cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6780524
title: Performance Criteria and Example Parameter Sets Comparing Different Variants of the Ensemble Kalman Filter as Applied to Volcanology

description: This dataset contains the results of various Ensemble Kalman Filter (EnKF) inversions in which synthetic GNSS and InSAR observations from an inflating magma system are assimilated into numerical models of rock deformation around a pressurized ellipsoidal magma reservoir. Each inversion uses a different variant of the EnKF, with changes to workflow meta-parameters such as the number of ensemble members or the particular update algorithm used. In particular, each filter variant is evaluated by comparing the final output model to the original synthetic model. The specific performance criteria used include (1) the root mean square error (RMSE) between the model predictions and the assimilated observations, as well as normalized misfit terms measuring the filter's ability to resolve (2) reservoir wall tensile stress, (3) easily-observable unique parameters such as reservoir position and aspect ratio, and (4) difficult-to-derive non-unique parameters such as the specific size and internal pressure of the reservoir. The assimilated data include two different scenarios, one in which inflation is caused by pressurization and another in which it is driven by a lateral reservoir expansion. Both datasets are tested with each EnKF variant. Finally, we include example matrices from within an EnKF update step to demonstrate inter-parameter correlations that develop during the assimilation and how they can be mitigated through randomization.
DOI: 10.5281/zenodo.6780523
title: Performance Criteria and Example Parameter Sets Comparing Different Variants of the Ensemble Kalman Filter as Applied to Volcanology

description: This dataset contains the results of various Ensemble Kalman Filter (EnKF) inversions in which synthetic GNSS and InSAR observations from an inflating magma system are assimilated into numerical models of rock deformation around a pressurized ellipsoidal magma reservoir. Each inversion uses a different variant of the EnKF, with changes to workflow meta-parameters such as the number of ensemble members or the particular update algorithm used. In particular, each filter variant is evaluated by comparing the final output model to the original synthetic model. The specific performance criteria used include (1) the root mean square error (RMSE) between the model predictions and the assimilated observations, as well as normalized misfit terms measuring the filter's ability to resolve (2) reservoir wall tensile stress, (3) easily-observable unique parameters such as reservoir position and aspect ratio, and (4) difficult-to-derive non-unique parameters such as the specific size and internal pressure of the reservoir. The assimilated data include two different scenarios, one in which inflation is caused by pressurization and another in which it is driven by a lateral reservoir expansion. Both datasets are tested with each EnKF variant. Finally, we include example matrices from within an EnKF update step to demonstrate inter-parameter correlations that develop during the assimilation and how they can be mitigated through randomization.
DOI: 10.3886/ykyk-2q60
title: El Salvador Compact - Investment Support and Financial Services: Interim Analysis Report
DOI: 10.3886/krbe-kv81
title: El Salvador Compact - Investment Support and Financial Services: Interim Analysis Report
DOI: 10.3886/j6rv-8k75
title: El Salvador Compact - Production and Business Services: Interim Analysis Report
DOI: 10.3886/hs6c-n770
title: El Salvador Compact - Production and Business Services: Interim Analysis Report
DOI: 10.5066/p9usgdwc
title: Simulated impacts of feather oiling on avian energetics and migration: R environment model code and raw output

description: This dataset represents a modeling effort intended to explore the impacts of oiling on migratory birds. The purpose of this model is to provide a first principles approach to predict potential biological impacts of altered energetics dynamics in north American migratory birds due to oiling of feathers. This data includes predicted theoretical impacts on migration timing, wintering latitude, starvation rates, and increased food uptake. This data was generated through model implementation in R (R Core Team 2020; Version 4.0.4).
DOI: 10.3886/7098-n418
title: El Salvador Compact - Production and Business Services: Baseline Analysis Report
DOI: 10.3886/yd38-r195
title: El Salvador Compact - Production and Business Services: Baseline Analysis Report
DOI: 10.3886/af23-qy25
title: El Salvador Compact - Production and Business Services: Design Report
DOI: 10.3886/8swe-bj61
title: El Salvador Compact - Production and Business Services: Design Report
DOI: 10.3886/d62c-sj46
title: El Salvador Compact - Production and Business Services: Baseline Analysis Report_Handicrafts
DOI: 10.3886/s44g-jw62
title: El Salvador Compact - Production and Business Services: Baseline Analysis Report_Handicrafts
DOI: 10.26300/hhy0-g366
title: Data documentation for "State Regulations and Assisted Living Residents’ Potentially Burdensome Transitions at the End of Life"
DOI: 10.3886/ahm8-4416
title: Armenia Compact - Rural Road Rehabilitation: Final Analysis Report
DOI: 10.3886/hs9v-hd11
title: Armenia Compact - Rural Road Rehabilitation: Final Analysis Report
DOI: 10.5519/qd.zffyink1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (419 records)
DOI: 10.5281/zenodo.7135955
title: Storm drain water level measurements from Beaufort, North Carolina

description: This dataset contains water level measurements from within a storm drain in Beaufort, North Carolina, USA. Water level measurements were collected using a Sunny Day Flooding Project (https://tarheels.live/sunnydayflood/) sensor system. The data span from June 22, 2021 to November 30, 2021. Drift-corrected water level measurements relative to the road are in column "road_water_level_adj", and drift-corrected water level measurements relative to NAVD88 are in column "sensor_water_level_adj".
DOI: 10.5281/zenodo.7135954
title: Storm drain water level measurements from Beaufort, North Carolina

description: This dataset contains water level measurements from within a storm drain in Beaufort, North Carolina, USA. Water level measurements were collected using a Sunny Day Flooding Project (https://tarheels.live/sunnydayflood/) sensor system. The data span from June 22, 2021 to November 30, 2021. Drift-corrected water level measurements relative to the road are in column "road_water_level_adj", and drift-corrected water level measurements relative to NAVD88 are in column "sensor_water_level_adj".
DOI: 10.5281/zenodo.7195664
title: TnB AE data set

description: This is a data set containing LoRa traces used in the evaluation of TnB.
DOI: 10.5281/zenodo.7195663
title: TnB AE data set

description: This is a data set containing LoRa traces used in the evaluation of TnB.
DOI: 10.5281/zenodo.7196045
title: TnB AE data set

description: This is a data set containing LoRa traces used in the evaluation of TnB.
DOI: 10.5281/zenodo.7196536
title: TnB AE data set

description: This is a data set containing LoRa traces used in the evaluation of TnB.
DOI: 10.5281/zenodo.7199527
title: TnB AE data set

description: This is a data set containing LoRa traces used in the evaluation of TnB.
DOI: 10.6084/m9.figshare.21335640.v1
title: Serum #9.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335640
title: Serum #9.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335631
title: Serum #8.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335631.v1
title: Serum #8.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335619.v1
title: Serum #6.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335619
title: Serum #6.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335625
title: Serum #7.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335625.v1
title: Serum #7.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335601
title: Serum #5.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335601.v1
title: Serum #5.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335589
title: Serum #3.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335589.v1
title: Serum #3.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335598
title: Serum #4.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335598.v1
title: Serum #4.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335721
title: Serum #23.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335721.v1
title: Serum #23.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335715
title: Serum #22.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335715.v1
title: Serum #22.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335706
title: Serum #20.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335706.v1
title: Serum #20.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335580
title: Serum #2.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335580.v1
title: Serum #2.qgd

description: Data file
DOI: 10.7910/dvn/lawiyw/7ivmpv
title: MRRJ_ordinary_visiting_given_by_one_call_over_shifts.tab

description: The estimation given by only one cell phone call would not be directly considered as O-D, so we consider it as a visiting probability from the place of the presumed domicile. For each visit over each shift, it is considered only the most visited of all the visiting places of each active cell phone user. If a tie happens, it is considered the far place from home.
DOI: 10.7910/dvn/lawiyw/cketsy
title: MRRJ_extraordinary_mobility_carnival.tab

description: This shows the extraordinary mobility related to the Carnival blocks in Rio de Janeiro in 2014.
DOI: 10.7910/dvn/lawiyw/jzrhab
title: MRRJ_extraordinary_mobility_beaches_visiting_in_summer.tab

description: This shows the extraordinary mobility related to the weekend average visiting in the beaches of Rio de Janeiro on the summer of 2014.
DOI: 10.7910/dvn/lawiyw/ea7xlr
title: MRRJ_extraordinary_mobiity_new_yr_eve2014.tab

description: This shows the extraordinary mobility related to the 2014 New Year's Eve visiting in the places of MRRJ were it was planned to happen pyrotechnics.
DOI: 10.7910/dvn/lawiyw/goqaad
title: MRRJ_extraordinary_mobiity_new_yr_eve2015.tab

description: This shows the extraordinary mobility related to the 2015 New Year's Eve visiting in the places of MRRJ were it was planned to happen pyrotechnics.
DOI: 10.7910/dvn/lawiyw/ixqozc
title: MRRJ_21_area_new_years_eve.zip

description: Unions of the set of voronoi considered as the regions visited on the New Year's Eve.
DOI: 10.7910/dvn/lawiyw/70jxpx
title: MRRJ_21_area_beaches.zip

description: Unions of the set of voronoi considered as the cell phone covering area of the famous Rio de Janeiro's beaches.
DOI: 10.7910/dvn/lawiyw/cwem97
title: MRRJ_21_area_carnivals_blocks.zip

description: Unions of the set of voronoi considered as the regions visited by the popular Carnival's blocks. Attention to the fact that most blocks happen at the same place, but on different dates. You may see these areas with the abbreviated names of the blocks listed together.
DOI: 10.6084/m9.figshare.21335709
title: Serum #21.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335709.v1
title: Serum #21.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335700
title: Serum #19.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335700.v1
title: Serum #19.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335673
title: Serum #15.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335673.v1
title: Serum #15.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335679
title: Serum #16.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335679.v1
title: Serum #16.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335685
title: Serum #17.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335685.v1
title: Serum #17.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335691
title: Serum #18.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335691.v1
title: Serum #18.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335664
title: Serum #14.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335664.v1
title: Serum #14.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335649
title: Serum #11.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335649.v1
title: Serum #11.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335655
title: Serum #12.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335655.v1
title: Serum #12.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335661
title: Serum #13.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335661.v1
title: Serum #13.qgd

description: Data file
DOI: 10.17632/krbhsg5xrt.1
title: SNMP 2016 dataset

description: The enormous growth in computer networks and in Internet usage in recent years,
combined with the growth in the amount of data exchanged over networks, have shown
an exponential increase in the amount of malicious and mysterious threats to computer
networks. Among many security issues, network attack is a major one. For example,
Denial of Service (DoS) flooding attacks have recently become attractive to attackers,
and these have posed devastating threats to network services. Therefore, the intrusion
detection and network anomalies become very critical tasks in the field of network
security research area. Researchers suffer from the lack of real-life datasets. Most of
the datasets in hand depend on simulated-based approaches, which cannot represent the
exact and the nature of network intrusion and anomaly scenarios. Hence, generating
realistic datasets is very important as it allows for accurate and appropriate evaluation
of the detection techniques. To overcome such shortcoming of the existing datasets, in
this paper, we identify the important requirements to generate effective dataset and we
also identify important attack scenarios and the method of injecting them in such data.
Our systematic approach involves the investigation of Simple Network Management
Protocol (SNMP) for network anomaly detection. For that, we present a Management
Information Base (MIB) based mechanism capturing realistic SNMP-MIB statistical
data. Then we use this data from an SNMP agent by means of real-life experiments
involving six types of DoS attacks and Brute Force attack. Our dataset consists of 4998
records, where each record consists of 34 MIB variables, which are categorized into
their corresponding groups, namely: Interface, IP, TCP and ICMP.
DOI: 10.6084/m9.figshare.21335646
title: Serum #10.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335646.v1
title: Serum #10.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335736
title: NCI fucose 2022-08-18.qgb

description: Batch file
DOI: 10.6084/m9.figshare.21335736.v1
title: NCI fucose 2022-08-18.qgb

description: Batch file
DOI: 10.17632/vx8x5fx95n.1
title: Effect of storage temperature and protease inhibitor on ß-galactosidase extract enzyme activity and protein concentration

description: Extraction buffer omitting protease inhibitor was prepared and 1 protease inhibitor tablet was dissolved in 20ml. The extracts were prepared as follows: six flies expressing lacZ (DJ694,Bg2 recombinant strain BDSC:8176, BDSC:1776) were each ground in 50µl of buffer without protease inhibitor. The extracts were centrifuged and 40µl of supernatant was recovered from each fly and pooled (240µl total). The extract was split into two tubes (120µl each) and 120µl of +protease inhibitor buffer was added to one tube and 120µl of -protease inhibitor buffer was added to the other tube. Each extract condition was measured at 0h. From each extract tube 60µl was removed and stored on ice, 60µl was removed and stored at 4℃, and 5 aliquots of 12µl each were removed and stored at -20℃. The remaining extract from each tube was stored at room temperature. Measurements from each temperature condition were taken at 6, 24, 48, 72h. The extract preparations and measurements were done in triplicate. Independent extract preparations were made to measure enzyme activity (CPRG assay) and protein content (Bradford assay). Replicates 1,2,3 were used for the ß-gal activity measurements and Replicates 4,5,6 were used for the Protein content measurements. Extracts stored at 25°C were left on the bench, 0°C were stored on ice, 4°C were stored in the fridge, -20°C were stored in the freezer.
Raw microplate readings are available upon request.
DOI: 10.6084/m9.figshare.21335520
title: Serum #1.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335520.v1
title: Serum #1.qgd

description: Data file
DOI: 10.6084/m9.figshare.21335724
title: PFB sugars 20220818_NCI_fucose_v2.qgm

description: Method file
DOI: 10.6084/m9.figshare.21335724.v1
title: PFB sugars 20220818_NCI_fucose_v2.qgm

description: Method file
DOI: 10.17632/bw2drzb9vc.1
title: Supplement to “Arrowhead sign: the presenting diagnostic sign of lichen planopilaris in a case series of 24 African American women.” 

description: Supplement to “Arrowhead sign: the presenting diagnostic sign of lichen planopilaris in a case series of 24 African American women.”
DOI: 10.17632/49c4nhw7ch.1
title: X-ray photoelectron spectra of oxidized ordered mesoporous carbon materials

description: This set contains data used for characterization of ordered mesoporous carbon materials oxidized with oxygen plasma and ammonium persulfate described in a publication: Speciation of oxygen functional groups on the carbon support controls the dispersion of cobalt oxide nanoparticles and catalytic activity in the oxygen evolution reaction.
1. Description of the samples.
2. *.dat text file with the set of the C 1s spectra
3. *.dat text file with the set of the O 1s spectra
4. Original data files in the vms format - zipped
DOI: 10.5281/zenodo.4671059
title: Merged Adult Human Kidney sc & snRNA-seq dataset

description: A merged human kidney scRNA-seq dataset made from the following scRNA-seq studies: Lake, B.B. et al. A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys. Nat Commun 10, 2832 (2019). Liao, J., Yu, Z., Chen, Y. et al. Single-cell RNA sequencing of human kidney. Sci Data 7, 4 (2020). Menon, R. et al. Single cell transcriptomics identifies focal segmental glomerulosclerosis remission endothelial biomarker. JCI Insight 5, e133267 (2020). Wu, H. et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J Am Soc Nephrol 29: 2069–2080 (2018). Young, M. D. et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361, 594–599 (2018).
DOI: 10.5281/zenodo.7199569
title: Merged Adult Human Kidney sc & snRNA-seq dataset

description: A merged human kidney scRNA-seq dataset made from the following scRNA-seq studies: Lake, B.B. et al. A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys. Nat Commun 10, 2832 (2019). Liao, J., Yu, Z., Chen, Y. et al. Single-cell RNA sequencing of human kidney. Sci Data 7, 4 (2020). Menon, R. et al. Single cell transcriptomics identifies focal segmental glomerulosclerosis remission endothelial biomarker. JCI Insight 5, e133267 (2020). Wu, H. et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J Am Soc Nephrol 29: 2069–2080 (2018). Young, M. D. et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361, 594–599 (2018).
DOI: 10.17632/k2m2m3jgmn.1
title: Reproducibility of ß-galactosidase specific activity measurements by CPRG and Bradford assays

description: ß-galactosidase specific activity was measured from two Drosophila genotypes. Two different muscle-specific GAL4 drivers, Mef2-Gal4 (BDSC:27390) and DJ694 (BDSC: 8176), were each crossed with a second chromosome insertion of UAS-lacZ (Bg2) (BDSC: 1776), generating Bg2/+;Mef2/+ and DJ694/Bg2 genotypes. Flies were raised at 29℃. Crosses were performed at 29℃ in bottles in duplicate, after 2 days bottles were flipped into a new set of bottles, effectively producing 4 experimental replicates. Progeny was maintained at at 29℃. Measurements were performed on whole third instar larvae (L3) and early pupae (EP), and 15 day old adult male and female thoraces (Adult 15). Five extracts (1 individual in each) were measured per experimental replicate. Raw microplate readings are available upon request.
DOI: 10.17632/4gf2tcx8n4.1
title: TableS1

description: The objectives of this study were: (1) to develop a computer vision system to individually monitor detailed feeding behaviors of group-housed dairy heifers; and (2) to determine the optimal frequency of image acquisition to perform inference with minimal impact on feeding behavior prediction quality. Eight Holstein heifers (96 ± 6 d old) were housed in a group and a total of 25,214 images (one image every second) were acquired using one RGB camera. A total of 2,209 images were selected and each animal in the image was labeled with its respective identification (1-8). The label was annotated only on animals that were at the feed bunk (head through the feed rail). From the labeled images, 1,392 were randomly selected to train a deep learning algorithm for object detection with YOLOv3 ("You Only Look Once" version 3) and 154 images were used for validation. An independent dataset (testing set = 663 out of the 2,209 images) was used to test the algorithm. The average accuracy for identifying individual animals in the testing set was 96.0%, and for each individual heifer from 1 to 8 the accuracy was 99.2%, 99.6%, 99.2%, 99.6%, 99.6%, 99.2%, 99.4%, and 99.6%, respectively. After identifying the animals at the feed bunk, we computed the feeding behavior parameters: number of visits (NV), mean visit duration (MVD), mean interval between visits (MIBV), and feeding time (FT) for each heifer using a dataset composed by 8,883 sequential images (one image every second) from four time-points. The R2 was 0.39, 0.78, 0.48, and 0.99, and the root mean square error (RMSE) were 12.3 (count), 0.78 (min), 0.63 (min), and 0.31 (min) for NV, MVD, MIBV, and FT, respectively, considering one image every second. When we moved from one image per second to one image every five (MIBV) or ten (NV, MDV, and FT) seconds, the R2 observed were: 0.55 (NV), 0.74 (MVD), 0.70 (MIBV), and 0.99 (FT); and the RMSE were: 2.27 (NV, count), 0.38 (MVD, min), 0.22 (MIBV, min), and 0.44 (FT, min). Our results indicate that computer vision systems can be used to individually identify group-housed Holstein heifers (overall accuracy = 99.4%). Based on individual identification, feeding behavior such as MVD, MIBV, and FT can be monitored with reasonable accuracy and precision. Regardless of the frequency for optimal image acquisition, our results suggested that longer time intervals of image acquisition would reduce data collecting and model inference while maintaining adequate predictive performance. However, we did not find an optimal time interval for all feeding behavior; instead, the optimal frequency of image acquisition is phenotype specific. Overall, the best R2 and RMSE for NV, MDV, and FT were achieved using one image every ten seconds, and for MIBV it was achieved using one image every five seconds, and in both cases model inference and data storage could be drastically reduced.
DOI: 10.17632/7zfmb4n9gs.1
title: Timeline

description: The GMT tab contains the original time, Greenwich Mean Time, and the Central European Time of the news.