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In this paper, the relationship between anisotropic mechanical properties and corresponding microstructure evolution of wrought magnesium alloys is critically reviewed. The experimental observations on the strong anisotropy (including strength differential effect) induced by texture and twinning are investigated under different loading conditions (i.e., monotonic loading, cyclic loading and multiaxial loading).
Data Types:
  • Tabular Data
  • Document
Datasets in this publication report the number of diagnoses with coronavirus disease (COVID-19) based on RIVM reports in The Netherlands. Since 3 March, RIVM reports the number of diagnoses with the coronavirus and their municipality of residence on a daily base. The data contains the total number of positively tested patients. It is not a dataset with the current number of sick people in the Netherlands. The RIVM does not currently provide data on people who have been cured. RIVM provides daily updates of the data. The data is not stored in a persistent way and is updated on the fly. RIVM removes data from previous days from their website. Therefore, it is not possible to monitor the spread of the coronavirus disease in the Netherlands on this data standalone. The data in this publication is composed of hourly downloads of the data of the website of RIVM. All code to compose the data was found on https://github.com/J535D165/CoronaWatchNL as well as graphs based on the data.
Data Types:
  • Tabular Data
  • Dataset
Datasets in this publication report the number of diagnoses with coronavirus disease (COVID-19) based on RIVM reports in The Netherlands. Since 3 March, RIVM reports the number of diagnoses with the coronavirus and their municipality of residence on a daily base. The data contains the total number of positively tested patients. It is not a dataset with the current number of sick people in the Netherlands. The RIVM does not currently provide data on people who have been cured. RIVM provides daily updates of the data. The data is not stored in a persistent way and is updated on the fly. RIVM removes data from previous days from their website. Therefore, it is not possible to monitor the spread of the coronavirus disease in the Netherlands on this data standalone. The data in this publication is composed of hourly downloads of the data of the website of RIVM. All code to compose the data was found on https://github.com/J535D165/CoronaWatchNL as well as graphs based on the data.
Data Types:
  • Tabular Data
  • Dataset
Data on competency (360 degree feedback), employability and career success
Data Types:
  • Tabular Data
  • Document
Filename: 1_wind_vector_tunnels.xlsx Variables: 1. variant - experimental approach: W- wind tunnel; V - vector tunnel 2. rep_id - repetition number 3. pop - population size on the source patch 4. n_disp - number of individuals that left the source patch 5. n_col - population size on the target patch after several generations Filename: 2_departure_tunnel.xlsx Variables: 1. variant - host plant species: B - smooth brome (Bromopsis inermis); W - wheat (Triticum aestivum) 2. rep_id - - repetition number 3. n_beg - number of individuals at the beginning of the experimental session 4. n_end - number of individuals at the end of the experimental session 5. n_blown - number of individuals blown away
Data Types:
  • Tabular Data
  • Dataset
This database provides construction of Large Urban Regions (LUR) in the world. A Large Urban Region (LUR) can be defined as an aggregation of continuous statistical units around a core that are economically dependent on this core and linked to it by economic and social strong interdependences. The main purpose of this delineation is to make cities comparable on the national and world scales and to make comparative social-economic urban studies. Aggregating different municipal districts around a core city, we construct a single large urban region, which allows to include all the area of economic influence of a core into one statistical unit (see Rozenblat, 2020 or Rogov & Rozenblat, 2020 for Russia). In doing so we use four principal urban concepts (Pumain et al., 1992): local administrative units (Municipality or localities: MUNI), morphological urban area (MUA), functional urban area (FUA) and conurbation that we call Large Urban Region (LUR). The LURs are the spatial extensions of influence of one or several FUAs or MUAs. MUAs and FUAs are defined by various national or international sources. We implemented LURs using criteria such as the population distribution among one or several MUAs or FUAs, road networks, access to an airport, distance from a core, presence of multinational firms. FUAs and MUAs perimeters, if they form a part of a LUR, belong to a unique LUR. In this database we provide the composition of the LURs in terms of local administrative units (MUNI), Morphological Urban Area (MUA), Functional Urban Area (FUA).
Data Types:
  • Tabular Data
  • Dataset
ESEC/FSE 2020 Submission #527 Dataset This dataset contains the NPM packages that we built using our tool-chain. It consists of the diffoscope outputs, the versions built by our tool-chain, and the pre-built packages present on the npmjs registry.
Data Types:
  • Tabular Data
  • Dataset
  • File Set
The data and Python script are part of the forum article "A text mining analysis of the climate change literature in industrial ecology" authored by Dayeen, F.R., Sharma, A.S., and Derrible, S., and published in the Journal of Industrial Ecology in 2020. The Python script and instructions are included in the LiTCoF_v1.00-py.zip file. The original data is available in two formats: .csv and .pkl. Updates of the script will be posted at https://github.com/csunlab/LiTCoF and at https://csun.uic.edu/codes/LiTCoF.html. The data is also available at https://csun.uic.edu/datasets.html#AbstractsIE. Feel free to contact any of the authors for information and questions about the data and code.
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
  • File Set
The data was collected from a common garden genetics trial established in 2008 in northern Alberta, Canada. The trial represents 1978 (initial number) hybrid poplar clones from 63 families and includes interspecific crosses between Populus deltoides (D), Populus nigra (N), Populus balsamifera (B), P. maximowiczii (M), and P. × petrowskyana (P. laurifolia × P. nigra). Female clone 24 (‘Walker’ = (Populus deltoides × (P. laurifolia × P. nigra))) and male progeny clone 2403 (‘Okanese’ = (‘Walker’ × (P. laurifolia × P. nigra))) were used as reference clones. The study design was a randomized complete block design, with one ramet per clone in each of four blocks. Measurements were carried out after three, eight, and 10 growing seasons on the genetics trial. Results presented in ‘HybridPoplarsTrial.csv’ file, show is the raw data, while ‘Summary data.csv’ contains the mean values for clones obtained from the four blocks. Measured and calculated traits include: DBH (diameter at breast height; 1.3 m); H (height); canker (canker severity caused by Sphaerulina musiva (scale 0-3)); MAI (mean annual increment), V (volume). Description of headings: Trait [unit] - Description DBH_Age_3 [cm] - diameter at breast height at age 3 H_Age_3 [m] - height at age 3 DBH_Age_8 [cm] - diameter at breast height at age 8 H_Age_8 [m] - height at age 8 H_Age_10 [m] - height at age 10 DBH_Age_10 [cm] - diameter at breast height at age 10 Canker_Age_8 - canker severity caused by Sphaerulina musiva (scale 0-3) Canker_Age_10 - canker severity caused by Sphaerulina musiva (scale 0-3) V_Age_8 [m3 ha-1] - volume at age 8 MAI_Age_8 [m3 ha-1 yr-1] - mean annual increment at age 8 V_Age_10 [m3 ha-1] - volume at age 10 MAI_Age_10 [m3 ha-1 yr-1] - mean annual increment at age 10 WD_Age_10 [kg m-3] - wood density at age 10
Data Types:
  • Tabular Data
  • Dataset
TinySOL ======= Version 1.0, January 2020. Created By -------------- Carmine-Emanuele Cella (1), Daniele Ghisi (1), Vincent Lostanlen (2), Fabien Lévy (3), Joshua Fineberg (4), Yan Maresz (5) (1): UC Berkeley (2): New York University (3): Columbia University (4): Boston University (5): Conservatoire de Paris Description --------------- TinySOL is a dataset of 2478 samples, each containing a single musical note from one of 14 different instruments: Bass Tuba French Horn Trombone Trumpet in C Accordion Contrabass Violin Viola Violoncello Bassoon Clarinet in B-flat Flute Oboe Alto Saxophone These sounds were originally recorded at Ircam in Paris (France) between 1996 and 1999, as part of a larger project named Studio On Line (SOL). Although SOL contains many combinations of mutes and extended playing techniques, TinySOL purely consists of sounds played in the so-called "ordinary" style, and in absence of mute. TinySOL can be used for creative purposes insofar at the use complies with the Creative Commons Attribution 4.0 International license (see below). TinySOL can be used for education and research purposes. In particular, it can be employed as a dataset for training and/or evaluating music information retrieval (MIR) systems, for tasks such as instrument recognition or fundamental frequency estimation. For this purpose, we provide an official 5-fold split of TinySOL. This split has been carefully balanced in terms of instrumentation, pitch range, and dynamics. For the sake of research reproducibility, we encourage users of TinySOL to adopt this split and report their results in terms of average performance across folds. Data Files -------------- TinySOL contains 2478 audio clips as WAV files, sampled at 44.1 kHz, with a single channel (mono), at a bit depth of 16. This is equivalent to the audio quality of a compact disc. Audio clips vary in duration between two and ten seconds. Every audio file has a file path of the form: //ordinario/-ord---.wav where: corresponds to the instrument family: "Brass", "Keyboards" (includes accordion), "Strings", and "Winds" (i.e., woodwinds). is the full name of the instrument. "ordinario" denotes the ordinary playing technique. This is in contrast with the rest of the SOL dataset, which also encompasses extended playing techniques denotes the pitch of the musical note. This pitch is encoded in the American standard pitch notation: pitch class (C means "do") followed by pitch octave. According to this convention, A4 has a fundamental frequency of 440 Hz. denotes the intensity dynamics, ranked from pp (pianissimo) to ff (fortissimo). contains additional information, when applicable. For example, for bowed string instruments, the same pitch may sometimes be achieved on different positions and different strings, resulting in small timbre differences. In this case the label "1c", "2c", "3c", or "4c" denotes the string which is being bowed. (The letter c originates from the word "corde", which means string in French.) By convention, the first string is the one with the highest pitch when played as an open string. Furthermore, some pitches were never recorded, and thus missing from the chromatic scale. In this case, the tag contains a letter "R", to denote the fact that the corresponding WAV file has been obtained by transforming a different audio clip via some digital frequency transposition. The letter "R" stands for "resampled". If none of these tags apply, the field becomes "N", which stands for "None". For example, "Strings/Violin/ordinario/Vn-ord-G#6-mf-1cR.wav" corresponds to: a violin sound ; played in the ordinary playing technique ; at pitch G#6 (approximately 1661 Hz) ; with mezzoforte dynamics ; on the first string ; and resampled from a different sound, as opposed to genuinely recorded. Metadata File ------------------- The TinySOL_metadata.csv file contains 2478 rows, one for each audio clip. It can be opened by a text editor or by a spreadsheet software application. It contains 13 columns: Path to the WAV file, in UNIX filesystem format. For Windows compatibility, replace the slashes ("/") by backslashes ("\"). Ex: "Brass/BTb/BTb-ord-A#1-ff-N.wav" Fold ID. Either equal to 0, 1, 2, 3, or 4. Family. Ex: "Brass" Instrument abbreviation. Ex: "BTb" Instrument name in full. Ex: "Bass Tuba" Technique abbreviation. Always equal to "ord" in the case of TinySOL. Technique name in full. Always equal to "ordinario" in the case of TinySOL. Pitch. Ex: "A#1" Pitch ID in MIDI format. Ex: 34. Integer in the range 0-127. Dynamics. Ex: "ff". Dynamics ID. Integer. pp maps to 0 and ff maps to 4. The higher, the louder. Resampled. True if the file has been pitch-shifted; False otherwise. String ID. Equal to 1, 2, 3, 4, or empty if not applicable. Conditions of Use ------------------------ TinySOL was created in 2020 by Carmine-Emanuele Cella, Daniele Ghisi, Vincent Lostanlen, Fabien Lévy, Joshua Fineberg, and Yan Maresz. TinySOL is a derivative of SOL. We wish to thank Hugues Vinet and all coordinators of the Ircam Forum for their authorization to upload TinySOL to Zenodo. TinySOL is offered free of charge under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license: https://creativecommons.org/licenses/by/4.0/ The dataset and its contents are made available on an "as is" basis and without warranties of any kind, including without limitation satisfactory quality and conformity, merchantability, fitness for a particular purpose, accuracy or completeness, or absence of errors. Subject to any liability that may not be excluded or limited by law, the authors are not liable for, and expressly exclude all liability for, loss or damage however and whenever caused to anyone by any use of the TinySOL dataset or any part of it. We encourage TinySOL users to subscribe to the Ircam Forum so that they can have access to larger versions of SOL. While downloading full version of SOL requires premium membership (for a yearly fee), a medium-sized version named OrchideaSOL is made available free of charge to all members. Note, however, that TinySOL is the only subset of SOL which is released under a Creative Commons License. For more information, please visit: https://forum.ircam.fr/ Feedback ------------- Please help us improve TinySOL by sending your feedback to: carmine.cella@berkeley.edu For issues regarding the metadata encoding, the five-fold split, or the TinySOL module in mirdata, please write to: vincent.lostanlen@nyu.edu In case of a problem, please include as many details as possible.
Data Types:
  • Tabular Data
  • Dataset
  • File Set