cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7126853
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry . Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0). The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).
DOI: 10.5281/zenodo.8071008
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry . Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0). The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).
DOI: 10.5281/zenodo.8123974
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry . Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0). The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).
DOI: 10.5281/zenodo.8326546
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry . Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0). The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release). The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured. If you require more information about data or scales, please contact us. <em>LANIREM (</em><em>National MRI Laboratory)</em><em>, Institute of Neurobiology, </em> <em>Universidad Nacional Autónoma de México (UNAM), </em><em>Querétaro, México.</em> <strong>Diego Angeles Valdez, M. Sc. </strong> diego.ang.val@gmail.com diego.ang.val@inb.unam.mx <br> <strong>Eduardo A. Garza-Villarreal, M.D., Ph.D.</strong> egarza@gmail.com egarza@comunidad.unam.mx
DOI: 10.5281/zenodo.10409461
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry .


Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0).


The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).


The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured.


 


If you require more information about data or scales, please contact us. 


LANIREM (National MRI Laboratory), Institute of Neurobiology, 


Universidad Nacional Autónoma de México (UNAM), Querétaro, México.


Diego Angeles Valdez, M. Sc. 



	
diego.ang.val@gmail.com
	
diego.ang.val@inb.unam.mx




Eduardo A. Garza-Villarreal, M.D., Ph.D.



	
egarza@gmail.com
	
egarza@comunidad.unam.mx
DOI: 10.5281/zenodo.7126852
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry .


Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0).


The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).


The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured.


 


If you require more information about data or scales, please contact us. 


LANIREM (National MRI Laboratory), Institute of Neurobiology, 


Universidad Nacional Autónoma de México (UNAM), Querétaro, México.


Diego Angeles Valdez, M. Sc. 



	
diego.ang.val@gmail.com
	
diego.ang.val@inb.unam.mx




Eduardo A. Garza-Villarreal, M.D., Ph.D.



	
egarza@gmail.com
	
egarza@comunidad.unam.mx
DOI: 10.5281/zenodo.8326547
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry . Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0). The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release). The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured. If you require more information about data or scales, please contact us. <em>LANIREM (</em><em>National MRI Laboratory)</em><em>, Institute of Neurobiology, </em> <em>Universidad Nacional Autónoma de México (UNAM), </em><em>Querétaro, México.</em> <strong>Diego Angeles Valdez, M. Sc. </strong> diego.ang.val@gmail.com diego.ang.val@inb.unam.mx <br> <strong>Eduardo A. Garza-Villarreal, M.D., Ph.D.</strong> egarza@gmail.com egarza@comunidad.unam.mx
DOI: 10.5281/zenodo.8393976
title: The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS

description: The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry . Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0). The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release). The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured. If you require more information about data or scales, please contact us. <em>LANIREM (</em><em>National MRI Laboratory)</em><em>, Institute of Neurobiology, </em> <em>Universidad Nacional Autónoma de México (UNAM), </em><em>Querétaro, México.</em> <strong>Diego Angeles Valdez, M. Sc. </strong> diego.ang.val@gmail.com diego.ang.val@inb.unam.mx <br> <strong>Eduardo A. Garza-Villarreal, M.D., Ph.D.</strong> egarza@gmail.com egarza@comunidad.unam.mx
DOI: 10.6084/m9.figshare.21781829
title: Data set for “Double Puzzle” at the Shumagin seismic gap, Alaska Peninsula: intra-slab strike-slip faulting loaded by lateral variations in megathrust fault friction

description: Data set for “Double Puzzle” at the Shumagin seismic gap, Alaska Peninsula: intra-slab strike-slip faulting loaded by lateral variations in megathrust fault friction 
<br>
Contains, bathymetric profiles; Coulomb files;Flextureal model profiles;Flextural parameters data; GNSS coordinates and velocities.  GNSS Site velocity estimated from different Fault geometry and their Coulomb files 
<br>
DOI: 10.6084/m9.figshare.21781829.v4
title: Data set for “Double Puzzle” at the Shumagin seismic gap, Alaska Peninsula: intra-slab strike-slip faulting loaded by lateral variations in megathrust fault friction

description: Data set for “Double Puzzle” at the Shumagin seismic gap, Alaska Peninsula: intra-slab strike-slip faulting loaded by lateral variations in megathrust fault friction 
<br>
Contains, bathymetric profiles; Coulomb files;Flextureal model profiles;Flextural parameters data; GNSS coordinates and velocities.  GNSS Site velocity estimated from different Fault geometry and their Coulomb files 
<br>
DOI: 10.6084/m9.figshare.21781829.v3
title: Data set for “Double Puzzle” at the Shumagin seismic gap, Alaska Peninsula: intra-slab strike-slip faulting loaded by lateral variations in megathrust fault friction

description: Data set for “Double Puzzle” at the Shumagin seismic gap, Alaska Peninsula: intra-slab strike-slip faulting loaded by lateral variations in megathrust fault friction 
<br>
Contains, bathymetric profiles; Coulomb files;Flextureal model profiles;Flextural parameters data; GNSS coordinates and velocities.  GNSS Site velocity estimated from different Fault geometry and their Coulomb files 
<br>
DOI: 10.6084/m9.figshare.24873795
title: miR449_Ago_up_spec.txt

description: miR449_Ago_up_spec.txt
DOI: 10.6084/m9.figshare.24873795.v1
title: miR449_Ago_up_spec.txt

description: miR449_Ago_up_spec.txt
DOI: 10.6084/m9.figshare.24873786
title: miR449_PCA plot

description: miR449_PCA plot
DOI: 10.6084/m9.figshare.24873786.v1
title: miR449_PCA plot

description: miR449_PCA plot
DOI: 10.6084/m9.figshare.24873780
title: miR449_Intersection

description: miR449_Intersection
DOI: 10.6084/m9.figshare.24873780.v1
title: miR449_Intersection

description: miR449_Intersection
DOI: 10.6084/m9.figshare.24873777
title: miR449_Input_miR_vs_Input_Scramble

description: miR449_Input_miR_vs_Input_Scramble
DOI: 10.6084/m9.figshare.24873777.v1
title: miR449_Input_miR_vs_Input_Scramble

description: miR449_Input_miR_vs_Input_Scramble
DOI: 10.6084/m9.figshare.24873759
title: miR449_IgG_miR_vs_IgG_Scramble

description: miR449_IgG_miR_vs_IgG_Scramble
DOI: 10.6084/m9.figshare.24873759.v1
title: miR449_IgG_miR_vs_IgG_Scramble

description: miR449_IgG_miR_vs_IgG_Scramble
DOI: 10.6084/m9.figshare.24874131
title: Origdata

description: Our research aims to comprehensively assess the potential effects of genetic lipid-lowering medications on a range of lung-related diseases (LRD), including small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF),pulmonary edema(PE), and pneumonia. We strive to understand the possible impact of genetic lipid-lowering medications on the risk of developing these specific lung diseases. This study is anticipated to offer novel insights into the influence of genetically regulated lipid-lowering medications onLRD.
DOI: 10.5281/zenodo.10409516
title: CLONING IN SILKWORTH BREEDING (BOMBUX MORI L). CLONING IN SILKWORM BREEDING (BOMBYX MORI L).
DOI: 10.5281/zenodo.10409517
title: CLONING IN SILKWORTH BREEDING (BOMBUX MORI L). CLONING IN SILKWORM BREEDING (BOMBYX MORI L).
DOI: 10.25835/wiuc5jkf
title: Simulated LLR and DLLR data for different cases

description: The simulated LLR data are round-trip travel times between Earth station and lunar retro-reflector. And the simulated DLLR data are range differences between the ranges measured by the same station to different lunar reflectors within a short time interval. For the simulated DLLR data, the measurement time for the second reflector minus the measurement time for the first reflector is 1.5 minutes. 

The folders "ReflectorBaselines", "TimespanStations" and "NewReflectors" contain the simulated LLR and DLLR data used for different analysis cases. The type of the simulated data (LLR or DLLR) and the corresponding case are shown in the name of the simulated data files.

Below are the contents of the different columns of the simulated LLR and DLLR data.

The columns of the simulated DLLR data contain the following information:
 
1. station name
2. measurment time t1 for reflector 1 [JD-2440000.0]
3. reflector 1 name
4. reflector 2 name 
5. range difference [km]
6. accuracy [nm]
7. temperature [Celsius degree]
8. pressure [hPa]
9. wavelength [nm]
10. humidity [%] 

The columns of the simulated LLR data contain the following information: 

1. station name 
2. measurement time for a reflector [JD-2440000.0]
3. reflector name 
4. round-trip travel time [s] 
5. accuracy [ns] 
6. temperature [Celsius degree]
7. pressure [hPa]
8. wavelength [nm] 
9. humidity [%] 

More details about the data and their analysis can be found in:

1. Zhang M. (2023): Characteristics and Benefits of Differential Lunar Laser Ranging, PhD thesis at Leibniz Universität Hannover
2. Zhang M.; Müller J.; Biskupek L. (2024) : Benefit of combining Lunar Laser Ranging and Differential Lunar Laser Ranging, Astronomy & Astrophysics, 681, A5, DOI: 10.1051/0004-6361/202347643
DOI: 10.5281/zenodo.10409321
title: Data for SLAM Datasets

description: This project contains a dataset generated with a Kobuki Turtlebot 2 and a RP LiDAR A2. The goal of the project is that the user can experiment the issues that LiDAR has detecting glass walls or mapping with excessive light. The topics available contain robot odometry, laser scans, poseupdates, commands given to the robot, its trajectory, clocks, and the needed transforms to perform a map. With the bags included in bag folder you can replicate the ros topics generated during an indoor walkthrough of UC3M corridors.



This information can also be found in the next link, please check it for updates: PREDICT 6G / SLAM Datasets · GitLab (uc3m.es)

 



This work has been partly funded by the European Commission Horizon Europe SNS JU PREDICT-6G (GA 101095890) and Hexa-X-II (GA 101095759) projects, and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGeneration-EU through the UNICO 5G I+D 6G-EDGEDT and 6G-DATADRIVEN.

This work has been funded by the Spanish Ministry of Economic Affairs and Digital Transformation under European Union NextGeneration-EU projects TSI-063000-2021-59 RISC6G and TSI-063000-2021-63 MAP-6G.
DOI: 10.5281/zenodo.10409320
title: Data for SLAM Datasets

description: This project contains a dataset generated with a Kobuki Turtlebot 2 and a RP LiDAR A2. The goal of the project is that the user can experiment the issues that LiDAR has detecting glass walls or mapping with excessive light. The topics available contain robot odometry, laser scans, poseupdates, commands given to the robot, its trajectory, clocks, and the needed transforms to perform a map. With the bags included in bag folder you can replicate the ros topics generated during an indoor walkthrough of UC3M corridors.



This information can also be found in the next link, please check it for updates: PREDICT 6G / SLAM Datasets · GitLab (uc3m.es)

 



This work has been partly funded by the European Commission Horizon Europe SNS JU PREDICT-6G (GA 101095890) and Hexa-X-II (GA 101095759) projects, and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGeneration-EU through the UNICO 5G I+D 6G-EDGEDT and 6G-DATADRIVEN.

This work has been funded by the Spanish Ministry of Economic Affairs and Digital Transformation under European Union NextGeneration-EU projects TSI-063000-2021-59 RISC6G and TSI-063000-2021-63 MAP-6G.
DOI: 10.6084/m9.figshare.24874044
title: Voltaian Basin Research Project

description: Application of photogeology in understanding the geology and hydrocarbon Prospectively of the Voltain Basin, Onshore Ghana
DOI: 10.6084/m9.figshare.24874044.v1
title: Voltaian Basin Research Project

description: Application of photogeology in understanding the geology and hydrocarbon Prospectively of the Voltain Basin, Onshore Ghana
DOI: 10.5281/zenodo.10409075
title: Jordan growth charts
DOI: 10.5281/zenodo.10409076
title: Jordan growth charts
DOI: 10.17028/rd.lboro.24874200
title: Supplementary information files for On-chip phonon-magnon reservoir for neuromorphic computing

description: © the authors, CC-BY 4.0Supplementary files for article On-chip phonon-magnon reservoir for neuromorphic computingReservoir computing is a concept involving mapping signals onto a high-dimensional phase space of a dynamical system called “reservoir” for subsequent recognition by an artificial neural network. We implement this concept in a nanodevice consisting of a sandwich of a semiconductor phonon waveguide and a patterned ferromagnetic layer. A pulsed write-laser encodes input signals into propagating phonon wavepackets, interacting with ferromagnetic magnons. The second laser reads the output signal reflecting a phase-sensitive mix of phonon and magnon modes, whose content is highly sensitive to the write- and read-laser positions. The reservoir efficiently separates the visual shapes drawn by the write-laser beam on the nanodevice surface in an area with a size comparable to a single pixel of a modern digital camera. Our finding suggests the phonon-magnon interaction as a promising hardware basis for realizing on-chip reservoir computing in future neuromorphic architectures.
DOI: 10.17028/rd.lboro.24874200.v1
title: Supplementary information files for On-chip phonon-magnon reservoir for neuromorphic computing

description: © the authors, CC-BY 4.0Supplementary files for article On-chip phonon-magnon reservoir for neuromorphic computingReservoir computing is a concept involving mapping signals onto a high-dimensional phase space of a dynamical system called “reservoir” for subsequent recognition by an artificial neural network. We implement this concept in a nanodevice consisting of a sandwich of a semiconductor phonon waveguide and a patterned ferromagnetic layer. A pulsed write-laser encodes input signals into propagating phonon wavepackets, interacting with ferromagnetic magnons. The second laser reads the output signal reflecting a phase-sensitive mix of phonon and magnon modes, whose content is highly sensitive to the write- and read-laser positions. The reservoir efficiently separates the visual shapes drawn by the write-laser beam on the nanodevice surface in an area with a size comparable to a single pixel of a modern digital camera. Our finding suggests the phonon-magnon interaction as a promising hardware basis for realizing on-chip reservoir computing in future neuromorphic architectures.
DOI: 10.5281/zenodo.10409534
title: FESOM model data used in the study on the buffer zone for great salinity anomaly

description: Model data used in the study on the buffer zone for great salinity anomaly
DOI: 10.21227/sxzd-6658
title: Log file 

description: Abstract—Drones or Remote Piloted Aircrafts System (RPAS), have become incredibly popular in a variety of sectors. Critical uses of drones includes agriculture, delivery system and surveillance etc. As technology advances, the reliability of drone components becomes increasingly crucial. It is important to analyze the prime reasons of drone flight crashes as it can damage public property and it could also be harmful for human beings. Mechanical breakdowns, human error, battery failure, wildlife hazards could be one of the reasons for the flight crashes. In this study we are trying to make better understanding of the root causes of failures of drones for safer and more reliable drone technology. Sometimes the real reason related to the crash is not very clear, so flight log data analysis is required to pin point the causes. In this paper we analyzed data of one hexagonal drone crashed flight to identify the real cause of the failure of drone.