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opencc-by-4.0Jul 2024View details →

IODP Expedition 398 Core orientation

Core orientation data were measured downhole during advanced piston corer (APC) coring, either by Minex FlexIT or Icefield MI-5 core orientation tool. These tools measure magnetic strength and orientation, 3-axis accelerometer data, and tool temperature data.

opencc-by-4.0Aug 2021View details →

Qualitative dataset - Social justice-oriented narratives in European urban food strategies: Bringing forward redistribution, recognition and representation (Smaal et al., 2021)

This qualitative dataset contains the English translations of the plain texts of the urban food strategy documents or webpages of 16 European medium-sized cities: Basel [CH]; Bristol [UK]; Bruges [BE]; Cordoba [ES]; Donostia - San Sebastián [ES]; Ede [NL]; Geneva [CH]; Ghent [BE]; Grenoble [FR]; Groningen [NL]; Montpellier [FR]; Nantes [FR]; Rennes [FR]; Tours [FR]; Uppsala [SE]; and Vitoria-Gasteiz [ES]. The search for and translation of the urban food strategy documents and webpages have been performed in early 2019. The files have been analysed in NVivo (qualitative data analysis software). The upload also includes figures and a table with the authors' assessments connected to the resources and services codes and radar diagram visualisations presented in the following paper:  Smaal, S. A. L., Dessein, J., Wind, B. J., & Rogge, E. (2021). Social justice-oriented narratives in European urban food strategies: Bringing forward redistribution, recognition and representation. Agriculture and Human Values, 38(3), 709–727. <a href="http://doi.org/10.1007/s10460-020-10179-6">https://doi.org/10.1007/s10460-020-10179-6</a>  Abstract: More and more cities develop urban food strategies (UFSs) to guide their efforts and practices towards more sustainable food systems. An emerging theme shaping these food policy endeavours, especially prominent in North and South America, concerns the enhancement of social justice within food systems. To operationalise this theme in a European urban food governance context we adopt Nancy Fraser’s three-dimensional theory of justice: economic redistribution, cultural recognition and political representation. In this paper, we discuss the findings of an exploratory document analysis of the social justice-oriented ambitions, motivations, current practices and policy trajectories articulated in sixteen European UFSs. We reflect on the food-related resource allocations, value patterns and decision rules these cities propose to alter and the target groups they propose to support, empower or include. Overall, we find that UFSs make little explicit reference to social justice and justice-oriented food concepts, such as food security, food justice, food democracy and food sovereignty. Nevertheless, the identified resources, services and target groups indicate that the three dimensions of Fraser are at the heart of many of the measures described. We argue that implicit, fragmentary and unspecified adoption of social justice in European UFSs is problematic, as it may hold back public consciousness, debate and collective action regarding food system inequalities and may be easily disregarded in policy budgeting, implementation and evaluation trajectories. As a path forward, we present our plans for the RE-ADJUSTool that would enable UFS stakeholders to reflect on how their UFS can incorporate social justice and who to involve in this pursuit. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 765389.  Project webpage: <a href="https://recoms.eu/">https://recoms.eu/</a>

opencc-by-4.0Dec 2018View details →

Ouseley mission to Persia 1810-15 – Data on oriental manuscripts collected by the Ouseley brothers

These files form part of an archive of research data relating to the diplomatic mission to Persia 1810-15, led by Sir Gore Ouseley as ambassador. The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason;  their contact details are in the README file..  The files comprise a number of searchable listings relating to the reports produced by members of the mission and other relevant data.  The data formed the basis for a published report on the Ouseley Mission referenced below, which is also part of the archive.  This section of the archive contains three databases, under the general heading of ouscollect, listing the main items in the Ouseley collections of oriental manuscripts now held at the Bodleian Library in Oxford.  Some of these items were undoubtedly acquired during the Ouseley mission to Persia 1810-15.  Other were obtained during the brothers earlier stays in India or through booksellers in London and elsewhere.  The database files have been saved in two formats:  a Microsoft Access database (ouscollect.accdb) covering all the Ouseley holdings, and three separated comma-delimited text files (.txt).  The explanatory README text file contains a table showing the fields included in the databases and giving definitions of them and of the codings used in different cases.

opencc-by-4.0Oct 2022View details →

DATASET: Predicting Protein Function and Orientation on a Gold Nanoparticle Surface Using a Residue-Based Affinity Scale

This upload contains data for the manuscript "Predicting Protein Function and Orientation on a Gold Nanoparticle Surface Using a Residue-Based Affinity Scale." It contains kinetics data, UV-vis data, surface calculations, and activity assays for the systems described in the manuscript.

opencc-by-4.0Nov 2022View details →

Synchrotron X-ray Diffraction Analysis - Measuring Bulk Crystallographic Texture from Differently-Orientated Ti-6Al-4V Samples

A dataset of synchrotron X-ray diffraction (SXRD) analysis files, recording the refinement of crystallographic texture from six differently orientated Ti-6Al-4V (Ti-64) samples. Two different refinement methods were used to fit a range of diffraction pattern ring intensities, for determining crystallographic texture in both α (hexagonal close packed, hcp) and β (body-centred cubic, bcc) phases. The first procedure was based on an established Rietveld refinement method, using the software package <a href="https://maud.radiographema.eu">MAUD (Materials Analysis Using Diffraction)</a>. The second procedure uses a new Fourier-based peak fitting method from the <a href="https://pypi.org/project/continuous-peak-fit/">Continuous-Peak-Fit</a> Python package. Both methods were used to calculate texture from each of the six different sample orientations, a combination of the six sample orientations, and in a batch processing method for calculating spatially-resolved texture variation from 387 individual X-Y stage-scan SXRD measurements across one of the samples. Material The Ti-64 material used in this study was pre-rolled to 87.5% reduction at 915ºC and then air-cooled to develop a characteristic texture. Six different rectangular samples were cut from this material and are referenced according to alignment with the original rolling directions (RD – rolling direction, TD – transverse direction, ND – normal direction), and alignment with the horizontal (X) and vertical (Y) axes of the synchrotron detector; <table align="center"> <caption>A table recording the SXRD run number and sample orientation analysed.</caption> <thead> <tr> <th scope="col">Run Number</th> <th scope="col">Sample Orientation Reference</th> <th scope="col"> Sample Orientation (Horizontal - Vertical) </th> </tr> </thead> <tbody> <tr> <td>103840</td> <td>Sample 6</td> <td>TD45ºRD - ND</td> </tr> <tr> <td>103841</td> <td>Sample 5</td> <td>RD - TD45ºND</td> </tr> <tr> <td>103842</td> <td>Sample 4</td> <td>TD - RD45ºND</td> </tr> <tr> <td>103843</td> <td>Sample 3</td> <td>RD - TD</td> </tr> <tr> <td>103844</td> <td>Sample 2</td> <td>RD - ND</td> </tr> <tr> <td>103845</td> <td>Sample 1</td> <td>TD - ND</td> </tr> </tbody> </table> Diffraction Pattern Averaging The .cbf images found in the <a href="https://doi.org/10.5281/zenodo.7311306">raw dataset</a> were first converted into .tiff images. The stage-scan images were then averaged together for each of the different sample orientations, using a Python notebook <a href="https://github.com/LightForm-group/sxrd-tiff-summer">sxrd-tiff-summer</a>, to produce six averaged .tiff images. These averaged .tiff image capture average diffraction peak intensities from an area of about 96.75 mm2 (equivalent to a total volume of around 193.5 mm3) from each piece, which is therefore representative of bulk crystallographic texture from six different sample orientations. MAUD Analysis To process data using MAUD the diffraction pattern images must first be caked, which converts the data into .dat files of intensity versus 2θ profiles, using 72 azimuthal cakes, each of 5° azimuthal width. Although MAUD has an in-built function to cake data, using ImageJ, it is not possible to cake data in MAUD with ImageJ in an automated way. Therefore, caking was done using <a href="https://pyfai.readthedocs.io/en/master/">pyFAI</a>, an open-source Python package, with the caking procedure recorded in a separate Python notebook, <a href="https://github.com/LightForm-group/pyFAI-integration-caking">pyFAI-integration-caking</a>. The caking was applied to each of the six averaged tiff images, as well as being applied to 387 individual X-Y stage-scan tiff images from Sample 1 (103845). The caking procedure was also applied to the CeO2 calibrant diffraction pattern, creating a .dat file that could be used for calibration of the instrument parameters within MAUD, before fitting the experimental data from the different samples. A separate package <a href="https://github.com/LightForm-group/MAUD-batch-analysis">MAUD-batch-analysis</a> was used to record the setup of the files and details of the refinement procedure. Details about the refinement procedure are also recorded in an accompanying paper reporting on these results. A number of refinement steps were used to fit the caked data from the six different sample orientations, and calculate texture. Texture was also calculated from a .dat file that combined all six sample orientations together. The crystallographic texture was refined using the E-WIMV algorithm, which was found to best reproduce quantitative texture intensity values with an orientation distribution function (ODF) resolution of 15º. The MAUD-batch-analysis package also contains details about how to setup and run MAUD in an automated batch processing mode. MAUD's batch mode was used to calculate texture from a series of 387 individual stage-scan diffraction patterns from Sample 1 (103845). A MAUD-batch-analysis script was first used to substitute caked data from the 387 diffraction patterns into template .par files, which contained an initial refinement of the volume fraction, crystal sizes and micro-strain, as a starting point. Both the crystal parameters and texture were then iteratively refined, in MAUD, using a .ins batch analysis script launched from the terminal. This was done to refine both α and then β phase texture. The texture data from the MAUD analysis was recorded as an ODF, with 15º resolution over all Euler space, and extracted in text format using a script from MAUD-batch-analysis. These text files can be loaded into <a href="https://mtex-toolbox.github.io">MTEX</a>, for plotting and analysing both the α and β phase crystallographic texture. Continuous-Peak-Fit Analysis A .poni calibration file was created using <a href="https://www.clemensprescher.com/programs/dioptas">Dioptas</a>, through a refinement matching peak intensities from a CeO2 standard diffraction pattern image. Dioptas was then used to determine peak bounds in 2θ for characterising a total of 21 α and 4 β lattice plane rings from the Ti-64 diffraction pattern images, which were recorded in a .py input script. Using these two inputs, Continuous-Peak-Fit automatically converts full diffraction pattern rings into profiles of intensity versus azimuthal angle, for each 2θ section, which can also include multiple overlapping α and β peaks. The Continuous-Peak-Fit refinement can then be launched in a notebook or from the terminal, to automatically calculate a full mathematical description, in the form of Fourier expansion terms, to match the intensity variation of each individual lattice plane ring. The results for peak position, intensity and half-width for all 21 α and 4 β lattice plane peaks were recorded at an azimuthal resolution of 1º and stored in a .fit output file. Details for setting up and running this analysis can be found in the <a href="https://github.com/LightForm-group/continuous-peak-fit-analysis">continuous-peak-fit-analysis</a> package. This package also includes a Python script for extracting lattice plane ring intensity distributions from the .fit files, matching the intensity values with spherical polar coordinates to parametrise the intensity distributions from each of the six different sample orientations, in the form of pole figures. The script can also be used to combine intensity distributions from different sample orientations. The final intensity variations are recorded for each of the lattice plane peaks as text files, which can be loaded into MTEX to plot and analyse both the α and β phase crystallographic texture. This method was also used to analyse all 387 individual diffraction patterns recorded across Sample 1 (S1 – 103845), to quantify the texture variation across the piece. Metadata An accompanying YAML text file contains associated processing metadata for both the MAUD and the Continuous-Peak-Fit analyses, recording information about the different packages used to process the data, along with details about the different files contained within this analysis dataset.

opencc-by-4.0Nov 2022View details →

Synchrotron X-ray Diffraction Dataset - Measuring Bulk Crystallographic Texture from Differently-Orientated Ti-6Al-4V Samples

A dataset of raw synchrotron X-ray diffraction (SXRD) images, recording crystallographic texture from two different pre-processed Ti-6Al-4V (Ti-64) materials, analysing six differently orientated samples from each material. The aim of the work was to provide a large dataset for testing and improving crystallographic texture refinement from SXRD patterns, with the use of different computational fitting methods. Prior to the experiment, the Ti-64 materials had been pre-rolled and then air-cooled to develop the microstructure, rolling to 50% and 87.5% reduction at 915ºC using a rolling mill at The University of Manchester. Rectangular samples (2 mm thick) were then machined from these rolled blocks. The samples were cut along different directions, three samples along different orthogonal rolling directions, and three at different angles to the rolling directions. The samples are referenced according to alignment of the rolling directions (RD – rolling direction, TD – transverse direction, ND – normal direction) with the long horizontal (X) axis and short vertical (Y) axis of the rectangular specimens.  Data was recorded using a high energy 99.8 keV synchrotron X-ray beam and a 5 second exposure at the detector. The slits were adjusted to give a 0.5 x 0.5 mm beam area, chosen to optimally resolve both the α (hexagonal close packed, hcp) and β (body-centred cubic, bcc) phase peaks. The SXRD data was recorded across each of the specimens by stage-scanning the beam in sequential X-Y positions at 0.5 mm increments, forming a rectangular grid of measurement points across each sample. A powder Ti-64 sample was also measured as a random texture standard. As well as the main experiment, 3 samples (sample 1, 2 and 3) were held together in different orders (1, 2, 3 ; 2, 1, 3 ; 2, 3, 1) and analysed through-thickness, to measure how beam attenuation might affect the bulk texture measurement. In addition, different detector exposure times (1 to 0.04 seconds) were also tested to analyse the impact of exposure time on overall intensity, to see how well the α and β peaks could be resolved from background noise at very fast acquisition frequencies. The raw data is in the form of synchrotron diffraction pattern images which has been separated according to experiment type. An accompanying YAML text file contains associated beamline metadata for each measurement. Further details of the experimental setup can be found in a pdf document. The material data folder contains further details about the material and sample orientations, including an electron backscatter diffraction (EBSD) map that can be used to verify the crystallographic texture.

opencc-by-4.0Dec 2022View details →

Data from: Nest orientation and proximity to snow patches are important for nest site selection of a cavity breeder at high elevation

Abstract Reproductive timing and location are central to breeding success across taxa. Many species have evolved specific strategies to cope with environmental variability including shifts in timing of reproduction tracking resource availability or selecting favourable nest location. In mountain ecosystems, complex topography and pronounced seasonality result in particularly high spatiotemporal variability of environmental conditions, and the risk of climate-induced resource mismatches is particularly acute given that temperature is increasing more rapidly than in the lowlands. We investigated how a high-elevation passerine, the white-winged snowfinch Montifringilla nivalis, selects its nest site in relation to nest cavity characteristics, habitat composition and snow condition. We used a combination of field habitat mapping and satellite remote sensing to compare occupied nest sites with randomly selected pseudo-absence sites. In the first half of the breeding season, snowfinches preferred nest cavities oriented towards the morning sun while they used cavities proportional to their availability later on. This preference might relate to the nest microclimate offering eco-physiological advantages, namely thermoregulatory benefits for incubating adult and nestlings under the harsh conditions typically encountered in the alpine environment. Nest sites were consistently located in areas with greater-than-average snow cover at hatching date, likely mirroring the foraging preferences for tipulid larvae developing in meltwater along snowfields. Due to the particularly rapid climate shifts typical of mountain ecosystems, spatiotemporal mismatches between foraging grounds and nest sites are expected in the future, which may negatively influence demographic trajectories of the species concerned. The installation of well-designed nest boxes in optimal habitat configurations could to some extent help mitigate this risk.

opencc-by-4.0Feb 2023View details →

Datasets of the work named Development of a Low-Cost Smart Sensor GNSS System for Real-Time Positioning and Orientation for Floating Offshore Wind Platform

<pre>- 1_Motion_Simulator/     - IMU_results/         - 20211028101756.csv         - 20220114101543.csv         - 20220117000000.csv     - Rotary_Table/         - 15/             - rover_20220105.nav             - rover_20220105.obs             - solution_20220105_CAS.log         - 360/             - rover_20211221.nav             - rover_20211221.obs             - solution_20211221_CAS.log         - 360-15/             - rover_20220202_CAS.nav             - rover_20220202_CAS.obs             - solution_20220202_CAS.log     - Static_Tests/         - solution_SSRA00CAS0         - solution_SSRA00WHU0 - 2_GNSS_Signal_Simulator/     - platformmov_C1.xtd     - platformmov_C2.xtd     - platformmov_C3.xtd     - TestBetaNoneMov_C1     - TestBetaNoneMov_C1.nav     - TestBetaNoneMov_C1.obs     - TestBetaNoneMov_C1.ubx     - TestBetaNoneMov_C2     - TestBetaNoneMov_C2.nav     - TestBetaNoneMov_C2.obs     - TestBetaNoneMov_C2.ubx     - TestBetaNoneMov_C3     - TestBetaNoneMov_C3.nav     - TestBetaNoneMov_C3.obs     - TestBetaNoneMov_C3.ubx - 3_Test_Sea/     - 20220503000000.xlsx     - solution_28.nav     - solution_28.obs     - solution_28.ubx Background: {Journal Article using this dataset} 'Development of a Low-Cost Smart Sensor GNSS System for Real-Time Positioning and Orientation for Floating Offshore Wind Platform' Paper DOI: <a href="https://doi.org/10.3390/s23020925">https://doi.org/10.3390/s23020925</a> Abstract: a low-cost smart sensor GNSS system has been developed to provide accurate real-time position and orientation measurements on a floating offshore wind platform. The approach chosen to offer a viable and reliable solution for this application is based on the use of the well-known advantages of the GNSS system as the main driver for enhancing the accuracy of positioning. For this purpose, the data reported in this work are captured through a GNSS receiver operating over multiple frequency bands (L1, L2, L5) and combining signals from different constellations of navigation satellites (GPS, Galileo, and GLONASS), and they are processed through the precise point positioning (PPP) and real-time kinematic (RTK) techniques. Furthermore, aiming to improve global positioning, the processing unit fuses the results obtained with the data acquired through an inertial measurement unit (IMU), reaching final accuracy of a few centimeters. To validate the system designed and developed in this proposal, three different sets of tests were carried out in a (i) rotary table at the laboratory, (ii) GNSS simulator, and (iii) real conditions in an oceanic buoy at sea. The real-time positioning solution was compared to solutions obtained by post-processing techniques in these three scenarios and similar results were satisfactorily achieved. </pre>

opencc-by-4.0Mar 2023View details →

Dataset for BRDF representation in response to the build orientation in 3D-printed digital materials

This dataset folder contains data for the project "BRDF representation in response to the build orientation in 3D-printed digital materials" For more information please contact Ali Payami Golhin (payami.ag@gmail.com) Abbreviations: C:Cyan; M:Magenta; Y:Yellow; K:Black GoG: Glossy on Glossy finish; GoM: Glossy on Matte finish Folder "Color values": presents data for CIEXYZ, CIELab, CIELCh for 328 measurement geometries for each CMYK resins Folder "Spectral data": presents reflctance data for 328 measurement geometries for each CMYK resins. The first column in each file represent wavelength (nm) and the second column contains spectral data File "PCA.xlsx": presents PCA (PC1) scores for CMYK colors

opencc-by-4.0Jun 2023View details →

Dataset for 'Weld map tomography for determining local grain orientations from ultrasound'

This dataset contains data files and Jupyter notebooks used to produce figures in the manuscript 'Weld map tomography for determining local grain orientations from ultrasound'.

opencc-by-4.0Jul 2023View details →

SI2: How circular is an extractive economy? South Africa's export orientation results in low circularity and insufficient societal stocks for service-provisioning

Supporting information SI2 for the manuscript under review: How circular is an extractive economy? South Africa’s export orientation results in low circularity and insufficient societal stocks for service-provisioning     It provides the data used and the basic mass balanced calculation for a circularity assessment.

opencc-by-4.0Oct 2023View details →

FS_Orientation_Outline_Data

The following dataset contains the resulting normalized coefficients of Elliptical Fourier Analyses on frontal sinus outline data related to varying cranial orientation, associated with the grant listed below. The associated ReadMe file describes the samples and data collection procedures for the archived dataset.

Fig. 21 in Revision of the Eurybrachidae (XV). The Oriental genus Purusha Distant, 1906 with two new species and a key to the genera of Eurybrachini (Hemiptera: Fulgoromorpha: Eurybrachidae)

Fig. 21. Purusha vietnamica sp. nov., holotype, male genitalia (RBINS). A. Pygofer, anal tube and gonostylus, left lateral view. B. Posterodorsal process of left gonostylus, dorsal view. C. Anal tube, dorsal view. D. Pygofer and gonostyli, ventral view. E. Aedeagus, dorsal view. F. Aedeagus, left lateral view. Abbreviations: An = anal tube; G = gonostyli; Py = pygofer. Scale bars = 1 mm.

Fig. 13 in Revision of the Eurybrachidae (XV). The Oriental genus Purusha Distant, 1906 with two new species and a key to the genera of Eurybrachini (Hemiptera: Fulgoromorpha: Eurybrachidae)

Fig. 13. Purusha reversa (Hope, 1843), holotype, ♀ (OUMNH). A. Habitus, dorsal view. B. Habitus, ventral view. C. Head and thorax, dorsal view. D. Normal view of frons. E. Labels. C–E not to scale.

Fig. 6 in Revision of the Eurybrachidae (XV). The Oriental genus Purusha Distant, 1906 with two new species and a key to the genera of Eurybrachini (Hemiptera: Fulgoromorpha: Eurybrachidae)

Fig. 6. Purusha paradoxa (Gerstaecker, 1895), ♂ from Sumatra (RMNH). A. Habitus, dorsal view. B. Habitus, ventral view. C. Head and thorax, dorsal view. D. Normal view of frons. C–D not to scale.

Fig. 1 in Revision of the Eurybrachidae (XV). The Oriental genus Purusha Distant, 1906 with two new species and a key to the genera of Eurybrachini (Hemiptera: Fulgoromorpha: Eurybrachidae)

Fig. 1. Genera of Eurybrachini. A. Eurybrachys sp., ♀, dorsal view (USNM). B. Eurybrachys sp., ♂, dorsal view (USNM). C. Messena sp., ♀, dorsal view (RBINS). D. Nicidus fusconebulosus Stål, 1858, ♂, dorsal view (USNM). E. Purusha reversa (Hope, 1843), ♀, dorsal view (RBINS). F. Thessitus sp., ♂, dorsal view (RBINS). Scale bars = 10 mm.