SAVI is a comprehensive database of social indicators from the Indianapolis Metropolitan Statistical Area that human service agencies and community organizations use for planning, research, and evaluation. SAVI draws information from a wide variety;of sources, including census, criminal justice, health, vital statistics, education, welfare, social service agencies, service delivery catchment areas, churches, libraries, and other community facilities.

This dataset was published as part of SAVI Space—combinatorial encoding of the billion-size synthetically accessible virtual inventory (Korn, M., Judson, P., Klein, R. et al.,Sci Data (12) 1064, 2025) and holds the combinatorial chemical fragment space of the Synthetically Accessible Virtual Inventory (SAVI) Database.
The combinatorial fragment space is optimized for fast fingerprint similarity search with SpaceLight (Bellmann et al. J. Chem. Inf. 460 Model. 61 2020), and for fast maximum-common-substructure search with SpaceMACS (Schmidt et al., J. Chem. Inf. Model. 62 (9) 2133–2150, 2022), available at https://software.zbh.uni-hamburg.de.

Besides the chemical fragment space mimic the SAVI-Lib-2020 (SAVI-Space-2020-Librules) there is a updated version based on adapted rules called SAVI-Space-2020, and the Enamine Building Blocks (June 2024) called SAVI-Space-2024.
Additional, the preprocessed building blocks of the SAVI-Space-2020-Librules and SAVI-Space-2020 are available.

The SAVI-Space-2020(SAVI-Lib-Rules) is available as Database file (SAVI-Space-2020-Librules.tfsdb) and can be opened with SpaceLight Version 1.2.3 available at https://software.zbh.uni-hamburg.de.

The SAVI-Space-2020 and SAVI-Space-2024 are available as space files (SAVI-Space-{2020,2024}.space) and can be opened with the SpaceLightN Version 1.3.0 and SpaceMACS Version 1.1.0 also available at https://software.zbh.uni-hamburg.de.

Note: SpaceLight and SpaceLightN refer to different versions of the tool.

ℹ Info: This version of SAVI-Space isn’t fully optimized for SpaceMACS and needs more RAM than usual. Please allocate at least 64 GB for a successful run.

SAVI (Soil Adjusted Vegetation Index) map produced for the Central Arizona-Phoenix area from a 1993 Enhanced Landsat Thematic Mapper image.

Herbarium of Gaetano and Pietro Savi, some single sheets and two volume of bounded sheets.

No description is available. Visit https://dataone.org/datasets/79fb43b0b7ae8a8a9dc0e58ad4a7c42e for complete metadata about this dataset.

Soil Adjusted Vegetation Index (SAVI) produced from the 2005 Landsat Thematic Mapper(ETM) image. SAVI is a means of monitoring density and vigour of green vegetation growth using the spectral reflectivity of solar radiation. It is computed as follows:( (NIR-RED) / (NIR+RED+L))*(1+L), where NIR (Near Infra-Red) is the TM band 4 (0.76-0.9 micrometers), RED is band 3 (0.78-0.82 micrometers), and L is the correction factor whose values range from 0 (high vegetation cover) to 1 (low vegetation). L=0.5 was used. The index has been designed to correct for high soil reflectance in arid regions.

This dataset provides information about the number of properties, residents, and average property values for Savi Avenue cross streets in Waterford, CT.

Method: Boiled KOH (5mn), cold HCl 10%, decantation, sieving, liquid 2.22 density, acetolysis. The EPD (http://www.europeanpollendatabase.net) accepted species name is given in the parameter comment. This dataset was archived on 2010-05-11 from the EPD database.

This project calculates the Soil-adjusted Vegetation Index (SAVI) from 2010 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as multiple individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_SAVI_CAP2010-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf and kml index maps). Javascript code used to process SAVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.

Julkisen hallinnon sähköisen asioinnin viitearkkitehtuuri v. 1.0 (26.02.2013)

No description is available. Visit https://dataone.org/datasets/0ce67231ab3a1cdf75e492f5af95469d for complete metadata about this dataset.

The significance of STING (encoded by the TMEM173 gene), in tissue inflammation and cancer immunotherapy has been increasingly recognized. Intriguingly, common human STING alleles R71H-G230A-R293Q (HAQ) and G230A-R293Q (AQ) are carried by ∼60% of East Asians and ∼40% of Africans, respectively. Here, we examine the modulatory effects of HAQ, AQ alleles on STING-associated vasculopathy with onset in infancy (SAVI), an autosomal dominant, fatal inflammatory disease caused by gain-of function human STING mutations. CD4 T cellpenia is evident in SAVI patients and mouse models. Using STING knock-in mice expressing common human STING alleles HAQ, AQ, and Q293, we found that HAQ, AQ, and Q293 splenocytes resist STING-mediated cell death ex vivo, establishing a critical role of STING residue 293 in cell death. The HAQ/SAVI(N153S) and AQ/SAVI(N153S) mice did not have CD4 T cellpenia. The HAQ/SAVI(N153S), AQ/SAVI(N153S) mice have more (∼10-fold, ∼20-fold, respectively) T-regs than WT/SAVI(N153S) m..., Please see the "Method" section of the manuscript., , # Data from: The common TMEM173 HAQ, AQ alleles rescue CD4 T cellpenia, restore T-regs, and prevent SAVI (N153S) inflammatory disease in mice

https://doi.org/10.5061/dryad.m0cfxppcv

Description of the data and file structure

Figure 1. Splenocytes from HAQ, AQ, and Q293 mice are resistant to STING-mediated cell death ex vivo. (A). C57BL/6N splenocytes were treated directly (no transfection) with diABZI (100ng/ml), RpRpss-Cyclic di-AMP (5 μg/ml) or 2′3′-cGAMP (10μg/ml), DMXAA (25μg/ml) for 24hrs in culture. CD4, CD8 T cells and CD19 B cells death were determined by PI staining. (B). Splenocytes from C57BL/6N mice were pre-treated with indicated small molecules, GSK2334470 (1.25µM), GSK8612 (2.5µM), Bx-795 (0.5µM), QVD-OPH (25µM) for 2hrs. diABZI (100ng/ml) was added in culture for another 24hrs. Dead cells were determined by PI staining. (C-D). Flowcytometry of HAQ, AQ, IFNAR1-/- or C57BL/6N splenocytes treated with d...

Overview

Zip file contains two netCDF files with a subset of data from the "No Change 2" (NC2) experiment conducted by Savi et al., 2020 and published in Earth Surface Dynamics (https://doi.org/10.5194/esurf-8-303-2020) with the original data available via the Sediment Experimentalists Network Project Space SEAD Internal Repository (https://doi.org/10.26009/s0ZOQ0S6). Topographic scan data were re-formatted into the netCDF file "T_NC2_scans.nc", and overhead imagery was extracted from the video of the experiment approximately once every minute of experimental time and RGB band data is provided in the formatted netCDF file "T_NC2_images.nc". These data were formatted into netCDF files for easy loading into the "deltametrics" analysis toolbox.

Additional Details

Re-packaging the scan data from the .tif files was straightforward. From the metadata spreadsheet, we know the times at which the scans were taken (and can eliminate the redundant scan). From the paper itself we know the resolution of the topographic scans is 1 mm in the horizontal and vertical. We also know the input discharges, both water and sediment, through both the main channel and tributary, from the paper. We provide these values as metadata in the netCDF files. The scans form the 'eta' field representing the topography in the file. The packaged up netCDF file is called 'T_NC2_scans.nc'.

Overhead imagery from the T_NC2_Complete21fps.wmv video file was extracted using the following command:

ffmpeg -i T_NC2_Complete21fps.wmv -r 21 T_NC2_frames/%04d.png

This command utilizes the ffmpeg tool to extract the frames at a rate of 21 frames per second (-r 21) as the file name implies that is the rate at which the overhead photos were combined into a video. The NC designation indicates that this experiment was performed with no change in the input conditions in either the main or tributary channels.

The experiment ran for a total of 480 minutes. A total of 1466 images were obtained from the ffmpeg extraction. This translates to an image approximately every 20 seconds of real time (480 minutes / 1466 frames * 60 seconds/minute = 19.6453 seconds / frame). We sample every 3rd frame, which gives us images roughly once a minute (489 frames in all), to create the subset of data re-packaged as a netCDF file for deltametrics. Dimensions for the pixels were approximated based on our knowledge of the topographic scan resolution. Assuming the extents of the scans and overhead images are the same (although they are not), we calculate the number of millimeters per pixel in the x and y directions for the overhead images. We assume the pixels are more likely to be square than rectangular, so we average these values and assign this as the distance per pixel in both the x and y dimensions for these data.

References

Savi, Sara, et al. "Interactions between main channels and tributary alluvial fans: channel adjustments and sediment-signal propagation." Earth Surface Dynamics 8.2 (2020): 303-322.

Physical experiments on interactions between main-channels and tributary alluvial fans
S. Savi, Tofelde, A. Wickert, A. Bufe, T. Schildgen, and M. Strecker
https://doi.org/10.26009/s0ZOQ0S6

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Cave. The data include parameters of speleothems with a geographic location of Slovenia, Southern Europe. The time period coverage is from 15287 to 9260 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

savi-cyber/Project3 dataset hosted on Hugging Face and contributed by the HF Datasets community

STING-associated vasculopathy of infantile-onset (SAVI) is one of the newly identified types of interferonopathies. SAVI is caused by heterozygous gain-of-function mutations in the STING1. We herein report for the first time a homozygous variant in the STING1 gene in two siblings that resulted in constitutive activation of STING gene and the SAVI phenotype. Exome sequencing revealed a novel homozygous NM_198282.3: c.841C>T; p.(Arg281Trp) variant in exon 7 of the STING1 gene. The variant segregated in the family to be homozygous in all affected and either heterozygous or wild type in all healthy. Computational structural analysis of the mutants revealed changes in the STING protein structure/function. Elevated serum beta-interferon levels were observed in the patients compared to the control family members. Treatment with Janus kinase inhibitor (JAK-I) Ruxolitinib suppressed the inflammatory process, decreased beta-interferon levels, and stopped the progression of the disease.

STING-associated vasculopathy with onset in infancy (SAVI) is an autosomal dominant disorder due to gain-of-function mutations in STING1, also known as TMEM173, encoding for STING. It was reported as a vasculopathy of infancy. However, since its description a wider spectrum of associated manifestations and disease-onset has been observed. We report a kindred with a heterozygous STING mutation (p.V155M) in which the 19-year-old proband suffered from isolated adult-onset ANCA-associated vasculitis. His father suffered from childhood-onset pulmonary fibrosis and renal failure attributed to ANCA-associated vasculitis, and died at the age of 30 years due to respiratory failure. In addition, an overview of the phenotypic spectrum of SAVI is provided highlighting (a) a high phenotypic variability with in some cases isolated manifestations, (b) the potential of adult-onset disease, and (c) a novel manifestation with ANCA-associated vasculitis.

savi-cyber/insurance-charge-mlops-logs dataset hosted on Hugging Face and contributed by the HF Datasets community

test description1

ABSTRACT Soil moisture (SM) plays an important role in regulating the global water cycle, especially in arid areas, and is one of the main indicators of ecological environmental health. Although traditional methods can accurately measure SM at a single sample site, they are limited in large-scale and dynamic SM monitoring. Therefore, we used the Landsat images as the data source and the soil adjusted vegetation index (SAVI) to build the adjusted SAVI (aSAVI) index by modifying the soil adjustment parameter L and introducing the short-wave infrared band. According to the theory of temperature vegetation dryness index (TVDI) and feature space, we introduced a model, combined the measured SM data (Minqin Basin, China) through a comparative analysis of four vegetation indices (NDVI, SAVI, MSAVI, aSAVI) determine the optimal model. Taking the Minqin Basin as the study area, the spatiotemporal variation characteristics of SM in three sub-regions (the entire study area, irrigated region, and periphery of the irrigated regions) were quantitatively analyzed and compared in four different periods: pre-Comprehensive Treatment Program of the Shiyang River Basin (pre-CTSRB) (2000–2005), CTSRB I (2006–2010), CTSRB II (2011–2016), and CTSRB-end (2017–2021) to evaluate the ecological restoration effects of treatment programs from the SM perspective. The results showed that: 1) SM values derived from TVDI inversion and the aSAVI were more accurate, and the model sensitivity decreased with soil depth; 2) the mean value of SM fluctuated across the four periods but decreased slightly over the entire time series. The spatial variations of the SM were characterized by a “descending then ascending” trend. Soil moisture increased in 21.35 % of areas at 0.00-0.10 m in the past 22 years, and 59.66 % at 0.10-0.20 m. There was a negative correlation between the mean variation trend of SM and the percentage of area where SM fell in different periods; 3) the treatment program positively affected the ecological restoration of the Minqin Basin from the SM perspective. The area where SM increased was larger than that of decreasing SM, especially in 0.10-0.20 m soil layer. The increase can promote growth and confer resistance to desertification.