Find research datasets worth reusing

opencc-by-4.0Oct 2023View details →

Table 7 for the Study: "Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth."

Summary graphs for the study: "Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth". Data distributions of the Hypothesis 2, with the R² regression coefficients of the three σFR values and indices (parameters A, B and % Alert Time) of both the 200 earthquakes and the 63 earthquakes after 1988, for Section 3.2.1.The R² regression coefficients of each curve are calculated in the Excel files on the 2 Drives: https://docs.google.com/spreadsheets/d/17UGHZlvZ2N-g6TOzgqpIe248_IitBmka8DbGWsv-lKQ/edit?usp=sharing, for the 200 earthquakes.https://docs.google.com/spreadsheets/d/1Pyd4wZxZrq6G76nM2SwHYBBjbPZz7uM8GeO7PXG7obU/edit?usp=sharing, for the 63 earthquakes after 1988.

opencc-by-4.0Oct 2023View details →

Table 9 for the Study: "Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth."

Overview of the 200 analyzed earthquakes encompassing values and indices for σFR Parameters A, B, and the percentile of Alert Time across the three Analysis Lines, for Section 3.2.6.It contains 1 Excel calculation file, consisting of 3 excel sheet for each of the 3 lines of analysis, for both the 200 earthquakes since 1600 and for the 63 earthquakes that occurred after 1988.

W2 light curve, W1 - W2 color change and color-magnitude diagrams for all identified NEOWISE variables of ATLASGAL sources

Figures of the W2 light curve, W1 - W2 color change and color-magnitude relationship for different types of variability. The ZIP file contains six subsections, including linear, sin, and sin+linear light curves of the secular type, as well as burst, drop, and irregular light curves of the stochastic type. The evolutionary stage, source name and corresponding fitting parameters are given above each figure. The W2 light curves for all identified variables were presented using the mean Modified Julian Date (MJD) and the mean magnitude of each epoch. It should be noted that the full data for these light curve plots can be found in Table A1 of the published article. <div> <div> </div> <div> </div> <div> <div> <div> <div> </div> </div> </div> </div> </div>

opencc-by-4.0Mar 2024View details →

Dataset : Boosting 1H and 13C NMR signals by orders of magnitude on a bench

<h1>Spectroscopic Data DNP 1T 77K</h1> 1H DNP Juice with TEMPOL at 50mM Sample : 6/2/2 DMSO-d6/H2O/D2O 200µL Topspin Folder : 20231102_HDNPjuice_50mM_CB Note : no phc1 in the data processing not to affect the integral as we have a broad signal <ul> <li>TE : 100 / 200 / 300</li> <ul> <li>substraction of the 100 TE and 1000 BG with Topspin —> exp 1</li> <li>For 200 w BG1000 —> exp 2 proc 999</li> <li>For 300 w BG1000 —> exp 3 proc 999</li> </ul> </ul> <ul> <li>DNP : 105 / 205 / 305</li> <ul> <li>MW 28,16 GHz ± 20 MHz @ 60 kHz</li> <li>E 105 (comp to 2) : 110</li> <li>E 205 (comp to 3) : 97</li> <li>E 305 (comp to 4) : 95</li> </ul> </ul> <ul> <li>T build up with satrec : 206</li> <ul> <li>28,18 GHz no fmod</li> </ul> </ul>   General model:      val(t) = a*(1-exp(-(t)/T)+d)      Coefficients (with 95% confidence bounds):        T =      0.5164  (0.4523, 0.5805)        a =      0.7312  (0.6996, 0.7628)        d =      0.3518  (0.3163, 0.3873) <ul> <li>T1 : 207</li> <ul> <li>satrec experiment at TE</li> <li>General model:</li> <li>     val(t) = a*(1-exp(-(t)/T)+d)</li> <li>    Coefficients (with 95% confidence bounds):</li> <li>       T =      0.5067  (0.4584, 0.555)</li> <li>        a =      0.7826  (0.7567, 0.8085)</li> <li>        d =      0.2713  (0.2458, 0.2967)</li> </ul> </ul>

Behavior and ERP data for "A logarithmic magnitude representation in working memory"

Behavior and ERP data for "The foundation of Fechner's law"

Empirical relation among earthquake magnitude (Mw) and deformed area as imaged by InSAR

This document presents a dataset of 96 earthquakes with available information on moment magnitude and the dimension of the deformed area, as imaged by InSAR.

opencc-by-4.0Nov 2024View details →

Ambisonics Binaural Rendering via Masked Magnitude Least Squares - Supplemental Material

Refer to the readme file for more information.

opencc-by-4.0Nov 2021View details →

Structural features and according references on the asperities of large earthquakes with the magnitude larger than 6.0

Reviews of Geophysics and Planetary Physics Supporting Information for Structure-controlled asperity on the generation of large earthquakes

opencc-by-4.0Dec 2021View details →

Supplemental data to Magnitude and Origin of CO2 evasion from high-latitude lakes

Supplemental dataset to the publication: Supplemental data to Seasonal Shifts in Magnitude and Source Contribution of CO2 evasion from High-latitude Lakes submitted to Journal of Geophysical Research: Biogeosciences

opencc-by-4.0May 2022View details →

Icequake-magnitude scaling relationship along a rift within the Ross Ice Shelf, Antarctica

This data set contains the icequake catalog used for Huang et al. (2022).

opennotspecifiedNov 2017View details →

Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925). in Muridae

Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925).

opencc-zeroApr 2024View details →

Data for: Projecting changes in the frequency and magnitude of ozone pollution events under uncertain climate sensitivity

Climate change is projected to worsen ozone pollution over many populated regions, with larger impacts at higher concentrations. More intense and frequent ozone episodes risk setbacks to human health and environmental policy achievements. However, assessing these changes is complicated by uncertain climate sensitivity, closely related to climate model response, and internal variability in simulations projecting climate's influence on air quality. Here, leveraging a global modeling framework that one-way couples a human activity model, an Earth system model of intermediate complexity, and an atmospheric chemistry model, we investigate the role of climate sensitivity in climate-induced changes to high ozone pollution episodes in the United States using multiple greenhouse gas emissions scenarios, representations of climate sensitivity, and initial condition members. We bias correct and evaluate historical model simulations, identifying modeled and observed O3 episodes using extreme value theory, and extend the approach to projections of mid- and end-century climate impacts. Results show that the influence of climate sensitivity can be as significant as that of greenhouse gas emissions scenario absent precursor emissions changes. Climate change is projected to increase the magnitude of the highest annually occurring O3 concentrations by over 2.3 ppb on average across the U.S. at mid-century under a high climate sensitivity and moderate emissions scenario, but the increase is limited to less than 0.3 ppb under lower climate sensitivity. Further, we show that areas in the U.S. currently meeting air quality standards risk being pushed into non-compliance due to a climate-induced increase in frequency of high ozone days.

Procedimiento para el pronóstico de la magnitud del desplazamiento y el tiempo de estabilización del Macizo Geológico - Archivos Complementarios

Hojas de Cálculo que implementan el Procedimiento para el pronóstico de la magnitud del desplazamiento y el tiempo de estabilización del Macizo Geológico.

opencc-by-4.0Jul 2018View details →

GRB 070306: Host magnitudes

Host magnitudes of GRB 070306 from Jaunsen et al. (2008), Ap.J. 681, p.453-461

opencc-by-4.0Sep 2024View details →

Data for "Technical reports: Methods - The Effects of Noise Magnitude and Measurement Resolution on Groundwater Tidal Analysis"

This data for the technical note submitted to Water Resources Research.

opencc-zeroDec 2016View details →

Data from: A century of changing flows: forest management changed flow magnitudes and warming advanced the timing of flow in a southwestern US river

The continued provision of water from rivers in the southwestern United States to downstream cities, natural communities and species is at risk due to higher temperatures and drought conditions in recent decades. Snowpack and snowfall levels have declined, snowmelt and peak spring flows are arriving earlier, and summer flows have declined. Concurrent to climate change and variation, a century of fire suppression has resulted in dramatic changes to forest conditions, and yet, few studies have focused on determining the degree to which changing forests have altered flows. In this study, we evaluated changes in flow, climate, and forest conditions in the Salt River in central Arizona from 1914–2012 to compare and evaluate the effects of changing forest conditions and temperatures on flows. After using linear regression models to remove the influence of precipitation and temperature, we estimated that annual flows declined by 8–29% from 1914–1963, coincident with a 2-fold increase in basal area, a 2-3-fold increase in canopy cover, and at least a 10-fold increase in forest density within ponderosa pine forests. Streamflow volumes declined by 37–56% in summer and fall months during this period. Declines in climate-adjusted flows reversed at mid-century when spring and annual flows increased by 10–31% from 1964–2012, perhaps due to more winter rainfall. Additionally, peak spring flows occurred about 12 days earlier in this period than in the previous period, coincident with winter and spring temperatures that increased by 1–2°C. While uncertainties remain, this study adds to the knowledge gained in other regions that forest change has had effects on flow that were on par with climate variability and, in the case of mid-century declines, well before the influence of anthropogenic warming. Current large-scale forest restoration projects hold some promise of recovering seasonal flows.

opencc-zeroDec 2016View details →

Data from: Non-breeding range size predicts the magnitude of population trends in trans-Saharan migratory passerine birds

Understanding why populations of some migratory species show a directional change over time, i.e. increase or decrease, while others do not, remains a challenge for ecological research. One possible explanation is that species with smaller non-breeding ranges may have more pronounced directional population trends, and their populations are thus more sensitive to the variation in environmental conditions in their non-breeding quarters. According to the serial residency hypothesis, this sensitivity should lead to higher magnitudes (i.e. absolute values) of population trends for species with smaller non-breeding ranges, with the direction of trend being either positive or negative depending on the nature of the environmental change. We tested this hypothesis using population trends over 2001–2012 for 36 sub-Saharan migratory passerine birds breeding in Europe. Namely, we related the magnitude of the species' population trends to the size of their sub-Saharan non-breeding grounds, whilst controlling for factors including number of migration routes, non-breeding habitat niche and wetness, breeding habitat type and life-history strategy. The magnitude of species' population trends grew with decreasing absolute size of sub-Saharan non-breeding ranges, and this result remained significant when non-breeding range size was expressed relative to the size of the breeding range. After repeating the analysis with the trend direction, the relationship with the non-breeding range size disappeared, indicating that both population decreases and increases are frequent amongst species with small non-breeding range sizes. Therefore, species with small non-breeding ranges are at a higher risk of population decline due to adverse factors such as habitat loss or climatic extremes, but their populations are also more likely to increase when suitable conditions appear. As non-breeding ranges may originate from stochasticity of non-breeding site selection in naive birds ('serial-residency' hypothesis), it is crucial to maintain a network of stable and resilient habitats over large areas of birds' non-breeding quarters.

opencc-zeroSep 2021View details →

Magnitude and timing of resource pulses interact to affect plant invasion

Human activities can cause resource fluctuations through reducing uptake by the resident vegetation (e.g., disturbance) or through changing external resource supply (e.g., fertilization). Resource fluctuations often occur as pulses which are low frequency, large magnitude and short duration, and now are recognized as an important driver of plant invasions. However, resource pulses often vary dramatically in a number of attributes, yet how these attributes mediate the impacts of resource pulses on plant invasions remains unclear. Erigeron canadensis is a serious invader of disturbed habitats and agricultural fields in China. Thus, it experiences nutrient pulses with different magnitudes and timings. Here, we grew E. canadensis and six co-occurring native plant species with three different magnitudes of nutrient enrichment (low, medium or high). For each magnitude, we added equivalent amounts of nutrients with a constant supply as a control or one of three pulses with different timings (early, middle or late stages). We found that pulse magnitude, timing and their interaction significantly affected E. canadensis growth (biomass production) and invasion (proportion of biomass in a pot). For each timing, E. candensis growth and invasion increased with nutrient magnitude. At low magnitude, middle and late pulses promoted E. canadensis growth and invasion. At medium magnitude, late pulses suppressed E. canadensis growth, but did not affect its invasion. At high magnitude, early and middle pulses strongly suppressed E. canadensis growth and invasion. In contrast, natives generally exhibited different responses to nutrient pulses. Our study shows that plant responses are not just dependent on the presence of a resource pulse but also on its attributes. In contrast to theory and many empirical studies, our results show that resource fluctuation does not always promote plant invasion. We highlight that the attributes of resource pulses are key to understanding the impact of resource fluctuations on plant invasion.

opencc-zeroSep 2021View details →

Magnitude and mechanisms of nitrogen-mediated responses of tree biomass production to elevated CO2: a global synthesis

1. Elevated atmospheric CO2 concentration (eCO2) typically stimulates tree growth, which is mediated by nitrogen (N) availability; but how N regulates tree biomass responses to eCO2 remains uncertain, which limits our prediction of forest carbon (C) cycling under future global change scenarios. 2. A meta-analysis of a global dataset including 3399 observations from 283 papers published from 1980s to February 2021 was conducted with the aim of elucidating N-mediated responses of tree biomass production to eCO2 and the underlying mechanisms. 3. We found that eCO2 stimulated tree biomass production (+32.0%), while it induced accumulation of nonstructural carbohydrates in leaves rather than in woods and roots, suggesting that the production may be C-limited but depend on the sink strength of organs. Biomass responses to eCO2 of N-fertilized trees (+39.6%) were 68.4% greater than those of non-fertilized trees (+25%), confirming that tree growth is also N-limited. Such N limitation was alleviated by the eCO2-induced increases in N uptake and N-use efficiency (NUE), with the former being more important. Increases in tree N pool arose from the enhanced production of fine roots with a lower specific root length, whereas increases in NUE resulted from the flexibility in tissue C:N ratios instead of N resorption efficiency. The positive responses of tree biomass production to eCO2 were greater for ectomycorrhizal trees and conifers than for arbuscular mycorrhizal trees and angiosperms, respectively. 4. Synthesis: Our findings suggest that eCO2 stimulates tree biomass production by increasing C availability, and alleviating N limitation in a feedback way via enhancing N uptake and NUE; and they improve our mechanistic understanding of responses of forest productivity and C sequestration to eCO2 under global change.