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SGS-LTER Long-term Monitoring Project: Spotlight Rabbit Count on the Central Plains Experimental Range, Nunn, Colorado, USA 1994-2006, ARS Study Number 98 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/136/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83448. Rabbits are the most important small-mammal herbivores in shortgrass steppe, and may significant influence the physiognomy and population dynamics of herbaceous plants and woody shrubs. Rabbits also are the most important prey of mammalian carnivores such as coyotes and large raptors such as golden eagles and great horned owls. Two hares (Lepus californicus, L. townsendii) and one cottontail rabbit (Sylvilagus audubonii) occur in shortgrass steppe. In 1994, we initiated long-term studies to track changes in relative abundance of rabbits on the Central Plains Experimental Range (CPER). On four nights each year (one night each season, usually on new moon nights in January, April, July, October), we drove a 32-km route consisting of pasture two-track and gravel roads on the CPER. This wa
SGS-LTER Long-Term Montioring Project: Arthropod Pitfall Trapping on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1998-2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/134/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83450. With the exception of heteromyids, eg kangaroo rats and pocket mice, most small rodents in shortgrass steppe are omnivorous. Depending on season, arthropods (insects and arachnids) make up 40-85% of the diet of grasshopper mice and thirteen-lined ground squirrels, the most widespread rodents in northern shortgrass steppe. Small mammals are among the most important predators of ground-dwelling macroarthropods and herbivorous insects provide a direct resource link between weather and plant production. Understanding temporal variability in the abundance of arthropods is central to determining the mechanisms that drive small rodent populations. At present, there are no long-term studies of arthropods in shortgrass steppe, despite the important role that these taxa play in grassland food w
SGS-LTER Long-Term Monitoring Project: Small Mammals on Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/137/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83452. Small mammals (rabbits, rodents) are integral components of semiarid ecosystems because of their roles as consumers of plants, seeds and arthropods, as soil disturbance agents, and as food for raptors, snakes and mammalian carnivores. Because of their vagility and intermediate trophic position, populations of small mammals may track changes in vegetation and the abiotic environment that may result from shifts in land-use and other anthropogenic disturbances. However, these populations are variable over space and time, and their response to environmental changes may not be immediately apparent given their behavioral flexibility and relatively long life-spans and generation times. Patterns in the distribution and abundance of small mammals thus may simultaneously reflect and affect the
Salmonid habitat use monitoring used to determine effectiveness of habitat improvement projects in the Sacramento River, CA
Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains five datasets. Enclosure Study – Growth Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Fish growth was tracked for approximately 6.5 weeks. Annual reports summarize the survey findings. Enclosure Study – Gut Contents Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Enclosures remained in the river for approximately 6.5 weeks. At the end of the study, fish were euthanized, and we dissected their guts and enumerated the taxa found. Annual reports summarize the survey findings. Microhabitat Use Data This dataset covers salmonid microhabitat use conducted in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Surveys are conducted roughly monthly and include pre-project sites, constructed habitat project sites, and control sites where no treatment is planned. Based upon habitat inventory data, annually identify which habitat units within each side channel will be selected for the collectio
Soil surface temperature measurements from the GCE-LTER Seawater Addition Long-Term Experiment (SALTEx) Project
SALTEx (Seawater Addition Long-Term Experiment) is a field experiment designed to simulate saltwater intrusion in a tidal freshwater wetland to predict how chronic (Press) and acute (Pulse) salinization will affect this and other tidal freshwater ecosystems. The SALTEx experiment was initiated in 2012 and consists of 31 field plots, each 2.5 m on a side. There are three treatments (Press, Pulse, and Fresh) and two types of controls (with and without sides), each consisting of six replicates. The Press treatment plots receive regular (4 times each week) additions of a mixture of seawater and fresh river water. Pulse plots receive the same mixture of seawater and river water during September and October, which is historically a time of low flow in the river when natural saltwater intrusion occurs. The Fresh treatment plots receive regular additions of fresh river water. Treatment water is added during low tide to facilitate its infiltration into the soil, and all plots are inundated by astronomical tides at high tide. We are measuring soil surface temperature in the plots as one of the response variables for the SALTEx project.
Green algae, cyanobacteria and diatom concentrations from the GCE-LTER Seawater Addition Long-Term Experiment (SALTEx) Project
SALTEx (Seawater Addition Long-Term Experiment) is a field experiment designed to simulate saltwater intrusion in a tidal freshwater wetland to predict how chronic (Press) and acute (Pulse) salinization will affect this and other tidal freshwater ecosystems. The SALTEx experiment was initiated in 2012 and consists of 31 field plots , each 2.5 m on a side. There are three treatments (Press, Pulse, and Fresh) and two types of controls (with and without sides), each consisting of six replicates. The Press treatment plots receive regular (4 times each week) additions of a mixture of seawater and fresh river water. Pulse plots receive the same mixture of seawater and river water during September and October, which is historically a time of low flow in the river when natural saltwater intrusion occurs. The Fresh treatment plots receive regular additions of fresh river water. Treatment water is added during low tide to facilitate its infiltration into the soil, and all plots are inundated by astronomical tides at high tide. We are measuring the abundance of benthic algae with a BenthoTorch as one of the response variables for the SALTEx project.
Hubbard Brook Wildlife Monitoring Project: Assessing wildlife population presence, activity and habitat use through continual camera trap monitoring, 2018
Monitoring of wildlife at Hubbard Brook is essential to understand how these species are responding to forest and environmental condition over time, while also placing those wildlife species in the context of ecosystem structural and functional attributes. The presence and persistence of wildlife species common to an area can indicate suitable habitat conditions as well as refugia for less common species. Changes in species presence and activity, such as fewer to no sightings, may point to shifting conditions not suitable to the species missing from the area. Camera trap monitoring allows for continuous, non-obtrusive observation of many different species of wildlife and can be used as part of our understanding of current suitability of habitat condition. To better understand integrated forest condition, we established a camera trap network located at the Hubbard Brook Experimental Forest in the White Mountains of central New Hampshire. The cameras have logged over 1,500 wildlife observations, confirming the presence of many species, including those not previously reported (pine marten and river otter). A total of 15 mammal species have been detected and have also been effective at detecting some bird species, including the Northern Harrier. Natural history observations have provided insight into the lives of the species detected, including reproduction (Bull moose following cow during rut, moose calves, deer fawns), predation (red fox with snow-shoe hare) and presence of parasites (winter ticks on moose with hairless shoulders). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE): Project description, plot characteristics and design
Although temperate forests are generally thought of as N-limited, resource optimization theory predicts that ecosystem productivity should be co-limited by multiple nutrients. These ideas are represented in the Multi-Element Limitation (MEL) model (Rastetter et al. 2012). To test the patterns of resource limitation predicted by MEL, we are conducting nutrient manipulations in three study sites in New Hampshire: Bartlett Experimental Forest (BEF), Hubbard Brook Experimental Forest (HBEF), and Jeffers Brook in the White Mountain National Forest. We are monitoring stem diameter, leaf area, sap flow, foliar chemistry, leaf litter production and chemistry, foliar nutrient resorption, root biomass and production, mycorrhizal associations, soil respiration, heterotrophic respiration, N and P availability, N mineralization, soil phosphatase activity, soil carbon and nitrogen, nutrient uptake capacity of roots, and mineral weathering. These data can be found in the EDI repository, using the search term "MELNHE" (http://portal.edirepository.org), and through the data catalog on https://hubbardbrook.org, using the same search term. This data package is referenced by the MELNHE datasets, and includes a datatable of site descriptions and a pdf file with the project description, and diagrams of plot configuration. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Jornada Basin and Experimental Range Mesquite Herbicide Project (JERHM) Core Methods Data, 2020-2022
This dataset includes contains line-point intercept, plant height, gap, and species inventory data collected over three years (2020-2022) as part of the Jornada Experimental Range Herbicide Mesquite Project (JERHM). Data were collected to assess plant community composition and structural change to herbicide application across a Black grama (Bouteloua eriopoda) grassland to Honey mesquite (Neltuma glandulosa [=Prosopis glandulosa]) shrubland encroachment gradient. Twenty sets of paired, 5-hectare plots (n=40 plots total) were established across a N. glandulosa encroachment gradient in 2020. One plot within each plot pair received an aerial application of herbicide in 2021, with the second plot left untreated by herbicide as a control. Data were collected annually following the following the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems (Herrick et al. 2017) on each of three, 50m permanent transects established on each plot. These data are also available within the Landscape Data Commons (https://landscapedatacommons.org/) under ProjectKey=Jornada_JERHM. There are no immediate plans to continue data collection.
STREAMS Project: Emergent landscape patterns in stream ecosystem processes resulting from groundwater/surface water interactions
This Data Set is hosted by the Luquillo LTER Program (LUQ) and owned by a LUQ's investigator. Our primary objective is to understand the linkage between surface-subsurface water interactions and ecosystem processes in neotropical lowland streams over an extended time frame (>25 yrs). Proposed research will occur at La Selva Biological Reserve in Costa Rica, which is owned and operated by the Organization for Tropical Studies In tectonically active regions of Central America, it is common for solute-rich groundwater to emerge at gradient breaks within the complex volcanic topography of mountains and foothills which intergrade with the coastal plain. These groundwaters can significantly influence solute chemistry and related ecological and ecosystem-level processes in receiving surface waters. Many solute-rich groundwaters are associated with underlying volcanic activity which has altered the chemistry of receiving streams throughout Central America. Geothermally-modified groundwaters, surfacing at the gradient break between the Central Mountain range and the coastal plain at La Selva Biological Station, have high levels of P (up to 400 mg SRP L-1) and other solutes (Ca, Cl, Mg, SO4) but are not elevated in temperature. Spatial patterns in stream solute chemistry are determined by geomorphic features of the volcanic landscape that include: upland lavas drained by P-poor streams; a gradient break (~50 m.a.s.l.), at or near where P-rich springs emerge; and lowland alluvial areas drained by streams that are both P-rich and P-poor depending on whether they receive the input of solute-rich springs. Our project is the first to determine long-term effects of nutrient enrichment in a detrital-based stream within the wet tropics. We will continue to build upon our long-term(1988-present) data set on stream solute chemistry, which is the only one that we are aware of for lowland primary rainforest of Central America. The proposed project will build on 18 years of past resear
Soil biota data from the Pulse-Press Project (P3), McMurdo Dry Valleys, Antarctica (2010-2020)
Climate warming in polar regions is associated with thawing of permafrost, resulting in significant changes in soil hydrology, biogeochemical cycling, and in the activity and composition of soil communities. While ongoing, directional climate warming can elicit such responses over decadal time scales, their manifestation typically occurs as discrete thawing pulses. Indeed, in the McMurdo Dry Valleys of Antarctica abrupt changes in community structure and biogeochemical cycling in terrestrial and aquatic ecosystems following a summer warming event (Jan. 2002) exceeded the influences of a decadal cooling trend in both magnitude and rate of response. Thus, we anticipate that climate-mediated permafrost changes and their associated impacts on soil communities and biogeochemical cycles may occur over seasonal time scales. Our objective is to simulate different frequencies of permafrost thawing events in Antarctic permafrost soils. Since the top horizons of most Antarctic soils are dry permafrost (i.e., there is insufficient water content to generate ice-cement), with ice-cement or massive ice typically below 30 cm, permafrost thawing events are likely to result in subsurface movements of water that may manifest as groundwater seeps down gradient.
Cascade Project at North Temperate Lakes LTER Temperature Chain Data 2009 - 2019
Summer temperature chain data were collected from three lakes (Peter, Paul, and Tuesday) using NexSens temperature thermistors. Data are available for five years: 2013–2015 and 2018–2019. Peter and Paul Lakes have complete records for all five years, while Tuesday Lake has data for three years. During 2013–2015, thermistors recorded temperatures at depths of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and 5.0 meters. Beginning in 2018, thermistors were added at 4.5 and 6.0 meters.
10-meter elevation contours, Niwot Ridge LTER Project Area, Colorado
10-meter contour map spanning the Silver Lake Watershed, including Green Lakes Valley, Niwot Ridge LTER, and parts of adjacent Brainard Lake Recreation Area and Indian Peaks Wilderness. Made from a filtered 10-meter lattice, which was made from the Niwot Ridge LTER TIN model (ltertin). This dataset was made to support hierarchical GIS databases at the Niwot Ridge LTER. Additional information concerning the Niwot Ridge LTER hierarchical GIS can be found in Walker et al. (1993).
20-meter elevation contours, Niwot Ridge LTER Project Area, Colorado
20-meter contour map spanning the Silver Lake Watershed, including Green Lakes Valley, Niwot Ridge LTER, and parts of adjacent Brainard Lake Recreation Area and Indian Peaks Wilderness. Made from a filtered 10-meter lattice, which was made from the Niwot Ridge LTER TIN model (ltertin). This dataset was made to support hierarchical GIS databases at the Niwot Ridge LTER. Additional information concerning the Niwot Ridge LTER hierarchical GIS can be found in Walker et al. (1993).
Bids Pilot Project
Open the record for dataset details and reuse information.
Research data supporting for "The embedded research librarian: a project partner"
<p>This dataset contains the data that supports the following paper: Féret, R. and Cros, M., 2019. The embedded research librarian: a project partner. <em>LIBER Quarterly</em>, 29(1), pp.1–20. DOI: <a href="https://dx.doi.org/10.18352/lq.10304">10.18352/lq.10304</a></p> <p>The dataset contains 3 files related to the bibliographic metadata of the publications of the 7 H2020 projects supported by the University Library of Lille and a general file providing the data for the table, figure 2 and 3 and for the data on H2020 projects coordinators:</p> <ul> <li>figures: this file contains the information related to the projects supported by the Library, including the data presented in the figure 2 (tab 1), the figure 3 (tab 2), the table 1 (tab 3) and the data on 2020 project coordinators (tab 4).</li> <li>wos_publications : the data extracted from the Web of Science for 106 publications (.txt, UTF-8, Windows), searched on the base of the 7 H2020 projects Cordis number.</li> <li>refined_wos_publications : the same data after having been transformed into a .xlsx format in the tool OpenRefine.</li> <li>processed_publications : contains the main bibliographic data (authors, article title, source title, DOI, date of publication) and their open status.</li> </ul> <p><strong>Abstract of the paper</strong><br> This paper presents new services developed by the Lille University Library for European and National research project coordinators. This is a specific audience that libraries are not used to target, with a widely recognised institutional status and academic background. Supporting them in their coordination activities is an opportunity to gain a new role for libraries, which starts from the design of research at the submission stage and lasts several years after, during the project lifetime. These services help coordinators to meet their funders’ expectations on open access and research data management. It is also a way to develop new collaborations with research units and some university services, such as the Grant Office. The Lille University Library has already supported the writing of forty grant proposals since 2017, including about thirty since early 2019. The Library currently follows twelve projects on open access, research data management or both. This second figure is likely to increase in 2020 due to the number of projects supported at submission stage since the beginning of 2019. The paper describes our set of services and the lessons we learned from our approach.</p>
Undirected Node Attributed Social Network Graph of Twitter Users interested in plastic pollution - created in the framework of the PlasticTwist project
<p>This dataset has been created in the framework of the Plastic Twist project (<a href="https://ptwist.eu/">Ptwist</a>) and more specifically using the Ptwist crowdsourcing application (<a href="https://crowdsourcing.plastictwist.com/">crowdsourcing.plastictwist.com/</a>). We are sharing the edge list and specific node attributes (hashtags) of Twitter users posting about plastic pollution. The dataset can be used for community detection,clustering, node importance, influence maximization tasks, etc. Each user is represented by a unique integer which has nothing to do with the official Twitter user ID. The dataset contains three (3) files: </p> <ul> <li>ptwist.edgelist: A list containing all the 1,362,863 edges between the users. When loaded they create an undirected graph of 800K+ users.</li> <li>node_attributes.txt: This file contains information about the hashtags used by each user. (e.g. "652003": ["SingleUsePlastic"] -> user 6529003 has used the hashtag SingleUsePlastic) </li> <li>annotated_graph: A pickle file which, when loaded, returns a <a href="https://networkx.github.io/">NetworkX</a> node attributed undirected graph.</li> </ul> <p> </p> <p> </p>
Project files provided as supporting information to the manuscript "Ligand-protein interactions in lysozyme investigated through a dual-resolution model"
<p><strong>README file for the project files provided as supporting information to the manuscript "Ligand-protein interactions in lysozyme investigated through a dual-resolution model"</strong></p> <p>February 12, 2020</p> <p>Authors: Raffaele Fiorentini, Kurt Kremer and Raffaello Potestio</p> <p>================================</p> <p>Overview</p> <p>The dataset is organised in three (compressed) subfolders (see the tree diagrams in each section):</p> <p>- annihilation<br> - decoupling<br> - density</p> <p>The figure deltaG_binding_ann_dec_comparison.png shows the results of binding free energy calculations comparing the values obtained both for annihilation and decoupling.</p> <p>The figure deltaG_binding_annih_gromacs_espp.png displays the results for Binding FE, comparing the values obtained in GROMACS and ESPResSo++.</p> <p>The README.pdf file contains detailed information about these folders and their content.</p> <p>================================</p> <p>The "annihilation" folder contains all results concerning the calculation of binding free energy in case of annihilation and it is divided in two parts: </p> <p>- complex<br> - ligand</p> <p>In "complex" are reported the results of Ligand-Protein FE both in ESPResSo++ and GROMACS. All simulations are fully-atomistic. </p> <p>In "ligand" are reported the results of ligand solvation free energy both in ESPResSo++ and GROMACS. All simulations are fully-atomistic. </p> <p>====</p> <p>The "decoupling" folder contains all results concerning the calculation of binding free energy in case of decoupling and it is divided in three parts: </p> <p>- complex-DualRes<br> - complex-FullyAT<br> - ligand</p> <p>In "complex-DualRes" are reported the results of Ligand-Protein FE only in ESPResSo++ (GROMACS cannot do decoupling). The system is simulated in Dual-Resolution. It is possible to find the trajectory files in the sub-directories "lambdaindex-0" and "lambdaindex-30".</p> <p>In "complex-fullyAT" are reported the results of Ligand-Protein FE only in ESPResSo++. The system simulated is fully-atomistic. It is possible to find the trajectory file in the sub-directories "lambdaindex-0" and "lambdaindex-30".</p> <p>In "ligand" are reported the results of ligand solvation free energy only in ESPResSo++. All simulations are fully-atomistic. It is possible to find the trajectory file in the sub-directories "lambdaindex-0" and "lambdaindex-20".</p> <p>====</p> <p>The "density" folder contains the data for the tuning of the c parameter of the steric repulsion among residues. This parameter is tuned so that the water density attains the value computed in all-atom simulations.</p>
From A to Z: Projective coordinates leakage in the wild: research data and tooling
<p>Description</p> <p>This dataset and software tool are for reproducing the research results related to CVE-2020-10932 and CVE-2020-11735, resulting from the article "From A to Z: Projective coordinates leakage in the wild" (to appear at CHES 2020). The data was used to carry out the attack in Section 6 of the article.</p> <p>Data format</p> <p>txt files</p> <p>The <code>[int].txt</code> files contain an encoded page-fault trace prefixed by <code>trace:</code>.</p> <p>A trace represents the sequence of tracked memory pages that were executed during the generation of an ECDSA signature. The trace is encoded using ASCII characters for better visualization.</p> <p>The encoding follows this table:</p> <pre><code class="language-markdown">| Functions | Symbol | Page offset | | ---------------------- |:------:|:-------:| | _gcry_ecc_ecdsa_sign | T | 0xa1000 | | _gcry_mpi_invm | . | 0xcf000 | | _gcry_mpi_set | S | 0xd5000 | | _gcry_mpi_add | A | 0xcd000 | | _gcry_mpih_sub_n | - | 0xd8000 | | _gcry_mpih_rshift | - | 0xd8000 |</code></pre> <p><code>_gcry_ecc_ecdsa_sign</code> is the highest level function tracked in the attack. This allows to differentiate different calls to the <code>_gcry_mpi_invm</code> function which contains an insecure version of a Binary Extended Euclidean Algorithm (BEEA).</p> <p>Using these pages it is possible to locate the execution of <code>_gcry_mpi_invm</code> corresponding to the computation of <code>Z mod p</code> during projective to affine coordinates conversion (see <code>preprocess_trace</code> function).</p> <p>It can be seen, that <code>_gcry_mpih_sub_n</code> and <code>_gcry_mpih_rshift</code> shares a page. However, they can be differentiated using mainly the caller memory page. This sharing, instead of being a drawback, allows a straightforward recovery of BEEA execution flow (see <code>extract_Zi</code> and <code>extract_Xi</code> functions in <code>recover_z.py</code>).</p> <p>dat files</p> <p>The format of the <code>[int].dat</code> files is as follows.</p> <ul> <li><code># X [hex]</code>: Ground truth projective output of scalar multiplication, before affine conversion</li> <li><code># Y [hex]</code>: Ground truth projective output of scalar multiplication, before affine conversion</li> <li><code># Z [hex]</code>: Ground truth projective output of scalar multiplication, before affine conversion</li> <li><code># curve_name [str]</code>: The curve (P256)</li> <li><code># h [hex]</code>: Hash of the message to be signed</li> <li><code># k [hex]</code>: Ground truth ECDSA nonce</li> <li><code># q [hex]</code>: Curve order</li> <li><code># r [hex]</code>: First component of the ECDSA signature</li> <li><code># s [hex]</code>: Second component of the ECDSA signature</li> <li><code># x [hex]</code>: Ground truth ECDSA private key</li> <li><code># y [hex] [hex]</code>: Public key coordinates</li> <li><code># leak_pad [int],[int],[int]</code>: Leakage recovered during backtracking. Example: <code>0,4,15 => 0 = k % 2**4 = k & 15</code></li> </ul> <p>Tooling</p> <p>The <code>recover_z.py</code> script</p> <ul> <li>Loads a trace.</li> <li>Recovers the corresponding Z coordinate from the trace data.</li> <li>verifies the recovered Z matches the ground truth Z.</li> </ul> <p>Example</p> <p>Unpack the data:</p> <pre><code>tar xf traces.tar.gz</code></pre> <p>Run the tooling on trace index 123:</p> <pre><code>$ python2 recover_z.py 123 INFO:recovered Z:65b9b7006bc7b030218bef1b6e569f9f7acaee059b53d669388c6b860f67e213 INFO: real Z:65b9b7006bc7b030218bef1b6e569f9f7acaee059b53d669388c6b860f67e213</code></pre> <p>The output demonstrates the recovered Z coordinate is correct, i.e. matches the ground truth.</p> <p>Credits</p> <p>Authors</p> <ul> <li>Alejandro Cabrera Aldaya (Tampere University, Tampere, Finland)</li> <li>Cesar Pereida García (Tampere University, Tampere, Finland)</li> <li>Billy Bob Brumley (Tampere University, Tampere, Finland)</li> </ul> <p>Funding</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 804476).</p> <p>License</p> <p>This project is distributed under MIT license.</p> <p> </p>
Site occupancy matrices, The River Ouse Project
<p>The <a href="http://www.sussex.ac.uk/riverouse/">River Ouse Project</a> was started by Dr Margaret Pilkington and colleagues in the Centre for Continuing Education, University of Sussex. Margaret is now retired with emeritus status and continues to run the project with a team of volunteers, in association with the University of Sussex. The team does botanical surveys of streamside grassland and steep wooded valleys (gills) in the upper reaches of the Sussex Ouse, a short flashy river arising on the southern slopes of the High Weald AONB (Area of Outstanding Natural Beauty). Survey sites are chosen on the basis of species richness, potential for restoration and contribution to flood control, and surveyed using the sampling methods outlined in Rodwell, J S (1992. British Plant Communities, Volume 3, Grasslands and Montane Communities). Survey data are transferred from the paper record taken in the field to Excel spreadsheets, and from there after validation and cleaning into two MySQL (MariaDB) databases, meadows and gills.</p> <p>The file is an extract from the meadows database. It contains binary data of the site occupancy for most of the plants encountered in meadow sites (stands, assemblies) sampled using five 2m x 2m quadrats. Details of the database are available here: <a href="https://zygodon.github.io/River-Ouse-Project-databases/">River Ouse Project databases</a>. </p> <p>For further details and access to the full database contact the author.</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.