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Data in summary: 1- Building total B side: This is metered data from one of two mains busbars that supplies all none-emergency services and HVAC equipment 2- Building total A side: This is metered data from the second of two mains busbars that supplies all emergency services including fire safety, comm rooms, emergency lighting and public announcement. It also is connected to a PV array with peak electrical supply of around 33kWe. 3- Half hourly building demand and deferrable load breakdowns: This is processed data that includes building total and HH instances of deferrable loads for all sub-categories of loads considered in this work. It also includes HH instances of PV generation, and outside air temperature. 4- Early morning ramp rates following plant start-up: This is a file containing the difference between two instantaneous recordings of total building electricity consumption that shows the continuous fluctuation in total electricity demand in the building. 5- CO2-raw (Typical office): This files contains actual CO2 data in an office that represents typical space occupant density in the case study building. 6- CO2-raw (worst case): This files contains actual CO2 data in a teaching space that represents the highest observed space occupant density in the case study building. 7- Warming and cooling rates in the worst case zones: This file include actual data describing the operational temperature in the worst case zones most prone to overheating in summer and excessive heat loss in winter.
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This study included 451 anonymized UWF and 745 FP images. The ultra-widefield (UWF) images, which include both normal and pathologic retinal images, were based on Tsukazaki Optos Public Project. The traditional fundus photograph (FP) images were extracted from the publicly accessible database by using the Google image and Google dataset search that included English keywords related to retina. The search strategy was based on the following key terms: “fundus photography”, “retinal image”, and “fundus dataset”. The images were manually reviewed by two board-certified ophthalmologists, and blurred and low-quality images were removed to clarify the image domains. Duplicated images were also removed. Consequently, 451 images with artifacts and 745 images without artifacts were collected. The UWF images were cropped and masked after registration for CycleGAN.
Data Types:
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Data for the manuscript "Influence of information presentation manner on risky choice".
Data Types:
  • Other
  • Software/Code
  • Tabular Data
  • Dataset
Foremost, my pleasure and encouragement rest with future endeavors, research, computations, and empirical and experimental analyses, which are welcomed, that will exceed beyond the expectations of own research. Pertaining to the Excel dataset, please refer to article titled, “Corporate Cultures at the Forefront of MNE Organization Structures, Evaluating Cost and Profit Centers” for in-depth empirical findings. All data were collected from external observations and publicly disclosed Annual Reports, Sustainability Reports (CSRs) and SEC filings of 10-K and 10-Q forms. Earnings per shares (EPS) were converted to U.S. dollars (USD). Specifically refer to datasheet labeled “TEST” in the Excel file for executive intervention analysis. For replication of the empirical analysis, i.e. the cultural intervention analysis and its respective forecasting and diagnostic figures, the Gretl statistical software was used. Enclosed please refer to the corresponding Gretl session to conduct IMA models. Please note that despite the few degrees of freedom, IMA models are not as susceptible to irrelevant variable lag biases (overparamterization) as with other ARIMA, times series models. Also as mentioned before, spuriousness within EPS data points beyond the mid-1990’s were incompatible for sound inferences. Unfortunately, stronger structural break tests or unit root tests as robustness checks such as Monte Carlo tests for ARIMA (0,1,1) should be conducted. Nonetheless, time series assumptions were not violated, and the time-tested, Box-Jenkins approach successfully worked. The findings suggest that EPS remains a sought-after measurable, quantitative financial indicator for predicting organizational shifts as it relates to profit and cost centers of multinational enterprises (MNEs), specifically truck manufacturers. Evidence suggests that EPS movements follow those of MNE executive policies, whether organizational restructuring of profit centers or adopting new accounting protocols that impact the corporate culture. Hence, the conclusions imply a scientific notion that shareholder ownership of MNE and enhancing long-run operating profits distort executives' organizational decision-making processes often resulting in negative externalities such as a cannibalization effect.
Data Types:
  • Other
  • Tabular Data
  • Dataset
The dataset includes 2,016 impact echo signals from eight identical laboratory-made concrete specimens. This dataset is annotated in two classes: sound concrete (Class S) and defected concrete (Class D).
Data Types:
  • Dataset
  • File Set
The objective of this dataset was to present the forage biomass production over time in different pasture management systems. We selected two farms located in the Western region of São Paulo State, Brazil. Pasture field data collection was carried out in two farms during three dates (June and November 2018 and March 2019) over two seasons (wet and dry). Samples were regularly taken through time to monitor forage biomass. These fields represent a wide variety of pasture management, as follow: Farm 1 (Santa Clara): i) traditional, low forage productivity, cattle rotation; ii) traditional, intermediate forage productivity, fertilized, cattle rotation; iii) intensified pasture, high forage productivity, reformed, cattle rotation. Farm 2 (Poderosa): i) traditional degraded*, recently reformed with millet + grass, cattle rotation; ii) traditional, low forage productivity, signs of degradation, fertilized, cattle rotation. *degraded was based on visual analysis of pasture area with sparse grass and exposed soil in some areas. With the support of NDVI images from the MODIS sensor, sample pixels were used to allocate the sample points. The areas of these pixels were divided into nine sampling points and in each of these points, the forage biomass was collected. Soil analyses were also carried out in two seasons (June 2018 and March 2019). The data files were organized in three folders. Each folder represents one field campaign. These folders have a shapefile of all the fields, the same file in kml extension (to open on Google Earth) and a zip file with photography of each field during the field campaign. The attribute table of the shapefile has a description of the fields and biomass. Excel files show the same information of the attribute table and a description of the items. A figure with the template of the biomass collection scheme is also available. Soil analyses are in the folders 'June 2018' and 'March 2019'. A more detailed description and discussion about these data and their association with soil chemical analysis were described in a scientific report (available by request). The biomass collection allowed the analysis of the forage production and better diagnoses about resource utilization strategies over the different pasture systems. This work was funded by the São Paulo Research Foundation (process numbers 2018/10770-1, 2017/06037-4, 2016/08741-8, 2017/08970-0, 2018/11052-5 and 2014/26767-9) as part of the Global Sustainable Bioenergy Initiative.
Data Types:
  • Software/Code
  • Geospatial Data
  • Tabular Data
  • Dataset
  • Document
  • File Set
Data for Analysis of Nano-Silica and Xanthan Gum as a High-Temperature Thixotropic Agent for Oil-Well Cement
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Supplementary materials corresponding to the identically named paper including R scripts, derived data sets, and the full statistical test results.
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  • Dataset
  • File Set
The raw sequencing data obtained from hamsters treated with different interventions including 1) standard diet (control); (2) standard diet and monosodium glutamate (MSG) in drinking water (MSG); (3) high-fat and high-fructose diets (HFF), and (4) MSG+HFF.
Data Types:
  • Dataset
  • File Set
These datasets involve 1) ambient air quality testing, 2) spontaneous combustion fire frequency record, 3) temperature anomalies detected by Landsat, 4) photos of mine waste heap as well as affected environment, 5) estimation of remedial cost, 6) VDO of gas emission from a crack on top of the mine waste heap, and 7) XRD analysis of coal-mine waste
Data Types:
  • Other
  • Image
  • Video
  • Tabular Data
  • Dataset
  • Document
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