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5,526 results for “information”
Dataset: Information Services Group, Inc. (III) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
An environmental resistance model to inform the biogeography of aquatic invasions in complex stream networks
<p>Freshwater invasions are a global conservation issue. Emerging tools for biogeographical analyses can provide critical information for their effective management and monitoring. Here, we propose a method to assess the distribution of environmental resistance of stream ecosystems to biological invasions by coupling multi‐stage habitat potential models for non‐native species. Location: Andean Patagonia (Chile and Argentina).Taxa: North American beaver (<em>Castor canadensis</em>), Chinook salmon (<em>Oncorhynchus tshawytscha</em>), and coho salmon (<em>O. kisutch</em>). Methods: Environmental resistance to invasive species was mapped throughout a large region of Patagonia by stacking multi‐stage habitat relationships for each target species and assessing the complementation between critical habitats at multiple scales. We generated an environmental model of stream networks derived from high‐resolution topographic and climatic data representing 15,406 drainage basins (>1 km2) covering an area of 369,791 km2. We quantified the intrinsic potential of stream reaches (100 m and 1000 m) to sustain high‐quality habitats and assessed habitat complementation (i.e., abundance and proximity) at the sub‐basin scale as a proxy for environmental resistance. Results: Our model revealed high heterogeneity in the distribution of environmental resistance to invasions throughout the study region, providing case‐specific insights for the research and management of invaders. Conclusions: Environmental resistance modelling is a novel method to study the biogeography of riverine invasions. Our approach is compatible with additional sources of information about species and the environment and shows versatility to diverse invasion scenarios and data sources. This method can be useful in prioritising research and management of incipient and spreading invasions, especially for large and data‐poor regions.</p>
Figure 2 in Environmental DNA as a tool to help inform zebra mussel, Dreissena polymorpha, management in inland lakes
Figure 2. The mean number of cycles needed to detect DNA of zebra mussels from water samples collected at the surface, mid-column and bottom of Lake Minnetonka directly above a known zebra mussel population. A lower number of cycles indicates a greater amount of DNA. Bars represent the 95% confidence intervals.
Figure 3 in Environmental DNA as a tool to help inform zebra mussel, Dreissena polymorpha, management in inland lakes
Figure 3. Structural Equation Model for zebra mussels in two lakes near Alexandria, Minnesota: Lake Le Homme Dieu (A) and Maple Lake (B). Nodes are environmental DNA copy numbers of zebra mussel DNA (eDNA), habitat, depth, lake and ash-free dry weight (AFDW). AFDW is log(AFDW + 0.1). eDNA is log(copy number eDNA + 0.1). Numbers next to a line between two nodes represents the correlation between the two nodes. The r2 values in boxes correspond % variance of dependent variable explained by the independent variable. Values with an asterisk (*) indicate significant correlation between nodes. Our significance level was established at α ≤ 0.05.
FIGURE 1. A in A novel distance that reduces information loss in continuous characters with few observations
FIGURE 1. A. An interval and its components; B. Possible relationships between two intervals and A, B, and C in the Character X's space; C. DBI's behavior according to the possible relationships between the intervals of any two objects. For this, a mobile test interval of range X with its upper limit placed at Y was discreetly displaced by D units W times. For each of these W steps the DBI between the test interval and a fixed interval of range F with its lower limit placed at H were computed. The Left section shows the DBI for non-overlapped intervals; the Central section shows the DBI for partially overlapped intervals; and the Right section shows the DBI for fully overlapped intervals. Dashed lines show the results between intervals with different relative ranges (i.e., interval sizes). The asterisks show the paired distances between A, B, and C using DBI.
Dataset of historical hourly information of four european wind farms for wind energy forecasting and maintenance
<p><strong>If you use this dataset please cite this paper: Sánchez-Soriano, J.; Paniagua-Falo, P.J.; Gómez Muñoz, C.Q. Historical Hourly Information of Four European Wind Farms for Wind Energy Forecasting and Maintenance. Data 2025, 10, 38. <a href="https://doi.org/10.3390/data10030038" target="_blank" rel="noopener">https://doi.org/10.3390/data10030038</a></strong></p> <p>For an electric company, having an accurate forecast of the expected electrical production and maintenance from its wind farms is crucial. This information is essential for operating in various existing markets such as Iberian Energy Market Operator - Spanish Hub (OMIE in its Spanish acronym), Portuguese Hub (OMIP in its Spanish acronym), and Iberian electricity market between the Kingdom of Spain and the Portuguese Republic (MIBEL in its Spanish acronym), among others. The accuracy of these forecasts is vital for estimating the costs and benefits of the handling of electricity. This article explains the process of creating the complete dataset, which includes the acquisition of the hourly information of four European wind farms as well as a description of the structure and content of the dataset which amounts to 2 years of hourly information. The wind farms are in three countries, two from Auvergne-Rhône-Alpes (France), Aragon (Spain) and the Piemonte region (Italy). The presented dataset is available and accessible to improve the forecasting and management of wind farms, especially for the detection of faults and the elaboration of a preventive maintenance plan.</p> <p>The full description of the characteristics of the dataset, as well as its components, format and methodology, can be found here: "Historical Hourly Information of Four European Wind Farms for Wind Energy Forecasting and Maintenance". Data 2025, 10, 38. <a href="https://doi.org/10.3390/data10030038" target="_blank" rel="noopener">https://doi.org/10.3390/data10030038</a></p>
FIGURE 7 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 7. Boxplot of yield difference over area index by hiatus class. Note the median for each hiatus class is close to zero. This indicates similar amounts of collection between the earlier year and the later year regardless of the number of years the area has been left to erode.
FIGURE 6. Map showing estimated collection area. Points are field localities and 15 meter buffer shows estimated prospecting areas for 2008 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 6. Map showing estimated collection area. Points are field localities and 15 meter buffer shows estimated prospecting areas for 2008 (yellow), 2009 (green), and 2010 (blue). Precise locality information is available to qualified researchers upon request from JODA's museum program.
FIGURE 9. All field collections from 2013 - early 2019 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 9. All field collections from 2013 - early 2019 to be used for tracking previous collection area. Points outside of JODA boundaries are BLM, USFS, or private localities. Precise locality information is available to qualified researchers upon request from JODA's museum program.
Fig. 7 in Gross anatomy and histology of the alimentary system of Characidae (Teleostei: Ostariophysi: Characiformes) and potential phylogenetic information
Fig. 7. Phylogenetic relationship of the selected species after Mirande (2009, 2010) final hypothesis of phylogenetic relationships. A) Considering Markiana nigripinnis as a member of Stevardiinae sensu Oliveira et al. (2011) and Baicere-Silva et al. (2011) and B) with M. nigripinnis as a member of Astyanax clade sensu Mirande. Synapomorphies and autapomorphies obtained from optimization of the characters proposed herein are presented in italics above branches as character number. Node numbers are presented in red below branches.
Fig. 5 in Gross anatomy and histology of the alimentary system of Characidae (Teleostei: Ostariophysi: Characiformes) and potential phylogenetic information
Fig. 5. Histological sections of the alimentary tract of selected species of the Characidae family: A - Astyanax rutilus esophagus in transversal section showing a folded esophagus mucosa; B - Cheirodon interruptus esophagusin transversal section showing less conspicuous foldings and a proportionally greater development of the musculature; C - Gustative papillae detail of Cheirodon interruptus. Characters are indicated with numbers and character states between parentheses; D - Transition esophagus-stomach of Gymnocorymbus ternetzi in longitudinal section; E - Cardiac stomach of G. ternetzi in longitudinal section; F - Anterior portion of the fundic stomach of Aphyocharax anisitsi in transversal section with acinous glands; G - Posterior portion of the fundic stomach of A. anisitsi in transversal section showing developed connective tissue septa and tubular ramified glands. H - Pyloric portion of G. ternetzi intestine in transversal section. Abbreviations=BV: Blood vessel; CardSt: cardiac stomach; CnT: connective tissue; CSM: Circular smooth muscle; CStM: Circular striated muscle; F: folding; FundSt: fundic stomach; GA: Acinous Gland; L: lumen; LStM: Longitudinal striated muscle; Oesoph: Oesophagus. P: peritoneum; Pap: papillae; PsE: Pseudoestratified epithelium; SE: Simple Epithelium; SM: Striated muscle; Spt: Septum; TRG: Tubular Ramified Gland; *: space generated by a technical artifact. Bars units=µm.
Fig. 4 in Gross anatomy and histology of the alimentary system of Characidae (Teleostei: Ostariophysi: Characiformes) and potential phylogenetic information
Fig. 4. Liver lobes of selected species of Characidae. Lateral view anterior to left at the left side of the figure. Anterior to right at the right side of the figure. Proposed primary homologue lobes are delimited by the same color. Light blue bar indicates approximately position of anterior distal margin of gas bladder posterior chamber. A - Astyanax endy; B - Gymnocorymbus ternetzi; C - Characidium borellii. Bar=1mm.
Fig. 1 in Gross anatomy and histology of the alimentary system of Characidae (Teleostei: Ostariophysi: Characiformes) and potential phylogenetic information
Fig. 1. Alimentary tract of selected species of the Characidae family: A - Schematic representation of the alimentary tract; B - Astyanax endy; C - Astyanax rutilus; D - Cheirodon interruptus; E - Aphyocharax anisitsi. Characters are indicated with numbers and character states between parentheses. Red bar indicates the anterior distal margin of the stomach. Bar=1mm.
Fig. 6 in Gross anatomy and histology of the alimentary system of Characidae (Teleostei: Ostariophysi: Characiformes) and potential phylogenetic information
Fig. 6. Histological sections of the alimentary tract of selected species of the Characidae family: A - Transition stomachintestine of G. ternetzi in transversal section; B - Detail of an intestinal folding in A. anisitsi; C - Transversal section of a intestinal caeca of Cheirodon interruptus; D - A. anisitsi pancreas. Abbreviations= AcSe: Serous Acinus BC: Blood Capillary; C: Ceca; ColSE: Columnar Simple Epithelium; CnT: Connective Tissue; EndP: Endocrine Pancreas; FundSt: Fundic Stomach, GlC: Globlet Cell; Int: Intestine; L: Lumen; NPl: Nervous Plexus; P: Peritoneum; PD: Pancreatic duct; PilSt: Pyloric Stomach; PilVal: Pyloric Valve; St: Apical Striations; V: Folding. Bars units=µm.
Fig. 3 in Gross anatomy and histology of the alimentary system of Characidae (Teleostei: Ostariophysi: Characiformes) and potential phylogenetic information
Fig. 3. Liver lobes of selected species of Characidae family. Lateral view. Anterior to left at the left side of the figure. Anterior to right at the right side of the figure. Proposed primary homologue lobes are delimited by the same color. Light blue bar indicates approximately position of anterior distal margin of gas bladder posterior chamber. Characters are indicated with numbers and character states between parentheses. A - Aphyocharax anisitsi; B - Cheirodon interruptus; C - Bryconamericus thomasi; D - Astyanax rutilus; E - Markiana nigripinnis. Bar=1mm.
Figures 5‒6 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figures 5‒6. Fig fruits Ficus sp., a food resource of Silvery Pigeon Columba argentina, Linggam Island, Aceh province, Sumatra, 8 July 2021 (Muhammad Iqbal)
Figure 1 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 1. Silvery Pigeon Columba argentina chick, collected on Tepi Island, Aceh province, Sumatra, 3 July 2021 (Muhammad Iqbal)
Figure 4 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 4. Coconut frond where the Silvery Pigeon Columba argentina chick in Fig. 1 was reportedly found, Tepi Island, Aceh province, Sumatra, 4 July 2021 (Muhammad Iqbal)
Figure 3 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 3. Adult Silvery Pigeon Columba argentina, Tepi Island, Aceh province, Sumatra, 4 July 2021 (Muhammad Iqbal)
Figure 7‒8. Chinese Bayan fruit Ficus microcarpa, reportedly a in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 7‒8. Chinese Bayan fruit Ficus microcarpa, reportedly a major food resource of Silvery Pigeon Columba argentina, Bulu Hadik, Teluk Dalam subdistrict, Aceh province, Sumatra, 10 July 2021 (Muhammad Iqbal)
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.