohort) and 62 afterwards (covid cohort). Thirty-seven patients in the covid cohort additionally received neoadjuvant androgen deprivation therapy (mean duration of 3 months) consisting of bicalutamide 150 mg once a day for 4 weeks, with leuprolide 3.75 mg monthly injections commencing after week 1, up until the date of surgery. Results: Statistical analysis found no difference in peri-operative measures and length of stay for patients treated with or without neoadjuvant androgen deprivation therapy. Patients with delayed surgical treatment offered neoadjuvant androgen deprivation therapy showed a trend towards a reduction in positive surgical margins (p=0.134), N1 disease (p=0.424) and pathological down-staging (50% patients with pT2 disease). Patients within the covid cohort experienced significantly increased detectable prostate-specific antigen levels (p<0.007). Conclusion: Our study demonstrated that a three-month duration of neoadjuvant androgen deprivation therapy prior to robot-assisted laparoscopic prostatectomy may improve pathological outcomes but this time-frame is inadequate to influence detectable prostate-specific antigen levels. Covid-19-related treatment delays led to significantly increased detectable prostate-specific antigen levels. Level of evidence: 2b.

Exploring the Effect of Social Media and Spatial Characteristics During the COVID-19 Pandemic in China

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social platforms, such as Twitter, Facebook and WeChat. In this work, we investigate how the disease and information co-evolve in the population. We focus on COVID-19 and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. The co-evolution between disease and information is explored via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. High correlation between disease and information data is observed, and also people care about the spread of disease only when it comes to their neighborhood. Regard to the content of the information, we obtain that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, two machine learning algorithms, i.e., linear regression and random forest, are introduced to further predict the number of infected using characteristics, such as disease spatial related and information-related features. We obtain that both the disease spatial related characteristics of nearby cities and information-related characteristics can help to improve the prediction accuracy. The methodology proposed in this paper may shed light on new clues of emerging infections prediction. © 2013 IEEE.

Transnational lived citizenship turns local: Covid-19 and Eritrean and Ethiopian diaspora in Nairobi

This paper analyses how migrant community practices of transnational lived citizenship were altered by both, COVID-19 and the policy response from the Kenyan government. It is based on interviews with members of the Eritrean and Ethiopian diaspora residing in Nairobi. The paper demonstrates how policies introduced because of the pandemic caused migrant communities to lose local and remittance income. More than the loss of material resources, however, they were impacted by the elimination of social spaces that enable diaspora lives. These two dynamics have intensified a trend that may have been present before the pandemic, a local turn of transnational lived citizenship. By focusing on lived experiences and how they have been re-assessed during the pandemic, the paper argues that transnational lived citizenship is always in flux and can easily become reconfigured as more localized practices. The concept of transnational lived citizenship is demonstrated to be a useful lens for analysing shifting migrant livelihoods and belonging. © 2022 The Authors. Global Networks published by Global Networks Partnership and John Wiley & Sons Ltd.

A SIMULATION FRAMEWORK FOR STUDYING FOREIGN RELIANCE ON REGIONAL SUPPLY CHAINS AT THE INDUSTRY LEVEL

Simulations incorporating economic input/output models have been applied recently to assess the extent of labor shocks from COVID 19 and their impact on supply chains at the macro level. Research is being done to extend these simulations for application to other scenarios of economic shocks beyond what was triggered through COVID related labor reductions. The problem of foreign supply chain dependency is of particular concern to localized regions as a significant portion of their economy is dependent on supplies from overseas. The extended simulation approach proposed here aims to optimize the degree to which the increased inventory supply targets allow for improved economic productivity and the ideal allocation per industry which most efficiently achieves this mitigation. This paper considers the application of the proposed simulation framework to study the regional dependence on the Asian supply chain. The case study presented in this paper demonstrates the economic insight that can be obtained through simulation analysis to support regional government decision making for the state of Alabama. © 2022 Society for Modeling & Simulation International (SCS)

Partisanship and Fear are Associated with Resistance to COVID-19 Directives

Ideological differences have had a large impact on individual and community response to the COVID-19 pandemic in the United States. Early behavioral research during the pandemic showed that conservatives were less likely to adhere to health directives, which contradicts a body of work suggesting that conservative ideology emphasizes a rule abiding, loss aversion, and prevention focus. We reconcile this contradiction by analyzing semantic content of local press releases, federal press releases, and localized tweets during the first month of the government response to COVID-19 in the United States. Controlling for factors such as COVID-19 confirmed cases and deaths, local economic indicators, and more, we find that online expressions of fear in conservative areas lead to an increase in adherence to public health recommendations concerning COVID-19, and that expressions of fear in government press releases are a significant predictor of expressed fear on Twitter. © 2021 Association for Computational Linguistics.

A Simulation Framework For Studying Foreign Reliance On Regional Supply Chains At The Industry Level

Simulations incorporating economic input/output models have been applied recently to assess the extent of labor shocks from COVID 19 and their impact on supply chains at the macro level. Research is being done to extend these simulations for application to other scenarios of economic shocks beyond what was triggered through COVID related labor reductions. The problem of foreign supply chain dependency is of particular concern to localized regions as a significant portion of their economy is dependent on supplies from overseas. The extended simulation approach proposed here aims to optimize the degree to which the increased inventory supply targets allow for improved economic productivity and the ideal allocation per industry which most efficiently achieves this mitigation. This paper considers the application of the proposed simulation framework to study the regional dependence on the Asian supply chain. The case study presented in this paper demonstrates the economic insight that can be obtained through simulation analysis to support regional government decision making for the state of Alabama. © 2022 SCS.

Prostate cancer-Exercise and Metformin Trial (Pre-EMpT): study protocol for a feasibility factorial randomized controlled trial in men with localised or locally advanced prostate cancer.

BACKGROUND: Evidence from observational studies have shown that moderate intensity physical activity can reduce risk of progression and cancer-specific mortality in participants with prostate cancer. Epidemiological studies have also shown participants taking metformin to have a reduced risk of prostate cancer. However, data from randomised controlled trials supporting the use of these interventions are limited. The Prostate cancer-Exercise and Metformin Trial examines that feasibility of randomising participants diagnosed with localised or locally advanced prostate cancer to interventions that modify physical activity and blood glucose levels. The primary outcomes are randomisation rates and adherence to the interventions over 6 months. The secondary outcomes include intervention tolerability and retention rates, measures of insulin-like growth factor I, prostate-specific antigen, physical activity, symptom-reporting, and quality of life. METHODS: Participants are randomised in a 2 × 2 factorial design to both a physical activity (brisk walking or control) and a pharmacological (metformin or control) intervention. Participants perform the interventions for 6 months with final measures collected at 12 months follow-up. DISCUSSION: Our trial will determine whether participants diagnosed with localised or locally advanced prostate cancer, who are scheduled for radical treatments or being monitored for signs of cancer progression, can be randomised to a 6 months physical activity and metformin intervention. The findings from our trial will inform a larger trial powered to examine the clinical benefits of these interventions. TRIAL REGISTRATION: Prostate Cancer Exercise and Metformin Trial (Pre-EMpT) is registered on the ISRCTN registry, reference number ISRCTN13543667 . Date of registration 2nd August 2018-retrospectively registered. First participant was recruited on 11th September 2018.

A Deep Learning Framework for the Classification of Lung Diseases Using Chest X-Ray Images

Automated screening and classification of various lesions in medical images can assist clinicians in the treatment and management of many systemic and localized diseases. Manual inspection of medical images is often expensive and time-consuming. Automatic image-analysis employing computers can alleviate the difficulties of manual methods for screening a large amount of generated images. Inspired by the great success of deep learning, we propose a diagnostic system that can classify various lung diseases from chest X-ray images. In this work, chest X-ray images are applied to a deep-learning algorithm for classifying images into pneumothorax, viral pneumonia, COVID-19 pneumonia and healthy cases. The proposed system is trained with a set of 4731 chest X-ray images, and obtained an overall classification accuracy of 99% in images taken from two publicly available data sets. The promising results demonstrate the proposed system’s effectiveness as a diagnostic tool to assist health care professionals for categorizing images in any of the four classes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Conservative management of massive localised lymphoedema using compression wraps: a case study.

Massive localised lymphoedema (MLL) is an issue that affects patients with obesity. Much of the literature surrounding MLL focuses upon surgical management. This case study will explore the conservative management of a patient with MLL of the distal thighs. MLL of the legs negatively impacts patients' mobility, which, in turn, affects their ability to undertake physical activity. Encouraging exercise and activity forms part of conventional lymphoedema treatment, as well as compression garments (in this case, compression wraps), good skin care and weight management. The impact of the COVID-19 pandemic on this patient's lymphoedema treatment will also be considered. The treatment of not just MLL, but lymphoedema in general, requires commitment from patients, their carers and staff. This case study illustrates what can be achieved, despite a pandemic, when a patient, their carers and lymphoedema therapists fully commit to a treatment regimen that is manageable and well-supported. The patient's MLL has shrunk significantly, and her weight continues to reduce. Informed consent was gained from the patient concerned in this case study.

Wireless Battery-free Core-body Temperature Sensing Device for Key Workers

We propose a battery-free temperature monitoring device that can be fitted inside the ear for an accurate core-body temperature (CBT) measurement of a subject. The system can record instantaneous changes in the localized body temperature of authenticated users. The proposed application consists of 2 primary systems: (i) a battery-free temperature sensing Ultra High Frequency Radio Frequency Identification (UHF RFID) sensory tag and (ii), an auxiliary energy harvesting system, which enhances the sensing devices measurement accuracy and precision. The assembly demonstrated a temperature average accuracy of 0.14 C operating at 866 MHz. The system performance demonstrated high stability and repeatability of reported temperature measurements. The devices dimension is a form factor that can easily fit in a front shirt pocket, with a wire tethered earbud temperature sensor. The system is developed to make sensor measurements without requiring a battery for the device. Measurements are made remotely as users pass by checkpoints installed throughout a building. The device is a cost-effective solution for monitoring body temperature in work environments. IEEE

A decision-making framework for the design of local production networks under largescale disruptions

In this paper, a model-based decision-making framework for the design of localized networked production systems under largescale disruptions is developed. The framework consists of optimization and agent-based simulation models that run successively in an iterative manner, gradually improving the performance of the perceived system. The framework integrates uncertainty, provides decisions at different decision-making levels and embeds an algorithm that allows for communication between demand nodes and production sites once inventory shortages occur. The framework has been applied on a case study for the design of localized production and distribution networks, powered by additive manufacturing (AM), in South East England during the early stages of the COVID-19 pandemic outbreak. Results revealed that implementing the framework indeed results in performance improvements to AM-powered production networks, particularly with regards to inventory shortages and lead time. © 2021 The Authors. Published by Elsevier Ltd.