cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p93klm31
title: Evaluation of Hydrodynamic Mixing in Keswick Reservoir, California, 2021-22

description: California's State Water Resources Control Board (SWRCB) wishes to quantify how water and constituents introduced via the outflow from the Spring Creek Diversion Dam mix with water within Keswick Reservoir. Of primary interest is the degree of dilution that exists when this introduced flow reaches the main stem of Keswick Reservoir, and how this mixing is influenced by different operational parameters of the system. In addition to flows through the three relevant dams (Spring Creek Debris Dam, Keswick Dam, and Shasta Dam) that must be considered, there is additional flow entering the Spring Creek Arm of the Keswick Reservoir via two penstocks that carry water from Whiskeytown Lake - in a different watershed - to the Spring Creek Power Plant. In total there are thus four different flow rates to consider, all controlled by the U.S. Bureau of Reclamation to manage a combination of water supply, water quality and ecological interests. The problem was investigated by an approach that combines three-dimensional numerical modeling of hydrodynamics and an assumed conserved tracer with a small field measurement campaign to measure short-term mixing processes via monitoring of released dye for comparison to model results. The project involves the use of the public domain Delft3d hydrodynamic model, which includes conserved constituent transport. This data release contains data from: 1) a small-footprint bathymetric survey performed at the upstream end of the Spring Creek Arm on 12/3/22, and 2) Data from a Rhodamine dye mixing experiment conducted 4/4-4/8/22. This dataset includes: - discharge data to and from Keswick reservoir - some water level and water temperature data - a bathymetric survey dataset assembled from three different surveys, differing in scope, in 2010, 2016 and 2021. - data from 10 sondes deployed in Keswick Reservoir 4/4-4/8/22 to record Rhodamine dye concentration, water temperature, and specific conductivity, along with pressure head. - data from three GPS-equipped drifters that recorded surface flow pathlines for the first half-day of the April 2022 experiment. This this data release includes all of the measurements required to run the hydrodynamic model to simulate the April 2022 field experiment.
DOI: 10.6084/m9.figshare.21518727
title: Throughput Database Snapshot - Nov 8 2022

description: Regular snapshot of the Throughput Database, funded through the NSF EarthCube initiative.
DOI: 10.6084/m9.figshare.21518727.v1
title: Throughput Database Snapshot - Nov 8 2022

description: Regular snapshot of the Throughput Database, funded through the NSF EarthCube initiative.
DOI: 10.15131/shef.data.21517617
title: TD-GC-MS raw data measuring NVOC's in UK Forest Air

description: A TD-GC-MS study on the NVOC's in forest air. NVOC's are thought to have many beneficial effects on health however very little is known about the composition of air in a UK forest. This study was a preliminary analysis of forest air in a UK ancient woodland. Methods A BUCK Elite™ model Elite-1 Personal Air Sampler was used to pump air through Stainless Steel Tenax GR 60/80 Packed thermal desorption (TD) Sample Tubes (Perkin Elmer). The tubes were all pre-conditioned at a temperature of 300oC and a flow rate of 50ml/min helium. The pump was connected to a manifold allowing collection onto 4 tubes simultaneously. The pump was mounted at a height of 1.5m above the forest floor using a camera tripod. The flow rate of sampling was 500ml/min and air was sampled for 2 hours.4 samples were collected in the forest and 4 samples were collected in a control walled garden area. The tubes were removed from the manifold and end capped immediately after sampling. These tubes were then loaded within 24 hours onto a Perkin Elmer Turbo Matrix 650 thermal desorption unit attached to a Perkin Elmer Clarus SQ8T GC-MS system. The temperature ramp for desorption was 40oC/sec up to a final temperature of 290oC with a flow rate of 50ml/min of helium. The tubes underwent a 2-stage desorption of 5 minutes followed by 2 minutes. The samples were injected into the GC-MS onto a Perkin Elmer MS-5 fused silica capillary column (30 x 25um, Perkin Elmer). The initial oven temperature was 50oC and the temperature of the GC oven was ramped at 20oC per minute to a final temperature of 230oC and held there for 10 minutes. Data was acquired over the mass range 50-400amu.
DOI: 10.15131/shef.data.21517617.v1
title: TD-GC-MS raw data measuring NVOC's in UK Forest Air

description: A TD-GC-MS study on the NVOC's in forest air. NVOC's are thought to have many beneficial effects on health however very little is known about the composition of air in a UK forest. This study was a preliminary analysis of forest air in a UK ancient woodland. Methods A BUCK Elite™ model Elite-1 Personal Air Sampler was used to pump air through Stainless Steel Tenax GR 60/80 Packed thermal desorption (TD) Sample Tubes (Perkin Elmer). The tubes were all pre-conditioned at a temperature of 300oC and a flow rate of 50ml/min helium. The pump was connected to a manifold allowing collection onto 4 tubes simultaneously. The pump was mounted at a height of 1.5m above the forest floor using a camera tripod. The flow rate of sampling was 500ml/min and air was sampled for 2 hours.4 samples were collected in the forest and 4 samples were collected in a control walled garden area. The tubes were removed from the manifold and end capped immediately after sampling. These tubes were then loaded within 24 hours onto a Perkin Elmer Turbo Matrix 650 thermal desorption unit attached to a Perkin Elmer Clarus SQ8T GC-MS system. The temperature ramp for desorption was 40oC/sec up to a final temperature of 290oC with a flow rate of 50ml/min of helium. The tubes underwent a 2-stage desorption of 5 minutes followed by 2 minutes. The samples were injected into the GC-MS onto a Perkin Elmer MS-5 fused silica capillary column (30 x 25um, Perkin Elmer). The initial oven temperature was 50oC and the temperature of the GC oven was ramped at 20oC per minute to a final temperature of 230oC and held there for 10 minutes. Data was acquired over the mass range 50-400amu.
DOI: 10.5281/zenodo.7305008
title: Vides satraukuma indekss (piecu Rīgas pieostas apkaimju iedzīvotāju aptauja, 2019)

description: Datu avots: projekta <em>Dzīve līdzās ostai</em> piecu Rīgas pieostas apkaimju iedzīvotāju aptauja (2019). Tā aprakstīta grāmatā: Dace Bula (zin. red.). <em>Dzīve līdzās ostai</em>. Rīga: LU LFMI, 2022. 184. lpp. (tabula publicēta kā 3.pielikums, 168-173.lpp.). Vides satraukuma indekss parāda, cik satrauktas par vairākiem vidi apdraudošiem un piesārņojošiem aspektiem ir konkrētas iedzīvotāju grupas, piemēram, vīrieši un sievietes; jaunieši, vidējā vecuma iedzīvotāji un seniori. Indekss aprēķināts, ņemot vērā katra respondenta atbildes uz jautājumu par satraukumu par astoņiem vides piesārņojuma veidiem (putekļi, smakas, troksnis, vibrācijas, liegta piekļuve Daugavai, ūdens piesārņojums, gaismas piesārņojums, intensīva satiksme), katrai viņa atbildei piešķirot noteiktu vērtību un tad tās summējot. Zemāk ir seši iespējamie atbilžu varianti uz katru no indeksā iekļautajiem astoņiem rādītājiem, kā arī to svars jeb summēja­mā vērtība. Maksimālā indeksa vērtība ir 24, mini­mālā: -8 (“ļoti satrauc” =3, “drīzāk satrauc”=2, “drīzāk nesatrauc”= 1, “nemaz nesatrauc”=0, “[apkaimē] nav šīs problēmas”=-1). Detalizētāk indeksa izveide un analīze aprakstīta nodaļā «Iedzīvotāji vērtē dzīves vidi līdzās ostai» (sadaļa «Kuras iedzīvotāju grupas ir vissatrauktākās?», 98.lpp.). Ja konkrētā respondentu grupā aptaujāto skaits ir mazāks par 30, tad indekss netiek attēlots (tā vietā ir “..”), tāpēc tabulā atsevišķi nav izdalīti Kundziņsalas iedzīvotāji, jo kopējais aptaujāto kundziņsaliešu skaits ir 30, un to salīdzināšanai mazākās sociāli demogrāfiskajās šķērsgriezumu grupās nav statistiska pamatojuma. «Atšķirību būtiskums» parāda konkrētā respondentu dalījuma atšķirību statistisko nozīmīgumu («0.000» nozīmē lielākās, bet «0.005» — mazākās atšķirības; ja rādītājs ir lielāks nekā «0.005», atšķirības jāuzskata par statistiski nenozīmīgām, un tad rādītājs netiek attēlots). Piemēram, salīdzinot piecu apkaimju iedzīvotāju vides satraukuma indeksu, ir konstatējamas būtiskas statistiskās atšķirības starp dažādu apkaimju iedzīvotāju vērtējumiem, jo atšķirību būtiskuma rādītājs ir «0.000» (satrauktākie ir Mangaļsalas iedzīvotāji, indekss «17.2», bet vismazāk satrauktie — Daugavgrīvas iedzīvotāji, indekss «14.4»), bet nav atšķirību starp visu apkaimju vīriešu un sieviešu satraukumu (atšķirību būtiskuma rādītājs ir bijis lielāks nekā «0.005», tātad atšķirības nav statistiski nozīmīgas un tabulā atšķirību būtiskuma vērtība nav attēlota). «Dzīve līdzās ostai: ekonaratīvi, vietējā vēsture un vides aktīvisms Daugavas lejtecē» (Nr. lzp-2018/1-0446). Projekta vadītāja Dr. philol. Dace Bula. Dzīve līdzās ostai: ekonaratīvi, vietējā vēsture un vides aktīvisms Daugavas lejtecē // Living Next to the Port: Eco-Narratives, Local Histories and Environmental Activism in the Daugava Delta (https://zenodo.org/communities/ekohum) Kā <em>google sheets</em> publicēta: https://docs.google.com/spreadsheets/d/1k4o1cuNXLolHwqVKM1m2tR-5Xgb0Uk0T9OyusYUtUyo/edit?usp=sharing
DOI: 10.5281/zenodo.7305007
title: Vides satraukuma indekss (piecu Rīgas pieostas apkaimju iedzīvotāju aptauja, 2019)

description: Datu avots: projekta <em>Dzīve līdzās ostai</em> piecu Rīgas pieostas apkaimju iedzīvotāju aptauja (2019). Tā aprakstīta grāmatā: Dace Bula (zin. red.). <em>Dzīve līdzās ostai</em>. Rīga: LU LFMI, 2022. 184. lpp. (tabula publicēta kā 3.pielikums, 168-173.lpp.). Vides satraukuma indekss parāda, cik satrauktas par vairākiem vidi apdraudošiem un piesārņojošiem aspektiem ir konkrētas iedzīvotāju grupas, piemēram, vīrieši un sievietes; jaunieši, vidējā vecuma iedzīvotāji un seniori. Indekss aprēķināts, ņemot vērā katra respondenta atbildes uz jautājumu par satraukumu par astoņiem vides piesārņojuma veidiem (putekļi, smakas, troksnis, vibrācijas, liegta piekļuve Daugavai, ūdens piesārņojums, gaismas piesārņojums, intensīva satiksme), katrai viņa atbildei piešķirot noteiktu vērtību un tad tās summējot. Zemāk ir seši iespējamie atbilžu varianti uz katru no indeksā iekļautajiem astoņiem rādītājiem, kā arī to svars jeb summēja­mā vērtība. Maksimālā indeksa vērtība ir 24, mini­mālā: -8 (“ļoti satrauc” =3, “drīzāk satrauc”=2, “drīzāk nesatrauc”= 1, “nemaz nesatrauc”=0, “[apkaimē] nav šīs problēmas”=-1). Detalizētāk indeksa izveide un analīze aprakstīta nodaļā «Iedzīvotāji vērtē dzīves vidi līdzās ostai» (sadaļa «Kuras iedzīvotāju grupas ir vissatrauktākās?», 98.lpp.). Ja konkrētā respondentu grupā aptaujāto skaits ir mazāks par 30, tad indekss netiek attēlots (tā vietā ir “..”), tāpēc tabulā atsevišķi nav izdalīti Kundziņsalas iedzīvotāji, jo kopējais aptaujāto kundziņsaliešu skaits ir 30, un to salīdzināšanai mazākās sociāli demogrāfiskajās šķērsgriezumu grupās nav statistiska pamatojuma. «Atšķirību būtiskums» parāda konkrētā respondentu dalījuma atšķirību statistisko nozīmīgumu («0.000» nozīmē lielākās, bet «0.005» — mazākās atšķirības; ja rādītājs ir lielāks nekā «0.005», atšķirības jāuzskata par statistiski nenozīmīgām, un tad rādītājs netiek attēlots). Piemēram, salīdzinot piecu apkaimju iedzīvotāju vides satraukuma indeksu, ir konstatējamas būtiskas statistiskās atšķirības starp dažādu apkaimju iedzīvotāju vērtējumiem, jo atšķirību būtiskuma rādītājs ir «0.000» (satrauktākie ir Mangaļsalas iedzīvotāji, indekss «17.2», bet vismazāk satrauktie — Daugavgrīvas iedzīvotāji, indekss «14.4»), bet nav atšķirību starp visu apkaimju vīriešu un sieviešu satraukumu (atšķirību būtiskuma rādītājs ir bijis lielāks nekā «0.005», tātad atšķirības nav statistiski nozīmīgas un tabulā atšķirību būtiskuma vērtība nav attēlota). «Dzīve līdzās ostai: ekonaratīvi, vietējā vēsture un vides aktīvisms Daugavas lejtecē» (Nr. lzp-2018/1-0446). Projekta vadītāja Dr. philol. Dace Bula. Dzīve līdzās ostai: ekonaratīvi, vietējā vēsture un vides aktīvisms Daugavas lejtecē // Living Next to the Port: Eco-Narratives, Local Histories and Environmental Activism in the Daugava Delta (https://zenodo.org/communities/ekohum) Kā <em>google sheets</em> publicēta: https://docs.google.com/spreadsheets/d/1k4o1cuNXLolHwqVKM1m2tR-5Xgb0Uk0T9OyusYUtUyo/edit?usp=sharing
DOI: 10.5281/zenodo.7304956
title: Aggregated variant data from whole-genome sequenced tinnitus patients (TIGER)

description: Aggregated variant data obtained from tinnitus patients from Sweden. Uploaded datasets are storage in annotated csv files. Annotation was performed using VEP (v106), including population frequencies for each variant from gnomAD, non-finnish Europeans from gnomAD, and swedish population from SweGen project. Pathogenicity scores from CADD are also annotated for each variant. Variants from genes found to be enriched in a gene burden analysis can be found in this aggregated dataset. <strong>agg.tiger.csv</strong> - TIGER cohort is composed by 97 swedish whole-genome sequenced constant tinnitus patients. <strong>agg.jaguar.csv</strong> - JAGUAR cohort is composed by 147 swedish whole-exome sequenced tinnitus patients . <strong>agg.sevtin.csv</strong> - SEVTIN cohort is a subcohort from TIGER, with 34 WGS patients seggregating severe tinnitus phenotype. <strong>agg.controls.csv</strong> - Controls is a swedish population cohort composed by 151 whole-exome sequenced swedish individuals.
DOI: 10.5281/zenodo.7304955
title: Aggregated variant data from whole-genome sequenced tinnitus patients (TIGER)

description: Aggregated variant data obtained from tinnitus patients from Sweden. Uploaded datasets are storage in annotated csv files. Annotation was performed using VEP (v106), including population frequencies for each variant from gnomAD, non-finnish Europeans from gnomAD, and swedish population from SweGen project. Pathogenicity scores from CADD are also annotated for each variant. Variants from genes found to be enriched in a gene burden analysis can be found in this aggregated dataset. <strong>agg.tiger.csv</strong> - TIGER cohort is composed by 97 swedish whole-genome sequenced constant tinnitus patients. <strong>agg.jaguar.csv</strong> - JAGUAR cohort is composed by 147 swedish whole-exome sequenced tinnitus patients . <strong>agg.sevtin.csv</strong> - SEVTIN cohort is a subcohort from TIGER, with 34 WGS patients seggregating severe tinnitus phenotype. <strong>agg.controls.csv</strong> - Controls is a swedish population cohort composed by 151 whole-exome sequenced swedish individuals.
DOI: 10.21227/7d2b-9q15
title: Geometric machine learning based AOA estimation

description: This data set is the source code and data of the paper in the same name.
DOI: 10.21227/hcwn-fm86
title: Geometric machine learning based AOA estimation

description: This data set is the source code and data of the paper in the same name.
DOI: 10.5281/zenodo.7304381
title: SIM-MPC Dataset

description: This dataset contains the MPC simulation data of the paper "Simulating Interaction Movements via Model Predictive Control". To get an idea of how this data can be used, you might want to take a look at the Python package sim-mpc.
DOI: 10.5281/zenodo.7300219
title: SIM-MPC Dataset

description: This dataset contains the MPC simulation data of the paper "Simulating Interaction Movements via Model Predictive Control". To get an idea of how this data can be used, you might want to take a look at the Python package sim-mpc.
DOI: 10.5281/zenodo.7300062
title: ISO-VR-Pointing Dataset

description: This dataset contains the user study data of the paper "Simulating Interaction Movements via Model Predictive Control". Python packages using this data include user-in-the-box, sim-mpc, and cfat. <strong>Note: </strong>The<em> ISO_VR_Pointing_Dataset.zip </em>contains all relevant files. The <em>ISO_VR_Pointing_IK_Raw.zip</em> contains a subset of this dataset with all files required by cfat.<br> <br>
DOI: 10.5281/zenodo.7300061
title: ISO-VR-Pointing Dataset

description: This dataset contains the user study data of the paper "Simulating Interaction Movements via Model Predictive Control". Python packages using this data include user-in-the-box, sim-mpc, and cfat. <strong>Note: </strong>The<em> ISO_VR_Pointing_Dataset.zip </em>contains all relevant files. The <em>ISO_VR_Pointing_IK_Raw.zip</em> contains a subset of this dataset with all files required by cfat.<br> <br>
DOI: 10.15454/ixshf7/frgqm3
title: data_WOW_merinos.csv

description: :unav
DOI: 10.15454/ixshf7/bl6ijc
title: Data_WoW_Merinos.tab

description: :unav
DOI: 10.15454/ixshf7/izvbes
title: Data_WoW_Merinos-1.tab

description: :unav
DOI: 10.15454/ixshf7/rq12ui
title: Data_WoW_Mérinos.tab

description: :unav
DOI: 10.15454/ixshf7/sgd1bv
title: Data_WoW_Mérinos.tab

description: :unav
DOI: 10.15454/ixshf7/wjqv8u
title: data_Livewieght_WOW_&GS_merinos.csv

description: :unav
DOI: 10.57745/az2hoi
title: Database2.tab

description: :unav
DOI: 10.57745/gldlns
title: Database1.tab

description: :unav
DOI: 10.57745/jz8k2q
title: DatabaseStatic_GoldStandard.tab

description: :unav
DOI: 10.57745/ri5o6e
title: Raw database.tab

description: :unav
DOI: 10.57745/tbxh66
title: Database3.tab

description: :unav
DOI: 10.57745/zsdern
title: R_Codes.docx

description: :unav
DOI: 10.57745/79xlja
title: DatabaseSelectionExpAnimals.xlsx

description: :unav
DOI: 10.57745/c4ewvv
title: DatabaseSelectionExpAnimals.xlsx

description: :unav
DOI: 10.57745/iwqtne
title: Database3.tab

description: :unav
DOI: 10.57745/l39iwh
title: DatabaseAdaptation.tab

description: :unav
DOI: 10.57745/pia82n
title: Metadata_File.docx

description: :unav
DOI: 10.57745/cg1xnd
title: Database1.tab

description: :unav
DOI: 10.57745/mncwxp
title: DatabaseAdaptation.tab

description: :unav
DOI: 10.57745/mypy5q
title: DatabaseStatic_GoldStandard.tab

description: :unav
DOI: 10.57745/rppouj
title: Raw database.tab

description: :unav
DOI: 10.57745/tr6sxm
title: Database2.tab

description: :unav
DOI: 10.57745/bfverf
title: Database3.tab

description: :unav
DOI: 10.57745/db2pkw
title: Database Adaptation.tab

description: :unav
DOI: 10.57745/hpox8n
title: Rawdatabase.tab

description: :unav
DOI: 10.57745/sm0v4r
title: LW_ewelambs_Collect_clean (00000002).Rmd

description: In this file, the R scripts used for each database cleaning procedure as well as for the analyse of variance are contained.
DOI: 10.5281/zenodo.7297099
title: Saskatchewan seismic data set 2

description: Seismic data from Saskatchewan glacier. Includes the waveform data, the log files, and the instrument response file.
DOI: 10.5281/zenodo.7297098
title: Saskatchewan seismic data set 2

description: Seismic data from Saskatchewan glacier. Includes the waveform data, the log files, and the instrument response file.
DOI: 10.5281/zenodo.7297102
title: Saskatchewan seismic data set 3

description: Seismic data from Saskatchewan glacier. Includes the waveform data, the log files, and the instrument response file.
DOI: 10.5281/zenodo.7297101
title: Saskatchewan seismic data set 3

description: Seismic data from Saskatchewan glacier. Includes the waveform data, the log files, and the instrument response file.
DOI: 10.6073/pasta/1d9747426a546e8cebd15dd611184dd9
title: Soil carbon and nitrogen: Old-Field Chronosequence: Plant Productivity

description: The goal of this research is to study the change in plant growth and species distribution during succession. Annual plant growth above ground is annually sampled in more than 20 fields from 4 permanently marked 3m x 4m plots in each field. These fields were previously cultivated, but then abandoned from agriculture at various times in the past. The fields were left undisturbed for plants to develop from seeds within the soil or brought into the fields by wind or animals. The fields included in this study are 4, 5, 10, 24, 26, 28, 35, 39, 41, 45, 53, 70, 72, 77 and the Lawrence strip that was abandoned in 1988. This experiment was started in 1987 by lead investigators David Tilman and Johannes Knops. In 2001 new sampling was started in positions similar to the E054 plots in these E014 fields: 21, 27, 32, 40, 44, 47, 76. Past work at CDR and elsewhere has demonstrated an overriding influence of fire frequency in maintaining prairie openings and oak savanna at the prairie-forest border. Fire regimes harm some types of species while favoring others and drive light and nutrient dynamics, which in turn drive community functional attributes and diversity levels. Ultimately, fire frequency interacts with climate, N deposition, land use, and biotic invasion to determine the outcomes of tree-grass interactions and the dynamics of vegetation at ecotones such as the prairie-forest border in Minnesota. In 2006 each field was divided in half, and one half randomly chosen for periodic prescribed burning (a fire every other year). We anticipate that the burned half will continue succession to prairie grassland while the unburned half will become white pine stands if seed sources are nearby, or will otherwise undergo extremely slow succession to oaks.
DOI: 10.6073/pasta/8ef837d6826ba0410ee42364b805b838
title: Root biomass carbon and nitrogen: Old-Field Chronosequence: Plant Productivity

description: The goal of this research is to study the change in plant growth and species distribution during succession. Annual plant growth above ground is annually sampled in more than 20 fields from 4 permanently marked 3m x 4m plots in each field. These fields were previously cultivated, but then abandoned from agriculture at various times in the past. The fields were left undisturbed for plants to develop from seeds within the soil or brought into the fields by wind or animals. The fields included in this study are 4, 5, 10, 24, 26, 28, 35, 39, 41, 45, 53, 70, 72, 77 and the Lawrence strip that was abandoned in 1988. This experiment was started in 1987 by lead investigators David Tilman and Johannes Knops. In 2001 new sampling was started in positions similar to the E054 plots in these E014 fields: 21, 27, 32, 40, 44, 47, 76. Past work at CDR and elsewhere has demonstrated an overriding influence of fire frequency in maintaining prairie openings and oak savanna at the prairie-forest border. Fire regimes harm some types of species while favoring others and drive light and nutrient dynamics, which in turn drive community functional attributes and diversity levels. Ultimately, fire frequency interacts with climate, N deposition, land use, and biotic invasion to determine the outcomes of tree-grass interactions and the dynamics of vegetation at ecotones such as the prairie-forest border in Minnesota. In 2006 each field was divided in half, and one half randomly chosen for periodic prescribed burning (a fire every other year). We anticipate that the burned half will continue succession to prairie grassland while the unburned half will become white pine stands if seed sources are nearby, or will otherwise undergo extremely slow succession to oaks.
DOI: 10.6084/m9.figshare.21005152
title: Vitamin A Preserves Cardiac Energetic Gene Expression in a Murine Model of Diet-Induced Obesity

description: Supplemental Figures 1 and 2 Supplemental Tables 1-5 Supplemental Table 6
DOI: 10.6084/m9.figshare.21005152.v1
title: Vitamin A Preserves Cardiac Energetic Gene Expression in a Murine Model of Diet-Induced Obesity

description: Supplemental Figures 1 and 2 Supplemental Tables 1-5 Supplemental Table 6
DOI: 10.25574/19725
title: Chandra X-ray Observatory ObsId 19725

description: Spinup of 1E161348-5055 n RCW 103 monitoring
DOI: 10.25574/20744
title: Chandra X-ray Observatory ObsId 20744

description: Spinup and changes in pulse profile of 1E161348-5055 in RCW 103