cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3588440
title: ConFire Model input/output for South America

description: ConFIRE input and output used in the submission of Kelley et al. "Low Climatic Influence found in 2019 Amazonia Fires". "input" dir including "amazon_inference_data-2002-MCDBA_obs-TERRA_M__T.csv", just contains a csv file of all common grid data in other "input" subdirectories, which can be used in "optimise_run_model/bayesian_inference.ipynb" notebook. The files in the subdirectories are then used to make gridded model output using "optimise_run_model/make_model_output.ipynb". Output, also provided, is summerized in the files in "outputs/sampled_posterior_ConFire_solutions/constant_post_2018_full_2002_BG2020/" The three files contain: fire_summary_frequancy_of_counts.nc - Contains one spatial variable (long name "firecount frequency of occurrence") is the probability of a fire count (along the model_level_number dimension) at a particular month (time dimension) according to the models full posterior, \(P(y_j)\)(see papers supplementary). All months start on Jan 2001. fire_summary_precentile.nc - Contains one spatial variable (long name "firecount at percentile"), the fire count at each percentile of the full posterior in 1% increments from 1-99% (along the model_level_number dimension). Note, by definition, the 0a nd 100% percentile is 0 and \(\infty \) . fire_summary_observed_liklihood.nc - the position ( "variable_0") and p-value ("variable") of MCD64A1 in the model posterior. model_summary.nc - Summary of each variable of ConFire: "burnt_area": burnt area or fire count summary, described as percentiles as per "fire_summary_precentile", but this time just assessing parameter uncertainty, i.e \(P(\beta | Y_s)\) in supplementary of paper. All other variables describe different model controls in the same "burnt_area". Full information on how controls are constructed can be found in Kelley et al. (2019) with updates listed in supplementary of this paper. "fuel_continuity", "moisture_content", "ignitions", "suppression" are the actual values of the control "standard_&lt;&lt;control&gt;&gt;" is the standard limitation imposed by the control. "potential_&lt;&lt;control&gt;&gt; is the potential limitation "sensitivity_&lt;&lt;control&gt;&gt; is the senstivity of fire to a particular control.<br> <br> See Kelley et al. 2019 for the definition of limitation types and sensitivity Kelley, D.I., Bistinas, I., Whitley, R. <em>et al.</em> How contemporary bioclimatic and human controls change global fire regimes. <em>Nat. Clim. Chang.</em> <strong>9, </strong>690–696 (2019) doi:10.1038/s41558-019-0540-7
description: {"references": ["Kelley, D. I., Burton, C., Huntingford, C., J., B. M. A., Whitley, R. and Dong, N.: Low meteorological influence found in 2019 Amazonia fires, Biogeosciences, submitted.", "Kelley, D. I., Bistinas, I., Whitley, R., Burton, C., Marthews, T. R. and Dong, N.: How contemporary bioclimatic and human controls change global fire regimes, Nat. Clim. Chang., 9(9), 690\u2013696, 2019."]}
DOI: 10.5286/isis.e.rb2010098-2
title: The magnetic structure of CeFe12-xMnx (x = 5, 7)

description: Permanent magnets are material which retain magnetization even in absence of an applied magnetic field. A prototypical use is thus a common refrigerator magnet, however, they have wide-spread use in for instance renewable energy production in wind-mills and energy conversion in electrical vehicles. As of current, there exists a large gap between low-performance ferrite magnets and high-performance neodymium magnets. The aim here is to investigate the magnetic structure of cerium iron manganese alloys. These material have the potential to become viable gap magnets if the temperature at which they lose there magnetization is raised. To be able to tune the transition temperature we need to understand the baseline characteristics of these materials, i.e. solving its magnetic structure.
DOI: 10.21227/aq4d-wk56
title: 1.88kW BLDC Sensorless FOC with Adaptive Sliding Mode Observer

description: This dataset is on the study of Motor controllers, for which author has done numerous experiments, and the analysis along with these will also be shortly submitted to "IEEE Transactions on Power Electronics".The results contained in this dataset are graphs which give intutive idea on the control characteristics, whether the pole/zero is on the imaginary axis or the right half plane. Still in today's practice, the switching frequency for these controllers are used even 20 kHz or more, whereas MOSFETs can be switched to 2 MHz.BLDC motors ae used in medical industry ,ventillators, solar trackers, CNC servodrives, industrial robots, automative, electric vehicles- autos, rickshaws etc.Using this dataset, the industrial engineer can decide whether to run at that frequency or not. So, this study comes in handy to decide when designing in practice for industries and also for academia purposes.In this particular dataset, MOSFET is switched from 20 kHz to 2MHZ , at 46 different PWM frequencies and the resulting characteristics. The speed and the position estimation of BLDC is done using the sensorless vector control method i.e., Field Oriented control (FOC) with the addition of SMO observer which gives the estimation of speed and the sensorless rotor position. The switching pattern of the 3-phase inverter is implemented using space vector modulation.DIfferences in this paper dataset can be seen as the author has included following , with analysis which can be drawn from seeing attached graphs -performance comparison using Sliding Mode Observer (SMO) at different frequencies.PWM switching frequency is varied 46 times from 20 kHz to 2 MHz , - will help decide MOSFETs switching frequency. (as in industries even 20kHz is used)Of course, the Rdson, dc link inverter voltage ,other practical parameters etc has been taken into consideration (not submitted here) bu some analysis related to it,you may find in the authors Transaction paper.Separate results at all these 46 frequenciesStability Margins - Gain/PhaseOpen Loop Control PerformanceTransfer Function CompensationClosed loop TuningRoot Locus of Uncompensated System and Compensated SystemBode Plot - magnitude and phasePole Zero Map of Uncompensated System and Compensated SystemUnit-Step Response of Uncompensated System and Compensated SystemNyquist plot of Uncompensated System and Compensated SystemNichols chart of Uncompensated System and Compensated SystemImpulse Response of Uncompensated System and Compensated SystemSinusoidal ExcitationAll this is implemented on 32-bit Real-Time microcontroller. The pins usage not mentioned here are used for other General-Purpose-CAN,USB, RS485 etc.
DOI: 10.21227/591t-9w98
title: 1.88kW BLDC Sensorless FOC with Adaptive Sliding Mode Observer

description: This dataset is on the study of Motor controllers, for which author has done numerous experiments, and the analysis along with these will also be shortly submitted to "IEEE Transactions on Power Electronics".The results contained in this dataset are graphs which give intutive idea on the control characteristics, whether the pole/zero is on the imaginary axis or the right half plane. Still in practice, the switching frequency for these controllers are used even 20 kHz or more, whereas MOSFETs can be switched to 2 MHz.BLDC motors ae used in medical industry ,ventillators, solar trackers, CNC servodrives, industrial robots, automative, electric vehicles- autos, rickshaws etc.Using this dataset, the industrial engineer can decide whether to run at that frequency or not. So, this study comes in handy to decide when designing in practice for industries and also for academia purposes.In this particular dataset, MOSFET is switched from 20 kHz to 2MHZ , at 46 different PWM frequencies and the resulting characteristics.The speed and the position estimation of BLDC is done using the sensorless vector control method i.e., Field Oriented control (FOC) with the addition of SMO observer which gives the estimation of speed and the sensorless rotor position. The switching pattern of the 3-phase inverter is implemented using space vector modulation.DIfferences in this paper dataset can be seen as the author has included following , with analysis which can be drawn from seeing attached graphs -performance comparison using Sliding Mode Observer (SMO) at different frequencies.PWM switching frequency is varied 46 times from 20 kHz to 2 MHz , - will help decide MOSFETs switching frequency. Of course, the Rdson, dc link inverter voltage ,other practical parameters etc has been taken into consideration (not submitted here) bu some analysis related to it,you may find in the authors Transaction paper.Separate results at all these 46 frequenciesStability Margins - Gain/PhaseOpen Loop Control PerformanceTransfer Function CompensationClosed loop TuningRoot Locus of Uncompensated System and Compensated SystemBode Plot - magnitude and phasePole Zero Map of Uncompensated System and Compensated SystemUnit-Step Response of Uncompensated System and Compensated SystemNyquist plot of Uncompensated System and Compensated SystemNichols chart of Uncompensated System and Compensated SystemImpulse Response of Uncompensated System and Compensated SystemSinusoidal ExcitationAll this is implemented on 32-bit Real-Time microcontroller. The pins usage not mentioned here are used for other General-Purpose-CAN,USB, RS485 etc.
DOI: 10.21227/kbyh-f835
title: 1.88kW BLDC Sensorless FOC with Adaptive Sliding Mode Observer

description: This dataset is on the study of Motor controllers, for which author has done numerous experiments, and the analysis along with these will also be shortly submitted to "IEEE Transactions on Power Electronics".The results contained in this dataset are graphs which give intutive idea on the control characteristics, whether the pole/zero is on the imaginary axis or the right half plane. Still in practice, the switching frequency for these controllers are used even 20 kHz or more, whereas MOSFETs can be switched to 2 MHz.BLDC motors ae used in medical industry ,ventillators, solar trackers, CNC servodrives, industrial robots, automative, electric vehicles- autos, rickshaws etc.Using this dataset, the industrial engineer can decide whether to run at that frequency or not. So, this study comes in handy to decide when designing in practice for industries and also for academia purposes.In this particular dataset, MOSFET is switched from 20 kHz to 2MHZ , at 46 different PWM frequencies and the resulting characteristics.The speed and the position estimation of BLDC is done using the sensorless vector control method i.e., Field Oriented control (FOC) with the addition of SMO observer which gives the estimation of speed and the sensorless rotor position. The switching pattern of the 3-phase inverter is implemented using space vector modulation.DIfferences in this paper dataset can be seen as the author has included following , with analysis which can be drawn from seeing attached graphs -performance comparison using Sliding Mode Observer (SMO) at different frequencies.PWM switching frequency is varied 46 times from 20 kHz to 2 MHz , - will help decide MOSFETs switching frequency.Of course, the Rdson, dc link inverter voltage ,other practical parameters etc has been taken into consideration (not submitted here) bu some analysis related to it,you may find in the authors Transaction paper.Separate results at all these 46 frequenciesStability Margins - Gain/PhaseOpen Loop Control PerformanceTransfer Function CompensationClosed loop TuningRoot Locus of Uncompensated System and Compensated SystemBode Plot - magnitude and phasePole Zero Map of Uncompensated System and Compensated SystemUnit-Step Response of Uncompensated System and Compensated SystemNyquist plot of Uncompensated System and Compensated SystemNichols chart of Uncompensated System and Compensated SystemImpulse Response of Uncompensated System and Compensated SystemSinusoidal ExcitationAll this is implemented on 32-bit Real-Time microcontroller. The pins usage not mentioned here are used for other General-Purpose-CAN,USB, RS485 etc.
DOI: 10.6084/m9.figshare.7093565
title: Pilot Phase of the Pakistan Microbiome Initiative

description: Quality-controlled FASTQ files of 16S rRNA gene sequencing in gut and oral samples
DOI: 10.6084/m9.figshare.7093565.v1
title: Pilot Phase of the Pakistan Microbiome Initiative

description: Quality-controlled FASTQ files of 16S rRNA gene sequencing in gut and oral samples
DOI: 10.6084/m9.figshare.11605296
title: DATASET: Locked Cryptocurrencies in Ethereum

description: <br>(1) Destructed contracts with locked ETH/CBC.<br>(2) Attacked Parity wallet contracts with locked ETH/CBC.<br>(3) Contract-creation failure accounts with locked ETH/CBC.<br>(4) Analyzed transactions.<br><b>BibTeX citation:</b>@inproceedings{li2021clue, title={CLUE: Towards Discovering Locked Cryptocurrencies in Ethereum}, author={Li, Xiaoqi and Chen, Ting and Luo, Xiapu and Wang, Chenxu}, booktitle={Proceedings of the 36th ACM/SIGAPP Symposium on Applied Computing}, year={2021}}
DOI: 10.21227/bps1-t109
title: 1.88kW BLDC Sensorless FOC with Adaptive Sliding Mode Observer

description: This dataset is on the study of Motor controllers, for which author has done numerous experiments, and the analysis along with these will also be shortly submitted to "IEEE Transactions on Power Electronics".The results contained in this dataset are graphs which give intutive idea on the control characteristics, whether the pole/zero is on the imaginary axis or the right half plane. Still in practice, the switching frequency for these controllers are used even 20 kHz or more, whereas MOSFETs can be switched to 2 MHz.BLDC motors ae used in medical industry ,ventillators, solar trackers, CNC servodrives, industrial robots, automative, electric vehicles- autos, rickshaws etc.Using this dataset, the industrial engineer can decide whether to run at that frequency or not. So, this study comes in handy to decide when designing in practice for industries and also for academia purposes.In this particular dataset, MOSFET is switched from 20 kHz to 2MHZ , at 46 different PWM frequencies and the resulting characteristics.The speed and the position estimation of BLDC is done using the sensorless vector control method i.e., Field Oriented control (FOC) with the addition of SMO observer which gives the estimation of speed and the sensorless rotor position. The switching pattern of the 3-phase inverter is implemented using space vector modulation.DIfferences in this paper dataset can be seen as the author has included following , with analysis which can be drawn from seeing attached graphs -performance comparison using Sliding Mode Observer (SMO) at different frequencies.PWM switching frequency is varied 46 times from 20 kHz to 2 MHz , - will help decide MOSFETs switching frequency.Of course, the Rdson, dc link inverter voltage ,other practical parameters etc has been taken into consideration (not submitted here) bu some analysis related to it,you may find in the authors Transaction paper.Separate results at all these 46 frequenciesStability Margins - Gain/PhaseOpen Loop Control PerformanceTransfer Function CompensationClosed loop TuningRoot Locus of Uncompensated System and Compensated SystemBode Plot - magnitude and phasePole Zero Map of Uncompensated System and Compensated SystemUnit-Step Response of Uncompensated System and Compensated SystemNyquist plot of Uncompensated System and Compensated SystemNichols chart of Uncompensated System and Compensated SystemImpulse Response of Uncompensated System and Compensated SystemSinusoidal ExcitationAll this is implemented on 32-bit Real-Time microcontroller. The pins usage not mentioned here are used for other General-Purpose-CAN,USB, RS485 etc.
DOI: 10.6084/m9.figshare.13303457
title: mnist.pkl.gz

description: MNIST dataset originally hosted on https://deeplearning.net, re-hosted here because deeplearning.net is currently inaccessible.
DOI: 10.5281/zenodo.4298927
title: Training dataset: DIA data analysis of a HEK/Ecoli Spike-in dataset using OpenSwathWorkflow

description: The six raw files serve as a concise but meaningful training data set in the Galaxy training network (https://galaxyproject.github.io/training-material/). HEK and E.coli cell pellets were lysed with 5 % SDS, 50 mM triethylammonium bicarbonate (TEAB), pH 7.55. The obtained protein extracts were reduced by adding f.c. 5 mM TCEP and alkylated by the addition of f.c. 10 mM iodacetamide. Protein digestion and purification was performed on S-Trap columns. To ensure protein binding to the S-Trap columns, samples were acidified to a final concentration of 1.2 % phosphoric acid (~ pH 2). Six times the sample volume S-Trap buffer (90% aqueous methanol containing a final concentration of 100 mM TEAB, pH 7.1) was added to the samples which were then loaded on the columns and washed with S-Trap buffer. Protein digestion was performed with trypsin and LysC for one hour at 47 °C. Peptides were eluted in three steps with (1) 50 mM TEAB, (2) 0.2 % aqueous formic acid and (3) 50 % acetonitrile containing 0.2 % formic acid. Eluted peptides of HEK and E.coli were mixed in two different ratios and triplikates of each Spike/in ratio were measured: Sample HEK E.coli MS method<br> Sample1 2.5 0.05 DIA<br> Sample2 2.5 0.05 DIA<br> Sample3 2.5 0.05 DIA<br> Sample4 2.5 0.15 DIA<br> Sample5 2.5 0.15 DIA<br> Sample6 2.5 0.15 DIA Additionally, iRT peptides were added and 1µg of each samples was measured using data independent acquisition with a Q-Exactive Plus mass spectrometer. Briefly, a scan range from 400-1000 m/Z was first covered by an MS1 scan followed by 25 consecutive MS2 scans (each 24 m/z broad). In the next cycle another MS1 scan was acquired followd by 26 MS2 scans (also 24m/z broad) in which the window centers were shifted by 50% compared to the previous cycle of MS2 scans. The resulting raw files contain overlapping MS2 scans. Besides the six raw files, we uploaded a spectral library, a transition list for the iRT peptides as well as an sample annotation file.<br> Additionally, we uploaded the Galaxy PyProphet score training result files: PyProphet score report and PyProphet score.
DOI: 10.6084/m9.figshare.13304021
title: Featurized Elmo Embedding Sets

description: Featurized Elmo embeddings for data in the various train/test splits for 10.1021/acs.jcim.9b00995
DOI: 10.6084/m9.figshare.13304021.v1
title: Featurized Elmo Embedding Sets

description: Featurized Elmo embeddings for data in the various train/test splits for 10.1021/acs.jcim.9b00995
DOI: 10.21227/yhfa-gy58
title: 1.88kW BLDC Sensorless FOC with Adaptive Sliding Mode Observer

description: This dataset is on the study of Motor controllers and the reseach paper will also be shortly submitted to "IEEE Transactions on Power Electronics".The results contained in this dataset are graphs which give intutive idea on the control characteristics, whether the pole/zero is on the imaginary axis or the right half plane. Still in practice, the switching frequency for these controllers are used even 20 kHz or more, whereas MOSFETs can be switched to 2 MHz.BLDC motors ae used in medical industry ,ventillators, solar trackers, CNC servodrives, industrial robots, automative, electric vehicles- autos, rickshaws etc.Using this dataset, the industrial engineer can decide whether to run at that frequency or not. So, this study comes in handy to decide when designing in practice for industries and also for academia purposes.In this particular dataset, MOSFET is switched from 20 kHz to 2MHZ , at 46 different PWM frequencies and the resulting characteristics.The speed and the position estimation of BLDC is done using the sensorless vector control method i.e., Field Oriented control (FOC) with the addition of SMO observer which gives the estimation of speed and the sensorless rotor position. The switching pattern of the 3-phase inverter is implemented using space vector modulation.DIfferences in this paper dataset can be seen as the author has included following , with analysis which can be drawn from seeing attached graphs -performance comparison using Sliding Mode Observer (SMO) at different frequencies.PWM switching frequency is varied 46 times from 20 kHz to 2 MHz , - will help decide MOSFETs switching frequency.Of course, the Rdson, dc link inverter voltage ,other practical parameters etc has been taken into consideration (not submitted here) bu some analysis related to it,you may find in the authors Transaction paper.Separate results at all these 46 frequenciesStability Margins - Gain/PhaseOpen Loop Control PerformanceTransfer Function CompensationClosed loop TuningRoot Locus of Uncompensated System and Compensated SystemBode Plot - magnitude and phasePole Zero Map of Uncompensated System and Compensated SystemUnit-Step Response of Uncompensated System and Compensated SystemNyquist plot of Uncompensated System and Compensated SystemNichols chart of Uncompensated System and Compensated SystemImpulse Response of Uncompensated System and Compensated SystemSinusoidal ExcitationAll this is implemented on 32-bit Real-Time microcontroller. The pins usage not mentioned here are used for other General-Purpose-CAN,USB, RS485 etc.
DOI: 10.21227/0sas-xm84
title: 1.88kW BLDC Sensorless FOC with Adaptive Sliding Mode Observer

description: This dataset is in support of my planned research paper shortly to be submitted to "IEEE Transactions on Power Electronics".The results contained in this dataset are graphs which give intutive idea on the control characteristics, whether the pole/zero is on the imaginary axis or the right half plane. Still in practice, the switching frequency for these controllers are used even 20 kHz or more, whereas MOSFETs can be switched to 2 MHz.BLDC motors ae used in medical industry ,ventillators, solar trackers, CNC servodrives, industrial robots, automative, electric vehicles- autos, rickshaws etc.Using this dataset, the industrial engineer can decide whether to run at that frequency or not. So, this study comes in handy to decide when designing in practice for industries and also for academia purposes.In this particular dataset, MOSFET is switched from 20 kHz to 2MHZ , at 46 different PWM frequencies and the resulting characteristics.The speed and the position estimation of BLDC is done using the sensorless vector control method i.e., Field Oriented control (FOC) with the addition of SMO observer which gives the estimation of speed and the sensorless rotor position. The switching pattern of the 3-phase inverter is implemented using space vector modulation.DIfferences in this paper dataset can be seen as the author has included following , with analysis which can be drawn from seeing attached graphs -performance comparison using Sliding Mode Observer (SMO) at different frequencies.PWM switching frequency is varied 46 times from 20 kHz to 2 MHz , - will help decide MOSFETs switching frequency.Of course, the Rdson, dc link inverter voltage ,other practical parameters etc has been taken into consideration (not submitted here) bu some analysis related to it,you may find in the authors Transaction paper.Separate results at all these 46 frequenciesStability Margins - Gain/PhaseOpen Loop Control PerformanceTransfer Function CompensationClosed loop TuningRoot Locus of Uncompensated System and Compensated SystemBode Plot - magnitude and phasePole Zero Map of Uncompensated System and Compensated SystemUnit-Step Response of Uncompensated System and Compensated SystemNyquist plot of Uncompensated System and Compensated SystemNichols chart of Uncompensated System and Compensated SystemImpulse Response of Uncompensated System and Compensated SystemSinusoidal ExcitationAll this is implemented on 32-bit Real-Time microcontroller. The pins usage not mentioned here are used for other General-Purpose-CAN,USB, RS485 etc.