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(2026). <i>JYFL-ACCLAB-R61 Probing the N = 126 shell closure: alpha-decay spectroscopy of 220Pu</i>. V. 4.2.2025. University of Jyväskylä.","cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"R61: Probing the N = 126 shell closure: -decay spectroscopy of 220Pu\r\n\r\nSpokesperson: K. Auranen\r\n\r\nLiaisons: K. Auranen\r\n\r\nCollaboration: JYFL + Liverpool + UWS + Bratislava + GSI\r\n\r\nDate: 20.1.2025-3.2.2025\r\nNucleus: 220Pu\r\nBeam (charge state): 40Ca(8+), 40Ca(9+), 36Ar(8+)\r\nTarget (thickness): natW (~680 ug/cm²) on natC (~100 ug/cm²) backing (C downstream of W). 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We run approximately 5 days at average 100 pnA at this energy, corresponding to 10-15 pb sensitivity limit. We identified at least 217Th, 216Ac, 215Ra, 214Fr, 216Th, 218Ac, 219Th, 220Pa, 217Ac, 218Pa, 218U alpha decays in the data. We then reduced the beam energy to sub-barrier 201 MeV, and saw very similar alpha activities. This suggested that the alpha decays we've seen might come from 40-Ar contaminant in the beam that is impossible to avoid. PACE4 simulation supported this.\r\n\r\nWe then decided to go above the barrier at 214 MeV to search the 5n evaporation channel. Beam was on target about 3 days at 100+ pnA, no sign of Pu decays. We then decided to spend the weekend on something else, i.e. try to search isomeric states in 207Ac and 207Ra with 36Ar+175Lu at beam energy of 184 MeV. Turned out that 36Ar(8+) beam had 27Al(6+) contaminant.","fi":"R61: Probing the N = 126 shell closure: -decay spectroscopy of 220Pu\r\n\r\nSpokesperson: K. Auranen\r\n\r\nLiaisons: K. Auranen\r\n\r\nCollaboration: JYFL + Liverpool + UWS + Bratislava + GSI\r\n\r\nDate: 20.1.2025-3.2.2025\r\nNucleus: 220Pu\r\nBeam (charge state): 40Ca(8+), 40Ca(9+), 36Ar(8+)\r\nTarget (thickness): natW (~680 ug/cm²) on natC (~100 ug/cm²) backing (C downstream of W). 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Cox models were also fitted for mortality in relation to post-diagnostic use of the medications treating these as time-dependent exposures, and starting follow-up 1 year after the CC diagnosisResultsPre- and post-diagnostic metformin use was weakly associated with the risk of CC–related death (HR .75; 95% CI .58-.99, and HR .78; 95% CI .54-1.14, respectively) compared to the use of other oral ADMs. Pre- and post-diagnostic statin use predicted a reduced risk of CC–related death (HR .83; 95% CI .71- .98, and HR .69; 95% CI .54-.89, respectively).ConclusionAdditional evidence was found for use of statins being associated with an improved survival from CC in patients with pre-existing T2D, but for metformin use the evidence was weaker."},"field_of_science":[{"id":"309e1694-caf9-44f8-9d82-9e4b002bc5a7","url":"http://www.yso.fi/onto/okm-tieteenala/ta3121","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Internal medicine","fi":"Sisätaudit","sv":"Inre medicin"}},{"id":"1946ea74-e9b2-4b6f-9b9e-093d809467e3","url":"http://www.yso.fi/onto/okm-tieteenala/ta3122","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Cancers","fi":"Syöpätaudit","sv":"Cancersjukdomar"}}],"infrastructure":[],"issued":"2022-01-01","keyword":["Internal medicine","Cancers"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"eb8aa44e-e16b-4c6c-ae4d-b9be524b58ed","organization":"service_tuni"},"other_identifiers":[{"notation":"581506be-fc43-4bc0-bf96-42769672fe3c","metax_ids":[]}],"persistent_identifier":"doi:10.25384/sage.c.6317987.v1","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"The Association of Metformin, Other Antidiabetic Medications, and Statins With the Prognosis of Colon Cancer in Patients With Type 2 Diabetes: A Retrospective Cohort Study"},"created":"2025-01-28T16:36:23Z","modified":"2026-01-12T02:00:43Z","dataset_versions":[{"id":"957e5cfc-81c7-494b-a5b7-bd9ae79eeec4","title":{"en":"The Association of Metformin, Other Antidiabetic Medications, and Statins With the Prognosis of Colon Cancer in Patients With Type 2 Diabetes: A Retrospective Cohort Study"},"persistent_identifier":"doi:10.25384/sage.c.6317987.v1","state":"published","created":"2025-01-28T16:36:23Z","version":1}],"published_revision":5,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2025-01-28T16:36:23Z","record_modified":"2026-01-12T02:00:43Z"},{"id":"e25d9c4b-77e7-4b66-a863-42e74366a021","access_rights":{"id":"37aeedeb-47ad-4ded-83d1-9be929f02e4e","license":[{"id":"f88e0ace-d8ce-46dd-a1b6-f533035a8a0d","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-NC-ND-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","fi":"Creative Commons Nimeä-EiKaupallinen-EiMuutoksia 4.0 Kansainvälinen (CC BY-NC-ND 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"2ade9939-497d-4374-ad6f-221d777c4b8f","roles":["creator","publisher"],"person":{"id":"46e61f06-cbc4-46f1-9378-50e3a1b207d0","name":"Evelina Koivisto","email":"<hidden>","external_identifier":"https://orcid.org/0000-0003-1122-8257"},"organization":{"id":"3727eafe-5d0a-4fd2-b2cb-c70b2f4e53f5","pref_label":{"en":"Process- och systemteknik","fi":"Process- och systemteknik","sv":"Process- och systemteknik","und":"Process- och systemteknik"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01903-2804722","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"a4dc30ef-4be2-412a-a399-ebac8a37213e","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi","sv":"Åbo Akademi","und":"Åbo Akademi"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01903","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"The current metafile aims at explaining the open data related to tests presented and being discussed in the published journal article (2023) of ACS ES&T Water titled: “Performance Optimization of Bipolar Membrane Electrodialysis of Ammonium Sulfate/Bisulfate Reagents for CO2 Mineralization”, Authors: E. 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main data represents the estimated number of buildings by building stock year,\ntype of the building, building period, municipality, and source of heating,\nas well as the estimated average gross-floor areas of buildings by municipality,\ntype of building, and building period. See the end of the README for a detailed\ndescription of the dataset.\n\n\n## Contents\n\nHere's a quick overview of the important contents of this dataset,\nand a brief description of the contents of each file.\nFor a detailed description of the dataset, see the end of this README.\n\n1. `datapackage.json`, the [Data Package](https://specs.frictionlessdata.io/data-package/) definition.\n2. `forecasts2csvs.bat`: A script for processing the original raw `.xlsx` files into the translated `.csv` files using [BuildingStockForecasts.jl](https://vttgit.vtt.fi/flexib/BuildingStockForecasts). Mainly included for example purposes.\n3. `import_finnish_building_stock_forecasts.json`, the [Spine Toolbox](https://github.com/Spine-project/Spine-Toolbox) importer specification.\n4. `LICENSE` contains information about the permitted use of this dataset.\n5. `data/average_floor_areas_m2.csv`: Contains estimated average gross-floor areas of buildings by `municipality`, `building_type` and `building_period`.\n6. `data/building_periods.csv`: Contains each `building_period` with their start and end years as integers.\n7. `data/frame_material_shares.csv`: Contains `municipality`-level data of building frame material shares across `building_types`.\n8. `data/municipalities.csv`: Contains the list of included `municipality` IDs and names.\n9. `data/number_of_buildings.csv`: Contains the building stock forecasts as estimated number of buildings by `building_stock_year`, `building_type`, `building_period`, `municipality`, and `heat_source`.\n\n\n## Usage\n\nThe dataset is formatted as a [Data Package](https://specs.frictionlessdata.io/data-package/),\nhopefully facilitating interoperability and reuse.\nHowever, this dataset was originally designed to be used via [Spine Toolbox](https://github.com/Spine-project/Spine-Toolbox),\nand thus contains the necessary definitions to easily set up an importer into a Spine Datastore:\n\n1. Add a *Data Connection* item, and refer it to the `datapackage.json` file.\n2. Use the *Add specification from a file* option from the toolbar, and select the `import_finnish_building_stock_forecasts.json` file to add the necessary *Importer* definition.\n3. Add an *Importer* item, connect the above *Data Connection* to it, and select the above importer specification for it.\n4. Connect the *Importer* to the desired *Spine Datastore* where you want the data to be imported to.\n\n\n## License\n\nAll rights reserved, see `LICENSE` for more information.\n\nIt is possible to gain access to the dataset if you can agree to the following conditions:\n\n1. **The dataset is for academic use only.** Any sort of commercial use is strictly prohibited, as the original underlying data is owned by the Finnish Digital and Population Data Services Agency.\n2. **Re-distribution or re-publishing of the dataset is prohibited.** If there are other people in your team/group who also need access to the data, they need to be made aware of these conditions. We recommend you refer them directly to us so that we have an idea who is using the dataset, but I understand this might be a bit cumbersome for very limited use of the data.\n3. **Results based on the use of this data shouldn't be presented using the maximum resolution.** The detailed nature of the data makes it somewhat sensitive, as combining it with other registry data could potentially be used to identify individual buildings and their owners.\n4. **If you end up not using this dataset, please delete all copies of it.** This aims to prevent accidental access by people who aren't aware of these conditions.\n\nIf you want access to the data, please contact the data curators directly.\n\n## Acknowledgements\n\nOriginal dataset and the building stock forecasts were created by Terttu Vainio at VTT.\nTopi Rasku merely gathered all the data in the original dataset *(lots of .xlsx files)* into fewer .csv files,\nas well as translated the data into English.\n\nThis dataset was built for the [Academy of Finland](https://www.aka.fi/en) project\n[*\"Integration of building flexibility into future energy systems (FlexiB)\"*](https://akareport.aka.fi/ibi_apps/WFServlet?IBIF_ex=x_hakkuvaus2&CLICKED_ON=&HAKNRO1=332421&UILANG=en&TULOSTE=HTML)\nunder grant agreement No 332421.\n\n[CSC – IT Center for Science, Finland](https://csc.fi/en/home) provides the [Fairdata.fi](https://www.fairdata.fi/en/) service for easy research metadata publication.\n\n\n# Dataset description\n\nThis section hopes to describe the raw data in enough detail to give you a better idea\nof what is and isn't included in the dataset.\nSince significant parts of the raw data is owned by [the Finnish Digital Agency](https://dvv.fi/en/digital-and-population-data-services-agency),\nit is likely that only the descriptive metadata of this dataset can ever be published.\nHowever, access to this dataset for academic use can be requested from the copyright holders.\n\nIn general, the dataset contains 5 key dimensions over which the data is organized:\n\n- `building_stock_year`: The year for which the building stock data is for. The years 2030, 2040, and 2050 are forecasts based on assumptions explained briefly below using forecasting models at VTT. The included building stock years are:\n    - `2020`, `2030`, `2040`, `2050`.\n- `building_type`: The type of the building, based on the divisions in Official Statistics Finland, and the Building and Dwelling Register. The building types in the data include:\n    - `apartment_block`, `communal_building`, `detached_house`, `office_building`, `service_building`, `terraced_house`\n- `building_period`: The time period during which the building was built. Division based on Official Statistics Finland data. The building periods in the data include:\n    - `0000-1920`, `1921-1939`, `1940-1959`, `1960-1969`, `1970-1979`, `1980-1989`, `1990-1999`, `2000-2009`, `2010-2019`, `2020-2029`, `2030-2039`, `2040-2049`\n- `municipality` as a `(location_id, location_name)` pair: Finnish municipalities as they were at the end of the year 2020, except for those in Ahvenanmaa.\n    - 294 municipalities in total.\n- `heat_source`: The primary heat source of the building, e.g. fuel or electricity. The included heat sources are:\n    - `district_heating`, `light_oil`, `heavy_oil`, `electricity`, `natural_gas`, `coal`, `wood`, `peat`, `ground_source_heat`, `other`\n\nHistorical information about the gross floor area of the Finnish building stock is based on the\n*\"Official Statistics Finland (OSF): Buildings and free-time residences [e-publication]. ISSN=1798-6796. Helsinki: Statistics Finland [referred: 1.3.2021], access method https://www.stat.fi/en/statistics/rakke\"*\nThe municipality level data about the heat source of buildings is based on the *Building and Dwelling Register (BDR), https://dvv.fi/kiinteisto-rakennus-ja-paikkatiedot*\nthat VTT has access to for research purposes.\nThe forecast for the heat sources follows Finnish energy and climate strategy, that aims to move away from fossil\nfuels by 2030 in the majority of cases, and completely by 2050.\n\n\n## Important notes on data quality and scope\n\n### The forecasts are not entirely consistent\n\n_(2026-01-07)_ Unfortunately, turns out the forecasts are not completely consistent.\nSome subsets of the future building stock increase as `building_stock_year` increases,\nwhich shouldn't be the case.\nWhile these inconsistencies are relatively small\n_(less than 1% in terms of count, around 1-2% in terms of magnitude)_,\nit is still important to be aware of them.\n\n### Missing data\n\nThe municipalities in Ahvenanmaa are missing from the dataset!\nFurthermore, the frame material data for KU687 Rautavaara was missing from the underlying data,\nso data from the neighbouring KU686 Rautalampi is used in its place.\n\n### Included `building_type`s\n\nThis dataset was originally compiled for analysing the future Finnish building stock heating/cooling demand,\nas well as its potential flexibility for energy system analysis purposes.\nThus, it only contains a select subset of the Finnish building stock.\n\nThe detailed mapping is based on the *(now-outdated)*\n[1994 Classification of Buildings](https://www.stat.fi/en/luokitukset/rakennus/rakennus_1_19940101/) as follows:\n - `apartment_block`: Includes `A03 - Blocks of flats`.\n - `communal_building`: Includes `F - Buildings for institutional care`, `G - Assembly buildings`, and `H - Educational buildings`\n - `detached_house`: Includes `A01 - Detached and semi-detached houses`.\n - `office_building`: Includes `D - Office buildings`.\n - `service_building`: Includes `C - Commercial buildings`, and parts of `E - Transport and communications buildings` that are assumed to be heated *(e.g. some large transit stations)*.\n - `terraced_house`: Includes `A02 - Attached houses`.\n\nBuilding categories excluded from this dataset include:\n - `B - Free-time residential buildings` due to inconsistent occupation and heating patterns.\n - Parts of `E - Transport and communications buildings` that are assumed not to be heated *(e.g. parking garages)*.\n - `J - Industrial buildings` and `M - Agricultural buildings` due to challenges in separating heating demand from process energy demand.\n - `K - Warehouses` and `L - Fire fighting and rescue service buildings` due to inconsistent heated volumes.\n - `N - Other buildings` due to insufficient information on their nature.\n\n### Air-source heat pumps\n\nThe underlying statistics unfortunately don't distinguish between electric heating and air-source heat pumps.\n\n\n## Individual data file descriptions\n\n### `data/average_floor_areas_m2.csv`\n\nThis file contains a pivot table of the estimated average gross-floor areas of the buildings\nin square meters for all `(building_type, (location_id, location_name), building_period)`.\nThe first three columns define the `building_type` and `(location_id, location_name)`,\nwhile the `building_period` is pivoted into the headers of the rest of the columns,\nas indicated by the header row of the `.csv` file.\nThe estimated average gross-floor area in square metres is contained in the pivoted columns\n4-15.\n\n\n### `data/building_periods.csv`\n\nThis file contains flat tabular definitions for all the possible `building_period`s.\nAs indicated by the header row in the `.csv` file, the first column defines the `building_period`,\nthe second column contains the `period_start` year as an integer,\nand the third column contains the `period_end` year as an integer.\n\n\n### `data/frame_material_shares.csv`\n\nThis file contains pivoted tabular data about the frame materials used in the Finnish building stock\nfor all `(building_type, (location_id, location_name), frame_material)`,\nwhere `frame_material` includes `concrete`, `brick`, `steel`, `wood`, and `other`.\nThe first three columns define the `building_type` and `(location_id, location_name)`,\nwhile the rest contain the shares of the pivoted `frame_material`,\nas indicated by the header row in the `.csv` file.\n\n\n### `data/municipalities.csv`\n\nThis file simply contains flat tabular definitions for all the possible `(location_id, location_name)` pairs,\nas indicated by the header row in the `.csv` file.\n\n\n### `data/number_of_buildings.csv`\n\nThis file contains pivoted tabular data about the number of buildings in the Finnish building stock\nfor all `(building_stock, building_type, building_period, (location_id, location_name), heat_source)`.\nThe first 5 columns define the `building_stock, building_type, building_period, (location_id, location_name)`,\nwhile the rest contain the pivoted number of buildings per `heat_source`,\nas indicated by the header row in the `.csv` file."},"field_of_science":[{"id":"2b9f69ab-1068-4ecd-8552-ac6d4b9c6664","url":"http://www.yso.fi/onto/okm-tieteenala/ta212","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Civil and Construction engineering","fi":"Rakennus- ja yhdyskuntatekniikka","sv":"Byggnads- och samhällsteknik"}}],"infrastructure":[],"issued":"2022-04-25","keyword":["Finland","Building stock"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"1d3baf39-dd08-4841-afe6-3e3153b7a68e","organization":"vtt.fi","admin_organization":"vtt.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:att:a567a84b-fea4-4ca8-84a1-fe97f52caff4","pid_generated_by_fairdata":true,"projects":[{"id":"d05e4e11-4a1d-47a4-b53e-ea1faaf60499","title":{"en":"FlexiB - 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