Filter Results
14415 results
  • Corrosion and Electrochemical Impedance Spectroscopy data of Copper in 1.0 M HCl in the presence and absence of corrosion inhibitors gum arabic, sodium alginate and their blends. The data set also contains the XRD data and SEM image of polymer blends of gum arabic and sodium alginate. SEM and AFM images of the Copper coupons before and after electrochemical corrosion studies are also presented.
    Data Types:
    • Image
    • Dataset
    • Text
  • This data to support the quantitative research of knowledge sharing intentions
    Data Types:
    • Tabular Data
    • Dataset
  • supplementary-fig. 1. Spectra of the leader tip for As, Fs and Gs at different time. (1)-(12) the spectra of leader As. (13)-(22) the spectral images of leader Fs. (13a)-(22a) the corresponding spectra of leader Fs. (23)-(28) the spectral images of leader Gs. (23a)-(28a) the corresponding spectra of leader Gs. supplementary-fig. 2. Spectra of the dart stepped leader tip for Bds, Cds and dart leader Id and Kd at different time. (1)-(9) the spectra of dart stepped leader Bds, (10)-(14) the spectra of dart stepped leader Cds, (15)-(20) the spectra of dart leader Id, (21)-(26) the spectral images of dart leader Kd. (21a)-(26a) the corresponding spectra of dart leader Kd.
    Data Types:
    • Image
    • Dataset
  • There are 3345 groups training data which come from conventional wireline logging of Yan'an gas field and 3345 groups test data which come from logging while drilling of Yan'an gas field in the data file.
    Data Types:
    • Tabular Data
    • Dataset
  • This dataset is related to the research article entitled "A system of automatic recognition of species of Brazilian flora based on textural characteristics of macroscopic images of wood", by Deivison Venicio Souza, Joielan Xipaia Santos, Helena Cristina Vieira, Tawani Lorena Naide, Silvana Nisgoski and Luiz Eduardo S Oliveira accepted in the journal Wood Science and Technology. Wood samples were from the collection of the Wood Anatomy and Quality Laboratory (LANAQM) of Federal University of Paraná (UFPR), located in Curitiba, Paraná. The wood samples’ transversal surfaces were sanded with a 120 sandpaper and macroscopic images of 46 species were taken with a Zeiss Discovery V 12 stereomicroscope, with size of 2080 × 1540 pixels and 10× magnification. The captured images have a resolution of 150 dpi. A total of 1,901 macroscopic images were obtained. Of the 46 species used in this study, 7 are on Brazil’s official list of endangered species. More specifically, the species Araucaria angustifolia and Ocotea porosa are classified in the category “Endangered”, Cedrela fissilis, Bertholletia excelsa, Mezilaurus itauba and Swietenia macrophylla are part of the “Vulnerable” group, and Euxylophora paraensis is considered “Critically Endangered”.
    Data Types:
    • Image
    • Dataset
  • Research data are collected via an online self-administered questionnaire from a sample of Moroccan consumers of a dairy brand. The questionnaire was self-administered via the Google Forms tool during the months of April 2020. A total of 195 responses from consumers were received, including 110 women and 85 men. The age of the respondents varies between 16 and 60 years old with an average age of 24.9587. In addition, 78.6% of the respondents are single, 19.5% married and 1.9% divorced. The findings indicate a positive influence of consumer satisfaction on brand attitude, brand preference, and purchase intentions.
    Data Types:
    • Tabular Data
    • Dataset
  • This dataset is composed of 58 apple tree images. They were taken during full bloom in an apple orchard located at National Institute of Agricultural Technology (INTA) Experimental Station, General Roca, Argentina (39° 1’ 34’’ S; 67° 44’ 24.6’’ W).The orchard was established in 2003 with ‘Red Chief’ cultivar apple trees grafted on MM111 rootstock .Trees were planted in a total area of 0.8 ha at a distance of 1.5m between trees by 4m between rows and were trained as espalier. A few days before full bloom, images were obtained from 32 trees, under two conditions: i) natural daylight between 10 am and 13 pm, ii) at night with the artificial flash light of the camera. A black curtain was unfolded behind the trees when images were obtained under daylight conditions in order to avoid interference from neighboring trees. All images were taken with an RGB digital camera (14.1 MP) at approximately 3.0 m from the tree in a 90° angle to the row. An object of known dimensions (a 15x15 cm square) was placed in each tree as a scale reference. Simultaneously, all the flowers on each tree were manually counted. Images taken by using different proximal sensors can be used to estimate the number of flowers or fruits in trees. The accuracy of those methods have been studied and tested by many researchers during the past few years with encouraging results. Since manual counting method in fruit crops is a time-consuming labor and also lead to inaccurate results, image analysis could be used as an alternative procedure. The use of images could provide reliable and consistent data.
    Data Types:
    • Image
    • Dataset
  • Data obtained by testing materials for replacement of sand slag with natural sand in concrete and subsequent analysis which includes comparison and calculation
    Data Types:
    • Tabular Data
    • Dataset
  • En se basant sur les résultats de recherches réalisés ces derniers années, il a été démontré que le Ratio de Concentration présente une influence sur la performance global des collecteurs solaires cylindro-parabolique. Notament ce paramètre influe sur l'entropie et l'efficience thermique. De ce fait, sa variation pourait également avoir des conséquences sur l'éfficience optique du concentrateur. C'est a juste titre qu'il a été entrepris cette étude qui vise a comparer l'éfficience optique de trois modèles de concentrateurs distingués par trois differentes ratio de concentration en les simulant numeriquement para la méthode MCRT atravers le logiciel SolTrace. En effet, les trois valeurs du ratio de concentretion e les données de simulation ont été obtenus en optimisant les paramètres géométriques e optiques du concentrateur par le biais des équations mathématiques qui gouvernent son fonctionement. La simulation numérique a été fait en maintenant la distance du foyer constante a 1,75. Après la simulation numérique, les resultats obtenus sont présentés sous deux banques de données pour chaque modèle de collecteur : le flux de chaleur autour de du tube absorbeur e les points dínterssections des rayons solaires avec les éléments du concentrateur.
    Data Types:
    • Other
    • Image
    • Tabular Data
    • Dataset
  • Title: Fossil isotopic constraints (C, O and 87Sr/86Sr) on Miocene shallow marine incursions in Western and Eastern Amazonia: Supplementary Materials Version: 1.0 Date of Release: 2020/06/05 Identifier: doi: 10.17632/2smgvjr7np.1 Permalink: http://dx.doi.org/10.17632/2smgvjr7np.1 Contact information: Andre M. V. Alvim, Universidade de Brasilia, Darcy Ribeiro Campus, Asa Norte 70910-900 Brasilia, DF - Brazil, andre.mavaal@gmail.com Dates of data collection: 11/2018-12/2019 This directory contains the following supplementary materials: • Table 1 - Geographic location and stratigraphic position of the analyzed Miocene fossil samples. • Table 3 - Table of isotopic and geochemical data of the analyzed Miocene fossil samples. • Table 4 - Vital effect analysis using the stable isotopic composition of the analyzed Miocene fossil samples. • Table Extra - Binary mixing models for paleosalinity estimates of figure 6 of the manuscript Tables 1, 3 and 4 above are cited in the original manuscript. In manuscript results and discussion sections, Table 3 and Table Extra had the following roles: • Table 3 - Stable and strontium isotopic data from this table were treated in Origin software (version Pro 8) in order to elaborate the Figures 3 and 4 of the manuscript; • Table Extra - The mixing models presented in Figure 6 of the manuscript were calculated in this table using strontium isotopic data from Table 3 (above), and Equation 1 and Table 5 of the manuscript.
    Data Types:
    • Tabular Data
    • Dataset