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Text-fig. 1. Context and location of the Govone outcrop. a: Location of the Piedmont Basin at the northern margin of the Mediterranean Basin and distribution of Messinian evaporites. b: Simplified geological map of the Piedmont Basin showing the location of the Govone outcrop close to the town of Alba. in Remains Of A Subtropical Humid Forest In A Messinian Evaporitebearing Succession At Govone, Northwestern Italy - Preliminary Results
Text-fig. 1. Context and location of the Govone outcrop. a: Location of the Piedmont Basin at the northern margin of the Mediterranean Basin and distribution of Messinian evaporites. b: Simplified geological map of the Piedmont Basin showing the location of the Govone outcrop close to the town of Alba.
Results from Air Quality Monitoring and Surveys in UK Residences - Appendix (Survey Questions)
<p>Survey questions used in the paper titled "Results from Air Quality Monitoring and Surveys in UK Residences". Abstract below.</p> <p>Air pollution is a persistent issue in dwellings worldwide, costing an estimated 10-25 billion US dollars per year to the United Kingdom’s national health service alone. However, it is an “invisible problem” since background pollutants are often imperceptible except during acute pollution events such as wildfires. Although public awareness of ventilation has increased due to the COVID-19 pandemic, there are few tools available to assess its efficacy. Widely available sensor systems that can measure these pollutants tend to be single units with simple apps and little connection to mitigation, whereas different rooms in a house may have different pollution issues with different recommended actions. In this study, we present the results of a measurement study conducted using a multi-room sensor kit in twenty-nine dwellings across the UK. We also analyze the occupants’ reaction to the hardware, data, and a prototype alerting system. The study shows broad awareness of air quality in the participants. However, this awareness rarely corresponded to effective mitigation actions or ventilation provision. The concept of alerts was welcomed by participants if accompanied by actionable recommendations.</p> <p>The data showed significant pollution events, as measured by proxies such as total VOC and CO<sub>2</sub>, occurring almost daily, particularly in households with gas appliances. These incidents were concentrated around particular times of day and behaviors, indicating that the capacity of infiltration and extract ventilation to bring in adequate fresh air was overwhelmed. No significant outdoor pollution was detected in houses, which was expected given their sheltered peri-urban locations. The study highlights the need for comprehensive implementation of measurement, ventilation, and treatment measures in the UK housing stock to reduce the impact of indoor pollution on health.</p>
Asiantuntijakysely kaupunkibiotooppien monimuotoisuudesta ja kaupunkibiotooppikartta Suomen pääkaupunkiseudulla / Expert Questionnaire Results Regarding Biodiversity of Urban Biotopes and an Urban Biotope Map in Helsinki Metropolitan Area, Finland
<p>(in English below)</p> <p><strong>ASIANTUNTIJAKYSELY KAUPUNKIBIOTOOPPIEN MONIMUOTOISUUDESTA JA KAUPUNKIBIOTOOPPIKARTTA SUOMEN PÄÄKAUPUNKISEUDULLA</strong></p> <p><strong>Tausta ja tavoitteet</strong></p> <p>Luonnonsuojelu on keskittynyt perinteisesti Suomessa tiettyihin lajeihin ja luontotyyppeihin, mikä ei välttämättä kuvaa erilaisten kaupunkiympäristöjen ekologisia arvoja kattavasti. Lisäksi tulisi huomioida eliöyhteisöjä, jotka turvaavat kestävän ja monimuotoisen ekosysteemien toiminnallisuuden.</p> <p>Tämän asiantuntijakyselyn tavoitteena oli selvittää, miten erilaiset kaupunkibiotoopit tukevat erilaisia ekologisten yhteisöjen monimuotoisuutta kuvaavia tekijöitä eri eliöryhmillä. Nämä <em>monimuotoisuuden laatutekijät</em> kuvaavat yhdessä biotooppien roolia kaupunkiluonnon monimuotoisuudessa, toiminnallisuudessa ja täten epäsuorasti myös mm. ekosysteemipalvelujen tarjoamisessa. Kyselyn tuloksia voidaan hyödyntää ekologisten arvojen turvaamiseksi paremmin osana kaupunkisuunnittelua tai kaupunkiluonnon monimuotoisuuden kattavan turvaamisen perustana. Kysely keskittyi pääkaupunkiseudun (Helsinki, Espoo, Vantaa, Kauniainen) biotooppeihin. Lisäksi asiantuntijat antoivat arvionsa biotooppipisteytyksen sovellettavuudesta muualla Suomessa.</p> <p>Kysely on kuvattu Terra-lehdessä (Jalkanen & Vierikko 2022) sekä Jalkanen ym. (2020).</p> <p><strong>Menetelmät</strong></p> <p><em>Kaupunkibiotooppien pisteytys</em></p> <p>Aineisto kerättiin internetkyselyllä 5.10.-21.11.2016 välisenä aikana. Kysely lähetettiin 38 paikalliselle lajiasiantuntijalle (Luonnontieteellisessä keskusmuseossa, Helsingin yliopistossa, Suomen ympäristökeskuksessa, ympäristökonsulttiyrityksissä ja luontojärjestöissä), joista 24 osallistui kyselyyn.</p> <p>Mukana olleet asiantuntijat (suluissa heidän lajiryhmänsä):</p> <ul> <li>Heidi Björklund (Linnut)</li> <li>Tea von Bonsdorff (Sienet, muut kuin käävät)</li> <li>Eero Haapanen (Nisäkkäät, muut kuin lepakot)</li> <li>Nina Hagner-Wahlsten (Lepakot)</li> <li>Jari Kaitila (Perhoset)</li> <li>Jarkko Korhonen (Sienet, muut kuin käävät)</li> <li>Jaakko Kullberg (Perhoset)</li> <li>Eeva-Maria Kyheröinen (Lepakot)</li> <li>Esa Lammi (Putkilokasvit)</li> <li>Riku Lumiaro (Nisäkkäät, muut kuin lepakot)</li> <li>Sampsa Malmberg (Kovakuoriaiset)</li> <li>Ilpo Mannerkoski (Kovakuoriaiset)</li> <li>Olli Manninen (Käävät)</li> <li>Heikka Marttila-Tornio (Matelijat & sammakkoeläimet)</li> <li>Juho Paukkunen (Pistiäiset)</li> <li>Terhi Ryttäri (Putkilokasvit)</li> <li>Jarmo Saarikivi (Matelijat & sammakkoeläimet)</li> <li>Hannu Sarvanne (Linnut)</li> <li>Keijo Savola (Käävät)</li> <li>Ilkka Teräs (Pistiäiset)</li> <li>Stephen Venn (Kovakuoriaiset)</li> <li>Tarmo Virtanen (Perhoset)</li> <li>Terhi Wermundsen (Lepakot)</li> <li>Rauno Yrjölä (Linnut)</li> </ul> <p>Asiantuntijat pisteyttivät kyselyssä 68 biotooppia sen mukaan, kuinka ne tukevat heidän lajiryhmiensä eri ominaisuustekijöitä. Jokainen biotooppi arvioitiin erikseen kunkin tekijän näkökulmasta. Pisteet annettiin 5-portaisella asteikolla (0–4; 0 alin). Asiantuntijoita ohjeistettiin miettimäään koko vuodenaikaiskiertoa (arvioimaan biotooppien merkitystä siis myös esim. talvehtimisen kannalta). Kysely perustui Vierikon ym. (2014) biotooppiluokitteluun seuraavin muutoksin:</p> <ul> <li>Metsäbiotoopit jaettiin kahteen ikäluokkaan (30–100-vuotiaat ja yli 100-vuotiaat metsät)</li> <li>Piha-alueet jaettiin päällystettyihin ja maavaraisiin</li> <li>Tiiviiden pientaloalueiden ja townhouse-alueiden pihat lisättiin omana biotooppinaan</li> <li>Kalliolaet, -rinteet ja -seinämät sekä kivikot yhdistettiin samaksi biotoopiksi (paljaat kalliopinnat)</li> <li>Uimarannat, kanaalit ja rantaterassit yhdistettiin samaksi biotoopiksi (rakennetut rannat)</li> <li>Kiviseinät ja lintuluodot poistettiin</li> <li>Viherseinät lisättiin omana biotooppinaan</li> </ul> <p>Biotooppien merkitystä kysyttiin seuraavissa eliöyhteisöjen monimuotoisuuden laatua kuvaavissa kategorioissa:</p> <ol> <li>Lajirikkaus</li> <li>Vaatelias lajisto</li> <li>Biomassa</li> <li>Runsaus</li> <li>Tasaisuus</li> <li>Uniikkius</li> <li>Seudullinen edustavuus</li> <li>Herkkyys ihmissyntyisiä häiriöitä kohtaan</li> <li>Kytkeytyvyys</li> </ol> <p>Asiantuntijat arvioivat lisäksi omien vastaustensa luotettavuutta, erikseen jokaisen tekijän kohdalla. Tässä aineistossa biotooppien pisteet on painotettu nousevan painokertoimen mukaan, jotta luotettavat vastaukset korostuvat epäluotettavia voimakkaammin. Luotettavuuskertoimet ovat 0, 1, 2, 4 ja 8, mitkä tarkoittavat “erittäin epäluotettavia”, “epäluotettavia”, “jonkin verran epäluotettavia”, ”melko luotettavia” ja ”erittäin luotettavia” vastauksia.</p> <p> <em>Biotooppipisteiden sovellettavuus muualla Suomessa</em></p> <p>Kyselyn jälkeen asiantuntijat arvioivat työpajassa, kuinka hyvin heidän vastauksiaan voi soveltaa muissa suomalaisissa kaupungeissa. Työpaja pidettiin 29.11.2016. Tarkka kysymyksenasettelu oli:</p> <p><em>Tämä kysely on laadittu Etelä-Suomen ja erityisesti pääkaupunkiseudun (Helsinki, Espoo, Vantaa, Kauniainen) näkökulmasta. Kuinka hyvin kyselyn tulokset kuvaavat eliöryhmäsi lajistoa muiden Suomen maakuntien kaupungeissa? Vastaa asteikolla 0–10 (0: tämän kyselyn tuloksia ei voi soveltaa lainkaan ko. maakunnan kaupunkeihin, 10: kyselyn tulokset soveltuvat erittäin hyvin ko. maakunnan kaupunkiluontoon). Vastaa myös, kuinka luotettavina vastauksiasi voidaan pitää asteikolla 0-3 (0: hyvin epäluotettavina, 3: hyvin luotettavina). <strong>Vastaa oman eliöryhmäsi näkökulmasta.</strong></em></p> <p>Tässä aineistossa vastaukset näytetään alkuperäisinä, eli luotettavia vastauksia ei korosteta erikseen kuten biotooppipisteytyksessä.</p> <p><strong>Aineistot:</strong></p> <p>Aineistot ovat suomeksi (etuliite ”FIN”) ja englanniksi (”ENG”). Aineisto sisältää:</p> <ul> <li>Monimuotoisuuden laatutekijöiden luonnehdinnat ja pisteytysohjeet (.pdf)</li> <li>Kaupunkibiotooppien luonnehdinnat (.pdf)</li> <li>Kaupunkibiotooppien pisteytys taulukkona (.xlsx)</li> <li>Taulukko vastausten sovellettavuudesta muualla Suomessa (.xlsx)</li> </ul> <p>Taulukkotiedostoissa monimuotoisuuden laatutekijän tai eliöryhmän perässä oleva numero viittaa asiantuntijaan (esim. lintuja koskevissa sarakkeissa ”Lajirikkaus 1” ja ”Vaateliaat lajit 1” viittaavat saman lintuasiantuntijan vastauksiin). Asiantuntijoiden vastaukset on listattu satunnaisjärjestyksessä. Kaikki asiantuntijat ovat suostuneet heidän vastaustensa ja nimiensä julkaisemiseen kirjallisesti.</p> <p><strong>KAUPUNKIBIOTOOPPIKARTTA</strong></p> <p>Kansiossa "FIN_Kaupunkibiotooppikartta" on rasterimuotoinen kartta pääkaupunkiseudun kaupunkibiotoopeista paikkatietomuodossa. Kartta on luotu 2021 eri paikkatietolähteistä (ks. Jalkanen ym. 2020). Kaupunkibiotooppikartta mahdollistaa esimerkiksi monimuotoisuusarvojen tarkastelun pääkaupunkiseudulla yhdessä asiantuntijakyselyn tulosten kanssa. HUOM! Karttaa ei ole tarkoitettu sellaisenaan suunnittelukäyttöön. Minkäänlaisia takuita tulosten oikeellisuudesta, virheettömyydestä tai käytettävyydestä ei myönnetä.</p> <p>Kansiossa on seuraavat tiedostot:</p> <ul> <li>Kaupunkibiotooppikartta (.tif) (CRS: EPSG 3902)</li> <li>Kaupunkibiotooppikartan soluarvojen selitykset (.xlsx). Kaupunkibiotooppikartta käsittää 53 biotooppia/maanpeiteluokkaa, eli kaikkia asiantuntijakyselyn biotooppeja ei ole pystytty koostamaan kartalle.</li> <li>Kaupunkibiotooppikartan koostamisen ja lähtöaineistojen kuvaus (.pdf)</li> </ul> <p><strong>Kiitokset: </strong>Kiitämme Silviya Korpiloa, Susanna Lehvävirtaa ja Stephen Venniä avusta englanninnosten kanssa. </p> <p><strong>Viittausohje:</strong> Jalkanen, J. & Vierikko, K. (2022) Asiantuntijakysely kaupunkibiotooppien monimuotoisuudesta sekä kaupunkibiotooppikartta Suomen pääkaupunkiseudulla [Aineisto] https://doi.org/10.5281/zenodo.6563190</p> <p>Aineistoon tulee viitata käytettäessä.</p> <p><strong>Viitteet: </strong></p> <ul> <li>Jalkanen, J. & Vierikko, K. (2022) Viheralueiden elonkirjo – Asiantuntijakysely ja luonnon monimuotoisuuden laatumittaristo kaupunkisuunnittelun tueksi. <em>Terra</em> 134: 207–223. https://doi.org/10.30677/terra.120163</li> <li>Jalkanen, J., Vierikko, K. & Moilanen, A. (2020) Spatial prioritization for urban Biodiversity Quality using biotope maps and expert opinion. <em>Urban Forestry & Urban Greening</em> 49: 126586. https://doi.org/10.1016/j.ufug.2020.126586.</li> <li>Vierikko, K., Niemelä, J., Salminen, J., Jalkanen, J. & Tamminen, N. 2014: Helsingin kestävä viherrakenne –Miten turvata kestävä viherrakenne ja kaupunkiluonnon monimuotoisuus tiivistyvässä kaupunkirakenteessa. Helsingin kaupunkisuunnitteluviraston yleissuunnitteluosaston selvityksiä 2014:27. Helsinki. 132 s.</li> </ul> <p> </p> <p><strong>EXPERT QUESTIONNAIRE RESULTS REGARDING BIODIVERSITY OF URBAN BIOTOPES AND AN URBAN BIOTOPE MAP IN HELSINKI METROPOLITAN AREA, FINLAND</strong></p> <p><strong>Background and aim:</strong></p> <p>Finnish biodiversity conservation has traditionally focused on certain species and biotopes, which does not necessarily describe urban areas’ ecological values in a comprehensive manner. In addition, focus should be put on ecological communities that enable resilient and diverse ecosystem functioning.</p> <p>The aim of this questionnaire was to determine how different urban biotopes support different biodiversity quality attributes of ecological communities of different higher taxonomic groups. Together these attributes describe biotopes’ support for sustainable urban ecosystem functioning and, thus, indirectly for ecosystem services provisioning. The results can be used to better preserve ecological values in urban planning and as a basis for comprehensive urban biodiversity conservation. The questionnaire focused on biotopes found in the Helsinki Metropolitan Area (HMA; municipal cities of Helsinki, Espoo, Vantaa, and Kauniainen), Southern Finland. In addition, the applicability of the scoring elsewhere in Finnish cities was evaluated.</p> <p>The questionnaire is described in Terra (Jalkanen & Vierikko 2022; in Finnish with English abstract) and in Jalkanen et al. (2020).</p> <p><strong>Methods:</strong></p> <p><em>Scoring of urban biotopes</em></p> <p>The data was collected using an online questionnaire during 5.10.-21.11.2016. It was sent to 38 local taxonomic experts (from Finnish Museum of Natural History, University of Helsinki, Finnish Environment Institute, environmental consultant firms, and local environmental NGOs), out of which 24 replied.</p> <p>Experts who participated were (their taxon):</p> <ul> <li>Heidi Björklund (Birds)</li> <li>Tea von Bonsdorff (Fungi, other than polypores)</li> <li>Eero Haapanen (Mammals, other than bats)</li> <li>Nina Hagner-Wahlsten (Bats)</li> <li>Jari Kaitila (Butterflies)</li> <li>Jarkko Korhonen (Fungi, other than polypores)</li> <li>Jaakko Kullberg (Butterflies)</li> <li>Eeva-Maria Kyheröinen (Bats)</li> <li>Esa Lammi (Vascular plants)</li> <li>Riku Lumiaro (Mammals, other than bats)</li> <li>Sampsa Malmberg (Beetles)</li> <li>Ilpo Mannerkoski (Beetles)</li> <li>Olli Manninen (Polypores)</li> <li>Heikka Marttila-Tornio (Herpetofauna)</li> <li>Juho Paukkunen (Hymenoptera)</li> <li>Terhi Ryttäri (Vascular Plants)</li> <li>Jarmo Saarikivi (Herpetofauna)</li> <li>Hannu Sarvanne (Birds)</li> <li>Keijo Savola (Polypores)</li> <li>Ilkka Teräs (Hymenoptera)</li> <li>Stephen Venn (Beetles)</li> <li>Tarmo Virtanen (Butterflies)</li> <li>Terhi Wermundsen (Bats)</li> <li>Rauno Yrjölä (Birds)</li> </ul> <p>In the questionnaire, the experts scored 68 local urban biotopes in terms of how well they support different biodiversity attributes of their taxonomic group. Each biotope was scored separately for every attribute. Scores were given on a 5-rank scale (0–4; 0 being the lowest). Experts were advised to consider all seasons (e.g., to consider the importance of the biotope also for wintering). We used the biotope classification from the expert questionnaire by Vierikko et al. (2014) with the following modifications:</p> <ul> <li>Forest biotopes were further divided into two age classes (30-100 y. and over 100 y.)</li> <li>Yards were further divided into sealed and bare yards</li> <li>Densely-built residential gardens & townhouse gardens were added as a new biotope</li> <li>Outcrops, ledges, and rocky grounds were combined to one biotope (bare rocks)</li> <li>Beaches, canals, and terraced embankments were combined to one biotope (artificial shores)</li> <li>Stone walls and bird-colonized islets were excluded</li> <li>Green walls were added as a new biotope</li> </ul> <p>The relevance of biotopes was evaluated for the following Biodiversity Quality attributes that describe or relate to the diversity of urban ecological communities:</p> <ol> <li>Species richness</li> <li>Habitat specialist species</li> <li>Biomass</li> <li>Abundance</li> <li>Evenness</li> <li>Uniqueness</li> <li>Regional representativeness</li> <li>Sensitivity towards anthropogenic disturbance</li> <li>Connectivity</li> </ol> <p>In addition, experts gave overall self-evaluated confidence rates for their answers concerning each attribute. In the data, biotopes’ scores are weighted by an increasing confidence coefficient in order to emphasize confident answers over non-confident ones. Confidence coefficients are 0, 1, 2, 4, and 8 that refer to ‘very unconfident’, ‘unconfident’, ‘somewhat unconfident’, ‘somewhat confident’, and ‘very confident’ answers, respectively.</p> <p><em>Applicability of the urban biotope scores elsewhere in Finland</em></p> <p>After the questionnaire, experts assessed how applicable their answers are elsewhere in Finland. This task was done in an expert workshop on 29.11.2016. The exact question, given to the experts, was:</p> <p><em>This questionnaire is designed from Southern Finnish, and especially from the Helsinki Metropolitan area (cities of Helsinki, Espoo, Vantaa, Kauniainen) perspective. How well do the questionnaire results describe the species assemblages of your taxon found in cities in other Finnish provinces? Answer on a scale of 0-10 (0: the results of this questionnaire are completely inapplicable to the cities in the given province, 10: the results of the questionnaire apply very well to the urban nature of the given province). Also evaluate the confidence of your answers at the scale of 0-3 (0: very unconfident, 3: very confident). <strong>Answer from the point of view of your own taxon.</strong></em></p> <p>In the data, the expert answers are reported as they were given, i.e., confident answers are not emphasized over non-confident ones like with biotope scores.</p> <p><strong>Data:</strong></p> <p>Data is provided in Finnish (files starting with ‘FIN’) and in English (‘ENG’). This data set includes:</p> <ul> <li>Biodiversity Quality attribute descriptions and scoring instructions (.pdf)</li> <li>Urban biotope descriptions (.pdf)</li> <li>Table of urban biotope scores (.xlsx)</li> <li>Table of the applicability of biotope scores elsewhere in Finland (.xlsx)</li> </ul> <p>In the tables, the Arabic number after the attribute or taxon name refers to the corresponding expert (i.e., under birds (‘Richness 1’ and ‘Specialist species 1’ refer to the answers of the same bird expert). Experts’ answers are listed in random order. All experts have agreed on publication of their answers and names using written informed consent.</p> <p><strong>URBAN BIOTOPE MAP</strong></p> <p>The folder ’ENG_UrbanBiotopeMap’ includes a raster-type GIS layer of urban biotopes in the Helsinki Metropolitan area. The map has been compiled from several GIS sources (see Jalkanen et al. 2020). The urban biotope map allows for example spatial analyses of biodiversity values together with the expert questionnaire results. OBS! The map is not meant for planning purposes. No warrant about the correctness, flawlessness, or feasibility of the results is given.</p> <p>The folder includes the following files:</p> <ul> <li>The urban biotope map (.tif) (CRS: EPSG 3902)</li> <li>The explanation of the cell values of the urban biotope map (.xlsx). The urban biotope map comprises of 53 different biotopes/land cover types, i.e., every biotope asked in the questionnaire are not found in the map.</li> </ul> <p><strong>Acknowledgements:</strong> We thank Silviya Korpilo, Susanna Lehvävirta, and Stephen Venn for help with the English translations.</p> <p><strong>How to cite: </strong>Jalkanen, J. & Vierikko, K. (2022) Expert questionnaire results regarding biodiversity of urban biotopes and an urban biotope map in Helsinki Metropolitan Area, Finland [Data set] https://doi.org/10.5281/zenodo.6563190</p> <p>Data should be properly cited when used.</p> <p><strong>References:</strong></p> <ul> <li>Jalkanen, J. & Vierikko, K. (2022) Viheralueiden elonkirjo – Asiantuntijakysely ja luonnon monimuotoisuuden laatumittaristo kaupunkisuunnittelun tueksi (Biodiversity in urban green spaces: Expert questionnaire about urban Biodiversity Quality to support urban planning) . <em>Terra</em> 134: 207–223. https://doi.org/10.30677/terra.120163 [In Finnish with English abstract.]</li> <li>Jalkanen, J., Vierikko, K. & Moilanen, A. (2020) Spatial prioritization for urban Biodiversity Quality using biotope maps and expert opinion. <em>Urban Forestry & Urban Greening</em> 49: 126586. https://doi.org/10.1016/j.ufug.2020.126586.</li> <li>Vierikko, K., Salminen, J., Niemelä J., Jalkanen, J. & Tamminen, N. 2014: Sustainable green infrastructure of Helsinki – urban ecological research report and recommendations for the Helsinki master plan 2050. Strategic Planning Office of the City Planning Department of the City of Helsinki. Research report. [In Finnish with English abstract.] Available in: <a href="https://www.hel.fi/hel2/ksv/julkaisut/yos_2014-27.pdf">https://www.hel.fi/hel2/ksv/julkaisut/yos_2014-27.pdf</a> (Cited 16.1.2018). 132 pp.</li> </ul> <p> </p>
Quantum calculation results for "Butyl Acetate Pyrolysis and Combustion Chemistry: Mechanism Generation and Shock Tube Experiments"
<p>This repository contains the quantum calculation results associated with the paper "Butyl Acetate Pyrolysis and Combustion Chemistry: Mechanism Generation and Shock Tube Experiments" by Xiaorui Dong, Gianmaria Pio, Farhan Arafin, Andrew Laich, Jessica Baker, Erik Ninnemann, Subith S. Vasu, and William H. Green.</p> <p>In the BA_QM.zip, there are five subfolders:</p> <ul> <li>The "BA_Habs" folder has 18 entries related to the calculations of butyl acetate H abstraction reactions</li> <li>The "BA_Retroene" folder has 6 entries related to the calculations of butyl acetate retro-ene reactions</li> <li>The "Species" folder has 606 entries related to the calculations of non-TS species included in the kinetic mechanisms.</li> <li>The "TS_XYZ" and "XYZ" folders contain the XYZ files of the calculated TS and non-TS geometries, respectively.</li> </ul> <p>For each species and TS calculation, the CBS-QB3 optimization/single point energy calculation is stored in the "composite" folder, the frequency calculation is stored in the 'freq' folder, and scan jobs for torsional modes (if available) are stored in the 'scan_XXXX' folders. For reaction and TS entries, folders are named in a user-readable way. For species, folders are named according to their SMILES representation.</p>
Results: Modeling the impact of the Omicron infection wave in Germany
<p># Modeling the impact of the Omicron infection wave in Germany</p> <p>This repository contains results of a modelling study regarding the spread of SARS-CoV-2 VOC "Omicron" in Germany.</p> <p>## Columns and values</p> <p>| column name | type | description EN | description DE |<br> | -- | -- | -- | -- |<br> | `infectious_period_both` | int | Mean infectious period (in days) for both variants | Mittlere Infektiositaetsperiode fuer beide Varianten (in Tagen) |<br> | `omicron_latent_period` | int | Mean latent period of VOC Omicron (in days) | Mittlere Latenzzeit der VOC Omikron (in Tagen) |<br> | `booster_reach` | str | Reach of the booster campaign | Reichweite der Auffrischkampagne |<br> | `booster_VE` | str | Vaccine efficacy of the booster vaccination | Impfeffektivitaet der Auffrischimpfung |<br> | `contact_reduction_scenario_id` | int | ID of the contact reduction scenario | ID des Kontaktreduktionsszenarios |<br> | `contact_reduction_strength` | float | prefactor with which the contact modulation f(t) is multiplied | Vorfaktor, mit der die Kontaktmodulation f(t) waehrend der Kontaktreduktionsperiode skaliert wird |<br> | `contact_reduction_start` | date (ISO 8601) | Date when contact reduction begins | Beginn der Kontaktreduktion |<br> | `contact_reduction_end` | date (ISO 8601) | Date when contact reduction ends | Ende der Kontaktreduktion |<br> | `relative_risk_hospitalization` | float | Relative risk (RR) of hospitalization after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Hospitalisierung nach Infektion mit Omicron gegenueber Infektion mit Delta |<br> | `relative_risk_icu` | float | Relative risk (RR) of ICU admission after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Intensivpflichtigkeit nach Infektion mit Omicron gegenueber Infektion mit Delta |<br> | `value_type` | str | Wich value is shown in the `value` column | Art des Wertes in der Spalte `value` |<br> | `date` | date (ISO 8601) | Date associated with the modeling result given in column `value` | Datum assoziiert mit dem Modellergebnis des Wertes in der Spalte `value` |<br> | `value` | int | Model result (rounded to nearest integer) | Modellergebnis (gerundet auf ganze Zahl) |</p> <p>Additional columns regarding combinations of plausible scenarios (rounded to nearest integer) and 180 stochastic simulations per parameter combination:</p> <p>| column name | type | description EN | description DE |<br> | -- | -- | -- | -- |<br> | `95_PI_lower` | int | 95% PI lower bound (rounded to nearest integer) | Untere Schranke des 95% PIs (gerundet auf ganze Zahl) |<br> | `50_PI_lower` | int | 50% PI lower bound (rounded to nearest integer) | Untere Schranke des 50% PIs (gerundet auf ganze Zahl) |<br> | `median` | int | median (rounded to nearest integer) | Median (gerundet auf ganze Zahl) |<br> | `50_PI_upper` | int | 50% PI upper bound (rounded to nearest integer) | Obere Schranke des 50% PIs (gerundet auf ganze Zahl) |<br> | `95_PI_upper` | int | 95% PI upper bound (rounded to nearest integer) | Obere Schranke des 95% PIs (gerundet auf ganze Zahl) |</p> <p>### Values: `booster_reach`</p> <p>| value | description EN | description DE |<br> | -- | -- | -- |<br> | `md` | medium booster campaign reach (80% of those that received full vaccination in 2021 receive booster vaccination) | Medium, 80% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung |<br> | `hi` | high booster campaign reach (100% of those that received full vaccination in 2021 receive booster vaccination) | Hoch, 100% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung |<br> | `hi-and-90perc-2dose` | 100% receive booster vaccination and vaccine uptake of first immunization suddenly increases to 90% in Jan 2022 | 100% erhalten Auffrischimpfung und Impfquote der Erstimmunisierung erreicht schnell 90% im Januar 2022 | </p> <p><br> ### Values: `booster_VE`</p> <p>| value | description EN | description DE |<br> | -- | -- | -- |<br> | `lo` | low booster vaccine efficacy (assumption: booster protects as well against infection as 2nd dose) | Niedrige Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie 2 Dosen) |<br> | `hi` | high booster vaccine efficacy (assumption: booster protects as well against infection as against symptomatic disease) | Hohe Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie vor symptomatischer Erkrankung) |</p> <p>### Values: `value_type`</p> <p>| value | description EN | description DE |<br> | -- | -- | -- |<br> | `inc` | incidence (absolute number of new reported cases per day) | Inzidenz (Zahl der gemeldeten Neuinfektion an diesem Tag, absolut) |<br> | `hsp` | hospitalization incidence (absolute number of new hospital admissions per day) | Hospitalisierungsinzidenz (Zahl der gemeldeten Neuhospitalisierungen an diesem Tag, absolut) |<br> | `icu` | total number of patients in ICUs | Gesamtzahl der intensivpflichtigen Patient:innen |</p> <p>## License</p> <p>Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).<br> </p>
Compiled dataset and posterior results for NEMo analyses on Acacia tolerance to aridity and salinity
<p>The dataset contains the compiled data for the aridity and salinity conditions at <em>Acacia</em> species' presence and absence locations, factors on sampling bias, as well as <em>Acacia</em> phylogeny. The data file is the input to the NEMo analyses. The dataset also contains the result files from the analyses.</p>
Composition and electrical resistance results of a Ir-Pd-Pt-Rh-Ru composition spread thin film materials library
<p>The dataset contains the results of electrical resistance measurement and composition analysis of a thin film composition spread materials library. </p> <p>342 measurement areas were evaluated for chemical composition using energy dispersive X-ray spectroscopy and electrical resistance using a 4-point probe.</p> <p>CSV columns:</p> <p>x: x-coordinate of materials library in µm</p> <p>y: y-coordinate of materials library in µm</p> <p>Ir: relative chemical composition in at.%</p> <p>Pd: relative chemical composition in at.%</p> <p>Pt: relative chemical composition in at.%</p> <p>Rh: relative chemical composition in at.%</p> <p>Ru: relative chemical composition in at.%</p> <p>Resistance: electrical resistance in Ohm</p> <p> </p> <p>This dataset is supplementary information for an associated publication. A link to the publication will be provided after publishing.</p>
In-silico PCR results for PSSC primer sets exhibiting >50% amplification rate
<p>using in-silico PCR, 2,161 genomes from<em> </em>the <em>Pseudomonas syringae</em> species complex were amplified using 16 established PCR primer sets, allowing one mismatch per primer. Each file here contains amplicons generated from a single primer set, with each amplicon sequence named with the GenBank accession number for the associated genome.</p>
CMB heat flux PCA results
<p>Results of the CMB heat flux PCA from the Coltice et al. (2019) mantle convection model in the numpy (.npy) format. The PCA is computed on the snapshots of the simulations between 300 Myr and 1131 Myr in the simulation time.</p> <p>-avg_pattern.npy: Spherical harmonic decomposition of the CMB heat flux average pattern</p> <p>-patterns.npy: Spherical harmonic decomposition of the PCA components patterns</p> <p>-sing_val.npy: Singular value of the PCA components</p> <p>-weights.npy: Time dependent weights of the PCA components</p>
Supporting data sets for "Estimating Carbon Fixation of Plant Organs for Afforestation Monitoring using a Process-based Ecosystem Model and Ecophysiological Parameter Optimization". (the survey of tree breast diameter and tree height in 11-year old Eucommia ulmoides plantation, values of simulation results used in figures and tables.)
<p>Supporting data sets for Miyauchi et al., Ecology and Evolution, 2019 (accepted).</p> <p>The files store: </p> <p>(1) The survey of tree breast diameter and tree height in <em>Eucommia ulmoides</em> plantation<em>.</em> The ring and stem analysis and dry weight of seven harvested sample trees in the plantation.</p> <p>(2) Values of optimization result used fig.7.</p> <p>(3) Values of prediction result used fig.8. and table 4.</p> <p>(4) Values of optimized parameters by optimization methods, parameter range and constrain.</p>
FLEX model results
Model results (FLEX model) for 27 basins in Europe for soil moisture compared to AMSR-E, ASCAT, NDII, SMOS, evaporation compared to LSA-SAF and MOD16, snow compared to MOD10 and MYD10 snow products and total water storage anomaly compared to GRACE.
TUW model results
Model results (TUW model) for 27 basins in Europe for soil moisture compared to AMSR-E, ASCAT, NDII, SMOS, evaporation compared to LSA-SAF and MOD16, snow compared to MOD10 and MYD10 snow products and total water storage anomaly compared to GRACE.
HYPE model results
Model results (HYPE model) for 27 basins in Europe for soil moisture compared to AMSR-E, ASCAT, NDII, SMOS, evaporation compared to LSA-SAF and MOD16, snow compared to MOD10 and MYD10 snow products and total water storage anomaly compared to GRACE.
FLEXtopo model results
Model results (FLEXtopo model) for 27 basins in Europe for soil moisture compared to AMSR-E, ASCAT, NDII, SMOS, evaporation compared to LSA-SAF and MOD16, snow compared to MOD10 and MYD10 snow products and total water storage anomaly compared to GRACE.
HYMOD model results
Model results (HYMOD model) for 27 basins in Europe for soil moisture compared to AMSR-E, ASCAT, NDII, SMOS, evaporation compared to LSA-SAF and MOD16, snow compared to MOD10 and MYD10 snow products and total water storage anomaly compared to GRACE.
Results of L-S and L-L analyses
<p>Dataset for the paper entitled "<strong>Spatial patterns of local species richness reveal importance of frugivores for tropical forest diversity". </strong>The results of large-large and large-small analyses of common trees in the Mo Singot plot, Thailand.</p>
Datasets containings simulation results
<p>These are the datasets containings the simulation results presented in "Approximate Bayes factors: flexible and likelihood-free model comparison with ABrox".</p>
Source Location Privacy Aware Routing Protocols Selection Results
<p>This is the dataset used to generate the results for the journal paper " A Decision Theoretic Framework for Selecting Source Location Privacy Aware Routing Protocols in Wireless Sensor Networks" at Future Generation Computer Systems (FGCS) 2018.</p> <p> </p> <p> </p>
Supplementary Data: Full Results: Synergies of sector coupling and transmission extension in a cost-optimised, highly renewable European energy system
<p>Supplementary Data</p> <p><a href="https://arxiv.org/abs/1801.05290"><strong>Synergies of sector coupling and transmission extension in a cost-optimised, highly renewable European energy system</strong></a></p> <p>Authors: T. Brown, D. Schlachtberger, A. Kies, S. Schramm, M. Greiner</p> <p><a href="https://arxiv.org/abs/1801.05290">arXiv:1801.05290</a></p> <p>The files in this record contain the full output data from each of the scenarios considered in the above publication. They also include the post-processed input data, which might be useful if you want to rerun the scenarios with only small changes to the input data.</p> <p>The scripts to build the model, input data and result summaries can be found in a <a href="https://zenodo.org/record/1146665">companion Zenodo repository</a>. (The supplementary data was split because of the size of the full results.)</p> <p>For each scenario, there is a <a href="https://github.com/PyPSA/PyPSA">PyPSA</a> network file in <a href="https://en.wikipedia.org/wiki/Hierarchical_Data_Format">HDF5 format</a> and a CSV of shadow prices.</p> <p>To read in a network file do:</p> <pre><code class="language-python">import pypsa network = pypsa.Network("network_file_name.h5")</code></pre> <p>All data is released under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International Licence</a> (CC BY 4.0).</p>
Correcting for population stratification reduces false positive and false negative results in joint analyses of host and pathogen genomes [G2G-Simulator: Simulated dataset]
<p>Data associated with the paper 'Correcting for population stratification reduces false positive and false negative results in joint analyses of host and pathogen genomes'.</p> <p>It contains the raw simulated data from the 'G2G-Simulator' program. </p> <p>Those data need to be loaded in a R environment .</p> <p>You can reproduce plots present in the paper by parsing the R object using the script 'parse_paper_data.R' present in the G2G-Simulator GitHub repository (https://github.com/onaret/G2G-Simulator/paper/parse_paper_dataset.R). </p>
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.