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This dataset includes the yearly decomposed concentrations of four spatial components ("long-range", "mid-range", "neighborhood", "near-source") for PM2.5 and NO2, from year-2000 to year-2015. The concentrations are at the census block level. The unit of concentrations is ug/m3 for both pollutants. Block is identified by variable "block_fip"; the longitude and latitude of each block centroid are indicated by "longitude" and "latitude". Names of concentration variables follow the pattern as "COMPONENT_YEAR". "COMPONENT" represents four spatial components; "YEAR" represents the last two digits of year-2000 to year-2015. For example, "long-range_00" represents the "long-range" component concentrations for the year-2000.
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The datasets described herein provide the foundation for a decision support prototype (DSP) toolkit aimed at assisting stakeholders in determining evidence of which aspects of river ecosystems have been impacted by hydropower. A series of 42 river function indicators were used to characterize divergent aspects of river ecosystems while also serving to consolidate the dimensionality of these complex systems into a manageable number of measures. These indicators were developed from a comprehensive literature review of the environmental impacts of hydropower and are associated with six main categories of impacts to river systems: biota and biodiversity, water quality, hydrology, geomorphology, land cover, and river connectivity. The three tools comprising the DSP toolkit and associated data include: 1) Science-Based Questionnaire (SBQ): A series of structured survey-style 140 questions for understanding impacts of dams on river ecosystems were developed through a global literature review. A spreadsheet program was developed to summarize the results of questions into evidence of dam impacts on the 42 ecological indicators. Output is provided in tabular and graphical/chart formats. 2) Environmental Envelope Model (EEM): The EEM is a model to predict the likelihood of hydropower impacting indicators based on a several variables. The intended use of the EEM is for situations of new hydropower development where results of the SBQ are incomplete or highly uncertain. A dataset containing attributes of dams, reservoirs, and geospatial information on environmental concerns were compiled and combined with data on ecological indicators measured at those sites. The data were used to develop models predicting impacts of dams on ecological indicators. A total of 247 envelopes and weighting factors, representing the individual effect of each variable on each ecological indicator, were developed in a spreadsheet program. 3) River Function Linkage Assessment Tool (RFLAT): The purpose of RFLAT is to examine causal relationships amongst indicators. Based on literature review, a node and edge dataset was developed representing causal relationships (“edges”) between ecological indicators (“nodes)”. Bayes theorem was used estimate conditional probabilities of inter-indicator relationships based on the output of the SBQ. Nodes and edges were imported into R programming environment to visualize ecological indicator networks.
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The excel data and the original data (uncropped, unmodified images) for figures .
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LF--Pumping frequency HF--Probing frequency Fs--Sample Frequency All the sample length is 1M points the probing amplitude is 10Vpp the pumping amplitude is 3N except for the data of Figure 7
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Datasets and codes replicating the results in "International spillovers of quantitative easing".
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  • Document
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A lemon (Le) leaf (Le) images dataset for aphids (Phid) detection. It includes 665 files with annotations regarding objects (leaves) and state (healthy and aphids presence).
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  • Software/Code
  • Image
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There are an increasing number of neuroimaging studies that can better understand the efficacy and neural correlation of language therapy in post-stroke aphasia (PSA) patients to date. However, the results of these studies were difficult to compare as they included PSA patients at acute to chronic stages of the disease and employed different language therapy methods, so the statistical results of neuroimaging data showed a high degree of variability.
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Raw data
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Metagenomic DNA isolated and analyzed from soils of three varillal forests from the Allpahuayo-Mishana National Reserve, Loreto Region, Peru.
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The dataset contains the raw data used for the figure in the manuscript "The UPR sensor IRE1a and the adenovirus E3-19K glycoprotein sustain persistent and lytic infections"
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