cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mcryj6cnnh.1
title: PANNA: Properties from Artificial Neural Network Architectures

description: Prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.
DOI: 10.17632/rssf5nxxby.3
title: Data belonging to Predicting the 1p/19q co-deletion status of presumed low grade glioma with an externally validated machine learning algorithm

description: Data belonging to the 'Predicting the 1p/19q co-deletion status of presumed low grade glioma with an externally validated machine learning algorithm' paper, as publisched in Clinical Cancer Research. When using this data please cite: Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm. Sebastian R. van der Voort, Fatih Incekara, Maarten M.J. Wijnenga, Georgios Kapas, Mayke Gardeniers, Joost W. Schouten, Martijn P.A. Starmans, Rishie Nandoe Tewarie, Geert J. Lycklama, Pim J. French, Hendrikus J. Dubbink, Martin J. van den Bent, Arnaud J.P.E. Vincent, Wiro J. Niessen, Stefan Klein and Marion Smits. Clin Cancer Res December 15 2019 (25) (24) 7455-7462; DOI: 10.1158/1078-0432.CCR-19-1127 Data includes trained SVM models, image features derived for all patients, labels for all patients, PCE models used to derive feature importance and segmentations made for the LGG-1p19qDeletion dataset from The Cancer Imaging Archive (https://wiki.cancerimagingarchive.net/display/Public/LGG-1p19qDeletion#a888d85b04c640eeaf802e12db2dc8ad)
DOI: 10.17632/2t5c59rrrf.1
title: FLAME: A library of atomistic modeling environments

description: FLAME is a software package to perform a wide range of atomistic simulations for exploring the potential energy surfaces (PES) of complex condensed matter systems. The available methods include molecular dynamics simulations to sample free energy landscapes, saddle point searches to identify transition states, and gradient relaxations to find dynamically stable geometries. In addition to such common tasks, FLAME implements a structure prediction algorithm based on the minima hopping method (MHM) to identify the ground state structure of any system given solely the chemical composition, and a framework to train a neural network potential to reproduce the PES from ab initio calculations. The combination of neural network potentials with the MHM in FLAME allows a highly efficient and reliable identification of the ground state as well as metastable structures of molecules and crystals, as well as of nano structures, including surfaces, interfaces, and two-dimensional materials. In this manuscript, we provide detailed descriptions of the methods implemented in the FLAME code and its capabilities, together with several illustrative examples.
DOI: 10.17632/b87xzmzm2z.1
title: PWDFT.jl: A Julia package for electronic structure calculation using density functional theory and plane wave basis

description: We describe the implementation of PWDFT.jl, a package for electronic structure calculations written in Julia programming language using plane wave basis set and pseudopotentials. In this package, a typical Kohn–Sham density functional theory (KSDFT) is divided into three steps: initializing the molecular or crystalline structure, constructing the Kohn–Sham Hamiltonian, and solving the Kohn–Sham problem using self-consistent field (SCF) calculation. To facilitate various tasks involved in these steps, we provide several custom data types which are transparent and easy to be modified. Basic operations such as wave function orthogonalization, action of kinetic and potential operators to wave functions and iterative diagonalization of Hamiltonian have been implemented in pure Julia. Several algorithms to solve the Kohn–Sham problems such as self-consistent field and direct energy minimization have also been implemented in PWDFT.jl. To assess the validity of our implementation, we present the results of total energy calculations against the well-established ABINIT package. We also show how one can use PWDFT.jl to write a simple self-consistent field implementation.
DOI: 10.17632/phnz2gg8mz.1
title: CONUNDrum: A program for orbital-free density functional theory calculations

description: We present a new code for energy minimization, structure relaxation and evaluation of bulk parameters in the framework of orbital-free density functional theory (OF-DFT). The implementation is based on solving the Euler–Lagrange equation on an equidistant real space grid on which density dependent variables and derivatives are computed. Some potential components are computed in Fourier space. The code is able to use semilocal and non-local kinetic energy functionals (KEF) as well as neural network based KEFs thus facilitating testing and development of emerging machine-learned KEFs. For semi-local and machine-learned KEFs the kinetic energy potentials are evaluated with real-space differentiation of the components, which are partial derivatives of the KE with respect to the electron density, its gradient and Laplacian.
DOI: 10.17632/p85d34mc8w.1
title: 3D BM model
DOI: 10.17632/cr6gn33dzr.1
title: FaultRecovery

description: FaultRecovery is a tool to restore fault displacement, and you can easily obtain the horizontal displacement of fault with this tool. The following date include user manual, test data, output files, source code and Executable program
DOI: 10.17632/34rczh25kc.2
title: KU-MWQ: A Dataset for Monitoring Water Quality Using Digital Sensors.

description: Water quality depends on many factors. Among them some factors have direct effect in maintaining minimum sustainable environment. Any change in these parameters can affect them. Monitoring some of these mandatory water quality factors can help maintain water’s life sustainability. The following dataset contains parameters of three basic water quality factors. Temperature, pH factor and Water Turbidity. Arduino based digital sensors were used to collect these data. Two sets of sensors were used to measure data from different depth of the water label. Data were collected from a fish pond within the premises of Khan Jahan Ali Hall, Khulna University, 22.8054° N, 89.5370° E. It has an approximate area of 1350 square meter and depth of 3 meter. Data were recorded 24 hours continuously for 7 days, from 15 January 2020 to 22 January 2020. All the sensors collected data in parallel at the same time. An Arduino Mega microcontroller board acted as the central processing unit and recorded all the sensors’ data altogether. Recording rate was 1 set of data per minute in average. The dataset has total 9623 sets of data. Each set has multiple data samples from the corresponding sensors. Data file contents: Data 1:: Sensor data for 30 cm.xlsx: Contains raw sensor data collected from the first set of sensors, data of pH sensor, Temperature sensor and Turbidity sensor. All the sensors were 30 cm below from the water surface. This file has 9623 set of data each set having 3 data samples from the corresponding sensors. Data arrangement is described below: Column 1: Date and time of data recording in the format of YYYY-MM-DD [hh]:[mm]:[ss]. Time is in 24-hour format. Column 2: Data from Temperature sensor in °C. Temperature values have maximum two decimal places. Column 3: Data from pH sensor. pH values have maximum two decimal places. Column 4: Data from turbidity sensor in “NTU” unit. Data 2:: Sensor data for 60 cm.xlsx: Contains raw sensor data from the second set of sensors, data of Temperature sensor and Turbidity sensor. All the sensors were 60 cm below from the water surface. This file has 9623 sets of data each set having 2 data samples from the corresponding sensors. Data arrangement is described below: Column 1: Date and time of data recording, same as the previous file. Column 2: Data from Temperature sensor in °C. Temperature values have maximum two decimal places. Column 3: Data from turbidity sensor in “NTU” unit. Each row represents one set of data for that consecutive time of the day. Data samples were taken from a fixed place of the venue hence it represents the exact environmental condition of the place for that time period. Therefore this dataset can be used to determine environmental suitability of the local area for fish farming. Machine learning based projects can use this data for forecasting near future aquatic environmental condition. Such dataset can be also useful for unsupervised machine learning to detect anomalies.
DOI: 10.17632/6mw5gdwfkt.1
title: POLALMM: A program to compute polarizabilities for nominal one-electron systems using the Lagrange-mesh method

description: We present a program to compute polarizabilities of nominal one-electron systems using the Lagrange-mesh method (LMM) (Baye, 2015), that was used by Filippin et al., (2018). A semiempirical-core-potential approach is implemented, ultimately solving a Dirac-like equation by diagonalizing the corresponding Hamiltonian matrix. In order to build the core potential, the core orbitals are obtained from independent calculations using the Grasp2018 package (Fischer et al., 2019). Therefore we provide an easy-to-use interface between the Grasp2018 package and the LMM complete finite basis, allowing to switch easily from one one-electron basis to the other.
DOI: 10.17632/5rdw9jv5vp.1
title: AMP2: A fully automated program for ab initio calculations of crystalline materials

description: Ab initio calculations based on the density functional theory (DFT) become a vital tool in material science for understanding and predicting material properties. However, DFT calculations involve several parameters and procedures that call for deep understanding on underlying theories and preceding knowledge on certain properties of target materials. Such technicalities cost a significant amount of human time and expose practitioners to mistakes. Here, we introduce a fully automated package for DFT calculations, automated ab initio modeling of materials property package (AMP2), which aims to produce key DFT properties of crystalline materials with essentially no user intervention except for initial structural information. This is achieved through algorithms that automatically determine various technical parameters and make self-decisions during computational workflow. As results, AMP2 is material-agnostic and provides a highly accurate band structure, band gap, effective mass, density of states and dielectric constant for the given material. Notably, the package finds the antiferromagnetic ground state by applying a genetic algorithm to effective Ising models. AMP2 also addresses band-gap underestimation in semilocal functionals with help of a hybrid functional, thereby producing a more accurate band gap, even if the material turns out to be metallic within the semilocal functional. We believe that the present package will significantly expand usage of DFT calculations by making them more accessible.
DOI: 10.17632/k74twh2phn.1
title: Tribological behaviour study of aluminium-alumina hybrid nano metal matrix composites
DOI: 10.17632/hzkg4h4v6b.2
title: Studies on the Influence of Stirrer Blade Design on the Microstructure and Mechanical Properties of a Novel Aluminium Metal Matrix Composite
DOI: 10.17632/4cb2cngpf2.1
title: Data for the analyses of the " Recent volcano-tectonic activity of the Ririba rift and the evolution of rifting in South Ethiopia"

description: This repository comprehends all the data supporting the analysis of the recent volcano-tectonic activity of the Ririba rift, at the southern tip of the Ethiopian Rift Valley, near the Kenya/Ethiopia border. It consists of a pdf file, two .kmz files and two Excel tables. Specifically, the pdf file ('Supplementary material') includes a list of the samples collected during fieldwork (Table S1), details concerning the methodology employed in the morphometric analysis of volcanic structures (S2) and in the statistical analysis of vent clustering and its results (S3), and chemical analysis of the collected volcanic rock samples (Table S4). The two Excel tables report the data used for the morphometric analysis of the subset of volcanic centres (specifically, 26 for Dilo VF and 41 for Mega VF) which could be well delimited from satellite images (Table S2d contains information of the volcanic cones and lava flows, while Table S2e regards maars and tuff rings). The data collected from remote sensing analysis of the two volcanic fields it is also reported as two .kmz files ("Dilo VF" and "Mega VF"). In each volcanic field, the subset of volcanic centres which have been used to extract morphometric measurements, lava flows, characteristic alignment and vent elongation trends and the sampling sites of the collected rocks are marked.
DOI: 10.17632/dnhjb3ymcc.2
title: Dataset for the publication intitled "Construction and psychometric evaluation of the Scale for the Assessment of Strategies on Writing"

description: Dataset for the publication intitled "Construction and psychometric evaluation of the Scale for the Assessment of Strategies on Writing"
DOI: 10.17632/brx6gb5887.2
title: Details of the specification of different MDR pattern (P1-4) according to the antibiotypes of the isolates

description: Details of the different MDR pattern and antibiotypes of E. coli of healthy ostrich and poultry with colibacillosis
DOI: 10.17632/nm45wtkt2k.1
title: 2019_Meathybrid
DOI: 10.17632/y9dgyhx99w.2
title: Data for: Photo-optical luminance analysis of transfer films: Measurement principle, data analysis and result plotting

description: The shown results in this article are meant to be a demonstration of the presented method. The data files included in this archive contain all raw data used for plotting all the figures shown in the article. The shown figures are based on three different, but representative experiments. The file numbers represent our internal identification number (ID). Use the following key to resolve IDs to material names and a short description of the material: ID 546214 (EP-10SCF) refers to a bisphenol A based epoxy (DER 331, DOW) filled with 10 vol.% short carbon fiber (A385, Tenax) and was in-house manufactured. ID 548671 (PA6-10SCF-8Gr) refers to a polyamide 6 (Durethan, Lanxess) filled with 10 vol. % short carbon fibers (A385, Tenax) and 8 vol.% graphite (RGC39A, Superior Graphite) and was in-house manufactured. ID 550187 (PPS-40GR) refers to a polyphenylene sulfide filled with 40 wt.% graphite which is commercially available as TECACOMP PPS TC black 4084 by Ensinger, Germany. To each id belong at least of two files, one with file extension 'proc' and one with 'proc.header.yaml'. The proc file is a tab separated ascii table and contains data recorded by our tribometer as well as data processed from them. The yaml files contain all necessary header information of each respective proc file of which especially the header name and (column) index is important for reproduction purpose. Additionally, id 550187 contains files with extension 'xt' and 'xt.header.yaml'. The xt file is tab separated ascii table and contains the temporally and laterally resolved data of the luminance used for plotting the xt plot. The yaml file, similar for the proc file, contain all necessary header information. Information for importing the data files: All header files follow a standardized serialization format called yaml. The proc and xt files files are tab separated ascii tables. Therefore, all data can be easily read by any programming language of your choice, e.g. python, ruby or matlab. With minimal effort, an import into excel or similar software is also possible.
DOI: 10.17632/c6jxj2kgry.1
title: A Reference-Dependent Utility Model of Attraction and Compromise Effects_Study 1

description: Data set for reference dependence of context effects (Study 1). Participants were told to imagine that they would be making product choices across several categories. The order in which they saw the four product categories was randomized. For purposes of illustration, we use the lawn mower category here. Participants were told that they were looking to buy a lawn mower, and were about to choose between two (or among three) options. They were also told that these options differed mainly on the two attributes presented and were otherwise similar on other relevant attributes. Participants were then asked to choose one of the lawn mowers. They repeated the choice task for the remaining three product categories. They then indicated their gender and age, followed by whether (a) they responded randomly at any point during the study, and (b) they read the instructions. The data was gathered from Amazon MTurkers in August 2019.
DOI: 10.15161/oar.it/30552
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.17632/f5t9d2fp8y.1
title: Nitrate accumulation in lemna minor on 6 different media

description: Duckweed is a potential alternative protein source for food and feed. However, little is known about the nitrate accumulation in this plant. A high nitrate level in vegetables can indirectly lead to an elevated intake of nitrites and N-nitroso compounds, increasing the risk of diseases for humans and animals. This research evaluated whether duckweed grown on different media accumulates nitrate beyond legal safety levels for human and animal intake. Duckweed was grown on (i) rainwater, and (ii) three synthetic media containing different nutrient levels. Furthermore, (iii) biological effluent of swine manure treatment and (iv) aquaculture effluent from pikeperch production were used, as these are potential media for closing nutrient loops in the agriculture sector. It was found that nitrate levels increased with the increasing availability of macronutrients in the water, and pH showed a particularly strong negative correlation with the nitrate levels in duckweed. Nevertheless, nitrate content of duckweed never exceeded 530 mg NO3 kg-1 fresh weight. To conclude, duckweed’s nitrate content was below safety limits for human consumption in all tested growing media; however, a potential risk for ruminants was observed as these are more sensitive to nitrate conversions in their gastro-intestinal track. The first tab contains information on the units and the measured parameters in both the water and duckweed.
DOI: 10.17632/vt4xjss66j.1
title: 空调集群的需求响应潜力分析数据

description: 本数据集基于Umass数据集、美国Austin地区居民用户用电数据集、中国某省台区用电数据进行空调集群的需求响应潜力分析
DOI: 10.17632/ph7tf2y7k3.5
title: Huijing Wang's Data

description: These are supplementary materials for "Characteristics, treatments, and outcomes of Chinese Patients with Giant Congenital Melanocytic Nevus: A Retrospective Cohort Study".
DOI: 10.17632/kdn5v76wb3.1
title: Fake COVID-19

description: Synthetic COVID-19 dataset, including 1186 chest CT images
DOI: 10.17632/4dg2c9vzft.3
title: Data for: Estimating apple flower stigma temperature with infrared thermography, thermocouples, and development of a proxy temperature model for potential use in fire blight predictions.

description: Thermal_Imagery_Data.csv is the processed data for the infrared thermograph on flower temperatures. - The column IR_Temperature indicates the infrared temperature (in Celcius). - The column Mounted_Thermocouple is either a number or a nan. When it is a number, it refers to the thermocouple that was measuring the same flower at the time of the thermal photograph. - The column Cloud_Cover indicates the cloud cover at the time of sampling (C for cloudy, S for sunny, M for mixed, N for night). - The column ID is to distinguish each flower. Weather_Station_Data.csv is the raw weather data taken by the weather station within the orchard - Data is for 2018 and 2019, from May 1 to July 1 - The columns Max_Temperature, Min_Temperature, Mean_Temperature all refer to the hourly maximum, minimum and mean temperature recorded at the station - The columns with the added sufix "Lag" indicates that it is the data from the previous hour. - The column Cloud_Cover is to indicate the cloud cover at each hour (C for cloudy, S for sunny, N for night) Thermocouple_Data.csv is the processed thermocouple data taken from the stationnary thermocouples for both 2018 and 2019 - Each number in paranthese (ex : Temp_C_Avg(1)) designates a specific thermocouple - The columns with "Avg" are for the 5-min average temperature data, the columns with "Min" are for the 5-min minimum temperature recorded data and the columns with "Max" are for the 5-min maximum temperature recorded data. - When there is no data means that there was no recording at that time or that it was removed because the thermocouple was detached from the flower.
DOI: 10.17632/w7m95wwrb5.1
title: Mujoco demonstrates for Imitation learning

description: This dataset can be used for studying imitation learning for robot control.
DOI: 10.17632/ysx3m9p3s3.1
title: FEV1/FEV6 DPD COPD data

description: this data was collected for evaluation of FEV1/FEV6 as surrogate for FEV1/FVC for COPD diagnosis
DOI: 10.17632/dv43z9x72t.1
title: Analysis code and raw data for 'Automatic Etch Pit Density Analysis in Multicrystalline Silicon'

description: "etch_pit_density_analysis.zip" contains the analysis code. See the README.txt for more information. "secco_etched_mc_Si_wafer_image.png" - Optical microscope image, depicting a 2.5cm*1.2cm Secco etched multicrystalline Silicon wafer. Dark spots are etch pits, typically associated with dislocation lines that intersect with the wafer surface. Dark lines are grain boundaries. The leftmost 20% of the wafer have been in contact with the sample carrier during defect etching, explaining the uneven etch result.
DOI: 10.17632/34z9fm2ptw.1
title: Data for: When and where did the Tibetan Meso-Tethys Ocean open? Volcanic and paleomagnetic evidence for a Mid-Triassic rifting between the Lhasa and Qiangtang Terranes

description: The supplementary data for "When and where did the Tibetan Meso-Tethys Ocean open? Volcanic and paleomagnetic evidence for a Mid-Triassic rifting between the Lhasa and Qiangtang Terranes" include sample analysis data (Bulk-rock major, trace element and Sr-Nd-Pb isotopic of the trachytic lavas, Zircon LA-ICP-MS U-Pb age data, and Zircon Hf isotopic data), and paleomagnetic data of the Lhasa and Qiangtang terranes.
DOI: 10.17632/4dcz8cj7cs.1
title: Research data

description: Research data for the manuscript Full moment-deflection response and bond stiffness reduction of RC elements strengthened with prestressed FRP materials by Justas Slaitas and Juozas Valivonis