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2,135 results for “stabling”
A Stable Software Architecture Modularity Metric
<p>Anonymous Replication Package for A Stable Software Architecture Modularity Metric</p>
Fig. 1 in A Stable Isotope Investigation into the Feeding Behavior of Brychius Hungerfordi Spangler (Coleoptera: Haliplidae), a Federally Endangered Crawling Water Beetle
Fig. 1. Keeling Plots of carbon (a) and nitrogen (b) signals against the reciprocal of the mass. The y-intercept is the isotopic value of the source dominating the mixture of Cocconeis and Dichotomosiphon and agrees well with the observed isotopic signature of Dichotomosiphon.
Fig. 2 in A Stable Isotope Investigation into the Feeding Behavior of Brychius Hungerfordi Spangler (Coleoptera: Haliplidae), a Federally Endangered Crawling Water Beetle
Fig. 2. Dual Isotope Plot showing the relation between primary producers and Brychius larvae and adults (consumers have been corrected for trophic enrichment). Key: Larvae (L); Adult (A); Dichotomosiphon (1); Cocconeis (2); Cladophora (3); Spirogyra (4); Chara (5); error bars represent (SD).
Data and R-Scripts for the manuscript "Arctic tundra ecosystems under fire – potential trajectories for stable state shifts"
Open the record for dataset details and reuse information.
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable Diffusion
<p>In this work, we investigate the problem of Model-Agnostic Zero-Shot Classification (MA-ZSC), which refers to training non-specific classification architectures (downstream models) to classify real images without using any real images during training. Recent research has demonstrated that generating synthetic training images using diffusion models provides a potential solution to address MA-ZSC. However, the performance of this approach currently falls short of that achieved by large-scale vision-language models. One possible explanation is a potential significant domain gap between synthetic and real images. Our work offers a fresh perspective on the problem by providing initial insights that MA-ZSC performance can be improved by improving the diversity of images in the generated dataset. We propose a set of modifications to the text-to-image generation process using a pre-trained diffusion model to enhance diversity, which we refer to as our <strong>bag of tricks</strong>. Our approach shows notable improvements in various classification architectures, with results comparable to state-of-the-art models such as CLIP. To validate our approach, we conduct experiments on CIFAR10, CIFAR100, and EuroSAT, which is particularly difficult for zero-shot classification due to its satellite image domain. We evaluate our approach with five classification architectures, including ResNet and ViT. Our findings provide initial insights into the problem of MA-ZSC using diffusion models.</p>
Stable isotope dataset of different water components in a tyical permafrost-dominated Basin on the Qinghai–Tibet Plateau
<p>Different water bodies, including precipitation, thermokarst lakes/ponds, stream, natural springs, as well as ground ice were monitored in a permafrost-dominated Basin (the Beiluhe basin) on central Qinghai-Tibet Plateau (QTP). Six years’ continuous sampling work were conducted between 2017 and 2022 in this permafrost basin. Totally, 554 precipitation samples, 2402 lakes/ponds samples, 675 stream water samples, 102 supra-permafrost water samples, and 19 sub-permafrost water samples were collected during six years’ continuous sampling work. Importantly, 355 ground ice samples were collected from 17 boreholes and 4 samples were obtained from 2 thaw slump profiles. The stable isotopes (δ18О, δD, and d-excess) were obtained. This is the first comprehensive dataset in permafrost regions on the QTP, which will facilitate the understanding of hydrological processes under permafrost degradation in the Asian water Tower.</p>
Atmospheric water vapor stable isotopes at Lulang, southeastern Tibetan Plateau
<p>These data had been published in the following paper. If you use them, please cite this paper.</p> <p>M. Chen, J. Gao, L. Luo, A. Zhao, X. Niu, W. Yu, Y. Liu, G. Chen, Temporal variations of stable isotopic compositions in atmospheric water vapor on the Southeastern Tibetan Plateau and their controlling factors, Atmospheric Research, 2024, 107328, https://doi.org/10.1016/j.atmosres.2024.107328.</p>
Figure 3 in Trophic discrimination factors and stable isotope variability in a captive feeding trial of the southern rock lobster Jasus edwardsii (Hutton, 1875) (Decapoda: Palinuridae) in Tasmania, Australia
Figure 3. Isoplot showing the fit of different trophic discrimination factors (TDFs) to a wild population of Jasus edwardsii (■) and associated wild prey sources: Haliotis rubra (▲), Heliocidaris erythrogramma (■), and Lunella undulata (●), demonstrating that our experimentally derived TDFs provide the best fit. Black dots represent the isotope signatures of individual dorsal-muscle samples of lobsters. Mean and standard deviation values refer to the three source signatures with no TDF correction, with correction using multi-taxa TDFs from the literature (∆13C 0.4‰ and ∆15N 3.4‰ (Post, 2002)) and previously determined TDFs for J. edwardsii (∆13C 0.84‰ and ∆15N 3.28‰ (Suring & Wing, 2009)), with correction using our experimentally determined dorsal muscle TDFs (∆13C 4.45‰ and ∆15N 4.36‰), and correction with our experimentally determined leg muscle TDFs (∆13C 3.86‰ and ∆15N 5.05‰).
Figure 1 in Trophic discrimination factors and stable isotope variability in a captive feeding trial of the southern rock lobster Jasus edwardsii (Hutton, 1875) (Decapoda: Palinuridae) in Tasmania, Australia
Figure 1. Correlation plots showing the relationship between samples of captive Jasus edwardsii leg muscle and dorsal muscle (N = 34) for δ13C (A) and δ15N (B).
Figure 2 in Trophic discrimination factors and stable isotope variability in a captive feeding trial of the southern rock lobster Jasus edwardsii (Hutton, 1875) (Decapoda: Palinuridae) in Tasmania, Australia
Figure 2. Change in mean (± SE) isotopic signatures over time for captive Jasus edwardsii in three diet treatments: sea urchin (●), fish (▲), and mussel (■). Plots show change in δ13C (A) and change in δ15N (B). Solid lines represent lobster muscle tissue as represented by a leg-muscle icon, and dashed lines represent lobster exoskeleton as represented by a red-leg exoskeleton icon. Dotted lines represent the mean diet isotope + trophic discrimination factor (TDF) calculated as of 12 months. All mean values have a minimum sample size of five replicates except for the following samples: 4-month mussel (N = 4), 18-month fish (N = 4), and 18-month mussel (N = 3). For lethal samples (initial, 12, and 18 monts), exoskeleton samples are the mean of leg and dorsal samples where both were collected. Exoskeleton samples are only leg samples for non-lethal samples.
A Stable High-Potential Na7V4(P2O7)4(PO4) Cathode for Sodium-Ion Batteries Developed from a Water-Based Slurry
<p>These are the corresponding raw data related to the publication:</p> <p>A Stable High-Potential Na7V4(P2O7)4(PO4) Cathode for Sodium-Ion Batteries Developed from a Water-Based Slurry</p> <p> </p> <p>Ruihao Gong,<sup>+a</sup> Fabio Maroni,<sup>+a</sup> Mario Marinaro<sup>*a</sup></p> <p> </p> <p><sup>a</sup>Zentrum für Sonnenenergie- und Wasserstoff- Forschung, Baden-Württemberg (ZSW)</p> <p>Helmholtzstraße 8 - 89081 Ulm, Germany</p> <p> </p> <p><sup>+</sup>: The authors contribute equally to this study.</p> <p>*: Corresponding: <a href="mailto:mario.marinaro@zsw-bw.de">mario.marinaro@zsw-bw.de</a></p> <h3> </h3>
Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations: Data and Visualization Notebooks
<p>The data, jupyter notebooks, and saved model weights for the "Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations" Hu et al. (2025) arxiv preprint: <a href="https://arxiv.org/abs/2407.00124">arXiv:2407.00124</a>. This updated version contains more analysis notebooks together with related data/model.</p>
Recursive InPainting with Stable Difussion 2 Inpainting
<h1>Recursive inpainting with Stable Difussion</h1> <p>The dataset contains images extracted from <a href="https://huggingface.co/datasets/huggan/wikiart">WikiArt</a> that have been recursively versioned using inpainting techniques with a version of the Stable Diffusion model oriented towards instructional inpainting called <a href="https://huggingface.co/stabilityai/stable-diffusion-2-inpainting">stable-diffusion-2-inpainting</a>, used in the paper <a href="https://doi.org/10.48550/arXiv.2407.09549">How Stable is Stable Diffusion under Recursive InPainting (RIP)?</a> Presented at the GenAI Evaluation KDD2024: KDD workshop on Evaluation and Trustworthiness of Generative AI Models</p> <div> <div> </div> </div> <div> <p>The dataset contains two folders with two different experiments. Each experiment consists of performing recursive inpainting on 512x512 px images until reaching a percentage of pixels affected by the inpainting of 400% compared to the original image. Each experiment contains the following files:</p> <ul> <li><em>original_imgs_grid.png* </em>file with all the base images in an ordered grid or <em>dataset</em> folder with the original images.</li> <li><em>mask_64x64/[number_figure]_64x64.png*</em> with the inpainting version of [number_figure] and 64x64 mask</li> <li><em>mask_128x128/[number_figure]_128x128.png*</em> with the inpainting version of [number_figure] and 128x128 mask</li> <li><em>mask_256x256/[number_figure]_256x256.png* </em>with the inpainting version of [number_figure] and 256x256 mask</li> <li><em>lpips_distances.xlsx</em> with the results of applying the Learned Perceptual Image Path Similarity (LPIPS) metric in its variants SqueezeNet, AlexNet, and VGG. The metrics are calculated with respect to the original image and the previous image.</li> </ul> <p>* Only images that license allow to share</p> <p>There are three different experiments:</p> <ul> <li><em>lpips_distances_100_images_1_seed</em>: contains recursive inpaintings of 100 different images with a single seed. This allows the analysis of different images when performing recursive inpainting.</li> <li><em>lpips_distances_10_images_15_seeds</em>: contains recursive inpaintings of 10 different images with 15 different seeds. This allows the analysis of the differences in inpaintings when applying different seeds in the inpainting on the same image.</li> <li><em>lpisp_distances_styles:</em> contains recursive inpaintings of 80 images taken from seven pictorial styles and from sketches of an architect in subsets to 10 images. <ul> <li>Styles:</li> <li>Mods folder: contains the same inpaintings but for modifications of the base image: <ul> <li>Black_White</li> <li>Blue_Green: version with no red components.</li> <li>Red_Blue: version with no green components.</li> <li>Red_Green: version with no blue components.</li> </ul> </li> </ul> </li> </ul> <p>The folder <em>code</em> includes the a README.md with the instructions and the scripts to run the experiments<br><br>Cite our work in:</p> <pre><code>@misc{conde2024stablestablediffusionrecursive, title={How Stable is Stable Diffusion under Recursive InPainting (RIP)?}, author={Javier Conde and Miguel González and Gonzalo Martínez and Fernando Moral and Elena Merino-Gómez and Pedro Reviriego}, year={2024}, eprint={2407.09549}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2407.09549}, }</code></pre> </div>
Data for "Stable climate simulations using a realistic GCM with neural network parameterizations for atmospheric moist physics and radiation processes"
<p>This is sampling data of "Stable climate simulations using a realistic GCM with neural network parameterizations for atmospheric moist physics and radiation processes".</p> <p>'qv_nn_in' for the large scale specific humidity, [kg/kg]<br> 'T_nn_in' for the large scale temperature, [K]<br> 'dqvls_nn_in' for the large scale moisture advection, [kg/kg/s]<br> 'dTls_nn_in' for the large scale moisture advection, [K/s]<br> 'qtend_check' for the moistening rate by CRM, [kg/kg/s]<br> 'stend_check' for the heating rate by CRM, [K/s]<br> 'SOLS' for direct shorwave solar radiation down to surface, [W/m2]<br> 'SOLSD' for diffusive shortwave solar radiation down to surface, [W/m2]<br> 'SOLL' for direct near infrared solar radiation down to surface, [W/m2]<br> 'SOLLD' for diffusive near infrared solar radiation down to surface, [W/m2]<br> 'SOLIN' for insolation at model top, [W/m2]<br> 'FSNS' for net shortwave radiation at model surface, [W/m2]<br> 'FSNT' for net shortwave radiation at model top, [W/m2]<br> 'FLNS' for net longwave radiation at model surface, [W/m2]<br> 'FLNT' for net longwave radiation at model top, [W/m2]<br> 'SPPS' for surface pressure, [Pa]</p> <p>To download the full dataset of the SPCAM simulation in 1998. Please click the dropbox link: https://www.dropbox.com/s/p841v1tw00rokdy/SPCAM_VAR_1998.tar.gz?dl=0</p>
Data from: Calcium and strontium stable isotopes reveal similar behaviors of essential Ca and non-essential Sr in stream food webs
<p>Recent studies showed the potential of stable isotopes of the macronutrient calcium (δ<sup>44/40</sup>Ca) and non-essential strontium (δ<sup>88/86</sup>Sr) as new trophic level indicators in terrestrial vertebrates and marine teleost fishes. In this study, we tested whether similar Ca and Sr isotopic fractionation trends existed in macroinvertebrate dominated stream food webs compared to vertebrates despite their physiological differences. We have determined the δ<sup>44/40</sup>Ca and δ<sup>88/86</sup>Sr values as well as the <sup>87</sup>Sr/<sup>86</sup>Sr ratios of stream macroinvertebrates and of small gobies and of their potential metal sources (stream water, periphyton, terrestrial plant litter) collected in May and November 2018 in upper and lower reaches of two streams in the Lake Biwa catchment, central Japan.</p> <p>The data are organized in different spreadsheets for each sample type (Rock cobbles, Stream water, Periphyton, Plant litter, Aquatic macroinvertebrates, fishes). Each spreadsheet contains information of the sample type including stream name (Ado, Yasu), stream location (Upper, Lower), sampling month (May, November), where relevant the order and scientifc name of specimens, the δ<sup>44/40</sup>Ca and δ<sup>88/86</sup>Sr values with two standard deviations, the <sup>87</sup>Sr/<sup>86</sup>Sr ratios with two standard errors, the Ca and Sr concentrations and the calculated log(Sr/Ca) ratios of the samples.</p>
Individual dietary specialization in a generalist predator: A stable isotope analysis of urban and rural red foxes
<p>Some carnivores are known to survive well in urban habitats, yet the underlying behavioural tactics are poorly understood. One likely explanation for the success in urban habitats might be that carnivores are generalist consumers. However, urban populations of carnivores could as well consist of specialist feeders. Here, we compared the isotopic specialization of red foxes in urban and rural environments, using both a population and an individual level perspective. We measured stable isotope ratios in increments of red fox whiskers and potential food sources. Our results reveal that red foxes have a broad isotopic dietary niche and a large variation in resource use. Despite this large variation, we found significant differences between the variance of the urban and rural population for δ<sup>13</sup>C as well as δ<sup>15</sup>N values, suggesting a habitat-specific foraging behaviour. Although urban regions are more heterogeneous regarding land cover (based on the Shannon index) than rural regions, the dietary range of urban foxes was smaller compared to that of rural conspecifics. Moreover, the higher δ<sup>13</sup>C values and lower δ<sup>15</sup>N values of urban foxes suggest a relatively high input of anthropogenic food sources. The diet of most individuals remained largely constant over a longer period. The low intra-individual variability of urban and rural red foxes suggests a relatively constant proportion of food items consumed by individuals. Urban and rural foxes utilized a small proportion of the potentially available isotopic dietary niche as indicated by the low within-individual variation compared to the between-individual variation. We conclude that generalist fox populations consist of individual food specialists in urban and rural populations<b> </b>at least over those periods covered by our study.</p>
STable 1. Planted area, harvested area, production, and crop productivity in District of Samudera, North Aceh, Indonesia.
<p>The data is presented in a table (STable 1. Planted area, harvested area, production, and crop productivity in District of Samudera, North Aceh, Indonesia.) as supplement of a manuscript in mdpi <em>Agronomy | Special Issue “Smallholder Agriculture: Where We Are and Pathways towards the Future” </em>journal.</p>
How to trigger and keep stable directional Space–Number Associations (SNAs)
<p>Humans are prone to mentally organise the ascending series of integers according to reading habits so that in western cultures small numbers are positioned to the left of larger ones on a mental number line. Despite 140 years since seminal observations by Sir Francis Galton (Galton, 1880a, b), the functional mechanisms that give rise to directional Space–Number Associations (SNAs) remain elusive. Here, we contrasted three different experimental conditions, each including a different version of a Go/No-Go task with intermixed numerical and arrow-targets (Shaki and Fischer, 2018; Pinto et al., 2019a). We show that directional SNAs are not “all or none” phenomena. We demonstrate that SNAs get progressively less noisy and more stable the more contrasting small/large magnitude-codes and contrasting left/right spatial-codes are explicitly and fully combined in the task set. The analyses of the time–course of space-number congruency effects showed that both the absence and presence of the SNA were independent of the speed of reaction times. In agreement with our original proposal (Aiello et al., 2012), these findings show that conceptualising the ascending series of integers in spatial terms depends on the use of spatial codes in the numerical task at hand rather than on the presence of an inherent spatial dimension in the semantic representation of numbers. This evidence suggests that directional SNAs, like the SNARC effect, are secondary to the primary transfer of spatial response codes to number stimuli, rather than deriving from a primary congruency or incongruence between independent spatial-response and spatial-number codes. </p>
Data from: Effective specialist or jack of all trades? Experimental evolution of a crop pest in fluctuating and stable environments
<p>Understanding pest evolution in agricultural systems is crucial for developing effective and innovative pest control strategies. Types of cultivation, such as crop monocultures versus polycultures or crop rotation, may act as a selective pressure on pests' capability to exploit the host's resources. In this study, we examined the herbivorous mite <em>Aceria tosichella</em> (commonly known as wheat curl mite), a widespread wheat pest, to understand how fluctuating versus stable environments influence its niche breadth and ability to utilize different host plant species. We subjected a wheat-bred mite population to replicated experimental evolution in a single-host environment (either wheat or barley), or in an alternation between these two plant species every three mite generations. Next, we tested the fitness of these evolving populations on wheat, barley, and on two other plant species not encountered during experimental evolution, namely rye and smooth brome. Our results revealed that the niche breadth of <em>A. tosichella</em> evolved in response to the level of environmental variability. The fluctuating environment expanded the niche breadth by increasing the mite's ability to utilize different plant species, including novel ones. Such an environment may thus promote flexible host-use generalist phenotypes. However, the niche expansion resulted in some costs expressed as reduced performances on both wheat and barley as compared to specialists. Stable host environments led to specialized phenotypes. The population that evolved in a constant environment consisting of barley increased its fitness on barley without the cost of utilizing wheat. However, the population evolving on wheat did not significantly increase its fitness on wheat, but decreased its performance on barley. Altogether, our results indicated that, depending on the degree of environmental heterogeneity, agricultural systems create different conditions that influence pests' niche breadth evolution, which may in turn affect the ability of pests to persist in such systems.</p>
Supporting molecular simulations data for "Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells"
<p>Supplementary data for "Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells"</p>
ScienceDex guides
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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.