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Research data keyboard_double_arrow_right Dataset 2017Publisher:NERC Environmental Information Data Centre Reinsch, S.; Koller, E.; Sowerby, A.; De Dato, G.; Estiarte, M.; Guidolotti, G.; Kovács-Láng, E.; Kröel-Dula, G; Lellei-Kovács, E.; Larsen, K.S.; Liberati, D.; Ogaya, R; Peñuelas, J.; Ransijn, J.; Robinson, D.A.; Schmidt, I.K.; Smith, A.R.; Tietema, A.; Dukes, J.S.; Beier, C.; Emmett, B.A.;The data consists of annual measurements of standing aboveground plant biomass, annual aboveground net primary productivity and annual soil respiration between 1998 and 2012. Data were collected from seven European shrublands that were subject to the climate manipulations drought and warming. Sites were located in the United Kingdom (UK), the Netherlands (NL), Denmark ( two sites, DK-B and DK-M), Hungary (HU), Spain (SP) and Italy (IT). All field sites consisted of untreated control plots, plots where the plant canopy air is artificially warmed during night time hours, and plots where rainfall is excluded from the plots at least during the plants growing season. Standing aboveground plant biomass (grams biomass per square metre) was measured in two undisturbed areas within the plots using the pin-point method (UK, DK-M, DK-B), or along a transect (IT, SP, HU, NL). Aboveground net primary productivity was calculated from measurements of standing aboveground plant biomass estimates and litterfall measurements. Soil respiration was measured in pre-installed opaque soil collars bi-weekly, monthly, or in measurement campaigns (SP only). The datasets provided are the basis for the data analysis presented in Reinsch et al. (2017) Shrubland primary production and soil respiration diverge along European climate gradient. Scientific Reports 7:43952 https://doi.org/10.1038/srep43952 Standing biomass was measured using the non-destructive pin-point method to assess aboveground biomass. Measurements were conducted at the state of peak biomass specific for each site. Litterfall was measured annually using litterfall traps. Litter collected in the traps was dried and the weight was measured. Aboveground biomass productivity was estimated as the difference between the measured standing biomass in year x minus the standing biomass measured the previous year. Soil respiration was measured bi-weekly or monthly, or in campaigns (Spain only). It was measured on permanently installed soil collars in treatment plots. The Gaussen Index of Aridity (an index that combines information on rainfall and temperature) was calculated using mean annual precipitation, mean annual temperature. The reduction in precipitation and increase in temperature for each site was used to calculate the Gaussen Index for the climate treatments for each site. Data of standing biomass and soil respiration was provided by the site responsible. Data from all sites were collated into one data file for data analysis. A summary data set was combined with information on the Gaussen Index of Aridity Data were then exported from these Excel spreadsheet to .csv files for ingestion into the EIDC.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 21 Nov 2023Publisher:Harvard Dataverse Authors: Odersky, Moritz; Löffler, Max;doi: 10.7910/dvn/puu3nf
Journal of Economic Inequality, accepted
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Zenodo Alexander-Haw, Abigail; Dütschke, Elisabeth; Janßen, Hannah; Preuß, Sabine; Schleich, Joachim; Tröger, Josephine; Tschaut, Mareike;This dataset and codebook correspond to the second round of survey data gathered in Denmark in 2023, within the project FULFILL - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes. As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from six countries: Denmark, France, Germany, Italy, Latvia, and India. The first round of the survey, consisted of recruiting a representative sample of approximately 2000 households in each country. In this second survey round, we recruit around 500 respondents from the initial survey round, ensuring representativity is maintained. This survey is very similar to the survey in the first round and includes a lot of identical items, including a quantitative assessment of the carbon footprint in the housing, mobility, and diet sectors, socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. Furthermore, the survey includes measures of quality of life, encompassing aspects such as health and well-being, environmental quality, financial security, and comfort. New for this second round, we have incorporated questions regarding the measures respondents adopted in response to the 2022 energy crisis.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 NetherlandsPublisher:DANS Data Station Social Sciences and Humanities Authors: Gao, X.; De Hoge, I.E.; Fischer, A.R.H.;Fashion products made from repurposed materials (e.g., backpacks made from pineapple leaves) have become more prevalent nowadays, and their environmental sustainability is one of the core advantages. Yet, it is currently unclear how consumers respond to products made from repurposed materials. We conducted three experiments to examine the effects of three material features, namely function, sustainability, and distinguishability, on consumer preferences for fashion products made from repurposed materials. The results indicate that, when the function of repurposed materials is as good as that of conventional materials, consumers prefer a product made from repurposed materials over the same product made from conventional materials. Also, consumers in general prefer repurposed materials to be less visually distinguishable. Finally, when the sustainability of the repurposed products is emphasized, consumers appear more likely to choose products made from repurposed materials, even when these products have an inferior function. In conclusion, to promote fashion products made from repurposed materials, marketers may emphasize the function and sustainability of repurposed materials, and producers may manufacture repurposed materials that visually resemble conventional materials.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Funded by:EC | REINVENTEC| REINVENTHansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; Mölter, Helena; Nielsen, Hjalti; Pietzner, Katja; Sonesson, Ludwig B.; Stripple, Johannes; S.I. Aan Den Toorn; Tziva, Maria; Tönjes, Annika; Vallentin, Daniel; Van-Veelen, Bregje;This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Clinical Trial 2016 Austria, Belgium, Israel, Japan, Sweden, SwitzerlandPublisher:nct Authors: Prof. Claude Pichard;Background and Aims: This study aims at evaluating the ease of use of the new calorimeter for the measurement of energy expenditure (EE) in intensive care unit (ICU) patients. EE in ICU patients is highly variable depending on the severity of the disease and treatments. Clinicians need to measure EE by indirect calorimetry (IC) to optimize nutritional support for the better clinical outcome. However, indirect calorimeters available on the market have insufficient accuracy for clinical and research use. Difficulties of handling and interpretation of results often limit IC in ICU patients. An accurate, easy-to-use calorimeter has been developed to meet these needs. The Study Device: The new calorimeter (Quark RMR 2.0, COSMED) is capable of IC measurements in mechanically ventilated patients without warm-up and limited calibration. The disposable in-line pneumotach flow meter and direct sampling of respiratory gas from the ventilator circuit enables the accurate measurement of oxygen consumption volume (VO2) and CO2 production volume (VCO2) to derive the energy expenditure. The software interface to manage the device and the collected data provides easy-to-use, user-friendly interface. This calorimeter bears an European Commission (EC) Conformity Mark, and will be used in the way it is intended to be used as described in the instruction manual. Currently used indirect calorimeters at each study center will be used as the comparator. This study will evaluate the ease of use of the new calorimeter (Quark RMR 2.0 (COSMED, Italy)) in intensive care unit (ICU) patients compared to currently used calorimeters (i.e. Quark RMR 1.0(COSMED, Italy) or Deltatrac Metabolic Monitor (Datex, Finland)), as well as the stability and the feasibility of the measurements in various clinically relevant situations. Time needed to prepare and start indirect calorimetry (IC) measurement will be compared as the measure of the ease of use of the calorimeter.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Clinical Trial 2018 SwitzerlandPublisher:ClinicalTrials.org The prevalence of type 1 diabetes has been steadily increasing for about 20 years. Despite therapeutic progress, between 20 and 65% of people with diabetes develop diabetic neuropathy, resulting in increased morbidity and mortality. Diabetic neuropathy is not limited to sensitive pain in the lower limbs. It also affects the fibres of the autonomic nervous system (ANS), which results in systemic complications, often disabling (erectile dysfunction, dysidrosis, gastroparesis, orthostatism, etc.) and a probable alteration in the body's thermogenic capacities, although this possibility has not been studied in humans. In rodents, it is possible to activate induced thermogenesis via central stimulation of the ANS or to inactivate it, which promotes the development of obesity and greater insulin resistance. This knowledge is based on cellular and animal models that have identified the bio-molecular mechanisms that give brown adipose tissue (BAT) the ability to dissipate energy in the form of heat. Induced thermogenesis is mediated by decoupling proteins 1 (DCS-1) located on the mitochondrial inner membrane of the TAB. DCS-1 decouple oxidative phosphorylation from ATP production, dissipating the proton gradient. The activation of UCP1 is particularly influenced by the sympathetic system and more particularly by catecholamines which will bind to ß3 adrenergic receptors (Rß3). In humans, the persistence of active areas of TAB has recently been demonstrated by positron emission tomography (PET) imaging using a glucose analogue radiotracer, 18F-Fluoro-Deoxy-Glucose (18F-FDG), coupled with the scanner (CT). Recently, it has been shown that the use of 18F-FDG PET coupled with magnetic resonance (MRI) is equally effective in differentiating TAB from white fat tissue with less patient irradiation. The activity of the TAB is estimated using the measurement of SUV (standard uptake value) which represents the total glycolytic activity of the tissue and is also commonly referred to as the total metabolic volume. It has been shown in humans that TAB activity is inversely correlated with body mass index and age and positively correlated with exposure to cold and stress levels[6]. Among diabetics, the data are disparate but the spontaneous prevalence of TAB appears to be reduced compared to the general population (1.1% vs 7.5%). To date, no studies have investigated a possible link between the decrease in TAB activity observed in diabetics and the presence of autonomic neuropathy, which is a common and often under-diagnosed complication of diabetes. The main purpose of this study is to evaluate whether the activity and distribution of TAB in patients with diabetes is influenced by the presence of diabetic neuropathy. On the other hand, if the existence of diabetic neuropathy influences energy expenditure in the event of exposure to cold. Finally, whether any differences in the activity and distribution of TAB could be related to changes in the central nervous system. The investigators plan to include a total of 24 patients with type 1 diabetes and separate them into 2 groups: group A; no neuropathic complications and group B; presence of neuropathy. All patients will be characterized in terms of clinical, metabolic and energy expenditure. The activity of the TAB will be evaluated through the use of 18F-FDG PET/IRM imaging, after a cold stimulation protocol (refrigerated jacket) in order to activate the TAB in a homogeneous manner among the participants. Influence of diabetic neuropathy on cold induced brown adipose tissue in type 1 diabetic patients.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection , Dataset 2020 NetherlandsPublisher:figshare Van Erven, Gijs; Kleijn, Anne; Patyshakuliyeva, Aleksandrina; Di Falco, Marcos; Tsang, Adrian; De Vries, Ronald P.; Van Berkel, Willem J.H.; Kabel, Mirjam A.;Abstract Background The ascomycete fungus Podospora anserina has been appreciated for its targeted carbohydrate-active enzymatic arsenal. As a late colonizer of herbivorous dung, the fungus acts specifically on the more recalcitrant fraction of lignocellulose and this lignin-rich biotope might have resulted in the evolution of ligninolytic activities. However, the lignin-degrading abilities of the fungus have not been demonstrated by chemical analyses at the molecular level and are, thus far, solely based on genome and secretome predictions. To evaluate whether P. anserina might provide a novel source of lignin-active enzymes to tap into for potential biotechnological applications, we comprehensively mapped wheat straw lignin during fungal growth and characterized the fungal secretome. Results Quantitative 13C lignin internal standard py-GC–MS analysis showed substantial lignin removal during the 7 days of fungal growth (24% w/w), though carbohydrates were preferably targeted (58% w/w removal). Structural characterization of residual lignin by using py-GC–MS and HSQC NMR analyses demonstrated that Cα-oxidized substructures significantly increased through fungal action, while intact β-O-4′ aryl ether linkages, p-coumarate and ferulate moieties decreased, albeit to lesser extents than observed for the action of basidiomycetes. Proteomic analysis indicated that the presence of lignin induced considerable changes in the secretome of P. anserina. This was particularly reflected in a strong reduction of cellulases and galactomannanases, while H2O2-producing enzymes clearly increased. The latter enzymes, together with laccases, were likely involved in the observed ligninolysis. Conclusions For the first time, we provide unambiguous evidence for the ligninolytic activity of the ascomycete fungus P. anserina and expand the view on its enzymatic repertoire beyond carbohydrate degradation. Our results can be of significance for the development of biological lignin conversion technologies by contributing to the quest for novel lignin-active enzymes and organisms. Background The ascomycete fungus Podospora anserina has been appreciated for its targeted carbohydrate-active enzymatic arsenal. As a late colonizer of herbivorous dung, the fungus acts specifically on the more recalcitrant fraction of lignocellulose and this lignin-rich biotope might have resulted in the evolution of ligninolytic activities. However, the lignin-degrading abilities of the fungus have not been demonstrated by chemical analyses at the molecular level and are, thus far, solely based on genome and secretome predictions. To evaluate whether P. anserina might provide a novel source of lignin-active enzymes to tap into for potential biotechnological applications, we comprehensively mapped wheat straw lignin during fungal growth and characterized the fungal secretome. Results Quantitative 13C lignin internal standard py-GC–MS analysis showed substantial lignin removal during the 7 days of fungal growth (24% w/w), though carbohydrates were preferably targeted (58% w/w removal). Structural characterization of residual lignin by using py-GC–MS and HSQC NMR analyses demonstrated that Cα-oxidized substructures significantly increased through fungal action, while intact β-O-4′ aryl ether linkages, p-coumarate and ferulate moieties decreased, albeit to lesser extents than observed for the action of basidiomycetes. Proteomic analysis indicated that the presence of lignin induced considerable changes in the secretome of P. anserina. This was particularly reflected in a strong reduction of cellulases and galactomannanases, while H2O2-producing enzymes clearly increased. The latter enzymes, together with laccases, were likely involved in the observed ligninolysis. Conclusions For the first time, we provide unambiguous evidence for the ligninolytic activity of the ascomycete fungus P. anserina and expand the view on its enzymatic repertoire beyond carbohydrate degradation. Our results can be of significance for the development of biological lignin conversion technologies by contributing to the quest for novel lignin-active enzymes and organisms.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Publisher:DataverseNL Authors: Koretsky, Zahar; Hernández Serrano, Pedro; Adekunle, Seun; Dumontier, Michel;doi: 10.34894/q80que
Article Abstract To better allocate funds in the new EU research framework programme Horizon Europe, an assessment of current and past efforts is crucial. In this paper we develop and apply a multi-method qualitative and computational approach to provide a catalogue of climate crisis mitigation technologies on the EU level between 2014 and 2020. Using the approach, we observed no public EU-level funding for multiple technologies prioritised by the EU, such as low-carbon production and use of cement and chemicals, electric battery, and a number of industrial decarbonisation processes. We observed a rising trend in the funding of solar power and onshore wind, the adjacent to them power-to-X technology, as well as recycling. At the same time, the shares of funding into fuel cell, biofuel, demand-side energy management, microgrids, and waste management show a decline trend. With note of the exploratory character of the present paper, we propose that the EU Horizon 2020 funding of clean technologies only partially reflected the expectations of key institutionalised EU actors due to the existence of many non-funded prioritised technologies.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Authors: Markus Stoffel; Daniel G. Trappmann; Mattias I. Coullie; Juan A. Ballesteros-Cánovas; +1 AuthorsMarkus Stoffel; Daniel G. Trappmann; Mattias I. Coullie; Juan A. Ballesteros-Cánovas; Christophe Corona;This readme file provides all data and R codes used to perform the analyses presented in Figs. 2-4 of the main text and Supplementary Information Figures S1-S2-S3. FIGURE 2 - Seasonally_dated_GDs.txt: Contains information on the timing (Season) of rockfall (GD) in a given tree (Id) and a given year (yr) over the past 100 years. Inv refers to the operators which analyzed growth disturbances in the tree-ring series. Lat / Long refers to the position of the tree in CH1903/ Swiss Grid projection. Intensity (1-4) refers to (1), intermediate (2) and strong (3) GD. Intensity 4 was attributed to injuries (I). Only the 408 GD rated 3 (strong TRD) and 4 (injuries) were used in Fig. 2. Acronyms used for Response_type read as follows: TRD: Tangential rows of traumatic resin ducts; I: Injuries. Acronyms used for Season refer to Dormancy (1_D), early (2_EE), middle (3_ME) and late (4_LE) earlywood, whereas a GD found in the latewood was attributed to either the early (5_EL) or late (6_LL) latewood. - Trends_in_seasonality_R1.R: The data contained in "Seasonally_dated_GDs" were processed with the R script "Trends_in_Seasonality.R". This seasonal trend analysis code is inspired by work published by Schlögl et al. (2021; https://doi.org/10.1016/j.crm.2021.100294) and Heiser et al. (2022; https://doi.org/10.1029/2011JF002262). FIGURE 3-4-S1 - Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - Rockfall_frequency_climate.R: The data contained in "Tasch_GD.txt" were processed with the R script "Rockfall_frequency_climate.R". - The temperature (Imfeld23_tmp.txt) and precipitation (Imfeld23_prc.txt) data used in Fig. 3 are from the Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Täschgufer site. - The script set with temperature series enables to compute Fig. 4 (l.149:216) and Fig. 3 (l. 216:330); the script set with precipitation series enables to compute Fig. S1 FIGURE S2 - Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) at the Täschgufer site in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - Rockfall_frequency_borehole.R: is adapted from "Rockfall_frequency_climate.R" to work with the borehole dates. - Corvatsch0_6R1: Contains the Corvatsch borehole temperature series (2000-2020, 0.6m depth) (Hoelzle, M. et al. https://doi.org/10.5194/essd-14-1531-2022, 2022). FIGURE S3 - Plattje_GD.txt: Contains the raw data on rockfall impacts (GD) at the Plattje site in a given year (yr) as found all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - - Rockfall_frequency_climate_Plattje.R: The data contained in "Plattje_GD.txt" were processed with the R script "Rockfall_frequency_climate_Plattje.R". - The temperature (Imfeld23_tmp_Plattje.txt) and precipitation (Imfeld23_prc_Plattje.txt) data used in Fig. 3 are from Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Plattje site.
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Research data keyboard_double_arrow_right Dataset 2017Publisher:NERC Environmental Information Data Centre Reinsch, S.; Koller, E.; Sowerby, A.; De Dato, G.; Estiarte, M.; Guidolotti, G.; Kovács-Láng, E.; Kröel-Dula, G; Lellei-Kovács, E.; Larsen, K.S.; Liberati, D.; Ogaya, R; Peñuelas, J.; Ransijn, J.; Robinson, D.A.; Schmidt, I.K.; Smith, A.R.; Tietema, A.; Dukes, J.S.; Beier, C.; Emmett, B.A.;The data consists of annual measurements of standing aboveground plant biomass, annual aboveground net primary productivity and annual soil respiration between 1998 and 2012. Data were collected from seven European shrublands that were subject to the climate manipulations drought and warming. Sites were located in the United Kingdom (UK), the Netherlands (NL), Denmark ( two sites, DK-B and DK-M), Hungary (HU), Spain (SP) and Italy (IT). All field sites consisted of untreated control plots, plots where the plant canopy air is artificially warmed during night time hours, and plots where rainfall is excluded from the plots at least during the plants growing season. Standing aboveground plant biomass (grams biomass per square metre) was measured in two undisturbed areas within the plots using the pin-point method (UK, DK-M, DK-B), or along a transect (IT, SP, HU, NL). Aboveground net primary productivity was calculated from measurements of standing aboveground plant biomass estimates and litterfall measurements. Soil respiration was measured in pre-installed opaque soil collars bi-weekly, monthly, or in measurement campaigns (SP only). The datasets provided are the basis for the data analysis presented in Reinsch et al. (2017) Shrubland primary production and soil respiration diverge along European climate gradient. Scientific Reports 7:43952 https://doi.org/10.1038/srep43952 Standing biomass was measured using the non-destructive pin-point method to assess aboveground biomass. Measurements were conducted at the state of peak biomass specific for each site. Litterfall was measured annually using litterfall traps. Litter collected in the traps was dried and the weight was measured. Aboveground biomass productivity was estimated as the difference between the measured standing biomass in year x minus the standing biomass measured the previous year. Soil respiration was measured bi-weekly or monthly, or in campaigns (Spain only). It was measured on permanently installed soil collars in treatment plots. The Gaussen Index of Aridity (an index that combines information on rainfall and temperature) was calculated using mean annual precipitation, mean annual temperature. The reduction in precipitation and increase in temperature for each site was used to calculate the Gaussen Index for the climate treatments for each site. Data of standing biomass and soil respiration was provided by the site responsible. Data from all sites were collated into one data file for data analysis. A summary data set was combined with information on the Gaussen Index of Aridity Data were then exported from these Excel spreadsheet to .csv files for ingestion into the EIDC.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 21 Nov 2023Publisher:Harvard Dataverse Authors: Odersky, Moritz; Löffler, Max;doi: 10.7910/dvn/puu3nf
Journal of Economic Inequality, accepted
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Zenodo Alexander-Haw, Abigail; Dütschke, Elisabeth; Janßen, Hannah; Preuß, Sabine; Schleich, Joachim; Tröger, Josephine; Tschaut, Mareike;This dataset and codebook correspond to the second round of survey data gathered in Denmark in 2023, within the project FULFILL - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes. As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from six countries: Denmark, France, Germany, Italy, Latvia, and India. The first round of the survey, consisted of recruiting a representative sample of approximately 2000 households in each country. In this second survey round, we recruit around 500 respondents from the initial survey round, ensuring representativity is maintained. This survey is very similar to the survey in the first round and includes a lot of identical items, including a quantitative assessment of the carbon footprint in the housing, mobility, and diet sectors, socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. Furthermore, the survey includes measures of quality of life, encompassing aspects such as health and well-being, environmental quality, financial security, and comfort. New for this second round, we have incorporated questions regarding the measures respondents adopted in response to the 2022 energy crisis.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 NetherlandsPublisher:DANS Data Station Social Sciences and Humanities Authors: Gao, X.; De Hoge, I.E.; Fischer, A.R.H.;Fashion products made from repurposed materials (e.g., backpacks made from pineapple leaves) have become more prevalent nowadays, and their environmental sustainability is one of the core advantages. Yet, it is currently unclear how consumers respond to products made from repurposed materials. We conducted three experiments to examine the effects of three material features, namely function, sustainability, and distinguishability, on consumer preferences for fashion products made from repurposed materials. The results indicate that, when the function of repurposed materials is as good as that of conventional materials, consumers prefer a product made from repurposed materials over the same product made from conventional materials. Also, consumers in general prefer repurposed materials to be less visually distinguishable. Finally, when the sustainability of the repurposed products is emphasized, consumers appear more likely to choose products made from repurposed materials, even when these products have an inferior function. In conclusion, to promote fashion products made from repurposed materials, marketers may emphasize the function and sustainability of repurposed materials, and producers may manufacture repurposed materials that visually resemble conventional materials.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Funded by:EC | REINVENTEC| REINVENTHansen, Teis; Keaney, Monica; Bulkeley, Harriet A.; Cooper, Mark; Mölter, Helena; Nielsen, Hjalti; Pietzner, Katja; Sonesson, Ludwig B.; Stripple, Johannes; S.I. Aan Den Toorn; Tziva, Maria; Tönjes, Annika; Vallentin, Daniel; Van-Veelen, Bregje;This database includes more than 100 decarbonisation innovations in Paper, Plastic, Steel and Meat & Dairy sectors, across their value chains, as well as in Finance. For each innovation there is a description, information about its contribution to decarbonisation, actors and collaborators involved, sources of funding, drivers, (co)benefits and disadvantages. More information on the method for selecting innovations for the database is available here. The database was created as part of REINVENT – a Horizon 2020 research project funded by the European Commission (grant agreement 730053). REINVENT involves five research institutions from four countries: Lund University (Sweden), Durham University (United Kingdom), Wuppertal Institute (Germany), PBL Netherlands Environmental Assessment Agency (the Netherlands) and Utrecht University (the Netherlands). More information can be found on our website: www.reinvent-project.eu.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Clinical Trial 2016 Austria, Belgium, Israel, Japan, Sweden, SwitzerlandPublisher:nct Authors: Prof. Claude Pichard;Background and Aims: This study aims at evaluating the ease of use of the new calorimeter for the measurement of energy expenditure (EE) in intensive care unit (ICU) patients. EE in ICU patients is highly variable depending on the severity of the disease and treatments. Clinicians need to measure EE by indirect calorimetry (IC) to optimize nutritional support for the better clinical outcome. However, indirect calorimeters available on the market have insufficient accuracy for clinical and research use. Difficulties of handling and interpretation of results often limit IC in ICU patients. An accurate, easy-to-use calorimeter has been developed to meet these needs. The Study Device: The new calorimeter (Quark RMR 2.0, COSMED) is capable of IC measurements in mechanically ventilated patients without warm-up and limited calibration. The disposable in-line pneumotach flow meter and direct sampling of respiratory gas from the ventilator circuit enables the accurate measurement of oxygen consumption volume (VO2) and CO2 production volume (VCO2) to derive the energy expenditure. The software interface to manage the device and the collected data provides easy-to-use, user-friendly interface. This calorimeter bears an European Commission (EC) Conformity Mark, and will be used in the way it is intended to be used as described in the instruction manual. Currently used indirect calorimeters at each study center will be used as the comparator. This study will evaluate the ease of use of the new calorimeter (Quark RMR 2.0 (COSMED, Italy)) in intensive care unit (ICU) patients compared to currently used calorimeters (i.e. Quark RMR 1.0(COSMED, Italy) or Deltatrac Metabolic Monitor (Datex, Finland)), as well as the stability and the feasibility of the measurements in various clinically relevant situations. Time needed to prepare and start indirect calorimetry (IC) measurement will be compared as the measure of the ease of use of the calorimeter.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Clinical Trial 2018 SwitzerlandPublisher:ClinicalTrials.org The prevalence of type 1 diabetes has been steadily increasing for about 20 years. Despite therapeutic progress, between 20 and 65% of people with diabetes develop diabetic neuropathy, resulting in increased morbidity and mortality. Diabetic neuropathy is not limited to sensitive pain in the lower limbs. It also affects the fibres of the autonomic nervous system (ANS), which results in systemic complications, often disabling (erectile dysfunction, dysidrosis, gastroparesis, orthostatism, etc.) and a probable alteration in the body's thermogenic capacities, although this possibility has not been studied in humans. In rodents, it is possible to activate induced thermogenesis via central stimulation of the ANS or to inactivate it, which promotes the development of obesity and greater insulin resistance. This knowledge is based on cellular and animal models that have identified the bio-molecular mechanisms that give brown adipose tissue (BAT) the ability to dissipate energy in the form of heat. Induced thermogenesis is mediated by decoupling proteins 1 (DCS-1) located on the mitochondrial inner membrane of the TAB. DCS-1 decouple oxidative phosphorylation from ATP production, dissipating the proton gradient. The activation of UCP1 is particularly influenced by the sympathetic system and more particularly by catecholamines which will bind to ß3 adrenergic receptors (Rß3). In humans, the persistence of active areas of TAB has recently been demonstrated by positron emission tomography (PET) imaging using a glucose analogue radiotracer, 18F-Fluoro-Deoxy-Glucose (18F-FDG), coupled with the scanner (CT). Recently, it has been shown that the use of 18F-FDG PET coupled with magnetic resonance (MRI) is equally effective in differentiating TAB from white fat tissue with less patient irradiation. The activity of the TAB is estimated using the measurement of SUV (standard uptake value) which represents the total glycolytic activity of the tissue and is also commonly referred to as the total metabolic volume. It has been shown in humans that TAB activity is inversely correlated with body mass index and age and positively correlated with exposure to cold and stress levels[6]. Among diabetics, the data are disparate but the spontaneous prevalence of TAB appears to be reduced compared to the general population (1.1% vs 7.5%). To date, no studies have investigated a possible link between the decrease in TAB activity observed in diabetics and the presence of autonomic neuropathy, which is a common and often under-diagnosed complication of diabetes. The main purpose of this study is to evaluate whether the activity and distribution of TAB in patients with diabetes is influenced by the presence of diabetic neuropathy. On the other hand, if the existence of diabetic neuropathy influences energy expenditure in the event of exposure to cold. Finally, whether any differences in the activity and distribution of TAB could be related to changes in the central nervous system. The investigators plan to include a total of 24 patients with type 1 diabetes and separate them into 2 groups: group A; no neuropathic complications and group B; presence of neuropathy. All patients will be characterized in terms of clinical, metabolic and energy expenditure. The activity of the TAB will be evaluated through the use of 18F-FDG PET/IRM imaging, after a cold stimulation protocol (refrigerated jacket) in order to activate the TAB in a homogeneous manner among the participants. Influence of diabetic neuropathy on cold induced brown adipose tissue in type 1 diabetic patients.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection , Dataset 2020 NetherlandsPublisher:figshare Van Erven, Gijs; Kleijn, Anne; Patyshakuliyeva, Aleksandrina; Di Falco, Marcos; Tsang, Adrian; De Vries, Ronald P.; Van Berkel, Willem J.H.; Kabel, Mirjam A.;Abstract Background The ascomycete fungus Podospora anserina has been appreciated for its targeted carbohydrate-active enzymatic arsenal. As a late colonizer of herbivorous dung, the fungus acts specifically on the more recalcitrant fraction of lignocellulose and this lignin-rich biotope might have resulted in the evolution of ligninolytic activities. However, the lignin-degrading abilities of the fungus have not been demonstrated by chemical analyses at the molecular level and are, thus far, solely based on genome and secretome predictions. To evaluate whether P. anserina might provide a novel source of lignin-active enzymes to tap into for potential biotechnological applications, we comprehensively mapped wheat straw lignin during fungal growth and characterized the fungal secretome. Results Quantitative 13C lignin internal standard py-GC–MS analysis showed substantial lignin removal during the 7 days of fungal growth (24% w/w), though carbohydrates were preferably targeted (58% w/w removal). Structural characterization of residual lignin by using py-GC–MS and HSQC NMR analyses demonstrated that Cα-oxidized substructures significantly increased through fungal action, while intact β-O-4′ aryl ether linkages, p-coumarate and ferulate moieties decreased, albeit to lesser extents than observed for the action of basidiomycetes. Proteomic analysis indicated that the presence of lignin induced considerable changes in the secretome of P. anserina. This was particularly reflected in a strong reduction of cellulases and galactomannanases, while H2O2-producing enzymes clearly increased. The latter enzymes, together with laccases, were likely involved in the observed ligninolysis. Conclusions For the first time, we provide unambiguous evidence for the ligninolytic activity of the ascomycete fungus P. anserina and expand the view on its enzymatic repertoire beyond carbohydrate degradation. Our results can be of significance for the development of biological lignin conversion technologies by contributing to the quest for novel lignin-active enzymes and organisms. Background The ascomycete fungus Podospora anserina has been appreciated for its targeted carbohydrate-active enzymatic arsenal. As a late colonizer of herbivorous dung, the fungus acts specifically on the more recalcitrant fraction of lignocellulose and this lignin-rich biotope might have resulted in the evolution of ligninolytic activities. However, the lignin-degrading abilities of the fungus have not been demonstrated by chemical analyses at the molecular level and are, thus far, solely based on genome and secretome predictions. To evaluate whether P. anserina might provide a novel source of lignin-active enzymes to tap into for potential biotechnological applications, we comprehensively mapped wheat straw lignin during fungal growth and characterized the fungal secretome. Results Quantitative 13C lignin internal standard py-GC–MS analysis showed substantial lignin removal during the 7 days of fungal growth (24% w/w), though carbohydrates were preferably targeted (58% w/w removal). Structural characterization of residual lignin by using py-GC–MS and HSQC NMR analyses demonstrated that Cα-oxidized substructures significantly increased through fungal action, while intact β-O-4′ aryl ether linkages, p-coumarate and ferulate moieties decreased, albeit to lesser extents than observed for the action of basidiomycetes. Proteomic analysis indicated that the presence of lignin induced considerable changes in the secretome of P. anserina. This was particularly reflected in a strong reduction of cellulases and galactomannanases, while H2O2-producing enzymes clearly increased. The latter enzymes, together with laccases, were likely involved in the observed ligninolysis. Conclusions For the first time, we provide unambiguous evidence for the ligninolytic activity of the ascomycete fungus P. anserina and expand the view on its enzymatic repertoire beyond carbohydrate degradation. Our results can be of significance for the development of biological lignin conversion technologies by contributing to the quest for novel lignin-active enzymes and organisms.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Publisher:DataverseNL Authors: Koretsky, Zahar; Hernández Serrano, Pedro; Adekunle, Seun; Dumontier, Michel;doi: 10.34894/q80que
Article Abstract To better allocate funds in the new EU research framework programme Horizon Europe, an assessment of current and past efforts is crucial. In this paper we develop and apply a multi-method qualitative and computational approach to provide a catalogue of climate crisis mitigation technologies on the EU level between 2014 and 2020. Using the approach, we observed no public EU-level funding for multiple technologies prioritised by the EU, such as low-carbon production and use of cement and chemicals, electric battery, and a number of industrial decarbonisation processes. We observed a rising trend in the funding of solar power and onshore wind, the adjacent to them power-to-X technology, as well as recycling. At the same time, the shares of funding into fuel cell, biofuel, demand-side energy management, microgrids, and waste management show a decline trend. With note of the exploratory character of the present paper, we propose that the EU Horizon 2020 funding of clean technologies only partially reflected the expectations of key institutionalised EU actors due to the existence of many non-funded prioritised technologies.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.34894/q80que&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.34894/q80que&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Authors: Markus Stoffel; Daniel G. Trappmann; Mattias I. Coullie; Juan A. Ballesteros-Cánovas; +1 AuthorsMarkus Stoffel; Daniel G. Trappmann; Mattias I. Coullie; Juan A. Ballesteros-Cánovas; Christophe Corona;This readme file provides all data and R codes used to perform the analyses presented in Figs. 2-4 of the main text and Supplementary Information Figures S1-S2-S3. FIGURE 2 - Seasonally_dated_GDs.txt: Contains information on the timing (Season) of rockfall (GD) in a given tree (Id) and a given year (yr) over the past 100 years. Inv refers to the operators which analyzed growth disturbances in the tree-ring series. Lat / Long refers to the position of the tree in CH1903/ Swiss Grid projection. Intensity (1-4) refers to (1), intermediate (2) and strong (3) GD. Intensity 4 was attributed to injuries (I). Only the 408 GD rated 3 (strong TRD) and 4 (injuries) were used in Fig. 2. Acronyms used for Response_type read as follows: TRD: Tangential rows of traumatic resin ducts; I: Injuries. Acronyms used for Season refer to Dormancy (1_D), early (2_EE), middle (3_ME) and late (4_LE) earlywood, whereas a GD found in the latewood was attributed to either the early (5_EL) or late (6_LL) latewood. - Trends_in_seasonality_R1.R: The data contained in "Seasonally_dated_GDs" were processed with the R script "Trends_in_Seasonality.R". This seasonal trend analysis code is inspired by work published by Schlögl et al. (2021; https://doi.org/10.1016/j.crm.2021.100294) and Heiser et al. (2022; https://doi.org/10.1029/2011JF002262). FIGURE 3-4-S1 - Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - Rockfall_frequency_climate.R: The data contained in "Tasch_GD.txt" were processed with the R script "Rockfall_frequency_climate.R". - The temperature (Imfeld23_tmp.txt) and precipitation (Imfeld23_prc.txt) data used in Fig. 3 are from the Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Täschgufer site. - The script set with temperature series enables to compute Fig. 4 (l.149:216) and Fig. 3 (l. 216:330); the script set with precipitation series enables to compute Fig. S1 FIGURE S2 - Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) at the Täschgufer site in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - Rockfall_frequency_borehole.R: is adapted from "Rockfall_frequency_climate.R" to work with the borehole dates. - Corvatsch0_6R1: Contains the Corvatsch borehole temperature series (2000-2020, 0.6m depth) (Hoelzle, M. et al. https://doi.org/10.5194/essd-14-1531-2022, 2022). FIGURE S3 - Plattje_GD.txt: Contains the raw data on rockfall impacts (GD) at the Plattje site in a given year (yr) as found all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - - Rockfall_frequency_climate_Plattje.R: The data contained in "Plattje_GD.txt" were processed with the R script "Rockfall_frequency_climate_Plattje.R". - The temperature (Imfeld23_tmp_Plattje.txt) and precipitation (Imfeld23_prc_Plattje.txt) data used in Fig. 3 are from Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Plattje site.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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