cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23301377
title: Heeringa_etal_2023b_CVCs_Aging

description: This dataset belongs to the manuscript entitled: "<b>Altered neural encoding of vowels in noise does not affect behavioral vowel discrimination in gerbils with age-related hearing loss</b>" by Amarins Heeringa, Carolin Jüchter, Rainer Beutelmann, Georg Klump, and Christine Köppl from the University of Oldenburg. Published in Frontiers of Neuroscience (doi: 10.3389/fnins.2023.1238941). Each tab shows the data for the accompanying figures.
DOI: 10.6084/m9.figshare.24465754
title: AVIA-Indoor labels and predictions

description: The file provided the predictions for the dataset <i>AVIA-Indoor</i> generated by M-detector introduced in the paper titled "Moving Event Detection from LiDAR Point Streams".
DOI: 10.6084/m9.figshare.24465781
title: KITTI labels and predictions

description: The file provided the predictions for the dataset <i>KITTI</i> generated by M-detector introduced in the paper titled "Moving Event Detection from LiDAR Point Streams".
DOI: 10.6084/m9.figshare.24465781.v1
title: KITTI labels and predictions

description: The file provided the predictions for the dataset <i>KITTI</i> generated by M-detector introduced in the paper titled "Moving Event Detection from LiDAR Point Streams".
DOI: 10.6084/m9.figshare.24465790
title: nuScenes labels and predictions

description: The file provided the predictions for the dataset <i>nuScenes</i> generated by M-detector introduced in the paper titled "Moving Event Detection from LiDAR Point Streams".
DOI: 10.6084/m9.figshare.24465793
title: Waymo labels and predictions

description: The file provided the predictions for the dataset <i>Waymo</i> generated by M-detector introduced in the paper titled "Moving Event Detection from LiDAR Point Streams".
DOI: 10.4121/d65cfd80-74a5-4018-974c-8d82c1f51ab0
title: Data underlying the publication: "Redox-Controlled Shunts in a Synthetic Chemical Reaction Cycle"

description: Complete set of data underlying the experiments conducted in "Redox-Controlled Shunts in a Synthetic Chemical Reaction Cycle". The aim of this publication is to demonstrate a new use of beta'-substituted Michael acceptors (MAs). A new Chemical Reaction Network (CRN) is based based on addition-elimination- as well as oxidation-chemistry. An amine-functionalised MA can be turned into a thiol-functionalised MA with a thiol. This deactivated MA can be reactivated with different oxidants, making it prone to amine-readdition, recovering the starting material. We show that different oxidants lead to different pathways of this CRN with different side products and kinetics. Further, we show a flow-controlled switching between different species of this CRN, offering the ability to recover the starting material and recycle the waste species (disulfide).Please refer to the readme file, explaining the experiment identifiers and conditions of each experiment.
DOI: 10.4121/d65cfd80-74a5-4018-974c-8d82c1f51ab0.v1
title: Data underlying the publication: "Redox-Controlled Shunts in a Synthetic Chemical Reaction Cycle"

description: Complete set of data underlying the experiments conducted in "Redox-Controlled Shunts in a Synthetic Chemical Reaction Cycle". The aim of this publication is to demonstrate a new use of beta'-substituted Michael acceptors (MAs). A new Chemical Reaction Network (CRN) is based based on addition-elimination- as well as oxidation-chemistry. An amine-functionalised MA can be turned into a thiol-functionalised MA with a thiol. This deactivated MA can be reactivated with different oxidants, making it prone to amine-readdition, recovering the starting material. We show that different oxidants lead to different pathways of this CRN with different side products and kinetics. Further, we show a flow-controlled switching between different species of this CRN, offering the ability to recover the starting material and recycle the waste species (disulfide).Please refer to the readme file, explaining the experiment identifiers and conditions of each experiment.
DOI: 10.5281/zenodo.10056933
title: Geochemical sediment fingerprinting dataset from Oroua river catchment, New Zealand

description: Geochemical dataset collected to determine key source contributions to overbank sediment deposition for specific particle size fractions as described in "Vale, S., Smith, H., Matthews, A., & Boyte, S. (2020). Determining sediment source contributions to overbank deposits within stopbanks in the Oroua River, New Zealand, using sediment fingerprinting. Journal of Hydrology (New Zealand), 59(2), 147-172."
DOI: 10.5281/zenodo.10056932
title: Geochemical sediment fingerprinting dataset from Oroua river catchment, New Zealand

description: Geochemical dataset collected to determine key source contributions to overbank sediment deposition for specific particle size fractions as described in "Vale, S., Smith, H., Matthews, A., & Boyte, S. (2020). Determining sediment source contributions to overbank deposits within stopbanks in the Oroua River, New Zealand, using sediment fingerprinting. Journal of Hydrology (New Zealand), 59(2), 147-172."
DOI: 10.4121/fdc1b44a-1fa5-45dd-917a-33cba31c62ba
title: Two-dimensional bathymetry data around control measures in the lower Rhine River (1999-2020)

description: This repository contains bathymetry data around four erosion control measures in the lower Rhine River, in the form of raster (tif) files. The locations covered are Spijk, Erlecom, Nijmegen and Sint Andries. The data cover the period 1999-2020.<br>Metadata is included on the filename:Location_Year_MonthPeriod.tif, e.g. Erlecom_1999_07to10.tif <br>
DOI: 10.4121/fdc1b44a-1fa5-45dd-917a-33cba31c62ba.v1
title: Two-dimensional bathymetry data around control measures in the lower Rhine River (1999-2020)

description: This repository contains bathymetry data around four erosion control measures in the lower Rhine River, in the form of raster (tif) files. The locations covered are Spijk, Erlecom, Nijmegen and Sint Andries. The data cover the period 1999-2020.<br>Metadata is included on the filename:Location_Year_MonthPeriod.tif, e.g. Erlecom_1999_07to10.tif <br>
DOI: 10.5281/zenodo.10057006
title: Dataset: Temporal recalibration in response to delayed visual feedback of active versus passive actions

description: Data set related to the manuscript: 
Kufer, K., Schmitter, C. V, Kircher, T., Straube, B., 2023. Temporal recalibration in response to delayed visual feedback of active versus passive actions: An fMRI study. https://doi.org/10.21203/RS.3.RS-3493865/V1
Abstract:
The brain can adapt its expectations about the relative timing of actions and their sensory outcomes in a process known as temporal recalibration. This might occur as the recalibration of timing between the outcome and (1) the motor act (sensorimotor) or (2) tactile/proprioceptive information (inter-sensory). This fMRI recalibration study investigated sensorimotor contributions to temporal recalibration by comparing active and passive conditions. Subjects were repeatedly exposed to delayed (150ms) or undelayed visual stimuli, triggered by active or passive button presses. Recalibration effects were tested in delay detection tasks, including visual and auditory outcomes. We showed that both modalities were affected by visual recalibration. However, an active advantage was observed only in visual conditions. Recalibration was generally associated with the left cerebellum (lobules IV, V and vermis) while action related activation (active > passive) occurred in the right middle/superior frontal gyrus during adaptation and test phases. Recalibration transferred from vision to audition was related to action specic activations in the cingulate cortex, the angular gyrus and left inferior frontal gyrus. Our data provide new insights in sensorimotor contributions to temporal recalibration via the superior frontal gyrus and inter-sensory contributions mediated by the cerebellum.
DOI: 10.5281/zenodo.10057005
title: Dataset: Temporal recalibration in response to delayed visual feedback of active versus passive actions

description: Data set related to the manuscript: 
Kufer, K., Schmitter, C. V, Kircher, T., Straube, B., 2023. Temporal recalibration in response to delayed visual feedback of active versus passive actions: An fMRI study. https://doi.org/10.21203/RS.3.RS-3493865/V1
Abstract:
The brain can adapt its expectations about the relative timing of actions and their sensory outcomes in a process known as temporal recalibration. This might occur as the recalibration of timing between the outcome and (1) the motor act (sensorimotor) or (2) tactile/proprioceptive information (inter-sensory). This fMRI recalibration study investigated sensorimotor contributions to temporal recalibration by comparing active and passive conditions. Subjects were repeatedly exposed to delayed (150ms) or undelayed visual stimuli, triggered by active or passive button presses. Recalibration effects were tested in delay detection tasks, including visual and auditory outcomes. We showed that both modalities were affected by visual recalibration. However, an active advantage was observed only in visual conditions. Recalibration was generally associated with the left cerebellum (lobules IV, V and vermis) while action related activation (active > passive) occurred in the right middle/superior frontal gyrus during adaptation and test phases. Recalibration transferred from vision to audition was related to action specic activations in the cingulate cortex, the angular gyrus and left inferior frontal gyrus. Our data provide new insights in sensorimotor contributions to temporal recalibration via the superior frontal gyrus and inter-sensory contributions mediated by the cerebellum.
DOI: 10.6084/m9.figshare.24465856
title: clinical data

description: This is a study of lead poisoning in children.
DOI: 10.34740/kaggle/dsv/6842534
title: 📒Meta Kaggle ported to SQLITE DB
DOI: 10.5281/zenodo.10019002
title: Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment

description: The first Twin Test (TW1) of the TWEET-IE project (www.tweet-ie.eu) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements.
DOI: 10.5281/zenodo.10019001
title: Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment

description: The first Twin Test (TW1) of the TWEET-IE project (www.tweet-ie.eu) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements.
DOI: 10.6084/m9.figshare.19946632
title: Evaluation of neural networks applied in forensics; handwriting verification example

description: There is a growing interest in the possibility of artificial neural networks’ applications in forensics. Extensive research has been published on this subject, especially in the field of handwriting examination. However, it seldom discusses forensic and legal standards, which are the most fundamental of conditions for the acceptance of artificial neural networks in forensics. From the perspective of handwriting analysis, we have exemplified and systematized general methods for an informal falsification of artificial neural networks applied to verification of offline handwritten documents’ authorship. These approaches should be generally effective against applications of neural networks in forensics, aimed to objectively expose and prove models as unreliable.
DOI: 10.6084/m9.figshare.19946632.v1
title: Evaluation of neural networks applied in forensics; handwriting verification example

description: There is a growing interest in the possibility of artificial neural networks’ applications in forensics. Extensive research has been published on this subject, especially in the field of handwriting examination. However, it seldom discusses forensic and legal standards, which are the most fundamental of conditions for the acceptance of artificial neural networks in forensics. From the perspective of handwriting analysis, we have exemplified and systematized general methods for an informal falsification of artificial neural networks applied to verification of offline handwritten documents’ authorship. These approaches should be generally effective against applications of neural networks in forensics, aimed to objectively expose and prove models as unreliable.
DOI: 10.5281/zenodo.10047442
title: Tunable force transduction through the Escherichia coli cell envelope

description: Killing Assays, SDS Assays, Microscopy profiles and segmented cells (.res files for MicrobeJ).
DOI: 10.5281/zenodo.10047441
title: Tunable force transduction through the Escherichia coli cell envelope

description: Killing Assays, SDS Assays, Microscopy profiles and segmented cells (.res files for MicrobeJ).
DOI: 10.57841/casdc.0002954
title: 乙烯多相氢甲酰化催化剂规模化制备数据集
DOI: 10.5281/zenodo.10056654
title: Thermal images of steel bars

description: Information about image acquisition:  
one image is acquired for each product passing the bar.
 
Information about the files:
Each file is a matrix of temperatures of the framed scene. The framed scene contains the "hot" bar, which emissivity has been calibrated, and the "cold" backgorund. The framed products are incandescent suspension arms coming out of the descaling station. The datesets contains images from both transient and stationary stages of the manufacturing process.
 
Thermal camera employed: Optris PI 1M, spectral range 0.85-1.1 μm, temperature range 500 - 1800°C.
 
 
Date   - Time  - Number of Images  - Product Type:  
2023_10_12  - 12:00:00 to 21:00:00  - 443     - Type1
2023_10_13  - 8:00:00 to 14:00:00  - 261     - Type1
2023_10_16  - 13:00:00 to 21:00:00  - 282     - Type1
2023_10_17  - 8:00:00 to 20:00:00  - 389     - Type1
2023_10_19  - 8:00:00 to 14:00:00  - 144     - Type2
2023_10_20  - 8:00:00 to 14:00:00  - 323     - Type2
2023_10_23  - 8:00:00 to 21:00:00  - 585     - Type2
 
File Type: CSV
File Type Extension: CSV
DOI: 10.5281/zenodo.10056653
title: Thermal images of steel bars

description: Information about image acquisition:  
one image is acquired for each product passing the bar.
 
Information about the files:
Each file is a matrix of temperatures of the framed scene. The framed scene contains the "hot" bar, which emissivity has been calibrated, and the "cold" backgorund. The framed products are incandescent suspension arms coming out of the descaling station. The datesets contains images from both transient and stationary stages of the manufacturing process.
 
Thermal camera employed: Optris PI 1M, spectral range 0.85-1.1 μm, temperature range 500 - 1800°C.
 
 
Date   - Time  - Number of Images  - Product Type:  
2023_10_12  - 12:00:00 to 21:00:00  - 443     - Type1
2023_10_13  - 8:00:00 to 14:00:00  - 261     - Type1
2023_10_16  - 13:00:00 to 21:00:00  - 282     - Type1
2023_10_17  - 8:00:00 to 20:00:00  - 389     - Type1
2023_10_19  - 8:00:00 to 14:00:00  - 144     - Type2
2023_10_20  - 8:00:00 to 14:00:00  - 323     - Type2
2023_10_23  - 8:00:00 to 21:00:00  - 585     - Type2
 
File Type: CSV
File Type Extension: CSV
DOI: 10.7910/dvn/ctj7ol
title: Factors Contributing to the Success of Crop Diversification Programme

description: Various factors concerning policy design and implementation have been shown to influence the outcomes. Some experts argue that a policy's success relies on the alignment between the intended behavior of the beneficiaries and the policy's objectives. This study aims to assess Crop Diversification Programme (CDP) policies in relation to behavioral assumptions about the policy's intended targets. In the meta-analysis phase, data related to the study variables were collected from each study. All these variables are qualitative and were assigned specific codes. Conventional farmers were coded as 0, while sustainable farmers were coded as 1. Land types were categorized as small and marginal (coded as 1), medium (coded as 2), and large (coded as 3). Policy instruments were coded as incentives (0) and capacity-building (1). Policy outcomes were coded as failure (0) and success (1). This coded data was then analyzed using meta-analysis techniques. The studies have meticulously gathered factors contributing to success of crop diversification programme.
DOI: 10.34740/kaggle/dsv/6842880
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.10057039
title: Global 0.1° rootzone soil moisture dataset (1980-1989)
DOI: 10.5281/zenodo.10057040
title: Global 0.1° rootzone soil moisture dataset (1980-1989)
DOI: 10.5281/zenodo.10013525
title: Structural Data for the Antibody Developability Manuscript: Cartography of Developability Landscapes in Native and Human-Engineered Antibodies

description: Here is the additional structural data (predicted models and MD trajectories) for the "Cartography of the Developability Landscapes of Native and Human-Engineered Antibodies" manuscript. Please cite our paper when referring to and using this data. If you have any questions, please contact Eva Smorodina at ribes.ev@gmail.com. Thank you!
DOI: 10.5281/zenodo.10013524
title: Structural Data for the Antibody Developability Manuscript: Cartography of Developability Landscapes in Native and Human-Engineered Antibodies

description: Here is the additional structural data (predicted models and MD trajectories) for the "Cartography of the Developability Landscapes of Native and Human-Engineered Antibodies" manuscript. Please cite our paper when referring to and using this data. If you have any questions, please contact Eva Smorodina at ribes.ev@gmail.com. Thank you!
DOI: 10.5281/zenodo.10038733
title: Next-generation 3D object detection and tracking for self-driving vehicles using object velocity

description: The synthetic dataset was generated using KITTI-like specifications and annotations format. It is comprised by the training and testing sets, that include KITTI standard  folders: label_2, image_2 and calib. Furthermore, there is a velodyne file for each of the following use cases:

Point cloud 1: (x,y,z, (Float)Radial_Velocity): this point cloud has the relative radial velocity as an additional feature for each point. File: velodyne_radial_velocity;
Point cloud 2: (x,y,z,(Float)Absolute_Speed): in this point cloud, every point has the absolute speed of the object as the additional feature. File: velodyne_abs_speed;
Point cloud 3: (x,y,z,(Bool)Is_Moving): the additional feature of this point cloud is a Boolean value that is set to 1.0 if the object is moving; contrariwise, it is set to 0.0 for static objects. File: velodyne_is_moving;
Point cloud 4: (x,y,z,0): no additional feature information. If desired, requires post-processing to convert to (x,y,z) or changing the toolbox point cloud configuration to not consider the additional feature. File: velodyne_xyz;
Additionally, the detections generated with the OpenPCDet toolbox and Second-IoU model are provided.
This work was made as part of a master thesis of Informatics Engineering in the University of Aveiro.
DOI: 10.5281/zenodo.10038734
title: Next-generation 3D object detection and tracking for self-driving vehicles using object velocity

description: The synthetic dataset was generated using KITTI-like specifications and annotations format. It is comprised by the training and testing sets, that include KITTI standard  folders: label_2, image_2 and calib. Furthermore, there is a velodyne file for each of the following use cases:

Point cloud 1: (x,y,z, (Float)Radial_Velocity): this point cloud has the relative radial velocity as an additional feature for each point. File: velodyne_radial_velocity;
Point cloud 2: (x,y,z,(Float)Absolute_Speed): in this point cloud, every point has the absolute speed of the object as the additional feature. File: velodyne_abs_speed;
Point cloud 3: (x,y,z,(Bool)Is_Moving): the additional feature of this point cloud is a Boolean value that is set to 1.0 if the object is moving; contrariwise, it is set to 0.0 for static objects. File: velodyne_is_moving;
Point cloud 4: (x,y,z,0): no additional feature information. If desired, requires post-processing to convert to (x,y,z) or changing the toolbox point cloud configuration to not consider the additional feature. File: velodyne_xyz;
Additionally, the detections generated with the OpenPCDet toolbox and Second-IoU model are provided.
This work was made as part of a master thesis of Informatics Engineering in the University of Aveiro.
DOI: 10.25625/vicwcz/0nplur
title: bistability involving sinI.py

description: :unav
DOI: 10.25625/vicwcz/hqbzpm
title: alpha_I60k=50second.png

description: :unav
DOI: 10.25625/vicwcz/imwz8t
title: create_trajectories.py

description: :unav
DOI: 10.25625/vicwcz/jsiyzy
title: transition_rates alpha_i = 0.0 Burstsize = 10.0.png

description: :unav
DOI: 10.25625/vicwcz/yuxp9u
title: ontimesmatrix.tar.gz

description: :unav
DOI: 10.25625/vicwcz/a74ued
title: input.dat

description: :unav
DOI: 10.25625/vicwcz/arpjrs
title: ontimes.tar.gz

description: :unav
DOI: 10.25625/vicwcz/9b8q8m
title: Plot.py

description: :unav
DOI: 10.25625/vicwcz/dyppdx
title: parameter_sweep.py

description: :unav
DOI: 10.25625/vicwcz/lfbyzf
title: figure_together.png

description: :unav
DOI: 10.25625/vicwcz/nyxpsr
title: input.dat

description: :unav
DOI: 10.25625/vicwcz/pd3bqi
title: deterministic_trajectories.py

description: :unav
DOI: 10.25625/vicwcz/uvlcet
title: deterministic_trajectories.py

description: :unav
DOI: 10.25625/vicwcz/8budev
title: Data_2D.tar.gz

description: :unav
DOI: 10.25625/vicwcz/5pmovv
title: trajectoriealphar21alphas21

description: :unav
DOI: 10.25625/vicwcz/9t6eug
title: durations10deterministic.png

description: :unav
DOI: 10.25625/vicwcz/p74ivy
title: rootsalphar21alphas21

description: :unav
DOI: 10.25625/vicwcz/amigvc
title: bursting.py

description: :unav
DOI: 10.25625/vicwcz/nhgf5m
title: 4A.tar.gz

description: :unav
DOI: 10.25625/vicwcz/s2v60j
title: 3AB_4B.tar.gz

description: :unav
DOI: 10.25625/vicwcz/60j4sa
title: gillespie.py

description: :unav
DOI: 10.25625/vicwcz/rodw6z
title: 4CD.tar.gz

description: :unav
DOI: 10.25625/vicwcz/wxrygx
title: 3C.tar.gz

description: :unav
DOI: 10.25625/vicwcz/5xl0hk
title: solutions40kmatrix50kmotility50

description: :unav
DOI: 10.25625/vicwcz/a3abjc
title: solutions20kmatrix50kmotility50

description: :unav
DOI: 10.25625/vicwcz/wxkg8a
title: trajectorie_Relay

description: :unav
DOI: 10.25625/vicwcz/nvi1q0
title: stochastic.py

description: :unav
DOI: 10.25625/vicwcz/3gassh
title: solutions30kmatrix50kmotility50

description: :unav
DOI: 10.25625/vicwcz/src99z
title: solutions31kmatrix50kmotility50

description: :unav
DOI: 10.25625/vicwcz/6fzc8e
title: steady_state.py

description: :unav
DOI: 10.25625/vicwcz/u77wyj
title: stochastic.py

description: :unav
DOI: 10.25625/vicwcz/4artqz
title: solutions01kmatrix50kmotility50

description: :unav
DOI: 10.25625/vicwcz/og4i2l
title: solutions00kmatrix50kmotility50

description: :unav
DOI: 10.25625/vicwcz/oplq3j
title: solutions10kmatrix50kmotility50

description: :unav