Smart Distance Lab Art Fair - An experimental data set on social distancing during the COVID-19 pandemic

In the absence of a vaccine, social distancing behaviour is pivotal to mitigate COVID-19 virus spread. In this large-scale behavioural experiment, we gathered data during Smart Distance Lab: The Art Fair (n = 787) between August 28 and 30, 2020 in Amsterdam, the Netherlands. We varied walking directions (bidirectional, unidirectional, and no directions) and supplementary interventions (face mask and buzzer to alert visitors of 1.5 metres distance). We captured visitors' movements using cameras, registered their contacts (defined as within 1.5 metres) using wearable sensors, and assessed their attitudes toward COVID-19 as well as their experience during the event using questionnaires. We also registered environmental measures (e.g., humidity). In this paper, we describe this unprecedented, multi-modal experimental data set on social distancing, including psychological, behavioural, and environmental measures. The data set is available on Figshare and in a MySQL database. It can be used to gain insight into (attitudes toward) behavioural interventions promoting social distancing, to calibrate pedestrian models, and to inform new studies on behavioural interventions.

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Smart Distance Lab’s art fair, experimental data on social distancing during the COVID-19 pandemic

Scientific Data ◽

10.1038/s41597-021-00971-2 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Charlotte C. Tanis ◽

Nina M. Leach ◽

Sandra J. Geiger ◽

Floor H. Nauta ◽

Fabian Dablander ◽

...

Keyword(s):

Experimental Data ◽

Large Scale ◽

Wearable Sensors ◽

Face Mask ◽

Data Set ◽

Behavioural Interventions ◽

Social Distancing ◽

Behavioural Experiment ◽

Environmental Measures ◽

Insight Into

AbstractIn the absence of a vaccine, social distancing behaviour is pivotal to mitigate COVID-19 virus spread. In this large-scale behavioural experiment, we gathered data during Smart Distance Lab: The Art Fair (n = 839) between August 28 and 30, 2020 in Amsterdam, the Netherlands. We varied walking directions (bidirectional, unidirectional, and no directions) and supplementary interventions (face mask and buzzer to alert visitors of 1.5 metres distance). We captured visitors’ movements using cameras, registered their contacts (defined as within 1.5 metres) using wearable sensors, and assessed their attitudes toward COVID-19 as well as their experience during the event using questionnaires. We also registered environmental measures (e.g., humidity). In this paper, we describe this unprecedented, multi-modal experimental data set on social distancing, including psychological, behavioural, and environmental measures. The data set is available on figshare and in a MySQL database. It can be used to gain insight into (attitudes toward) behavioural interventions promoting social distancing, to calibrate pedestrian models, and to inform new studies on behavioural interventions.

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Computation of Engine Noise Propagation and Scattering off An Aircraft

International Journal of Aeroacoustics ◽

10.1260/147547202765275989 ◽

2002 ◽

Vol 1 (4) ◽

pp. 403-420 ◽

Cited By ~ 18

Author(s):

D. Stanescu ◽

J. Xu ◽

M.Y. Hussaini ◽

F. Farassat

Keyword(s):

Experimental Data ◽

Time Domain ◽

High Performance ◽

Large Scale ◽

Numerical Algorithms ◽

Spectral Element ◽

Spectral Element Methods ◽

Data Set ◽

Noise Field ◽

High Performance Computers

The purpose of this paper is to demonstrate the feasibility of computing the fan inlet noise field around a real twin-engine aircraft, which includes the radiation of the main spinning modes from the engine as well as the reflection and scattering by the fuselage and the wing. This first-cut large-scale computation is based on time domain and frequency domain approaches that employ spectral element methods for spatial discretization. The numerical algorithms are designed to exploit high-performance computers such as the IBM SP4. Although the simulations could not match the exact conditions of the only available experimental data set, they are able to predict the trends of the measured noise field fairly well.

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Physical Spacing and Social Interaction Before the Global Pandemic

Spatial Demography ◽

10.1007/s40980-021-00100-y ◽

2021 ◽

Author(s):

Mathew Creighton ◽

Daniel Capistrano ◽

Agnieszka Sorokowska ◽

Piotr Sorokowski

Keyword(s):

Social Interaction ◽

Large Scale ◽

Cultural Practice ◽

Cross Cultural ◽

Research Note ◽

Cultural Variation ◽

Religious Service Attendance ◽

Social Distancing ◽

Social Spacing ◽

Insight Into

AbstractSubsequent to the arrival of SARS-CoV-2 and emergence of COVID-19, policy to limit the further spread has focused on increasing distance between individuals when interacting, often termed social distancing although physical distancing is more accurate (Das Gupta and Wong in Canadian J Public Health 111:488–489, 2020; Gale in Is ‘social distancing’ the wrong term? Expert prefers ‘physical distancing,’ and the WHO agrees. The Washington Post, 2020; Sørensen et al. in Glob Health Promot, 28:5–14, 2021), and limiting the frequency of interaction by limiting/prohibiting non-essential and large-scale social gatherings. This research note focuses on social spacing, defined by distance and interaction, to offer a cross-cultural insight into social distancing and social interactions in the pre-pandemic period. Combining unique data on frequency of contact, religious service attendance and preferred interpersonal spacing in 20 countries, this research note considers variation in the extent to which physical distance was already practiced without official recommendations and underscores notable cross-cultural variation in the extent to which social interaction occurred. Results suggest that policy intervention should emphasize certain behavioral changes based on pre-existing context-specific patterns of interaction and interpersonal spacing rather than a one-size-fits-all approach. This research note is a descriptive first step that allows unique insight into social spacing and contact prior to the spread of SARS-CoV-2. It provides a baseline typology and a reference for future work on the cross-cultural implications of COVID-19 for pre-pandemic socio-cultural practice and vice versa.

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Auto Temperature and Mask Scanning Entry System

International Journal of Scientific Research in Science and Technology ◽

10.32628/ijsrst2183123 ◽

2021 ◽

pp. 557-562

Author(s):

Rubana Khan ◽

Kshitij Rangari ◽

Chetan Asutkar ◽

Payal Kapse ◽

Tejaswi Vaidya ◽

...

Keyword(s):

Computer Vision ◽

Body Temperature ◽

Data Privacy ◽

Large Scale ◽

Face Mask ◽

Temperature Sensing ◽

Infrared Sensor ◽

Thermal Camera ◽

Railway Stations ◽

Social Distancing

Now that many shops, offices and institutions are re-opening again after the Corona lockdown, many businesses are faced with the need to provide the best possible protection for their staff and customers. Face masks and body temperature checks play an important part in the protection effort. While this is already done routinely and at a large scale at airports or railway stations, many businesses and institutions are struggling to meet the challenge. Face mask monitoring often requires additional staff resources. At the same time, body temperature checks by staff come with certain risks in terms of hygiene and data privacy. In this project, we introduce an affordable IoT-based solution aiming to increase COVID-19 indoor safety, covering several relevant aspects: 1) contactless temperature sensing 2) mask detection. Contactless temperature sensing subsystem relies on Arduino Uno using infrared sensor or thermal camera, while mask detection and social distancing check are performed by leveraging computer vision techniques on camera- equipped computer.

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Carbon-Based Nanomaterials as Promising Material for Wastewater Treatment Processes

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17165862 ◽

2020 ◽

Vol 17 (16) ◽

pp. 5862

Author(s):

Krzysztof Piaskowski ◽

Paweł K. Zarzycki

Keyword(s):

Experimental Data ◽

Wastewater Treatment ◽

Large Scale ◽

Biological Effects ◽

Principal Component ◽

Sewage Water ◽

Active Sludge ◽

Data Set ◽

Complementary Techniques ◽

Carbon Based Nanomaterials

In the latest literature search, the technology based on graphite oxide (GO) nanomaterials exhibits a great potential in many aspects of wastewater treatment involving adsorption, photocatalysis, disinfection and membrane process. In this study experimental data involving the carbon element in different forms such as active carbon (AC), graphite and graphene oxide (GO) applied as the active reagents in wastewater treatment are summarized and discussed. The first step was to characterize the aforementioned carbon materials and nanoparticles using various complementary techniques. These include optical microscopy, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Raman spectrophotometry and zeta potential measurements. The second issue was to design the relatively simple experiment enabling us to observe the physicochemical and biological effects of carbon nanoparticles in the presence of sewage water and/or active sludge. Obtained experimental data have been inspected using univariate and multivariate (principal component analysis, PCA) approaches confirming the complex interaction of GO nanoparticles with microorganisms that are present in activated sludge. This experiment enabled the collection of an initial data set to design different large scale investigations focusing on active nanoparticles affecting wastewater purification. PCA calculations clearly revealed that GO strongly affects the wastewater technological processes investigated. It is hoped that the described results will allow the design of smart environmental protection systems in the future.

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Smart Distance Lab: A new methodology for assessing social distancing interventions

10.31219/osf.io/mjg2f ◽

2020 ◽

Author(s):

Tessa Blanken ◽

Charlotte Coosje Tanis ◽

Floor Nauta ◽

Fabian Dablander ◽

Bonne Zijlstra ◽

...

Keyword(s):

Experimental Design ◽

Large Scale ◽

Natural Experiment ◽

Scientific Research ◽

Contact Network ◽

Central Importance ◽

Immediate Feedback ◽

Network Modelling ◽

Behavioural Interventions ◽

Social Distancing

In the wake of the COVID-19 pandemic, the central importance of human behaviour in mitigating the spread of the virus has become universally recognized. We present a methodology to systematically assess the effectiveness of behavioural interventions to stimulate social distancing. In addition, we demonstrate the feasibility of this framework in a large-scale natural experiment. In an experimental design, we varied behavioural interventions to evaluate the effect of face masks, walking directions, and immediate feedback on visitors’ contacts. We represent visitors as nodes, and their contacts as links in a contact network. Subsequently, we used network modelling to test for differences in these contact networks. We find no evidence that face masks influence social distancing, while unidirectional walking directions and buzzer feedback do positively impact social distancing. The presented methodology represents a practically feasible way to optimize social distancing interventions through scientific research and may directly inform policy.

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