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.
81
datasets available to search
ShareScore release 0.9.0
Dataset results
81 results for “response surface”
Data from: Optimisation design and analysis of mobile pump truck frame using response surface methodology
<p><span>In order to realize the lightweight design of mobile pump truck, this paper takes the frame of a certain type of mobile pump truck as the research object. The response surface method is used to carry out lightweight design of the longitudinal beam structure of the frame, and the finite element method is used to establish the finite element model to analyze and compare the frame before and after optimization.The results show that the height, width and thickness of the optimized longitudinal beam section are reduced by 10 mm, 11 mm, and 0.8 mm respectively, and the weight of the whole frame is reduced by 35.8 kg.</span> <span>Before and after optimization, the displacement and stress changes of the frame are small in four motion situations, which meet the lightweight requirements of optimization design.</span></p>
Data for 'Surface heat fluxes drive a two-phase response in Southern Ocean mode water stratification'
<p>The files contained here are the output/sensitivity files of four adjoint sensitivity experiments in ECCOv4r2 that are combined to create the sensitivity of large-scale stratification to surface heat flux. (-f/Delta z) * (-alpha * (ADJqnet_t1 - ADJqnet_t2) + beta * (ADJqnet_s1 - ADJqnet_s2)) (Equation 7 in paper, where C = net heat flux). The files contained here are the output/sensitivity files for 6 years at 14 day time steps.</p> <p>ADJqnet_t1: (d J_1(theta_u)/ d qnet), Sensitivity of potential temperature over the upper depths to net heat flux.</p> <p>ADJqnet_t2: (d J_2(theta_l)/ d qnet), Sensitivity of potential temperature over the lower depths to net heat flux.</p> <p>ADJqnet_s1: (d J_3(salt_u)/ d qnet), Sensitivity of salinity over the upper depths to net heat flux.</p> <p>ADJqnet_s2: (d J_4(salt_l)/ d qnet), Sensitivity of salinity over the lower depths to net heat flux.</p> <p> </p> <p>Paper Abstract: Subantarctic mode waters (SAMW) have low stratification and are formed through subduction from thick winter mixed layers in the Southern Ocean. To investigate how external forcing affects the stratification in mode water formation regions in the Southern Ocean, we conduct a set of adjoint sensitivity experiments. The objective function is the annual-average stratification over the mode water formation region, which is evaluated from potential temperature and salinity adjoint sensitivity experiments. The analysis of impacts, from the product of sensitivities and forcing variability, identifies the separate effects of the wind stress, heat flux, and freshwater flux, revealing that the dominant control on stratification is from surface heat fluxes, as well as a smaller effect from zonal wind stress. The adjoint sensitivities of stratification to surface heat flux reveal a surprising change in sign over 2 years lead time. Surface cooling leads to the expected initial local decrease in stratification. However, there is a delayed response to surface cooling leading to an increase in stratification. This delayed response in stratification involves atmospheric damping of the surface thermal contribution, so that eventually the oppositely-signed advective haline contribution dominates. This two-phase response of stratification is found to hold over mode water formation regions in the South Indian and Southeast Pacific sectors of the Southern Ocean, where there are strong advective flows linked to the Antarctic Circumpolar Current.</p>
Data supporting 'The Response of Midlatitude Surface Temperature Persistence to Arctic Sea-Ice Loss' by Neil T Lewis, William J M Seviour, Hannah E Roberts-Straw, and James A Screen.
<p>Data supporting Lewis et al., 2023. The Response of Midlatitude Surface Temperature Persistence to Arctic Sea-Ice Loss. Submitted to Geophysical Research Letters.</p><p>All model output is contained within the folder data/. All data is in NetCDF format.</p><p>The folder data/PAMIP/ contains output from coupled AOGCMs that contributed piArcSIC and futArcSIC timeslice runs to PAMIP. The AOGCMS present are: HadGEM3-GC31-MM, IPSL-CM6A-LR, CESM2-WACCM6, and CESM-WACCM-SC. For each model + run, two data files are included. One contains the autocorrelation of surface temperature, at 5, 10, and 15 day lags. The second contains the frequency and duration of persistent extremes (as defined in Lewis et al., 2023).</p><p>Additional output is included in data/PAMIP/ from extended pdSIC-ext and futArcSIC-ext experiments run using CNRM-CM6-1. For each run, a file containing the autocorrelation of surface temperature (as above) is included.</p><p>The folder data/CMIP/ contains output from CMIP6 historical/SSP585 runs using three of the models listed above: HadGEM3-GC31-MM, IPSL-CM6A-LR, and CESM2-WACCM6. For each model, 'pre-industrial' and 'future' output is available. Output in these files was computed from 30-year time-periods, subsampled from the historical/SSP585 runs, selected so that the 30-year average sea-ice area matched that in the corresponding PAMIP runs above. For each model and time period, two data files are included. One contains the autocorrelation of surface temperature, at 5, 10, and 15 day lags. The second contains the frequency and duration of persistent extremes (as defined in Lewis et al., 2023).</p><p>Output is also included in data/CMIP/ from CNRM-CM6-1 'present day' and 'future' time periods, selected to match the sea-ice area in the CNRM -ext PAMIP runs. For this model, output files contain the autocorrelation of surface temperaure. </p>
Model output of: Excitation of an MJO event in response to a transient sea surface warming in Super-Parameterized CAM
Open the record for dataset details and reuse information.
Data from: Optimisation design and analysis of mobile pump truck frame using response surface methodology
Open the record for dataset details and reuse information.
Data from: Insensitivity of the cloud response to surface warming under radical changes to boundary layer turbulence and cloud microphysics: results from the ultraparameterized CAM
Open the record for dataset details and reuse information.
Data from: Above and belowground responses of four tundra plant functional types to deep soil heating and surface soil fertilization
1.Climate warming is faster in the Arctic than the global average. Nutrient availability in the tundra soil is expected to increase by climate warming through 1) accelerated nutrient mobilization in the surface soil layers, and 2) increased thawing depths during the growing season which increases accessibility of nutrients in the deeper soil layers. Both processes may initiate shifts in tundra vegetation composition. It is important to understand the effects of these two processes on tundra plant functional types. 2.We manipulated soil thawing depth and nutrient availability at a Northeast-Siberian tundra site to investigate their effects on above and belowground responses of four plant functional types (grasses, sedges, deciduous shrubs and evergreen shrubs). Seasonal thawing was accelerated with heating cables at ~15 cm depth without warming the surface soil, whereas nutrient availability was increased in the surface soil by adding slow-release NPK fertilizer at ~5 cm depth. A combination of these two treatments was also included. This is the first field experiment specifically investigating the effects of accelerated thawing in tundra ecosystems. 3.Deep soil heating increased the aboveground biomass of sedges, the deepest-rooted plant functional type in our study, but did not affect biomass of the other plant functional types. In contrast, fertilization increased aboveground biomass of the two dwarf shrub functional types, which both had very shallow root systems. Grasses showed the strongest response to fertilization, both above and belowground. Grasses were deep-rooted, and they showed the highest plasticity in terms of vertical root distribution, as grass root distribution shifted to deep and surface soil in response to deep soil heating and surface soil fertilization, respectively. 4.Synthesis - Our results indicate that increased thawing depth can only benefit deep-rooted sedges, while the shallow-rooted dwarf shrubs as well as flexible-rooted grasses take advantage of increased nutrient availability in the upper soil layers. Our results suggest that grasses have the highest root plasticity, which enables them to be more competitive in rapidly changing environments. We conclude that root vertical distribution strategies are important for vegetation responses to climate-induced increases in soil nutrient availability in Arctic tundra, and that future shifts in vegetation composition will depend on the balance between changes in thawing depth and nutrient availability in the surface soil.
Responses of Surface Evaporative Fluxes in Montane Cloud Forests to the Climate Change Scenario
<p>CL_surfobs_raw.mat and LHC_nodew_new_raw.mat are the analyzed CLM simulation output with atmospheric observations in Chi-Lan and Lien-Hua-Chih as input forcings.</p> <p>CLatm_LHC_prec*.mat are the analyzed CLM simulation output in sensitivity tests for the rainfall pattern.</p> <p>CL_*_transform_raw.mat are the analyzed CLM simulation output in CTL simulation and climate change sensitivity tests. </p> <p>Fig_*.m are matlab code files to reproduce figures in the article.</p> <p>Fig_11_ttest.m and Fig_11_LE_p_value.mat are the t-test for the decrease of latent heat flux in the diurnal cycle under climate change scenario and the resulting p-value.</p> <p>Fig_quantile.m and Fig_4_6_7_8_9_10_11_quantile.mat are to obtain first and third quantile of the changes of canopy water and surface heat fluxes in the diurnal cycle under climate change scenarios.</p>
Influence of Inner Surface Roughness on the SIP Response - a Numerical Study
<p>Supporting data for publication</p> <p>This repository contains Matlab scripts, Comsol Multiphysics models, and numerical simulation data used to generate the plots in the manuscript. Comsol models are those with the <em>.mph</em> extension and were created with Comsol Multiphysics v 5.5. All numerical data used in the manuscript is available without running the Comsol simulation.</p>
Changes in body surface temperature play an under-appreciated role in the avian immune response
<p>Fever and hypothermia are well characterized components of systemic inflammation. However, our knowledge of the mechanisms underlying such changes in body temperature is largely limited to rodent models and other mammalian species. In mammals, high dosages of an inflammatory agent (e.g., lipopolysaccharide, LPS) typically leads to hypothermia (decrease in body temperature below normothermic levels), which is largely driven by a reduction in thermogenesis, and not changes in peripheral vasomotion (i.e., changes in blood vessel tone). In birds, however, hypothermia occurs frequently, even at lower dosages, but the thermoeffector mechanisms associated with the response remain unknown. We immune-challenged zebra finches (<i>Taeniopygia guttata</i>) with LPS and monitored changes in subcutaneous temperature and energy balance (i.e., body mass, food intake), and assessed surface temperatures of, and heat loss across, the eye region, bill, and legs. We hypothesized that if birds employ similar thermoregulatory mechanisms to similarly-sized mammals, LPS-injected individuals would reduce subcutaneous body temperature and maintain constant surface temperatures when compared with saline-injected individuals. Instead, LPS-injected individuals showed a slight elevation in body temperature, and this response coincided with a reduction in peripheral heat loss, particularly across the legs, as opposed to changes in energy balance. However, we note that our interpretations should be taken with caution due to small sample sizes within each treatment. We suggest that peripheral vasomotion, allowing for heat retention, is an underappreciated component of the sickness-induced thermoregulatory response of small birds.</p>
Assessing the atmospheric response to subgrid surface heterogeneity in CESM2 - code, output, and analysis script
<p>This dataset contains the raw model output, analysis scripts, and CESM source code (containing modifications to include subgrid-scale surface heterogeneity impacts in CAM) that were used to produce the figures in a manuscript targeting the Journal of Advances in Modeling Earth Systems (JAMES) for submission, "Assessing the atmospheric response to subgrid surface heterogeneity in CESM2". For additional information on CESM2 and the most up to date source code, see https://github.com/ESCOMP/CESM. </p> <p>The pre-print of the submitted article is available here: <a href="https://doi.org/10.1002/essoar.10512837.1">https://doi.org/10.1002/essoar.10512837.1</a></p>
Metabolic phenotype mediates the outcome of competitive interactions in a response-surface field experiment
<p>Competition and metabolism should be linked. Intraspecific variation in metabolic rates and, hence, resource demands covary with competitive ability. The effects of metabolism on conspecific interactions, however, have mostly been studied under laboratory conditions.<b> </b>We used a trait-specific response-surface design to test for the effects of metabolism on pairwise interactions of the marine colonial invertebrate, <i>Bugula neritina</i> in the field. Specifically, we compared the performance (survival, growth, and reproduction) of focal individuals, both in the presence and absence of a neighbour colony, both of which had their metabolic phenotype characterised.<b> </b>Survival of focal colonies depended on the metabolic phenotype of the neighbouring individual, and on the combination of both the focal and neighbour colony metabolic phenotypes that were present. Surprisingly, we found pervasive effects of neighbour metabolic phenotypes on focal colony growth and reproduction, though the sign and strength of these effects showed strong microenvironmental variability.<b> </b>Overall, we find that the metabolic phenotype changes the strength of competitive interactions, but these effects are highly contingent on local conditions. We suggest future studies explore how variation in metabolic rate affects organisms beyond the focal organism alone, particularly under field conditions.</p>
Modeling and Application of Triple Drug Response Surface Models
ClinicalTrials.gov study NCT03813875. IPD Sharing: NO. Countries: 1. Publications: 7.
A Clinical Study to Determine What Effect the EyeCool Treatment Has on the Eye's Surface Anatomy and Inflammation Response After Being Treated for Having Chronic Ocular Surface Pain (COSP)
ClinicalTrials.gov study NCT07059754. IPD Sharing: NO. Countries: 1. Publications: 1.
The Application and Validation of Triple Drug Response Surface Models on Density Spectral Array in Clinical Anesthesia
ClinicalTrials.gov study NCT05525351. IPD Sharing: NO. Countries: 1. Publications: 8.
Predicting Response to CRT Using Body Surface ECG Mapping
ClinicalTrials.gov study NCT01831518. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Changes in body surface temperature play an under-appreciated role in the avian immune response
Open the record for dataset details and reuse information.
Data from: Above and belowground responses of four tundra plant functional types to deep soil heating and surface soil fertilization
Open the record for dataset details and reuse information.
Metabolic phenotype mediates the outcome of competitive interactions in a response-surface field experiment
Open the record for dataset details and reuse information.
Figure 1 from: Nair P, Huertas M, Nowlin WH (2020) Metabolic responses to long-term food deprivation in subterranean and surface amphipods. Subterranean Biology 33: 1-15. https://doi.org/10.3897/subtbiol.33.48483
Figure 1 Oxygen consumption in darkness for Stygobromus pecki and Synurella at 23 °C. Values are means ± Standard Error Means (SEM) for n = 5 animals.
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.