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Soil chemical and physical property data for Green Lakes Valley, 1986.
Laboratory analyses were performed on soil samples from the Green Lakes Valley in the City of Boulder Watershed in order to characterize the chemical characteristics of the soil resource. The samples were collected during the 1986 excavations that were required during installation of zero-tension soil solution samplers.
Soil interstitial water chemistry data for Green Lakes Valley, 1987 - 1992.
Soil interstitial water samples were collected from tension and zero-tension samplers at various locations within the Green Lakes Valley in the City of Boulder Watershed. Chemical analyses were performed on the samples in order to characterize soil solution concentrations and estimate fluxes of important chemical constituents. Samples were collected at several depths from within several soil types and topographic situations in this alpine/subalpine environment.
Snow horizon chemistry data for Niwot Ridge and Green Lakes Valley, 1993 - ongoing.
Snow pits were excavated at various locations on Niwot Ridge and within the Green Lakes Valley. Temperature and snow density were measured at various depths throughout the snow cover profiles in order to characterize the temperature and snow water equivalent (SWE) of the snowpack throughout the year. Snow density was measured at 10-cm intervals using a 1000-ml cutter. Data on snow grain qualities were collected beginning in the 1994-95 snow season. Snow samples were collected and analyzed for cations and anions at the Mountain Research Station's Arikaree (formerly Kiowa) Laboratory.
Red, yellow, green and blue are not particularly colorful
<p>This is supplementary material accompanying the article:</p> <p>Witzel, C., Maule, M., & Franklin, A. (2019) Red, yellow, green and blue are not particularly colorful. <em>Journal of Vision</em>.</p> <p>focsat_data.xlsx contains all the individual data, including adjustments of typical and unique hues (+ super-saturated condition), detection (JND0) and discrimination (JND) data for red, yellow, green, and blue; and average saturation matches (subjective saturation) from Witzel and Franklin (2014). Nine sheets overall. IMPORTANT: All data is matched by participants (rows); but participant ids are not provided for reasons of data protection. Empty rows correspond to missing data. Also note that detection thresholds are provided in the first 10 columns, discrimination thresholds in the following 10 columns (11-20).</p> <p>focsat_tables.xlsx contains the exact data from tables in the article (Table 2) and the Supplementary Tables S1-S10. Eleven sheets in total.</p> <p>weberfechner.m is a Matlab function that allows for calculating Weber fractions and discriminable saturation as reported in the article.</p>
Field campaign data for evaluating green infrastructure in Guildford
<p>Field campaign data collected using reference instruments before and after hedges (Green infrastructure) in Guildford by University of Surrey.</p>
Feasible Alternatives to Green Growth
<p>Climate change and increasing income inequality have emerged as twin threats to contemporary standards of living, peace and democracy. These two problems are usually tackled separately in the policy agenda. A new breed of radical proposals has been advanced to manage a fair low-carbon transition. In this spirit, we develop a dynamic macrosimulation model to investigate the long-run effects of three scenarios: Green Growth, Policies for Social Equity, and Degrowth. The Green Growth scenario, based on technological progress and environmental policies, achieves a significant reduction in greenhouse gas emissions at the cost of increasing income inequality and unemployment. The Policies for Social Equity scenario adds direct labour market interventions that result in an environmental performance similar to Green Growth while improving social conditions at the cost of increasing public deficit. The Degrowth scenario further adds a reduction in consumption and exports and achieves a greater reduction in emissions and inequality with higher public deficit despite the introduction of a wealth tax. This study argues that new radical social policies, although often deemed economically and politically unfeasible, can combine social prosperity and low-carbon emissions.</p>
Figure 1. A in The green June beetle (Cotinis nitida) (Coleoptera: Scarabaeidae): local variation in the beetle's major avian predators and in the competition for mates
Figure 1. A stack of males piled up on the back of a receptive female. Note that the top male is facing in a different direction from the others and that he has everted his aedeagus, a sign of his strong sexual motivation.
Fig. 5 in A new green-coloured Lusitanipus Mauriès, 1978 from the Iberian Peninsula (Diplopoda: Callipodida: Dorypetalidae)
Fig. 5. Gonopod of ♂ paratype (MNCN 20.07/2071). A. Posterior view. B. Lateral view. C. Anterior view. D. Distal part of right telopodite in posterior view. E. Tip of right telopodite with tip of solenomerite visible. Scale bars: A–D = 0.4 mm, E = 0.1 mm. Abbreviations: α, β = processes of telopodite; arc = semi-circular arc of gonocoxite; c = gonocoxite; f = pseudoflagellum (or hornflagellum); l = lamella; m = membranous structures; s = solenomerite; sp = subrectangular projection of membranous structures; srp = semi-rectangular process of gonocoxite; t = telopodite.
Fig. 6 in A new green-coloured Lusitanipus Mauriès, 1978 from the Iberian Peninsula (Diplopoda: Callipodida: Dorypetalidae)
Fig. 6. Telopodite and gonocoxite of Lusitanipus alternans and Lusitanipus xanin sp. nov. A. Distal part of gonopod of Lusitanipus alternans in anterior view, redrawn after Reboleira & Enghoff (2015). B. Distal part of gonopod of Lusitanipus xanin sp. nov. in anterior view. C. Tip of telopodite of Lusitanipus alternans in lateral view, redrawn after Verhoeff (1900) (original without scale bar). D. ip of telopodite of Lusitanipus alternans in ventrolateral view, redrawn after a SEM photograph by Reboleira & Enghoff (2015). E. Tip of telopodite of Lusitanipus xanin sp. nov. in lateral view. Scale bars = 0.1 mm. Abbreviations: α, β and γ = processes of telopodite; c = gonocoxite; f = pseudoflagellum (or hornflagellum); l = lamella; s = solenomerite; t = telopodite.
Fig. 4 in A new green-coloured Lusitanipus Mauriès, 1978 from the Iberian Peninsula (Diplopoda: Callipodida: Dorypetalidae)
Fig. 4. Legs of ♂ paratype (MNCN 20.07/2071) seen by optic microscopy. A. Leg 1. B. Leg 2. C. Leg 3. D. Coxa and coxal sac of leg 4. E. Tip of tarsus and claw of leg 4. Scale bars: A–D = 0.5 mm, E =0.1 mm.
Fig. 3 in A new green-coloured Lusitanipus Mauriès, 1978 from the Iberian Peninsula (Diplopoda: Callipodida: Dorypetalidae)
Fig. 3. Morphological details of Lusitanipus xanin sp. nov. A. Head of ♂ paratype (note: colour has faded after 13 years in ethanol) (MNCN 20.07/2071). B. Last antennomeres of ♀ paratype (MNCN 20.07/2070). C. Posterodorsal part of the head of ♀ paratype and collum in dorsal view (MNCN 20.07/2070). D. Dorsal part of pleurotergites 5 (only partially visible) to 7 in lateral view (MNCN 20.07/2070). E. Detail of ventral part of first rings of ♀ in lateral view, with posterior tip of collum and pleurotergite 2 visible, four first pair of legs (second reduced) and coxal sacs (MNCN 20.07/2070). F. Telson and last rings of ♀ paratype (MNCN 20.07/2070). Scale bars = 0.5 mm.
Point, polygon, or marker? In search of the best geographic entity for mapping Cultural Ecosystem Services using the online PPGIS tool, "My Green Place."
<p>Excel files include the raw database and the processed data that led to the quadrat analyses. The "Matrix_raw data" file includes the raw data as downloaded from the server. This data was cleaned and organized for its posterior use. "Quadrat analyzes "file includes all the quadrat analyses resulting in each research question in the paper except question four. Question 4 can be seen in the file "Water analysis_Blaarmeersen." All excel files come with a "CODE" tab that describes each of the codes used, their meaning, and ways that were calculated where necessary. Two zip files include all the GIS files. The first one includes the GIS files from which "Matrix_raw data" was built from. The second folder includes the resulting maps from the quadrat analyses. In order to visualize them as in the paper, configure the symbology tab at the GIS software in quantile and the categories number, as shown in the paper.</p> <p>The production of the files in the "GIS_Processed data" folder was done via a repetitive line of commands in ArcGIS pro. The same process was followed for each one of the quadrat analysis described in the paper. Refer to "<a href="https://zenodo.org/api/files/72403e0b-78a9-4bbf-8dca-ed9b8702e3ae/Reproduction%20commands%20and%20parameters.pdf">Reproduction commands and parameters.pdf</a>" for further information.</p>
Using Blender EEVEE for the Generation of Real Time Background Plate in Green Screen Movie Shots
<p>This talk will introduce you to the use of blender EEVEE for green screen shots for a short movie. Green (and blue) screen shots are notoriously difficult to get the lighting condition right, since the image from the camera is dominated by the bright green background. It is very helpful on the set to see in real time the final composition of the scene with the proper background to make adjustments of the camera and the lighting position and the lighting intensity and color.<br> For the shots a large volume mocap solution (Optitrack) was used to track the movie camera (Arri Alexa) and the transformation data was sent to Blender to animate the virtual camera. The previously laser scanned background was rendered in real time in EEVEE. To combine the camera image and the rendered image a dedicated live-keying hardware was used. The described set-up was used in connection with the research project Virtually Real – Aesthetics and Perception of Virtual Spaces in Film by the Zurich University of the Arts and the University of Bern, funded by the Swiss National Science Foundation. <br> </p>
Exiobase HYBRID | Green steel version
<h2>Description</h2> <p>This repository contains all data and code to extend the <a href="../records/10148587" target="_blank" rel="noopener">hybrid-units version of EXIOBASE</a> to account for new innovative steelmaking routes envisaged to be deployed in the EU to meet decarbonization targets for the steel industry. The new model was built by adopting the <a href="https://doi.org/10.5334/jors.473">MARIO</a> open-source framework. </p> <p>The database is an improved version of the one described in the following open-access paper (DOI: <a href="https://doi.org/10.1088/1748-9326/ad5bf1">https://doi.org/10.1088/1748-9326/ad5bf1</a>)</p> <h2>What's new</h2> <ul> <li>The new technologies have been characterized for all regions, assuming each inventory to be the same in all regions but differentiated by regional import patterns of each commodity.</li> <li>A slight aggregation on electricity production activities and commodities have been also performed, to nowcast electricity production mixes to 2024 based on <a href="https://ember-climate.org/data/data-tools/data-explorer/">Ember data.</a> Data from Ember have been rearranged to calculate electricity mixes by year and Exiobase regions</li> <li>The list of steel production technologies have been extended. Full list in the table below</li> </ul> <p>The database implements in the EU the following new activities and commodities:</p> <table> <tbody> <tr> <td><strong>New activities</strong></td> <td><strong>New commodities</strong></td> </tr> <tr> <td>Manufacturing of steam reformer</td> <td>Steam reformer</td> </tr> <tr> <td>Manufacturing of electrolyser</td> <td>Electrolyser</td> </tr> <tr> <td>Hydrogen production with steam reforming</td> <td>Steam reforming hydrogen</td> </tr> <tr> <td>Hydrogen production with electrolysis</td> <td>Electrolysis hydrogen</td> </tr> <tr> <td>DRI-EAF-NG</td> <td> </td> </tr> <tr> <td>DRI-EAF-NG-CCS</td> <td> </td> </tr> <tr> <td>DRI-EAF-COAL</td> <td> </td> </tr> <tr> <td>DRI-EAF-COAL-CCS</td> <td> </td> </tr> <tr> <td>DRI-EAF-H2</td> <td> </td> </tr> <tr> <td>DRI-EAF-BECCS</td> <td> </td> </tr> <tr> <td>DRI-SAF-BOF-NG</td> <td> </td> </tr> <tr> <td>DRI-SAF-BOF-H2</td> <td> </td> </tr> <tr> <td>DRI-SAF-BOF-BECCS</td> <td> </td> </tr> <tr> <td>SR-BOF</td> <td> </td> </tr> <tr> <td>SR-BOF-CCS</td> <td> </td> </tr> <tr> <td>BF-BOF-CCS-73%</td> <td> </td> </tr> <tr> <td>BF-BOF-CCS-86%</td> <td> </td> </tr> <tr> <td>BF-BOF-BECCSmax</td> <td> </td> </tr> <tr> <td>BF-BOF-BECCSmin</td> <td> </td> </tr> <tr> <td>AEL-EAF</td> <td> </td> </tr> <tr> <td>MOE</td> <td> </td> </tr> </tbody> </table> <p> </p> <p>Extended documentation of database adjustment and extension methodology available among the files in this repository. </p> <h2> </h2> <h2>Instructions</h2> <p>To use the database, please install MARIO following the <a href="https://mario-suite.readthedocs.io/en/latest/intro.html#installation">instructions.</a> The database can be parsed by using the following command<br><br></p> <div> <div>db = mario.parse_from_txt(</div> <div> path='PATH/TO/THE/FOLDER/WHERE/DATA/FROM/THIS/REPOSITORY/ARE/STORED',</div> <div> mode='coefficients',</div> <div> table='SUT',</div> <div>)</div> </div> <p> </p>
Data from: Ontogeny of color development in two green-brown polymorphic grasshopper species
<p class="MsoNormal">Many insects, including several orthopterans, undergo dramatic changes in body coloration during ontogeny. This variation is particularly intriguing in gomphocerine grasshoppers, where the green and brown morphs appear to be genetically determined (Schielzeth & Dieker, 2020; Winter, Varma, & Schielzeth, 2021). A better understanding of how these color morphs develop during ontogeny can provide valuable insights into the evolution and ecology of such a widespread color polymorphism. Here, we focus on the color development of two green-brown polymorphic species, the club-legged grasshopper <em>Gomphocerus sibiricus </em>and the steppe grasshopper <em>Chorthippus</em> <em>dorsatus</em>. By following the color development of individuals from hatching to adulthood, we found that color morph differences begin to develop during the second nymphal stage,<span> are clearly defined by the third nymphal stage,</span> and remain stable throughout the life of an individual. Interestingly, we also observed that <span>shed skins of late nymphal stages are identifiable by color morphs based on their yellowish coloration, rather than the green that marks green body parts. </span>Furthermore, by assessing how these colors are perceived by different visual systems, we found that certain potential predators can chromatically discriminate between morphs, while others may not. These results suggest that the putative genes controlling color morph are active during the early stages of ontogeny, and that green color is likely composed of two components, one present in the cuticle and one not. In addition, the effectiveness of camouflage appears to vary depending on the specific predator involved.</p>
Figure 4 in Purification and Characterization of Midgut α-Glucosidase from Larvae of the Rice Green Caterpillar, Naranga aenescens Moore
Figure 4. Irreversible thermoinactivation of the N. aenescens α-glucosidase at 35 (▲), 40 (■) and 45 °C (•). Different letters indicate that the relative activity of enzymes is significantly different from each other by Tukey's test (P <0.05).
Figure 3 in Purification and Characterization of Midgut α-Glucosidase from Larvae of the Rice Green Caterpillar, Naranga aenescens Moore
Figure 3. Effect of pH (a) and (b) temperature on the activity of N. aenescens α -glucosidase.Different letters indicate that the relative activity of enzymes is significantly different from each other by Tukey's test (P <0.05).
Figure 2 in Purification and Characterization of Midgut α-Glucosidase from Larvae of the Rice Green Caterpillar, Naranga aenescens Moore
Figure 2. Analysis of purified αglucosidase by SDS-PAGE. Lanes 1 and 2: Active fraction after ion exchange chromatography stained with histochemical and general staining, respectively; Lane 3: Molecular weight markers.
Figure 1 in Purification and Characterization of Midgut α-Glucosidase from Larvae of the Rice Green Caterpillar, Naranga aenescens Moore
Figure 1. Elution profile of N. aenescens α-glucosidase on DEAE-sepharose column. The active peak is indicated. Arrow is pointing to the fifth peak, eluted around 0.4 M salt, corresponding to the α-glucosidase activity.
Superadditive Communications with the Green Machine: Online Data Repository
<p>This online repository contains selected datasets and scripts for data processes in the paper "Superadditive Communications with the Green Machine: A Practical Demonstration of Nonlocality without Entanglement". arXiv.2310.05889</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.