https://researchdata.se/en/catalogue Search results en The ZIP file contains three Shapefiles with information on trenches, features and finds, and other metadata from the archaeological excavation, as well as a trench plan in GeoTIFF format. Wed, 21 Jan 2015 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/snd2451-1 https://researchdata.se/en/catalogue/dataset/snd2451-1 Uppsala University The study based to this dataset explored the variability in k600 and subsequent CO2 and CH4 emission rates within and across streams of different stream order (SO). We conducted, for the first time in streams, direct turbulence measurements using an acoustic Doppler velocimeter (ADV) to determine the spatial variability in k600 across a variety of scales with a consistent methodology. This study was conducted in an ∼80 km2 fourth-order catchment in south-central Sweden (; 59.803279°N, 15.167283°E). The catchment consists of 84.3% forest; 10% wetlands, marshes, fens and bogs; 5.1% lakes; 0.5% agriculture; and 0.06% habitation. The sampled sites were distributed along a hydrological chain of streams and lakes with streams ranging from SO1 to SO4. The average transect water velocity was multiplied by the cross-section area to obtain an average Q for the stream reach. Water temperature, electrical conductivity, and dissolved oxygen were measured in situ with an HQ40d Portable Multiparameter Meter (HACH), and pH was measured in the lab from water samples on a Metrohm 744 pH meter. We conducted sampling campaigns on 3 occasions: August 2015, April 2016, and June 2016. For further information about data and data collection, see "High spatial variability of gas transfer velocity in streams revealed by turbulence measurements" by Kokic et al (2018). The dataset was originally published in DiVA and moved to SND in 2024. Wed, 10 Jan 2018 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/2024-214 https://researchdata.se/en/catalogue/dataset/2024-214 Uppsala University Marcus Wallin To mitigate the development of antimicrobial resistance (AMR), antibiotic use (ABU) in the livestock sector needs to be reduced. In low- and middle-income countries, regulations have shown to be less successful in reducing ABU. Here, a bottom-up approach can complement legal frameworks which requires an understanding of the drivers for ABU. In this study, we investigated the influence of geographic and socioeconomic settings on determinants for ABU among pig farmers in Uganda. The data was collected through a questionnaire (containing 75 questions) in two districts, Lira and Mukono, and comparative statistical analyses were performed. Farmers in Lira had lower access to animal health services, applied disease preventive measures less and used antibiotics more. In Mukono, it was more common to consult a veterinarian in response to disease, while it in Lira was more common to consult an animal health worker. There was no difference in how many that followed treatment instructions from a veterinarian, but it was more common in Lira to follow instructions from pharmacies. The findings support the need for locally tailored AMR-reducing interventions to complement regulations. To accomplish this tailoring, systematic collection of knowledge of farm structures, farm practices and access to animal health services and veterinary drugs is necessary. The questionnaire was administered and recorded electronically on tablets using Open Data Kit (ODK) (https://getodk.org), an open-source tool for smart devices (i.e., smartphone or tablet) that enables creation and use of electronic questionnaires. The data collection through ODK was backed up daily. The dataset contains 72 columns and 463 rows. For explanations of the variables, see the separate file "AMUSE_Uganda_2022_dataset_Explanations". For explanations of the answer options, see the separate file "AMUSE_Uganda_2022_Questionnaire". Wed, 16 Feb 2022 16:18:55 GMT https://researchdata.se/en/catalogue/dataset/2021-344-1 https://researchdata.se/en/catalogue/dataset/2021-344-1 Swedish University of Agricultural Sciences Ulf Magnusson Michel Mainack Dione The unique multigenerational data base, Uppsala Birth Cohort Multigeneration Study (UBCoS), was established in 2004 by combining existing data on a representative and well-defined cohort of 14,192 males and females born in Uppsala from 1915-1929 with information on descendants of the original cohort members obtained from routine data registers. To date, the study has been further developed by additional data collection in school archives and records from Census 1930 and the period of follow-up extended till end of year 2010. Further data collection is currently ongoing. The study is unique in investigating intergenerational effects as "forward in time" processes, starting at the beginning of the last century (i.e. well before any of the routine registers were in place). Intergenerational associations can be currently investigated in more than 140,000 study subjects from families spanning up to five generations, including the 14,192 original cohort members, their 22,559 children, 38,771 grandchildren and 25,471 great grandchildren. The main research objectives are to: (i) Address questions of the extent to which and the mechanisms whereby social advantage and disadvantage are transmitted from one generation to the next, giving rise to continuity in social disadvantage both over the life cycle and across generations. (ii) Explore how early social and biological factors are transmitted from the parent generation to offspring generation(s). (iii) Integrate the understanding of broader social mechanisms with the understanding of disease specific aetiology to answer the question of how, and to what extent, health inequalities are reproduced into each new generation. Purpose: The aim of the study is to investigate life course and intergenerational determinants of social inequalities in health. Number of participants: 14,192 original cohort together with >140,000 family members. Wed, 20 May 2015 12:17:42 GMT https://researchdata.se/en/catalogue/dataset/ext0155-1 https://researchdata.se/en/catalogue/dataset/ext0155-1 Stockholm University Ilona Koupil The data contains results of a study that analysed solar access metrics for urban planning purposes. The purpose was to evaluate metric correlations to find suitable simple indicators of solar performance that can be applied to assess urban designs. The data contains inputs for creating the neighbourhood design iterations and metrics as outputs of simulations. Neighbourhood models were created using Rhino 7 and Grasshopper, while metrics were simulated using Grasshopper and Ladybug Tools. The metrics are described in the review article: Czachura, A., Kanters, J., Gentile, N., & Wall, M. (2022). Solar Performance Metrics in Urban Planning : A Review and Taxonomy. In Buildings (No. 393; Vol. 12, Issue 4). https://doi.org/10.3390/buildings12040393 The model setup is described in the article: Czachura, Agnieszka, Niko Gentile, Jouri Kanters, and Maria Wall. 2022. "Identifying Potential Indicators of Neighbourhood Solar Access in Urban Planning" Buildings 12, no. 10: 1575. https://doi.org/10.3390/buildings12101575 The excel file comprises of five data sheets: two containing data descriptions and three containing research data. The results are solar access metrics, which were used in a correlation study and other statistical analyses to determine their suitability for urban planning assessment purposes. Sheet 1 'metric_descriptions': Description of metrics Sheet 2 'headings': Description of headings Sheet 3 'Iterations_Stockholm': Neighbourhood models generated in an iterative process using geometrical constraints were simulated to obtain multiple solar access metrics, assuming the Stockholm climate. Sheet 4 'Iterations_Frankfurt': The same neighbourhood models generated in an iterative process using geometrical constraints were simulated to obtain multiple solar access metrics, assuming the Frankfurt climate. Sheet 5 'Case-Studies_Frankfurt': Case studies of real neighbourhood designs from Malmö city were simulated to obtain multiple solar access metrics, assuming the Frankfurt climate. These metric datasets were used for validation purposes. Data available in xlsx and csv format Mon, 03 Oct 2022 13:44:34 GMT https://researchdata.se/en/catalogue/dataset/2022-137-1 https://researchdata.se/en/catalogue/dataset/2022-137-1 Lund University Agnieszka Czachura