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458 results for “Data Protection”

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zenodo40/100

Linked collectors and determiners for: Improving Species-Based Area Protection in Antarctica - data.

Natural history specimen data linked to collectors and determiners held within, "Improving Species-Based Area Protection in Antarctica - data". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="http://bionomia.net/dataset/d61860b3-22fd-4c8f-a089-97a2d6893f8b">https://bionomia.net/dataset/d61860b3-22fd-4c8f-a089-97a2d6893f8b</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d61860b3-22fd-4c8f-a089-97a2d6893f8b">https://gbif.org/dataset/d61860b3-22fd-4c8f-a089-97a2d6893f8b</a>. Formatted as a Frictionless Data package.

opencc-zeroJan 2024View details →
zenodo40/100

The Right to Data Protection Ensuring the Autonomous Exercise of the Individual's Other Fundamental Rights

<p>The graphic illustrates the function of the fundamental right to data protection under Art. 8 ECFR protecting individuals against the risks caused by the processing of personal data against his or her&nbsp;other fundamental rights to privacy, freedom and non-discrimination.</p>

opencc-by-sa-4.0Mar 2018View details →
zenodo40/100

Tool-supporting Data Protection Impact Assessments with CAIRIS: PLA model

<p>This is the final CAIRIS model associated with the &#39;Tool-supporting Data Protection Impact Assessments with CAIRIS&#39; ESPRE 2018 paper.</p> <p>To import this model into CAIRIS, select the System/Import Model menu in CAIRIS, check the model type is set to &#39;model&#39;, choose the model file to import, and click on the Import button.</p>

opencc-by-4.0Aug 2018View details →
zenodo40/100

High resolution Sea Surface Wind retrieval over coastal Protected Areas by means of Sentinel-1 data

<p><br> The algorithm used, i.e. SARWIND LG-Mod ver. v4.01 (see reference below), is aimed at producing the Sea Surface Wind (SSW), i.e. Speed and Direction, from a single co-polarized (VV or HH) SAR image. We used EW (Extended Wide) and IW (Interferometric Wide) Swath Mode GRD (Ground Range, Multi-Look, Detected) HR (High Resolution) Sentinel-1 images, with pixel spacings of 40m x 40m and 10m x 10m (azimuth x range) respectively. Associated auxiliary products were obtained from ESA SNAP 5.0 release. SSW fields were provided for the two coastal Protected Areas (PAs) named Camargue and Wadden Sea.</p> <p>Each output folder of the SARWIND LG-Mod results contains useful plots and the estimated SSW field, provided in the file &#39;SAR_Sigma0_pp_decimationL2P2Tn_gradientOptSobel_LGMod_Results.txt&#39; (pp = VV or HH; n = smoothing/decimation level), which is in the sub-folder &#39;LG-Mod_Theoretical_Results/Results_MEdegTHxx.xxx_Fisher (where xx.xxx is the final threshold applied). This txt file reports the following 19 columns:</p> <p><br> 1) LAT; 2) LON; 3) AZI; 4) RNG; [Location of the centre of the processed AOI]</p> <p>5) REF_U; 6) REF_V; 7) REF_W; 8) REF_D; [ECMWF reference wind, as U/V components and speed/direction]</p> <p>9) SAR_U; 10) SAR_V; 11) SAR_W; 12) SAR_D; [SARWIND LG-Mod wind estimates, as U/V components and speed/direction]</p> <p>Both REF_D and SAR_D are wind directions (expressed in degrees) with respect to the geographic North (0&deg;=North, 90&deg;=East, 180&deg;=South, 270&deg;=West), that the wind is blowing to.<br> Both REF_W and SAR_W are wind speeds (expressed in m/s).<br> Regarding REF_U/SAR_U and REF_V/SAR_V, note that a positive U component represents wind blowing to the East; a positive V component represents wind blowing to the North.</p> <p>13) SceneCentre_TrueHeading_FF; [Mean angle formed between the geographical South-North direction and the SAR azimuth direction (wrt the centre of the SAR Full-Frame image)]</p> <p>SceneCentre_TrueHeading_FF is a positive clockwise angle. In particular: SceneCentre_TrueHeading_FF is in ]180,360[ [deg].<br> Thus:<br> Descending Pass &lt;-&gt; &nbsp;SceneCentre_TrueHeading_FF is in ]180,270[ [deg]<br> Ascending Pass &nbsp;&lt;-&gt; &nbsp;SceneCentre_TrueHeading_FF is in ]270,360[ [deg]</p> <p>14) ROI_Npoints_UnUsablePointsMasked; [Number of samples used for each SARWIND LG-Mod wind estimation]</p> <p>15) MeanIncAng; 16) MeanNRCS; [Mean incident angle (expressed in degrees) and NRCS of the ROI]</p> <p>17) MeanResultantLength; 18) Alpha2_Est; [Fisher&#39;s formula parameters]</p> <p>19) MEdeg [Margin of Error, i.e. accuracy of each wind direction estimate, between 0&deg; and 45&deg;]</p> <p>The accuracy MEdeg is given by the semi-width of the confidence interval, with a confidence level (1-&alpha;) fixed, which is assigned to the wind direction estimate. Consequently, lower MEdeg values correspond to better estimates. And, if MEdeg == 45&deg;, wind estimates must be discharged.</p> <p><br> Finally, note also that you can cut an entire row when [SAR_U SAR_V SAR_W SAR_D] == [NaN NaN NaN NaN] (typically, this happens for &#39;land pixels&#39;).</p> <p>% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %<br> %&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % REFERENCES: &nbsp; &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp; &nbsp;%<br> % &nbsp; &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp; &nbsp;%<br> % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % The algorithm SARWIND LG-Mod is based on the Ph.D thesis below: &nbsp; &nbsp; &nbsp; &nbsp; %<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % [1] Rana, Fabio Michele (2016) &quot;Exploitation of Satellite &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % Synthetic Aperture Radar Data for Geophysical Parameters Retrieval over %<br> % Land and Ocean&quot;. Unpublished Ph.D thesis. Politecnico di Bari. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % Some applications of the method are described in the following papers: &nbsp;%<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % [2] Fabio M. Rana, Maria Adamo, Guido Pasquariello, Giacomo De Carolis, %<br> % and Sandra Morelli, &quot;LG-Mod: A Modified Local Gradient (LG) Method to &nbsp; %<br> % Retrieve SAR Sea Surface Wind Directions in Marine Coastal Areas,&quot; &nbsp; &nbsp; &nbsp;%<br> % Journal of Sensors, vol. 2016, Article ID 9565208, 7 pages, 2016. &nbsp; &nbsp; &nbsp; %<br> % doi:10.1155/2016/9565208. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % [3] Rana, F. M., Adamo, M., &amp; Blanda, P. (2018, July). &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % LG-Mod Multi-Scale Approach for Sar Sea Surface Wind Directions &nbsp; &nbsp; &nbsp; &nbsp; %<br> % Retrieval. In IGARSS 2018-2018 IEEE International Geoscience and Remote %<br> % Sensing Symposium (pp. 3216-3219). IEEE. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % [4] Rana, F. M., Adamo, M., Lucas, R., &amp; Blonda, P. (2019). Sea surface %<br> % wind retrieval in coastal areas by means of Sentinel-1 and numerical &nbsp; &nbsp;%<br> % weather prediction model data. Remote Sensing of Environment, 225, &nbsp; &nbsp; &nbsp;%<br> % 379-391. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % Suggestions and comments are always welcome. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % Thanks in advance, &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % Fabio Michele Rana &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;%<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % MOB: (+39) 3804114171 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % E-MAILS: fabiomichele.rana@gmail.com; &nbsp;fabiomichele.rana@iia.cnr.it &nbsp; &nbsp; %<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % SKYPE: fabiomichelerana &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % SARWIND_LG-Mod_v4.01, 2014-2019 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % Author: Fabio M. Rana &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %<br> % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %<br> &nbsp;</p>

opencc-by-4.0Apr 2019View details →
zenodo40/100

Data for: Terrestrial land use signals on groundwater fauna beyond current protection buffers (Ecological Applications, 2024)

<p>Original research article: Kn&uuml;sel M., Alther R. &amp; Altermatt F. (2024). Terrestrial land use signals on groundwater fauna beyond current protection buffers. <em>Ecological Applications.</em></p>

opencc-by-4.0Sep 2024View details →
zenodo40/100

Dataset for Detecting False Data Injection Attacks in GOOSE Protocol Communication between RTU and Bay Protection Unit

<p>This dataset focuses on the detection and prevention of False Data Injection (FDI) attacks targeting the communication between a Remote Terminal Unit (RTU) and a Bay Protection Unit in a power substation, utilizing the Generic Object Oriented Substation Event (GOOSE) protocol. It includes both clean traffic events and recorded instances of FDI attacks.</p>

opencc-by-4.0Oct 2024View details →
zenodo40/100

MULTIPLIERS_WP5_Science learning project on Forest use vs. forest protection_UBO_Public data_20241014_v1

<p><span>This dataset contains the following data related to</span><span> the science learning project on <em>Forest use vs. forest protection</em></span><span>:</span></p> <ul> <li><span>S</span><span>ummary of transcripts from interviews with OSC members, and student groups (</span><span>Pseudo-/Anonymised)</span></li> </ul>

opencc-by-4.0Oct 2024View details →
zenodo40/100

MULTIPLIERS_WP3/4/5_Science learning project on Forest use vs. forest protection_Public data_UMU_20241025_v1

<p><span>This dataset contains the following data related to</span><span> the science learning project on <em>Forest use vs. forest protection</em></span><span>:</span></p> <ul> <li><span>S</span><span>ummary of transcripts from interviews with teachers, OSC members, and students (</span><span>Pseudo-/Anonymised)</span></li> <li><span><span>Summary</span><span> of transcripts from focus group discussions with students (</span><span>Pseudo-/Anonymised)</span></span></li> <li><span><span><span>An indicative set of key messages and exemplary quotes from the teachers and researchers gathered from<span>&nbsp; </span>interviews conducted after the end of Implementation Round 2 and 3.</span></span></span></li> </ul>

opencc-by-4.0Oct 2024View details →
zenodo40/100

Fig. 4 in Conservation importance of Nakai-Nam Theun National Protected Area, Laos, for small carnivores based on camera trap data

Fig. 4. Distribution of camera-trap records for Mustelidea and Herpestidea in Nakai-Nam Theun NPA from 2006–2011.

opencc-by-4.0Feb 2014View details →
zenodo40/100

Fig. 3 in Conservation importance of Nakai-Nam Theun National Protected Area, Laos, for small carnivores based on camera trap data

Fig. 3. Distribution of camera-trap records for Viverridae and linsang in Nakai-Nam Theun NPA from 2006–2011.

opencc-by-4.0Feb 2014View details →
zenodo40/100

Fig. 2 in Conservation importance of Nakai-Nam Theun National Protected Area, Laos, for small carnivores based on camera trap data

Fig. 2. Total survey effort (in camera trap days) per month over the 2006–2011 survey period (bars) and relative species encounter rate (i.e., total independent photos of small carnivore spp./total camera trap day for the month). Relative encounter rates were highest during the warmest and well-surveyed months—peaks are observed in March (start of the warm season) and October (still within the warm season). Despite high survey effort in January and December (cold season), encounter rates were low.

opencc-by-4.0Feb 2014View details →
zenodo40/100

Fig. 1 in Conservation importance of Nakai-Nam Theun National Protected Area, Laos, for small carnivores based on camera trap data

Fig. 1. Camera-trap sampling effort within Nakai–Nam Theun NPA in 2006–2011 (c.f. Table 1; Johnson et al., 2007) at 10 survey blocks; in chronological order of survey: (1) Khamkeut – Nam San; (2) Nam On – Boualapha; (3) Nam On – Gnomalath; (4) Khamkeut – Thong Pae; (5) Nam Chae – Makfuang; (6) Nam Chae – Navang; (7) Phou Vang – Houay Nam Heuy; (8) Thong Xet; (9) Nam Mon – Thongkacheng; (10) Nam Theun – reservoir.

opencc-by-4.0Feb 2014View details →
dryad40/100

Data from: Which traits optimize plant benefits? Meta-analysis on the effect of partner traits on the outcome of an ant-plant protective mutualism

<p><span>1. Theoretical models on mutualism dynamics predict that partner traits may influence the outcome of mutualistic interactions. However, most empirical data on this issue is restricted to case studies, limiting our ability to reach a more widespread comprehension of the role of partner traits on the dynamic of mutualisms. </span></p> <p><span>2. We investigated how the outcome of protective mutualisms between ants and plants bearing extrafloral nectaries (EFNs) is influenced by the traits of EFNs and ants feeding on EFNs. We used a meta-analytical approach based on 35 studies investigating the effect of ant attendance on the herbivores and reproductive performance of EFN-bearing plants. We evaluated how variation in the EFN vascularization and location on plants and the ant aggressiveness can modulate the effect of ant attendance on the plants. </span></p> <p><span>3. Both plant and ant traits investigated here drove the outcome of the protective mutualism for EFN-bearing plants. Plants exclusively bearing EFNs near reproductive organs benefited more from ant attendance than plants bearing EFNs on vegetative or vegetative and reproductive organs. Ants had a higher positive impact on the reproductive performance of plants bearing non-vascularized EFNs than plants bearing vascularized EFNs, although their effects on herbivores had been similar in both plant types. Regarding the ant behavior, plants often attended by more aggressive ant species had a higher reproductive performance than plants often attended by less aggressive ones. </span></p> <p><span>4. Synthesis</span><span>: Our results highlight that the selective pressures and evolutionary routes in ant-plant protective mutualisms may depend on the pool of traits exhibited by partner species. Although some studies have already reported some impact of species traits on the outcome of ant-plant mutualisms, this is the first time that a generalization about the role of species traits on the net balance of ant attendance was proposed. Due to this generalization, it was possible to advance our knowledge about the evolution of facultative mutualisms by showing that the role of species traits on the mutualistic outcome can vary in intricate ways due to a particular trait combination found among partners in communities where the interactions are embedded in.</span></p>

opencc-zeroNov 2022View details →
dryad40/100

Data and code from: Protection from fishing improves body growth of an exploited species

<p>Hunting and fishing are often size-selective which favours slow body growth. In addition, fast growth rate has been shown to be positively correlated with behavioural traits that increase encounter rates and catchability in passive fishing gears such as baited traps. This harvest-induced selection should be effectively eliminated in no-take marine-protected areas (MPAs) unless strong density dependence results in reduced growth rates. We compared the body growth of European lobster (<em>Homarus gammarus</em>) between three MPAs and three fished areas. After 14 years of protection from intensive, size-selective lobster fisheries, the densities in MPAs have increased considerably, and we demonstrate that females moult more frequently and grow more during each moult in the MPAs. A similar, but weaker pattern was evident for males. This study suggests that MPAs can shield a wild population from slow-growth selection, which can explain the rapid recovery of size structure following implementation. If slow-growth selection is a widespread phenomenon in fisheries, the effectiveness of MPAs as a management tool can be higher than currently anticipated.</p>

opencc-zeroNov 2022View details →
zenodo40/100

Dataset literatur review online business AND data protection

<p>Data ini digunakan untuk membuat penelitian berdasarkan tinjauan literatur dengan kata kunci &quot;online business &quot;dan&nbsp;&quot;data protection&quot;</p>

opencc-by-4.0Nov 2022View details →
zenodo40/100

Data and code from: Three decades of wildlife-vehicle collisions in a protected area: main roads and long-distance commuting trips to migratory prey increase spotted hyena roadkills in the Serengeti

<p>This is the first release. Potential updates will be&nbsp;available on GitHub: <a href="https://github.com/MarwanNaciri/Three_decades_of_spotted_hyena_roadkill_in_a_protected_area">https://github.com/MarwanNaciri/Three_decades_of_spotted_hyena_roadkill_in_a_protected_area</a></p>

openother-openFeb 2023View details →
zenodo40/100

Data repository - The role of peatland degradation, protection and restoration for climate change mitigation in the SSP scenarios

<p>This datasets provides regional and spatial-explicit gridded data for the analysis presented in the manuscrip &quot;The role of peatland degradation, protection and restoration for climate change mitigation in the SSP scenarios&quot; under review in &quot;Environmental Research: Climate&quot; with reference &quot;ERCL-100126&quot;</p>

opencc-by-4.0Feb 2023View details →
dryad40/100

Code and initial metapopulation data for model construction and simulation analyses for: Genetic rescue from protected areas is modulated by migration, hunting rate and timing of harvest

<p>Migrants from protected areas may buffer the risk of harvest-induced evolutionary changes in exploited populations that face strong selective harvest pressures in both terrestrial and marine ecosystems. Understanding the mechanisms favouring genetic rescue through migration could help ensure sustainable harvest outside protected areas and conserve genetic diversity inside those areas. We developed a stochastic individual-based metapopulation model to evaluate the potential for migration from protected areas to mitigate the evolutionary consequences of selective harvest. We parameterized the model with detailed data from individual monitoring of two populations of bighorn sheep subjected to trophy hunting. We tracked horn length through time in a metapopulation including large protected and trophy-hunted populations connected through male breeding migrations. We quantified and compared declines in horn length and rescue potential under various combinations of migration rate, hunting rate in hunted areas and temporal overlap in timing of harvest and migrations, which affects the migrants' survival and chances to breed within exploited areas. Our simulations suggest that the effects of size-selective harvest on male horn length in hunted populations can be dampened or avoided if harvest pressure is low, migration rate is substantial, and migrants have a low risk of being shot. Intense size-selective harvest impacts the phenotypic and genetic diversity in horn length, and population structure through changes in proportions of large-horned males, sex ratio and age structure. When hunting pressure is high and overlaps with male migrations, effects of selective removal also emerge in the protected population, so that instead of a genetic rescue of hunted populations, our model predicts undesirable effects inside protected areas. Our results stress the importance of a metapopulational approach to management, to promote genetic rescue from protected areas and limit ecological and evolutionary impacts of harvest on both harvested and protected populations.</p>

opencc-zeroApr 2023View details →
zenodo40/100

The source data for "Inductively shunted transmon: A superconducting qubit with flux noise insensitive plasmon states and a protected fluxon decay exceeding 3 hours"

<p>The following folder contains all the raw data, analysis Mathematica notebook and ScQubits python codes used to generate the results in &ldquo;Inductively shunted transmon: A superconducting qubit with flux noise insensitive plasmon states and a protected fluxon decay exceeding 3 hours&rdquo; in nature communications. Please follow the instruction below for proper navigation through the data:</p> <p>Fig. 1 folder:</p> <ol> <li>Run &ldquo;Color map of Matrix element Vs energy parameters&rdquo; to generate &ldquo;x.dat&rdquo;, &ldquo;y.dat&rdquo;, &rdquo;M.dat&rdquo;(respectively EJ/EL, EJ/EC and the matrix element of the first flux transition). <strong>Make sure to correct the address where these file should be saved</strong>.</li> <li>The mathematica notebook plots the dispersion in IST limit and the matrix element gray scale color map contours separately and the full image was constructed in illustrator later. The green dots on the dispersion plot represent the position of other qubits on the color map.&nbsp;</li> </ol> <p>Fig. 2&amp;3 folder:</p> <ol> <li>The python file &ldquo;paper figures&rdquo; uses ScQubits to generate different studies in IST limit presented in Fig. 2&amp;3 and generates the following files:</li> </ol> <p>Fig. 2a:</p> <p>&ldquo;fluxonium.hdf5&rdquo;: The spectrum of a typical fluxonium</p> <p>&ldquo;fluxoniumME.hdf5&rdquo;: The matrix element of all transition in &ldquo;fluxonium.hdf5&rdquo;</p> <p>&nbsp;</p> <p>Fig. 2d:</p> <p>&ldquo;case1.hdf5&rdquo;: The spectrum of fluxonium with EJ/EC=6.6</p> <p>&ldquo;ME1.hdf5&rdquo;: The matrix element of transition in &ldquo;case1.hdf5&rdquo;</p> <p>&ldquo;case2.hdf5&rdquo;: The spectrum of fluxonium with EJ/EC=13</p> <p>&ldquo;ME2.hdf5&rdquo;: The matrix element of transition in &ldquo;case2.hdf5&rdquo;</p> <p>.</p> <p>.</p> <p>&ldquo;case6.hdf5&rdquo;: The spectrum of fluxonium with EJ/EC=200</p> <p>&ldquo;ME6.hdf5&rdquo;: The matrix element of transition in &ldquo;case6.hdf5&rdquo;</p> <p>&ldquo;IST.hdf5&rdquo;: The spectrum of the IST qubit</p> <p>&ldquo;ISTME.hdf5&rdquo;: The matrix element of transition in &ldquo;IST.hdf5&rdquo;</p> <p>&ldquo;transmon.hdf5&rdquo;: The spectrum of a transmon with the same EJ and EC as IST qubit</p> <p>Fig. 3a</p> <p>&ldquo;Waveamp.hdf5&rdquo;: The wave functions and eigenenergies of the IST qubit</p> <p>&ldquo;WaveampT.hdf5&rdquo;: The wave functions and eigenenergies of the transmon</p> <p>&nbsp;</p> <p>Fig. 3b:</p> <p>&ldquo;ELcase1.hdf5&rdquo;: The spectrum of IST qubit with EL=2 GHz</p> <p>&ldquo;ELME1.hdf5&rdquo;: The matrix element of transition in &ldquo;ELcase1.hdf5&rdquo;</p> <p>&ldquo;ELcase2.hdf5&rdquo;: The spectrum of IST qubit with EL=1.5 GHz</p> <p>&ldquo;ELME2.hdf5&rdquo;: The matrix element of transition in &ldquo;ELcase2.hdf5&rdquo;</p> <p>.</p> <p>.</p> <p>&ldquo;ELcase6.hdf5&rdquo;: The spectrum of IST qubit with EL=0.25 GHz</p> <p>&ldquo;ELME6.hdf5&rdquo;: The matrix element of transition in &ldquo;ELcase6.hdf5&rdquo;</p> <p>&nbsp;</p> <p>Fig. 3b inset:</p> <p>&ldquo;WaveampEL.hdf5&rdquo;contains the wave functions for El={2,1.5,1,0.75,0.5,0.25}GHz.</p> <p>&nbsp;</p> <p>Fig. 3c:</p> <p>&ldquo;EC.hdf5&rdquo; contains numerical simulation of an IST qubit with fixed EJ and Ec while EL is changing to calculate anharmonicity.</p> <ol> <li>The Mathematica notebook &ldquo;Theory_figures&rdquo; runs based on the files above and plot the result presented in the paper.</li> </ol> <p>Fig. 5 folder:</p> <ol> <li>Fig. 5a&amp;b folder contains the raw data of spectroscopy of the IST qubit with different temperature and the Mathematica notebook &ldquo;Tempsweeps_figa&amp;b&rdquo; simply plots the data. In the data set the I and Q quadrature as well as the amplitude and power of the signal coming back from cavity is provided.</li> <li>Fig. 5c folder contains several sweeps of both spectroscopy and resonator performed at fridge base temperature (7mK) labeled as &ldquo;specge#.txt&rdquo; and &ldquo;Res_VNA_*.txt&rdquo; respectively. The ScQubits python code &ldquo;IST_Device&rdquo; provides a fit for the data using the fit procedure explained in Supplementary Note 4 and generates the bare spectrum of the device saved in &ldquo;Fit.h5&rdquo;. The Mathematica notebook &ldquo;spec_analysis&rdquo; uses all spectroscopy data and the fit file to plot Fig. 5c.</li> </ol> <p>Fig. 6 folder: Contains all the raw data of T1 and T2 experiment at different flux positions across a flux quantum. The Mathematica notebook &ldquo;T1&amp;2&rdquo; performs all the analysis presented in Fig. 6 for devices A, B and C.</p> <p>Fig. 7 folder:</p> <ol> <li>Fig. 7a: In this folder the we provide the raw data for fidelity experiment. The data is in the &ldquo;*.mat&rdquo;&nbsp; format and contains 40000 single shot I&amp;Q bins collected with measurement band width of 2MHz and integration time of 500ns. The files names indicate whether the data was taken with qubit prepared in ground/excited state by having &ldquo;_g_&rdquo;/&rdquo;_e_&rdquo;. Following the state preparation condition, the measurement power at which the data was taken is indicated. The Mathematica notebook &ldquo;fidelity_sweep&rdquo; takes the data and extract the fidelities shown in Fig. 7a and the 2D histogram plots presented in Supplementary Figure 5d.</li> <li>Fig. 7b:&nbsp; The raw data for QND-ness experiment is presented in this folder. Each file contains 500 time traces of the two consecutive pulses applied to the resonator to study the non-QND effects of the IST qubit in high power. The Qubit preparation condition is apparent in the file name along with the power at which the measurement was performed. The Mathematica notebook &ldquo;QND_ness&rdquo; extracts the QND_ness and plots the results shown in Fig. 7b</li> </ol> <p>&nbsp;</p> <p>Fig. 8 folder:</p> <ol> <li>Fig. 8a: This folder contains the spectroscopy sweeps conditions by the fluxon state using a strong microwave pulse applied to the resonator. The Mathematica notebook &ldquo;sweeps&rdquo; plots the data.</li> <li>Fig. 8c: This folder contains the raw data for long fluxon decays collected using quantum machines (QM). In this experiment the fluxon excitation pulse was applied and repeated until a successful fluxon state is detected. Afterwards, the experiment enters monitoring stage where every 30s we check the fluxon state until a tunneling to fluxon ground state is detected. This event is logged and the QM repeats the fluxon excitation immediately followed by a monitoring stage and logging the time it took for tunneling to occur. The raw data of every 30 second monitoring stage is saved in files with &ldquo;_raw_&rdquo; in their labels. The files containing &ldquo;_taus_&rdquo; in their names have only the logged tunneling time events. The Mathematica notebook &ldquo;qubit analysis&rdquo; takes the data for three external flux bias and, by loading the &ldquo;_taus_&rdquo; files, reconstructs the quasi quantum jump traces and finally the decay traces presented in Fig. 8c.</li> </ol>

opencc-by-4.0Jun 2023View details →
zenodo40/100

Flow cytometry data for "Vitamin B12 conveys a protective advantage to phycosphere-associated bacteria at high temperatures"

<p>More details&mdash;including the analysis pipeline&mdash;are available in the GitHub repository:&nbsp;<a href="http://github.com/maggimars/bactB12">https://github.com/maggimars/bactB12</a>.&nbsp;</p> <p>Direct link to analysis pipeline interactive document:&nbsp;<a href="https://maggimars.github.io/bactB12/Flow_Cytometry_Analysis.html">https://maggimars.github.io/bactB12/Flow_Cytometry_Analysis.html</a></p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2023View details →

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