Mobility Metrics for Glasgow City Region

Overview: Mobility Metrics for Glasgow City Region is an UBDC derivative product of Huq dataset and Tamoco datasets. This dataset provides metrics about mobility between different origins and destinations in the Glasgow City Region. E Location data from mobile phone apps aggregated by Huq Industries was used to derive the dataset. Huq dataset: Huq is a mobile phone app dataset. The app collects real-time, anonymised location data from users' smartphones, based on the use of a range of smart phone applications. This dataset offers researchers insights into human mobility patterns and behaviour. Researchers can leverage this data to study consumer trends, urban planning, and the impact of events on people's movements, amongst other applications. With a coverage of around 0.7% of the population and granular location information, Huq data offers the potential to understand changing societal dynamics and make data-driven decisions across various fields, from retail and transportation to public health and urban development. The data has a geographic coverage across Glasgow City Region. It has a time coverage of 5 years from 2019 to 2023. Tamoco dataset: Tamoco provides organisations with access to real-time location data. Tamoco’s geospatial data is derived directly from mobile devices using a combination of GPS and WiFi, in order to generate industry-leading location signals. The Tamoco dataset consists of Tamoco’s Standalone Location Data. Mobility Metrics for Glasgow City Region Data: The mobility metrics dataset was created using mobile phone application data from Huq and Tamoco data. The aim of the dataset is to produce small-area aggregate measures of mobility over time. The data covers Glasgow city-region with results broken down by Intermediate Zone (417 in the city-region) from 1st July 2019 – 31st December 2021 (2.5 years) with results aggregated quarterly (10 periods). The Mobility is measured following Cuebiq Mobility Index approach. Mobility analysis is limited to mobile phone users determined to live within the Glasgow city-region (see technical report ‘Calculating home location for mobile phone data’ for details. This report is sent with the dataset). As well as other derived datasets based on Huq data, are available for non-commercial academic research use only. The data is available to request as Safeguarded data under UBDC's End User Licence. Access and restrictions: Mobility Metrics for Glasgow City Region, as well as other derived datasets based on Huq data, are available for non-commercial academic research use only. The data is available to request as Safeguarded data under UBDC's End User Licence. More information: Technical report ‘Calculating home location for mobile phone data’ for details. This report is sent with the dataset. Other related outputs: https://www.ubdc.ac.uk/news/data-for-insights-into-mobilit

MosquitoAge-DDE V1.0

Julia code used for simulations of the article "Incorporating adult age into mosquito population models: implications for predicting abundances in changing climates"

Huq packaged data by city and year 2019-2024

Huq is a mobile phone app dataset. The app collects real-time, anonymised location data from users' smartphones, based on the use of a range of smart phone applications. This dataset offers researchers insights into human mobility patterns and behaviour. Huq's event-level geo-data offers a rich and descriptive record of how consumers move and interact with the places around them. Huq's footfall data can be combined with other data sources to build predictions relating to how public entities are likely to report, specifically, where it concerns footfall correlated with revenue. The data can be used to observe how consumers interact with traded or private physical assets in order to observe changes in consumer trends and consider how those may affect their investment positions. Researchers can leverage this data to study consumer trends, urban planning, and the impact of events on people's movements, amongst other applications. With a coverage of around 0.7% of the population and granular location information, Huq data offers the potential to understand changing societal dynamics and make data-driven decisions across various fields, from retail and transportation to public health and urban development. The data has a geographic coverage across Glasgow City Region. OD Matrices data UBDC researchers also created a derived dataset, based on Huq data, Glasgow Origin-Destination (OD) Matrices. You can find more information in the dedicated Glasgow Origin-Destination (OD) Matrices page. Access and Restrictions Huq data is currently available internally for Urban Big Data Centre Staff only. Derived Datasets based on Huq data, such as Mobility Metrics for Glasgow City Region, are available to request as safeguarded data under an End User Licence Agreement. For more information please refer to the OD matrices page

Airbnb daily listings/calendars

Overview: Airbnb lists worldwide a selection of homes and boutique hotels available for booking holidays. The Urban Big Data Centre (UBDC) conducts a daily web scraping exercise for the Airbnb website, with the code for this exercise openly available at https://github.com/urbanbigdatacentre/ubdc-airbnb. This exercise has been collecting daily information since 2020 on property characteristics, daily booking calendar updates, booking policies, host information, and guest reviews. Data are collected to support academic research by UBDC on the short-term rental sector (Wang 2023, 2024). These aggregated tables are published as a by-product of that work. This dataset generated from the scraped web content estimates available and occupied listings, visits, occupancy rates and income by tracking individual listings' daily booking calendars, following the open method published by Wang et al. (2024). These metrics are key performance and stock indicators. From June 2021, it has covered thirty Travel to Work Areas (TTWAs) in Scotland and ten in other parts of the UK. The first version of the dataset covers the Scottish TTWAs only. The dataset provides monthly estimates, covering a total of 30 months from June 2021 to December 2023. It is published at the Middle Super Output Area (MSOA)/Intermediate Zone (IZ) level for each TTWA, provided there are more than five observed Airbnb listings in that MSOA/IZ. MSOA is the term used in England and Wales, IZ is the term used in Scotland. For simplicity, we refer to both as MSOAs. MSOAs without sufficient observations are omitted. UBDC extracts/organises Airbnb scraped data into structuralized interconnected parts including booking activities, customer reviews, spatial location, host status and structural and service amenities. This dataset is the Airbnb daily listings/calendar dataset. . Airbnb daily listings/calendars . Airbnb small area summaries Airbnb daily listings/calendars: This dataset is the Airbnb daily listings and calendar dataset. There are calendar, listings details and reviews extracts for Cardiff, Edinburgh, Glasgow, Manchester and York from Jan 2017-Sept 2022. Access and restrictions: Access is only available to internal UBDC staff for non-commercial academic research use only. However the code for Airbnb webscraping is openly available at https://github.com/urbanbigdatacentre/ubdc-airbnb More information: Wang, Y., Livingston, M., McArthur, D.P. and Bailey, N., 2023. The challenges of measuring the short-term rental market: an analysis of open data on Airbnb activity. Housing Studies, pp.1-20. https://doi.org/10.1080/02673037.2023.2176829 Wang, Y., Livingston, M., McArthur, D. P. and Bailey, N. (2024) Enhancing our understanding of short-term rental activity: A daily scrape-based approach for airbnb listings. Plos one, 19(2), pp. e0298131. https://doi.org/10.1371/journal.pone.029813

Towards decentralized nitrogen fixation using pulsed ultrasound

The fixation of atmospheric nitrogen is one of the key processes required for life on Earth, and the development of anthropogenic nitrogen fixation methods in the early twentieth century revolutionized agricultural productivity. Non-natural nitrogen fixation is currently dominated by the Haber-Bosch process, which generates ammonia from nitrogen and (usually fossil fuel-derived) hydrogen. However, other potential nitrogen fixation products are equally useful, particularly nitrate, to which a significant proportion of ammonia produced by the Haber-Bosch process is converted via the Ostwald process. Both the Haber Bosch and Ostwald processes require high temperatures, elevated pressures and large, centralized facilities and are major emitters of CO2. Present nitrogen fixation routes therefore leave very little scope for the production of fertilizers in small, decentralized facilities close to the point-of-use, or for the development of truly resilient and sustainable supplies of these vital chemical building blocks. Such decentralized production would require the fixation of nitrogen without the need for high temperature or high pressure reactors, using only air and water and without any additional reagents. Herein, we report on a much under-explored route to nitrogen fixation that is compatible with all the above criteria: fixation using ultrasound. Through the optimization of various acoustic parameters, we demonstrate that just 60 seconds of sonication of an air/water mixture at room temperature, using pulsed ultrasound at 200 kHz with an optimal input protocol (pulse duration = 4 ms, interval between pulses = 80 ms), is sufficient to produce nitrate solutions at concentrations of approximately 15 μM. These results constitute a record rate of production of nitrogen oxides by sonication in aqueous solution and are a step-change in terms of energy requirements per mole of products relative to previous reports. In turn, our results suggest that this simple approach has potential for low capital cost and truly decentralized nitrogen fixation in areas where infrastructure is lacking

Housing Survey data

Overview: The collaboration between the Urban Big Data Centre (UBDC) and The Bureau of Investigative Journalism (TBIJ) TBIJ originated from a small pilot study carried out by UBDC in the winter of 2021, supported by the Economic and Social Research Council (ESRC). In the first small scale pilot study, the UBDC Urban Sensing & Analytics team tested a range of affordable sensors in the indoor environment and tested the methodology to include low-cost sensors in a traditional social survey. Although the initial pilot study mostly focused on methodology testing in the wintertime, investigative journalist Rachel Hamada from TBIJ reached out to UBDC and asked if it were possible to use the sensors for urban heat investigation. After constructive discussion, UBDC researchers decided to collaborate during summer 2023 on the London Southwark Heat Investigation project. Drawing upon the experience from the first pilot study, UBDC researchers chose to use the commercialised smart citizen kit for this project. The reason we choose the smart citizen kit, designed by Fablab Barcelona, is because the sensor designer and producer have done a very detailed lab-based sensor calibration, software system correction, and validation. The sensor designer also provided the open-source 3D printing enclosures for their sensor and that helped further protect the sensors in the survey process. The overall sensor data collection process, from late July to early September 2023, was smooth with local support from TBIJ colleagues in London. Besides the sensor data, TBIJ also collected several rounds of survey each week with the participants, including basic socio-demographic information and heat-health related questions. With the address information, he UBDC Urban Sensing & Analytics team were able to link other open-source administrative data including the Index of multiple deprivation (IMD) data and energy performance certificate (EPC) data to the survey dataset. The combination of indoor sensor measurement data, EPC data, IMD data, and household survey data create a unique household picture and dataset to better understand urban heat inequality among all the participants. In the initial data analysis, from September until December 2023, the UBDC Urban Sensing & Analytics team mostly focused on the air temperature and relative humidity data, along with the housing characteristics and EPC information. This dataset comprises sensor data collected from Smart Citizen Kits (SCK) sensors, along with survey data conducted by the Bureau of Investigative Journalism (TBIJ). The unique ID is utilized as a linking mechanism between the SCK sensor data and the TBIJ survey data. During the summer months from July 2023 to September 2023 (including a mini heatwave in early September 2023), 40 Smart Citizen sensors have recorded data in homes in Southwark, London, with recording duration from 24 days to 53 days. The SCK (Smart Citizen Kits) sensors captured a range of environmental parameters in homes, including air temperature, relative humidity, air quality, noise condition and light condition. SCK was calibrated in the lab-based environment by the sensor manufacturer first and further corrected based on its operational mode. Further validation procedures were implemented to ensure the accuracy and quality of the air temperature data and relative humidity data by comparing records between survey sensors and commercial sensors (HOBO MX1101 Wireless Temperature and Humidity Data Logger - Optional Remote Monitoring). Regarding the TBIJ survey data, only housing tenure, housing types, and self-reported housing conditions from the survey data are included in this dataset.Index of Multiple Deprivation (IMD) quintiles and existing Energy Performance Certificate (EPC) rating are also included in this dataset, linked based on the participants’ home addresses and Unique ID, providing deprivation level of neighbourhoods and energy conditions of homes. IMD data was obtained from UK government and the IMD quintile was calculated based on the IMD decile. The EPC data was collected from Energy Performance of Buildings Search Results. There are 2 datasets the open dataset and this licensed dataset which contains additional details on survey households’ building conditions, including building insulations and building age, linked and processed from the open EPC dataset. Access and restrictions: UBDC's licence agreement provides access for conducting non-commercial research. To use the data, researchers need to apply to UBDC setting out a summary of the work they plan to undertake so that the usage can be assessed against these criteria. Please apply to UBDC. If the intended use falls within the terms of the licence, researchers will be asked to sign an End User Licence agreement. Datasets will be shared with eligible applicants on receipt of completed license agreements. More information: Further information and Sensor-Enhanced Housing Survey Data for Urban Heat open dataset available at Zenodo at https://zenodo.org/records/14444475 and https://data.ubdc.ac.uk/datasets/cc9cb186-e090-46e9-9d5b-b57a332a08a4 The Bureau of Investigative Journalism (TBIJ): ‘Stifling, suffocating, unliveable’: Life in an overheating home; Revealed: escalating effects of hot summers on UK housing; The rising danger of hot summers; District heating leaves London residents sweltering during heatwave https://www.thebureauinvestigates.com/stories/2023-12-05/stifling-suffocating-unliveable-life-in-a-overheating-home

Diagnostic accuracy of a Brix refractometer to estimate porcine colostrum quality

Colostrum IgG concentration from sow

Impact of windward and effective slope on the roughness effect of ratchet-type surfaces in turbulent channel flow

This dataset contains velocity data discussed in the paper

Disentangling transport and trophic effects of animal movement on environmental parasite abundance

This data set contains counts of ruminant gastrointestinal nematode 3rd stage larvae (L3) collected from clipped grasses from an experiment carried out in Serengeti National Park, Tanzania. The experiment aimed to understand the role of varying intensity and duration of wildebeest migration on parasite risk to other ruminant hosts

SARS-CoV-2 cellular coinfection is limited by superinfection exclusion

This dataset contains all primary data used in the study “SARS-CoV-2 cellular coinfection is limited by superinfection exclusion