These are downsampled datasets for the single cell case study in Galaxy

https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-case_alevin-combine-datasets/tutorial.html

Dataset for "Combining in vitro and in silico New Approach Methods to investigate type 3 iodothyronine deiodinase chemical inhibition across species". This dataset is associated with the following publication: Mayasich, S., M. Goldsmith, K. Mattingly, and C. Lalone. Combining In Vitro and In Silico New Approach Methods to Investigate Type 3 Iodothyronine Deiodinase Chemical Inhibition Across Species. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 42(5): 1032-1048, (2023).

Raw data for "Combining Nickel- and Zinc-Porphyrin Sites via Covalent Organic Frameworks for Electrochemical CO2 Reduction" by Hugo Veldhuizen†, Maryam Abdinejad†, Pieter J. Gilissen, Thomas Burdyny*, Frans D. Tichelaar, Sybrand van der Zwaag, Monique A. van der Veen*

Dataset includes nitrogen sorption, PSD, SEM, TEM, EDX, XPS, UV-vis, TGA, FT-IR, PXRD, NMR data and extensive electrochemical data used for analysis and plotting.

Images of main text and SI figures are included as well.

The possibility that two data sets may have different underlying phylogenetic histories (such as gene trees that deviate from species trees) has become an important argument against combining data in phylogenetic analysis. However, two data sets sampled for a large number of taxa may differ in only part of their histories. This is a realistic scenario and one in which the relative advantages of combined, separate, and consensus analysis become much less clear. I suggest a simple methodology for dealing with this situation that involves (1) partitioning the available data to maximize detection of different histories, (2) performing separate analyses of the data sets, and (3) combining the data but considering questionable or unresolved those parts of the combined tree that are strongly contested in the separate analyses (and which therefore may have different histories), until a majority of unlinked data sets supports one resolution over another. In support of this methodology, computer simulations suggest that (1) the accuracy of combined analysis at recovering the true species phylogeny may exceed that of either of two separately analyzed data sets under some conditions, particularly when the mismatch between phylogenetic histories is small and the estimates of the underlying histories are imperfect (few characters and/or high homoplasy), and (2) combined analysis provides a poor estimate of the species tree in areas of the phylogenies with different histories but an improved estimate in regions that share the same history. Thus, when there is a localized mismatch between the histories of two data sets, separate, consensus, and combined analysis may all give unsatisfactory results in certain parts of the phylogeny. Similarly, approaches that allow data combination only after a global test of heterogeneity will suffer from the potential failings of either separate or combined analysis, depending on the outcome of the test. Excision of conflicting taxa is also problematic in that it may obfuscate the position of conflicting taxa within a larger tree, even when their placement is congruent between data sets. Application of the proposed methodology to molecular and morphological data sets for Sceloporus lizards is discussed.

The NexusStreets dataset contains human and autonomous driving scenes. They are collected by monitoring a target vehicle that can be either autonomous or controlled by a human driver. Data is presented in the shape of:

sequences of JPEG images, one image per timestamp

target vehicle state information for each timestamp

The dataset has been built on the CARLA simulator, thanks to Baidu Apollo and a Logitech G29 steering wheel for the autonomous and human drivings, respectively.The dataset consists of 520 scenes (260 pairs of mirrored scenarios) of 60 seconds each.The folders are organized as follows:

. ├── ... ├──
│ ├──
│ │ ├──
│ │ │ └── ...
│ │ └── ... │ └── ... └── ...

driving mode: corresponds to the control modality of the target vehicle under test and can be either Baidu Apollo or manual driving;

town: one of the five default maps in CARLA (e.g., Town01, Town02, etc);

trial: 60 different trials per map, they differ in traffic and weather conditions (except Town04). Each trial records 60 seconds of simulation, logging 120 frames per video and an equal number of rows per CSV. In particular, each trial includes:

video: this folder groups the JPEG images;

state_features.csv: reports the state information of the target vehicle for each frame;

detection_features.csv: reports the 2D bounding box detections obtained from a pre-trained YOLOv7 detector.

Locations of wetlands in the Coastal Zone. This data provides suitable land use designation information for many mapping applications. This data is appropriate for use at a regional scale and is intended as a reference.

Environmentally Sensitive Habitat Combining Designation - Wetland Habitat. The Coordinates for this dataset are State Plane Coordinate System, Zone 5, NAD 1983 Feet.

The Coherent Beam Combining market is experiencing robust growth, driven by increasing demand for high-power lasers in diverse applications such as defense, industrial material processing, and scientific research. The market size in 2025 is estimated at $250 million, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant growth is fueled by advancements in laser technology leading to more efficient and powerful beam combining techniques, and the rising adoption of these systems in various sectors. Key trends shaping the market include the miniaturization of coherent beam combining systems, the development of more robust and reliable components, and the integration of advanced control systems for improved precision and stability. While challenges such as high initial investment costs and the complexity of integrating these systems exist, ongoing technological advancements and the increasing need for high-power laser solutions are expected to offset these limitations. The market is segmented by technology (e.g., fiber, free-space), application (e.g., defense, industrial, scientific), and region. Key players such as Exail, Bonphat, PowerPhotonic, and DK Photonics are driving innovation and competition within the market. The North American region currently holds a significant market share, owing to a strong presence of defense and research organizations. However, the Asia-Pacific region is anticipated to witness the fastest growth in the coming years, driven by substantial investments in infrastructure and technological advancements. This growth trajectory is further supported by government initiatives promoting technological advancement in various sectors and an increase in research and development activities, especially in emerging economies. The forecast period of 2025-2033 presents significant opportunities for market expansion, making it an attractive space for investors and industry participants alike.

Version 1

A combination of multiple datasets. Datasets: dataset_solve_color.jsonl, dataset_solve_rotate.jsonl, dataset_solve_translate.jsonl.

  Version 2

Datasets: dataset_solve_color.jsonl, dataset_solve_rotate.jsonl, dataset_solve_translate.jsonl.

  Version 3

Datasets: dataset_solve_color.jsonl, dataset_solve_rotate.jsonl, dataset_solve_translate.jsonl.

  Version 4

Added a shared dataset name for all these datasets: SIMON-SOLVE-V1. There may be higher… See the full description on the dataset page: https://huggingface.co/datasets/neoneye/simon-arc-combine-v209.

First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. Currently, there are multiple, freely available wildland fire datasets that identify wildfire and prescribed fire areas across the United States. However, these datasets are all limited in some way. Time periods, spatial extents, attributes, and maintenance for these datasets are highly variable, and none of the existing datasets provide a comprehensive picture of wildfires that have burned since the 1800s. Utilizing a series of both manual processes and ArcGIS Python (arcpy) scripts, we merged 40 of these disparate datasets into a single dataset that encompasses the known wildfires within the United States from the 1800s to the present. These datasets were ranked by order of observed quality, and overlapping polygons in the same year were used individually or dissolved together with other polygons based on ranked quality (see individual steps in the polygon metadata for full details). The fire polygons were turned into 30 meter rasters representing various summary counts: (a) count of all wildland fires that burned a pixel, (b) count of wildfires that burned a pixel, (c) the first year a wildfire burned a pixel, (d) the most recent year a wildfire burned a pixel, and (e) count of prescribed fires that burned a pixel.

This dataset is the result of an Opportunity and Constraints Study for SLO County Department of Planning and Building. The shape of the Combining Designation is based on various environmental and renewable energy development constraints. Please see the Renewable Energy Streamlining Program Opportunities and Constraints Technical Study from February 2014 written by Aspen Environmental Group for details.

Geospatial data about San Luis Obispo County, CA Wetlands Combining Designation. Export to CAD, GIS, PDF, CSV and access via API.

Descriptive statistics of sexual violence victim-survivors in the Crime Survey for England and Wales (CSEW) and Rape Crisis England & Wales (RCEW) datasets.

RANS simulations and DNS simulations for the manuscript 'A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling'. The simulations are validated using a data set which can be found at http://www.kbwiki.ercoftac.org/w/index.php/UFR_3-30_Test_Case.

A central question concerning data collection strategy for molecular phylogenies has been, is it better to increase the number of characters or the number of taxa sampled to improve the robustness of a phylogeny estimate? A recent simulation study concluded that increasing the number of taxa sampled is preferable to increasing the number of nucleotide characters, if taxa are chosen specifically to break up long branches. We explore this hypothesis by using empirical data from noctuoid moths, one of the largest superfamilies of insects. Separate studies of two nuclear genes, elongation factor-1α (EF-1α) and dopa decarboxylase (DDC), have yielded similar gene trees and high concordance with morphological groupings for 49 exemplar species. However, support levels were quite low for nodes deeper than the subfamily level. We tested the effects on phylogenetic signal of (1) increasing the taxon sampling by nearly 60%, to 77 species, and (2) combining data from the two genes in a single analysis. Surprisingly, the increased taxon sampling, although designed to break up long branches, generated greater disagreement between the two gene data sets and decreased support levels for deeper nodes. We appear to have inadvertently introduced new long branches, and breaking these up may require a yet larger taxon sample. Sampling additional characters (combining data) greatly increased the phylogenetic signal. To contrast the potential effect of combining data from independent genes with collection of the same total number of characters from a single gene, we simulated the latter by bootstrap augmentation of the single-gene data sets. Support levels for combined data were at least as high as those for the bootstrap-augmented data set for DDC and were much higher than those for the augmented EF-1α data set. This supports the view that in obtaining additional sequence data to solve a refractory systematic problem, it is prudent to take them from an independent gene.

This repository contains the R code and aggregated data needed to replicate the analysis in our paper "Delineating Neighborhoods: An approach combining urban morphology with point and flow datasets". The enclosed renv.lock file provides details of the R packages used. Aside from these packages, an installation of the Infomap algorithm (freely available through standalone installations and Docker images) is also necessary but is not included in this repository. All code is organized in computational notebooks, arranged sequentially. Data required to execute these notebooks is stored in the data/ folder. For further details, please refer to the enclosed 'README' file and the original publication.

Script and accompanying notebook written in Python 2.7 for combining flood report data (output) and environmental data (input) into a format suitable for a data-driven model. These data used as target values for street data-driven flood prediction severity modeling for Norfolk, VA 2010-2016. This modeling is described in this Journal of Hydrology paper: https://doi.org/10.1016/j.jhydrol.2018.01.044.

Locations of prime riparian habitat in the Coastal Zone. This data provides suitable land use designation information for many mapping applications. This data is appropriate for use at a regional scale and is intended as a reference.

Environmentally Sensitive Habitat Combining Designation - Riparian Habitat. The Coordinates for this dataset are State Plane Coordinate System, Zone 5, NAD 1983 Feet.

1199 Global export shipment records of Combining Machine with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

In drought prone areas of Ethiopia, maize is produced by small-scale farmers’ where additional inputs are rarely applied. Although genetic tolerance is recommended for moisture stress, there is limited information on drought-tolerant genotypes reaction to variable environments. In this study, eight drought tolerant lines and their diallel crosses were tested separately in randomized complete block design under normal and high plant densities that combined with well watered and drought stress to estimate performance, heterosis and combining ability for grain yield. Both types of genotypes gave highest grain yield under well watered high plant density. However, least performance of inbred lines and highest heterosis was recorded under drought stressed high density, which confirmed more stress tolerance of hybrids than their parents. Although the predominant role of non-additive effects was observed for grain yield in most environments, the highly significant GCA x E and SCA x E interactions shows that combining ability effects change with growing conditions. Moreover, the observed weak association between grain yield of hybrids and inbred lines per se suggested the importance of evaluation of crosses in variable environments. Some of the new crosses gave better yield than local hybrids in less stress and stress environments. Generally, this study confirmed that hybrids developed from drought-tolerant inbred lines combined stress tolerance and high yield potential.