207322 results
Contributors: laura Miller
Date: 2019-07-20
... Sb K-edge XANES and EXAFS spectra of synthetic MORB and CMAS glasses prepared as a function of oxygen fugacity and pressure.
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Contributors: Sukhjit Sandhu
Date: 2019-07-18
... Plant (wheat) stress analysis and classification using Image processing and machine learning models
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Contributors: Miek Messerschmidt
Date: 2019-07-18
... This dataset is related to the paper "On compact packings of the plane with circles of three radii". For each of the 248395 elements of the set K defined in Definition 5.1, the dataset contains a file (in JSON format). Each file contains all data required to apply Proposition 6.1, which allows for establishing the bound of 13617 of the number of pairs (r,s) satisfying 0<s<r<1 and which admits a compact packing of circles of radii r,s and 1.
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Contributors: Hyungjun Cho, Peng Liu, Jothir Pichanndi, Taunia Closson, Daniel Majonis, Patricia Leighton, Eric Swanson, olga ornatsky, Vladimir Baranov, Mitchell Winnik
Date: 2019-07-17
... MCP for Zr and its Use in CyTOF
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Contributors: David Alberto García Arango
Date: 2019-07-17
... Se tienen referencias bibliográficas relacionadas con el concepto de ciencia abierta y que están organizadas por continentes. Igualmente se tiene la base de datos de revistas del Diejectory of Open Access Journal (DOAJ) con información a 2017
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Contributors: Trevor O'Grady, Don Vandegrift, Michael Wolek
Date: 2019-07-17
... Data used in Study 2 of the paper "On the Determinants of Other-Regarding Behavior: Field Tests of the Moral Foundations Questionnaire" by O'Grady, Vandegrift, Wolek and Burr. The dataset connects an individual's responses to the Moral Foundations Questionnaire with their decision to donate their bonus to charity in an economic game where any contributions to charity are matched. We hired 591 unique U.S. participants (workers) from Amazon Mechanical Turk (AMT) online labor market to complete the survey. Sixty-eight participants in the data set failed attention checks resulting in a 523 usable observations in Study 2. Study 2a includes 118 observations (Condition 1 n=36, Condition 2 n=40, Condition 3 n=42) with ages ranging from 22 to 71 (M=39.1, SD=11.0). Forty-three percent reported their gender as female and 81% reported their race as white. Study 2b includes 86 observations (Condition 4 n=43, Condition 5 n=43) aged 21 to 63 (M=37.8, SD=10.2), 40% female, and 84% white. Study 2c includes 319 observations (Condition 6 n=108, Condition 7 n=102, Condition 8 n=109) aged 24 to 70 (M=39.9, SD=10.4), 52% female, and 79% white. Version 3 Update: The "Final" subfolder now contains the processed dataset in CSV format as well as a codebook of variable descriptions.
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Contributors: NatSciLive Natra
Date: 2019-07-17
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Contributors: Benjamin Darde, Anh Minh Tang, Jean-Michel Pereira, Patrick Dangla, Jean-Noel Roux, Jean Talandier, Minh Ngoc Vu
Date: 2019-07-17
... Compression test results: pellet modulus, pellet strength and maximal displacement for axial and radial directions (Fig. 8 and Fig 9. in article).
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Contributors: Silvester vankoten
Date: 2019-07-17
... The data (as stata dta files) are the basis for a replication study, (re)testing the four hypothesis in Bessembinder & Lemmon (2002). The hypotheses are as following: The forward premium: H1: decreases in variance of prices H2: increasing in non-standardized skewness of price H3: initially decreases and then increases in demand standard deviation H4: increases in mean demand The results are that Hypotheses H1, H2 are not supported when the variable cost parameter is adaptive as specified in (2002, p.1360), but are supported when the variable cost parameter is fixed. Hypothesis H3 is supported for both cases and Hypothesis H4 for neither. The data have been generated using Bessembinder and Lemmon’s (2002) theoretical results (especially their Equation 3) to calculate outcomes (spot prices, forward prices, forward premia and optimal forward positions) for different demand distributions. As a robustness test, I also calculate forward positions, not by using Equation 3, but, as in Willems and Morbee (2010), by maximizing the joint utility of a producer and retailer, where the utility function is given by . The first welfare theorem implies that these solutions should be equal to the optimal solutions. Indeed the values I calculate in this manner are identical to the ones I calculate using Equation 3. I calculate the outcomes for eight configurations in total: four values of the cost convexity parameter (2, 3, 4, and 5) and two possible ways to determine the variable cost parameter (adaptive and fixed). For each configuration, outcomes are calculated for 195,891 different distributions (391 values for the demand standard deviation and 501 values for the mean demand). For each demand distribution in a configuration, I use a grid spanning 10 standard deviations with 1000 points per standard deviation. As another robustness test, I also run the same calculations using random samples of 1000 000 per distribution, programmed in Mathematica. All calculated outcomes are identical (except for minor rounding differences). To use the data, open the folder "Stata_analysis" > "Stata_analysis_home folder" > "stata_files" • "2. Analyse data_main.do" can be used to replicate all the figures in the paper. The data have been generated in Python. Run the full dofile. Before you run the dofile, make sure to unrar all the files in the folder "Stata_analysis_home folder\data_in_stata_format" with a rar-utility. • "3. Analyse data_robust.do" replicates the figures using the data generated by brute sampling in Mathematica. The results should be identical to those obtained with the dofile "2. Analyse data_main.do"
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Contributors: Danilo Hottis Lyra
Date: 2019-07-16
... We provided the raw phenotypic data (FA_data_raw.RData), and individual-TP BLUPs, B-spline bases, and the first functional PCs from the 5, 10, and 26 TPs (phenotypic_traits.RData). The rqtl package input files for scenarios R1, R5, and R9 are also provided (CSP_ph17_5t_R1, CSP_ph17_10t_R5, and CSP_ph17_R9). The additive genomic relationship matrix is available as VanRaden_matrixCSP.RData. The codes provided are (1) factor analytic model, (2) smoothing and dimensionality reduction, QTL scanning using (3) individual-TP and (4) functional mapping, (5) power simulations, genomic prediction (6) with and (7) without including covariates as fixed effects.
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