Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,480
datasets available to search
ShareScore release 0.9.0
Dataset results
3,480 results for “a value”
Indicator values for the many-body localization of the Heisenberg spin chain at various energies, system sizes and disorder magnitude
<p>This data set accompanies the preprint <em>Scalable approach to many-body localization via quantum data </em>(arXiv: <a href="https://arxiv.org/abs/2202.08853">2202.08853</a>) and its code, available at <a href="https://github.com/GreschAl/MBLlearning">GitHub</a>.</p> <p>It consists of the numerically obtained indicator values for the many-body localization for the Heisenberg model (see preprint for details and background) for various values of the energy density <span class="math-tex">\(\epsilon = 0.05, 0.1, \dots, 0.9, 0.95\)</span> and for chain lengths <span class="math-tex">\(L = 10, 12, 14\)</span>. For each tuple <span class="math-tex">\((\epsilon,L)\)</span>, there exist two files, representing the training and the test set, respectively. Each such file contains various values of the disorder parameter <span class="math-tex">\(h = 0.5, 1, \dots, 14.5, 15\)</span> with <span class="math-tex">\(N = 1000\ (100)\)</span> sampled realizations of the disorder vector for each <span class="math-tex">\(h\)</span> for the training (test) set, followed by the three calculated values of the three indicators.</p> <p>The data is automatically processable by the code provided in the GitHub repository.</p>
Moral Values of Twitter COVID-19 Vaccine Data
<p>This data is part of our accepted paper "Learning to Adapt Domain Shifts of Moral Values via Instance Weighting" at the 33rd ACM Conference on Hypertext and Social Media (HT ’22). We annotate moral values of COVID-19 vaccine-related tweets. </p>
Innovative agrifood value chains
<p>This data-set has been produced in the frame of H2020 project CO-FRESH, in Deliverable 1.2 "List of value chains and a data-set on the characteristics of the identified sustainable, innovative and competitive agrifood value chains"</p> <p>Grand societal challenges, such as climate change, environmental degradation, food security, immigration, and digital transformation, urge value chains actors from farm to fork to interact for improving the system. In this context, innovation, that has long been considered as a factor of growth and competitiveness, becomes an increasingly important factor to create value while addressing sustainability challenges (both environmental, social and economic).</p> <p><strong>The CO-FRESH project</strong> aims to enhance collaboration for sustainability-oriented innovation in the agri-food sector, by proposing interventions for re-designing fruit and vegetables (F&V) value chains across Europe. To reach these objectives, Work Package 1 takes the lead in <em>Identification, Analysis and Design of Innovative and Sustainable Agri-food Value Chains</em>. The current report is the outcome of <em>Task 1.2. Identify innovative agri-food value chains and collect empirical data. </em></p> <p><strong>Deliverable 1.2.</strong> presents a list of value chains and a data-set on the characteristics of the identified sustainable, innovative and competitive agrifood value chains. This list is the results of a participatory inventory led by WUR and involving all the CO-FRESH consortium partners.</p> <p>This report contains three core elements. <strong>First,</strong> it presents the methodology that was used for the inventory creation, drawing on the concepts and selection criteria developed in <em>D1.1.Review state of the art</em>. <strong>Second,</strong> the report provides the list of the selected 100+ value chains and their general characteristics. <strong>Third,</strong> the report shows the different types of sustainability-oriented innovations implemented in these value chains, as well as the various modes of collaboration used to design and implement the innovations.</p> <p>The inventory has been presented to the CO-FRESH consortium during a workshop held 7 October 2021 (CO-FRESH Milestone 2). The inventory will be used in the next step of the project for further data collection and analysis (Task 1.3). For the next milestone, a survey will be addressed to a representative of each of these 100+ value chains in order to gain better understanding of the drivers of collaboration and to assess the impact of the sustainability-oriented innovation implemented. Second, the inventory will be used to select and investigate a portfolio of business models in the Task 1.4. Based on this inventory and the following analysis in Task 1.3 and Task 1.4, recommendations will be developed for interventions to redesign the value chains of the CO-FRESH pilot cases.</p>
A Google Earth Engine code to analyze residential buildings' real estate values, summer surface thermal anomaly patterns and urban features: a Florence (Italy) case study
<ol> </ol> <p>The layers included in the code were from the study conducted by the research group of CNR-IBE (Institute of BioEconomy of the National Research Council of Italy) and ISPRA (Italian National Institute for Environmental Protection and Research), published by the Sustainability journal (<strong>https://doi.org/10.3390/su14148412</strong>).</p> <p>Link to the <strong>Google Earth Engine (GEE) code</strong> <strong>(link: <a href="https://code.earthengine.google.com/715aa44e13b3640b5f6370165edd3002">https://code.earthengine.google.com/715aa44e13b3640b5f6370165edd3002</a></strong>)</p> <p>You can analyze and visualize the following spatial layers by accessing the GEE link: </p> <ol> <li><strong>Daytime summer land surface temperature</strong> (raster data, horizontal resolution 30 m, from Landsat-8 remote sensing data, years 2015-2019)</li> <li><strong>Surface thermal hot-spot </strong>(raster data, horizontal resolution 30 m) was obtained by using a statistical-spatial method based on the Getis-Ord Gi* approach through the ArcGIS Pro tool.</li> <li><strong>Surface albedo</strong> (raster data, horizontal resolution 10 m, Sentinel-2A remote sensing data, year 2017)</li> <li><strong>Impervious area</strong> (raster data, horizontal resolution 10 m, ISPRA data, year 2017)</li> <li><strong>Tree cover</strong> (raster data, horizontal resolution 10 m, ISPRA data, year 2018)</li> <li><strong>Grassland area</strong> (raster data, horizontal resolution 10 m, ISPRA data, year 2017)</li> <li><strong>Water bodies</strong> (raster data, horizontal resolution 2 m, Geoscopio Platform of Tuscany, year 2016)</li> <li><strong>Sky View Factor</strong> (raster data, horizontal resolution 1 m, lidar data from the OpenData platform of Florence, year 2016)</li> <li><strong>Buildings' units</strong> of Florence (shapefile from the OpenData platform of Florence) include data on the residential real estate value from the Real Estate Market Observatory (OMI) of the National Revenue Agency of Italy (source: https://www1.agenziaentrate.gov.it/servizi/Consultazione/ricerca.htm, accessed on 14 July 2022). Data on the characterization of the buffer area (50 m) surrounding the buildings are included in this shapefile [the names of table attributes are reported in the square brackets]: averaged values of the daytime summer land surface temperature [LST_media], thermal hot-spot pattern [Thermal_cl], mean values of sky view factor [SVF_medio], surface albedo [alb_medio], and average percentage areas of imperviousness [ImperArea%], tree cover [TreeArea%], grassland [GrassArea%] and water bodies [WaterArea%]. </li> </ol> <p>Here attached the .txt file of the <strong>GEE code</strong>. </p> <p> </p> <p><em>E-mail</em></p> <p>Giulia Guerri, CNR-IBE, giulia.guerri@ibe.cnr.it</p> <p>Marco Morabito, CNR-IBE, marco.morabito@cnr.it</p> <p>Alfonso Crisci, CNR-IBE, alfonso.crisci@ibe.cnr.it</p>
Nectar values from: Quantifying nectar production by flowering plants in urban and rural landscapes
<p>Floral resources (nectar and pollen) provide food for insect pollinators but have declined in the countryside due to land use change. Given widespread pollinator loss, it is important that we quantify their food supply to help develop conservation actions. While nectar resources have been measured in rural landscapes, equivalent data are lacking for urban areas, an important knowledge gap as towns and cities often host diverse pollinator populations.</p> <p>We quantified the nectar supply of urban areas, farmland and nature reserves in the UK by combining floral abundance and nectar sugar production data for 536 flowering plant taxa, allowing us to compare landscape types and assess the spatial distribution of nectar sugar among land uses within cities.</p> <p>The magnitude of nectar sugar production did not differ significantly among the three landscapes. In urban areas the nectar supply was more diverse in origin and predominantly delivered by non-native flowering plants. Within cities, urban land uses varied greatly in nectar sugar production. Gardens provided the most nectar sugar per unit area and 85% of all nectar at a city scale, while gardens and allotments produced the most diverse supplies of nectar sugar. Floral abundance, commonly used as a proxy for pollinators' food supply, correlated strongly with nectar resources, but left a substantial proportion of the variation in nectar supply unexplained.</p> <p>Synthesis. We show that urban areas are hotspots of floral resource diversity rather than quantity and their nectar supply is underpinned by the contribution of residential gardens. Individual gardeners have an important role to play in pollinator conservation as ornamental plants, usually non-native in origin, are a key source of nectar in towns and cities.</p>
Raw Data to "Prediction of acid pKa values in the solvent acetone based on COSMO-RS"
<p>This data is a supplement to the publication entitled "Prediction of Acid pKa Values in the Solvent Acetone based on COSMO-RS" in the Journal of Computational Chemistry (DOI:10.1002/jcc.26864). The data includes initial starting structures as inputs for conformer searches using COSMOconf (versions 2020 and 2021) in combination with TURBOMOLE (version 7.3). The corresponding output files serve as inputs for the calculation of Gibbs free energies using COSMO-RS as provided by COSMOtherm.</p> <p>Additional information on the file structure is given in the README file.</p>
Aeolian saltation fieldwork: values for size-selective transport measurements
<p>This excel spreadsheet (‘SizeSelectiveTransport.xlsx’) contains the following information on surface and airborne particle size distributions (PSDs) for size-selective saltation transport analyses at our six field sites (Jericoacoara, Rancho Guadalupe, Oceano N1, Oceano S1, Oceano N2, Oceano S2):</p> <ul> <li><strong>“d_lower_mm”</strong> – Lower limit diameter for each particle size bin [mm].</li> <li><strong>“d_mid_mm”</strong> – Midpoint diameter for each particle size bin [mm].</li> <li><strong>“d_upper_mm”</strong> – Upper limit diameter for each particle size bin [mm].</li> <li><strong>“dVdlnd_bed”</strong> – Site-averaged non-dimensionalized volume fraction in each size bin for surface samples, <span class="math-tex">\(\frac{dV_{bed}}{d\ln(d)}\)</span>.</li> </ul> <p>The field measurements from which these values were calculated are described in Martin and Kok (2017).</p> <ul> <li><strong>“dVdlnd_air”</strong> – Site-averaged non-dimensionalized volume fraction in each size bin for airborne samples, <span class="math-tex">\(\frac{dV_{air}}{d\ln(d)}\)</span>.</li> <li>Site-averaged non-dimensionalized volume fraction in each size bin for airborne samples, conditioned on each non-dimensionalized shear stress range, <span class="math-tex">\(\frac{dV_{air}}{d\ln(d)}|_{\tau/\tau_{it}}\)</span>. Cases in which a PSD is lacking for a shear stress range are marked as “NaN”: <ul> <li><strong>“dVdlnd_air_taunorm_below_10”</strong> – for <span class="math-tex">\(\tau/\tau_{it} \leq 1.0\)</span></li> <li><strong>“dVdlnd_air_taunorm_10_15”</strong> – for <span class="math-tex">\(1.0 < \tau/\tau_{it} \leq 1.5\)</span></li> <li><strong>“dVdlnd_air_taunorm_15_22</strong>” – for <span class="math-tex">\(1.5 < \tau/\tau_{it} \leq 2.2\)</span></li> <li><strong>“dVdlnd_air_taunorm_22_30”</strong> – for <span class="math-tex">\(2.2 < \tau/\tau_{it} \leq 3.0\)</span></li> <li><strong>“dVdlnd_air_taunorm_30_40”</strong> – for <span class="math-tex">\(3.0 < \tau/\tau_{it} \leq 4.0\)</span></li> </ul> </li> <li><strong>“f_bed”</strong> – Fraction of bed surface particles in size bin <em>i</em>, <span class="math-tex">\(f_{bed,i}\)</span>. Fraction is computed only for bins with particle diameter <em>d</em> > 1.3 mm. Bins below this value are marked as “NaN”.</li> <li><strong>“f_air_bar”</strong> – Mean fraction of airborne particles in size bin <em>i</em>, <span class="math-tex">\(\langle f_{air,i} \rangle\)</span>. Fraction is computed only for bins with particle diameter <em>d </em>> 1.3 mm. Bins below this value are marked as “NaN”.</li> <li><strong>“f_air_sigma”</strong> – Uncertainty on mean fraction of airborne particles in size bin <em>i</em>, <span class="math-tex">\(\sigma_{\langle f_{air,i} \rangle}\)</span>. “NaN” values correspond to undefined values for f_air_bar.</li> </ul> <p>The Matlab file (‘GrainSizeData.mat’) includes further raw data, including number-based size distributions for individual samples.</p>
Disturbance indicator values for European plants
<p>We report a data set of disturbance indicator values identifying mean optima along gradients of natural and anthropogenic disturbance for 6,382 vascular plant species based on the analysis of 736,366 European vegetation plots and using an expert-based characterization of disturbance regimes in 236 habitat types. The indicator values presented here are crucial for integrating disturbance niche optima in large-scale assessments of vegetation and macroecological studies.</p> <p>The data set contains five main continuous indicator values for European plants: disturbance severity, disturbance frequency, mowing frequency, grazing pressure and soil disturbance. The first two indicators are provided separately for the whole community and the herb layer.</p> <p><strong>Reference:</strong><br> Midolo, G., Herben, T., Axmanová, I., Marcenò, C., Pätsch, R., Bruelheide, H., Karger D.N., Aćić, S., Bergamini, A., Bergmeier, E., Biurrun, I., Bonari, G., Čarni, A., Chiarucci, A., De Sanctis, M., Demina, O., Dengler, J., Dziuba, T., Fanelli, G., Garbolino, E., Giusso del Galdo, G., Goral, F., Güler, B., Hinojos-Mendoza, G., Jansen, F., Jiménez-Alfaro, B., Lengyel, A., Lenoir, J., Pérez-Haase, A., Pielech, R., Prokhorov, V., Rašomavičius, V., Ruprecht, E., Rusina, S., Šilc, U., Škvorc, Ž., Stancic, Z., Tatarenko, I., & Chytrý, M. (2022). Disturbance indicator values for European plants. <em>Global Ecology and Biogeography</em> (Accepted for publication)</p>
Text-fig. 1. Bivariate diagram of length and width of the upper dentition of selected European small and middle size Amphicyoninae compared with the Tuchořice specimens. a: P4; b: M1; c: M2; d: m1; e: m2. Data from Schlosser (1899, 1904), Thenius (1949), Dehm (1950), Heizmann (1973), Ginsburg (1977, 1989), Peigné (2012). Dotted line – ranges of maximum and minimum values from the average of teeth of Cynelos lemanensis from Ulm (Peigné and Heizmann 2003). Abbreviations: L – length; W – width. in The Amphicyoninae (Amphicyonidae, Carnivora, Mammalia) Of The Early Miocene From Tuchořice, The Czech Republic
Text-fig. 1. Bivariate diagram of length and width of the upper dentition of selected European small and middle size Amphicyoninae compared with the Tuchořice specimens. a: P4; b: M1; c: M2; d: m1; e: m2. Data from Schlosser (1899, 1904), Thenius (1949), Dehm (1950), Heizmann (1973), Ginsburg (1977, 1989), Peigné (2012). Dotted line – ranges of maximum and minimum values from the average of teeth of Cynelos lemanensis from Ulm (Peigné and Heizmann 2003). Abbreviations: L – length; W – width.
Text-fig. 4. a: Conglomeratic to massive sandstone facies 1, facies A are composed of Andesit (AF), Clay (CF) and Sandstone (SF) fragments lain on medium-sandstone. b: Conglomeratic to massive sandstone facies, outcropping of massive sandstone facies comprises of fine to medium grain size of grey to yellowish sandstone. c: Heterolithic sandstone-mudstone facies, intercalation of fine sand with silt and shale as type form of heterolithic sandstone mudstone as indicated by a high sand/shale ratio. d: Example outcrops of heterolithic sandstone-mudstone 2 indicated by low sand/shale ratio. e: Heterolithic fine sand and mudstone and mudstone facies, intercalation of thin sandstone and shale. f: Representative of slump deposits outcrops belong to conglomeratic to massive sandstone facies, which is indicated by the intercalation of sandstone and shale and some disturbed beds or layers as seen in slump deposits. The facies type is normally deposited within the basin floor, channel margin or as a product of the overbank deposits. In this figure the slump deposit is shown as internal bedding, some occurred on the bedding-plane. Trend slope measurement of the fold-axis revealed values N 135°E and N 108°E. in Lithofacies And Ichnofacies Of Turbidite Deposits, West Java, Indonesia
Text-fig. 4. a: Conglomeratic to massive sandstone facies 1, facies A are composed of Andesit (AF), Clay (CF) and Sandstone (SF) fragments lain on medium-sandstone. b: Conglomeratic to massive sandstone facies, outcropping of massive sandstone facies comprises of fine to medium grain size of grey to yellowish sandstone. c: Heterolithic sandstone-mudstone facies, intercalation of fine sand with silt and shale as type form of heterolithic sandstone mudstone as indicated by a high sand/shale ratio. d: Example outcrops of heterolithic sandstone-mudstone 2 indicated by low sand/shale ratio. e: Heterolithic fine sand and mudstone and mudstone facies, intercalation of thin sandstone and shale. f: Representative of slump deposits outcrops belong to conglomeratic to massive sandstone facies, which is indicated by the intercalation of sandstone and shale and some disturbed beds or layers as seen in slump deposits. The facies type is normally deposited within the basin floor, channel margin or as a product of the overbank deposits. In this figure the slump deposit is shown as internal bedding, some occurred on the bedding-plane. Trend slope measurement of the fold-axis revealed values N 135°E and N 108°E.
Text-fig. 4. Graphical visualization of Phytogeographic Reference Regions Assessment (PRRA) of nearest living relative genera of fossil-taxa from late Early Miocene Wiesa assemblage in eastern Germany. Analysis yields only NLRs which have modern distribution area (partly) in E and SE Asia. For relationships of fossil-taxa to nearest living relatives or ecological equivalents, see Tab. 6; taxa used for analysis marked with asterisks. Three geographic resolutions conducted: a – grid with 1.5° latitude/longitude resolution, b – grid with 2°, c – grid with 3°; similarity column indicates cooccurrences of genera of nearest living relatives in single grid box. Maximum value in our analysis: grid box marked with arrow in map a, located in western Yunnan Province, P. R. China and southern Kachin Province, NE Myanmar (east of Myitkyina city), area with 97.371 7–98.874 2° longitude and 24.586 7–25.837 5° latitude, yields 23 co-occurring species of 13 genera (Tab. 7). in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)
Text-fig. 4. Graphical visualization of Phytogeographic Reference Regions Assessment (PRRA) of nearest living relative genera of fossil-taxa from late Early Miocene Wiesa assemblage in eastern Germany. Analysis yields only NLRs which have modern distribution area (partly) in E and SE Asia. For relationships of fossil-taxa to nearest living relatives or ecological equivalents, see Tab. 6; taxa used for analysis marked with asterisks. Three geographic resolutions conducted: a – grid with 1.5° latitude/longitude resolution, b – grid with 2°, c – grid with 3°; similarity column indicates cooccurrences of genera of nearest living relatives in single grid box. Maximum value in our analysis: grid box marked with arrow in map a, located in western Yunnan Province, P. R. China and southern Kachin Province, NE Myanmar (east of Myitkyina city), area with 97.371 7–98.874 2° longitude and 24.586 7–25.837 5° latitude, yields 23 co-occurring species of 13 genera (Tab. 7).
Assessing the value of monitoring to biological inference and expected management performance for a European goose population
<p>1. Informed conservation and management of wildlife require sufficient monitoring to understand population dynamics and to direct conservation actions. Because resources available for monitoring are limited, conservation practitioners must strive to make monitoring as cost-effective as possible.</p> <p>2. Our focus was on assessing the value of monitoring to the adaptive harvest management (AHM) program for pink-footed geese (Anser brachyrhynchus). We conducted a retrospective analysis to assess the costs and benefits of a capture-mark-resight (CMR) program, a productivity survey, and biannual population censuses. Using all available data, we fit an integrated population model (IPM) and assumed that inference derived from it represented the benchmark against which reduced monitoring was to be judged. We then fit IPMs to reduced sets of monitoring data and compared their estimates of demographic parameters and expected management performance against the benchmark IPM.</p> <p>3. Costs and the precision and accuracy of key demographic parameters decreased with the elimination of monitoring data. Eliminating the CMR program, while maintaining other monitoring instruments, resulted in the greatest cost savings, usually with small effects on inferential reliability. Productivity surveys were also expensive and some reduction in survey effort may be warranted. The biannual censuses were inexpensive and generally increased inferential reliability.</p> <p>4. The expected performance of AHM strategies was surprisingly robust to a loss of monitoring data. We attribute this result to explicit consideration of parametric uncertainty in harvest-strategy optimization and the fact that a broad range of population sizes is acceptable to stakeholders.</p> <p>5. Synthesis and applications: Our study suggests that existing or potential monitoring instruments for wildlife populations should be scrutinized as to their cost-effectiveness for improving biological inference and management performance. Using Svalbard pink-footed geese as a case study, we show that the loss of some existing monitoring instruments may not be as adverse as commonly assumed if data are jointly analyzed in an integrated population model. Finally, regardless of the monitoring data available, we suggest that conservation strategies that explicitly account for uncertainty in demography are more likely to be successful than those that do not<span>.</span></p>
The Relationship between LRP5 (rs556442 and rs638051) Polymorphisms and Mutation with Bone Metabolism in Xinjiang women with Type 2 Diabetes after Menopause(Table 1 and Table 2 Statistical Values of Analysis Process)
<p>The Relationship between LRP5 (rs556442 and rs638051) Polymorphisms and Mutation with Bone Metabolism in Xinjiang women with Type 2 Diabetes after Menopause(Table 1 and Table 2 Statistical Values of Analysis Process)</p>
Reception of the values of the Aeschylus drama and mnemonic imprints by ancient tragedy spectators
<p>Data and questioner from VAST programme (Grant agreement No 101004949). The participants of the study completed a questionnaire of open and closed questions specially created in terms of subject matter and targeting by a three-member independent team of Professors from various universities in Greece (pretest). The same questionnaire was answered six months after the viewing of the show by the same spectators (December 2021-January 2022) (posttest).</p>
Supporting data sets for "Estimating Carbon Fixation of Plant Organs for Afforestation Monitoring using a Process-based Ecosystem Model and Ecophysiological Parameter Optimization". (the survey of tree breast diameter and tree height in 11-year old Eucommia ulmoides plantation, values of simulation results used in figures and tables.)
<p>Supporting data sets for Miyauchi et al., Ecology and Evolution, 2019 (accepted).</p> <p>The files store: </p> <p>(1) The survey of tree breast diameter and tree height in <em>Eucommia ulmoides</em> plantation<em>.</em> The ring and stem analysis and dry weight of seven harvested sample trees in the plantation.</p> <p>(2) Values of optimization result used fig.7.</p> <p>(3) Values of prediction result used fig.8. and table 4.</p> <p>(4) Values of optimized parameters by optimization methods, parameter range and constrain.</p>
Figure 6: Erythema values before and after 10 minutes from application 57 -STUDIES TOWARDS OBTAINING A PHOTOPROTECTIVE DERMO-COSMETIC COMPLEX PRODUCT WITH NATURAL EXTRACTS OF INORGANIC AND ORGANIC SUBSTANCES
<p>The values of the erythema are relatively low, which indicates that the<br> product is compatible with the skin and has no sensitizing potential (¯gure6).<br> Having a complex composition of ingredients with varying degrees of un-<br> saturation, with the major organic structure, the product is subjected to de-<br> structive processes at the impact of UV radiation and atmospheric oxygen.<br> As a result this organic substances undergo structural changes, embodied in<br> the initial color change, division of chain, forming oxidizing action groups and<br> oxygen free radicals that continue the destructive process. Because of these<br> features, the product was subjected to accelerated tests of thermal and photo<br> destruction. As a result of these tests, the product's characteristics have not<br> changed signi¯cantly.</p>
Figure 1 Scatter Plot of Standardized Residual by Standardized Predicted Value-Potential Predictability of ZPD of Children's Cognitive Development
<p>One of the essential assumptions that should be met in regression analysis is the linearity of<br> the data. The result of the analysis of variance (ANOVA) shows that regression model is linear; F<br> (1, 39) = 8.429, P <0.05 for model 1 and F (2, 38) = 8.648, P<0.05 for model 2. Moreover, Scatter<br> plot shows (Figure1) that there is no funnel shaped or crescent shaped cloud. This indicates that two<br> assumptions of linearity and homogeneity of variance have been met.</p>
Figure 3: The dependencies ² 00 (log !¿¾). The values are normalized at ² 00 max-TOWARD THE PHYSICAL BASIS OF COMPLEX SYSTEMS: DIELECTRIC ANALYSIS OF POROUS SILICON NANOCHANNELS IN THE ELECTRICAL DOUBLE LAYER LENGTH RANGE
<p>Fig.3. The conductivity relaxation occurs at<br> lowing frequencies. The form of the ²<br> 00<br> (!) = f(²<br> 0<br> (!)) diagrams changes from<br> a vertical line (a), to any deformate semicircles (b, c, d) having the angle to<br> real axe below ¼<br> 2 , Fig.4. This behaviour denotes that the EDL is not an ideally<br> capacitor, but also is not a disipative region, depending both on the EDL<br> thickness and the frequency range of the applied ¯eld [7]. The composition<br> (by thickness) of the EDL determines essentially the dielectric response of the<br> interface system. Compared with experimental results, the dielectric pro¯le<br> of this higher length scales model, can provides a more complet description of<br> the solvent properties for a given electrode.</p>
Figure 2: The dependencies ² 0 (log !¿¾). The values are normalized at ² 0 max-TOWARD THE PHYSICAL BASIS OF COMPLEX SYSTEMS: DIELECTRIC ANALYSIS OF POROUS SILICON NANOCHANNELS IN THE ELECTRICAL DOUBLE LAYER LENGTH RANGE
<p>The results of the model are shown that the frequency-dependences ²<br> 0<br> (log(!¿¾))<br> in Fig.2, ²<br> 00(log(!¿¾)) in Fig.3 and ²<br> 00<br> (²<br> 0<br> )T in Fig.4, where ²<br> 0<br> , ²<br> 00<br> are the real and<br> imaginary part, respectively, from (7), having the ¸D<br> ¸ ratio as parameter.</p>
Figure 4. Incorrect crossover operation. The High-High and High-Med probability values summation should be 1.-Genetic Algorithms Principles Towards Hidden Markov Model
<p>In this genetic operator, we choose two chromosomes at random and apply crossover between<br> them. Figure 3 shows the proposed crossover. We choose a crossing cut site at random. It is to be<br> noted that the crossing cut site should be even number. We should have two crossing cut sites. If<br> we make crossing cut site odd number, the resultant child will not have a correct value of<br> probability. The incorrect crossover is shown in Figure 4.</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.