cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/91971a4cf42b7762cf72838a695658f8
title: Barre Woods Soil Warming Experiment at Harvard Forest since 2001

description: Two of the major results of our original soil warming study were that: (1) warming stimulated the decay of a labile soil carbon pool; and (2) it also increased the availability of inorganic nitrogen to plants. Because of the small size of the original warming plots an important question we have not been able to answer conclusively is: Has the increase in available nitrogen led to an increase in carbon storage in the vegetation? And if yes, how much? In a systems context an additional question is: What is the balance between the carbon lost from the soil and the carbon stored in the vegetation in response to soil warming? We are now addressing these important questions with a new warming experiment in the Barre Woods area of the Harvard Forest. The Barre Woods site was chosen because it is of similarities to the Prospect Hill site - stand age, tree species composition, and soil type. There is no evidence of a plow horizon at the Barre Woods site, though surrounding stone walls indicate past use as pastureland. Historical records indicate the site was destroyed during the 1938 hurricane and then regrew naturally. During the summer and fall of 2001 we buried 3.4 miles of heating cable in a 30 x 30m plot. Cables were buried at a 10cm depth, spaced 20cm apart. A second 30 x 30m area was delineated to serve as the control plot. Results from the original soil warming experiment confirmed that the soil disturbance associated with the installation of heating cables has had no effect on soil temperatures and only minor and variable impacts on soil moisture. In April 2002, we began a one-year period of baseline measurements before turning on the heat in the new megaplot. These measurements included nitrogen mineralization, trace gas fluxes (CO2, CH4, N2O), tree growth (dendrometer bands), an under story species survey, canopy foliage analysis (C:N, NIR), and lysimetry. Thermistors were installed in both plots to begin tracking soil temperatures. The baseline measurements have confirmed that there are no significant differences between the two plots for key ecosystem processes prior to the initiation of the warming manipulation. We will turn on the power in April 2003 to begin the "manipulation phase" of this study. From this study, we expect to determine whether or not warming results in the movement of nitrogen from the soil to the trees and to learn how this movement affects the net carbon balance of the ecosystem.
DOI: 10.18716/nmrshiftdb2/2346
title: NMR data for Dioncophylline E
DOI: 10.18716/nmrshiftdb2/2345
title: NMR data for 13-Acetoxy 3-tigloyl-germacra-1(10)E,4E,7(11)-trien-12,6-olide
DOI: 10.18716/nmrshiftdb2/2349
title: NMR data for Dorstenic acid A
DOI: 10.18716/nmrshiftdb2/2351
title: NMR data for 8-epi-Grandifloric acid
DOI: 10.21227/ywct-zy31
title: The USyd Campus Dataset

description: Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation and deep-learning applications. Despite this success, the validation of algorithm robustness has recently been recognised as a major challenge for the massive deployment of these new technologies. It is well known that algorithms and models trained or tested with a particular dataset tend not to generalise well for other scenarios. For certain applications, autonomous vehicles in particular, algorithm failures can lead to potentially catastrophic consequences. To minimise this risk, it is essential to evaluate the robustness and reliability of algorithms before deploying them in real life applications. This paper presents a long-term, large-scale dataset collected over the period of 1.5 years on a weekly basis over the University of Sydney campus and surrounds. The USyd Campus Dataset has been designed to aid in the development, validation and testing of algorithm robustness under a wide variety of conditions. It includes multiple sensor modalities and covers various environmental conditions as well as diverse changes to illumination, scene structure, and pedestrian/vehicle traffic volumes. The dataset also includes a semantic segmentation dataset with different illumination conditions and camera perspectives, and a ‘Road’ class image dataset which is automatically generated using lidar. To facilitate the dataset use by researchers and practitioners, we also provide a set of development tools for the analysis and visualisation of the dataset.
DOI: 10.5281/zenodo.3365397
title: RNA-Seq data for mice ovaries

description: Ten days old mice were injected with melatonin to 17 days old, and the ovaries were collected for RNA sequencing. The data were analyzed to study the effects of melatonin on early follicular growth.
DOI: 10.5281/zenodo.3365396
title: RNA-Seq data for mice ovaries

description: Ten days old mice were injected with melatonin to 17 days old, and the ovaries were collected for RNA sequencing. The data were analyzed to study the effects of melatonin on early follicular growth.
DOI: 10.5281/zenodo.3365947
title: JAMES_paper_data

description: The simulation data used in paper in JAMES (Ocean-wave-atmosphere interaction processes in a fully coupled modelling system)
DOI: 10.5281/zenodo.3365948
title: JAMES_paper_data

description: The simulation data used in paper in JAMES (Ocean-wave-atmosphere interaction processes in a fully coupled modelling system)
DOI: 10.18716/nmrshiftdb2/2348
title: NMR data for 5-acetoxy-7-benzoyloxymethyl-7H-oxepin-2-one; Klaivanolide
DOI: 10.21227/7sn6-8g06
title: The USyd Campus Dataset

description: Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation and deep-learning applications. Despite this success, the validation of algorithm robustness has recently been recognised as a major challenge for the massive deployment of these new technologies. It is well known that algorithms and models trained or tested with a particular dataset tend not to generalise well for other scenarios. For certain applications, autonomous vehicles in particular, algorithm failures can lead to potentially catastrophic consequences. To minimise this risk, it is essential to evaluate the robustness and reliability of algorithms before deploying them in real life applications. This paper presents a long-term, large-scale dataset collected over the period of 1.5 years on a weekly basis over the University of Sydney campus and surrounds. The USyd Campus Dataset has been designed to aid in the development, validation and testing of algorithm robustness under a wide variety of conditions. It includes multiple sensor modalities and covers various environmental conditions as well as diverse changes to illumination, scene structure, and pedestrian/vehicle traffic volumes. The dataset also includes a semantic segmentation dataset with different illumination conditions and camera perspectives, and a ‘Road’ class image dataset which is automatically generated using lidar. To facilitate the dataset use by researchers and practitioners, we also provide a set of development tools for the analysis and visualisation of the dataset.
DOI: 10.5281/zenodo.3259730
title: Transcripts of interviews conducted with female agricultural entrepreneurs in the West of Ireland in 2018

description: The file contains transcripts of recorded interviews with 10 women in the West of Ireland, who in the past had started a diversification business on or with farm resources. The objective of the research was to identify barriers for starting and growing a business for women in the agricultural domain. Furthermore resources used by these women for starting a business were explored. The method employed was that of narrative enquiries. The interviewer in all instances was the researcher.
DOI: 10.5281/zenodo.3259731
title: Transcripts of interviews conducted with female agricultural entrepreneurs in the West of Ireland in 2018

description: The file contains transcripts of recorded interviews with 10 women in the West of Ireland, who in the past had started a diversification business on or with farm resources. The objective of the research was to identify barriers for starting and growing a business for women in the agricultural domain. Furthermore resources used by these women for starting a business were explored. The method employed was that of narrative enquiries. The interviewer in all instances was the researcher.
DOI: 10.7910/dvn/nvrwn5
title: The Prostate Cancer Outcomes Cohort Study

description: The Prostate Cancer Outcomes Cohort Study (ProCOC) is a richly annotated bio repository for radical prostatectomy and pelvic lymph nodes specimens and serves successfully as foundation for clinical and translational research projects. After accrual of 471 patients with a median follow up of 53 (range: 0.1 – 93.2) months, biochemical recurrence-free and secondary oncological treatment-free survival reached 48 (range: 1.3 – 93.2) and 44.8 (range: 0.1 – 93.2) months, respectively. The study protocol includes storage of serum, plasma and urine samples for further bio repository investigations including translational research and biomarker studies.
DOI: 10.7910/dvn/nvrwn5/zdvzb1
title: proCOC db.tab

description: SPSS file
DOI: 10.18716/nmrshiftdb2/2350
title: NMR data for 3-Oxo-11,13(18)-oleanadien-28-oic acid
DOI: 10.18716/nmrshiftdb2/2328
title: NMR data for Itomanol
DOI: 10.18716/nmrshiftdb2/2352
title: NMR data for 3,12-Diacetyl-7-benzoyl-8-nicotinylingol
DOI: 10.18716/nmrshiftdb2/2355
title: NMR data for 5,6,11,14,17(R)-pentaacetoxy-3-benzoyloxy-15-hydroxyseget-8(12)-en-9-one; Segetene A
DOI: 10.21227/3462-eh07
title: The USyd Campus Dataset

description: Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation and deep-learning applications. Despite this success, the validation of algorithm robustness has recently been recognised as a major challenge for the massive deployment of these new technologies. It is well known that algorithms and models trained or tested with a particular dataset tend not to generalise well for other scenarios. For certain applications, autonomous vehicles in particular, algorithm failures can lead to potentially catastrophic consequences. To minimise this risk, it is essential to evaluate the robustness and reliability of algorithms before deploying them in real life applications. This paper presents a long-term, large-scale dataset collected over the period of 1.5 years on a weekly basis over the University of Sydney campus and surrounds. The USyd Campus Dataset has been designed to aid in the development, validation and testing of algorithm robustness under a wide variety of conditions. It includes multiple sensor modalities and covers various environmental conditions as well as diverse changes to illumination, scene structure, and pedestrian/vehicle traffic volumes. The dataset also includes a semantic segmentation dataset with different illumination conditions and camera perspectives, and a ‘Road’ class image dataset which is automatically generated using lidar. To facilitate the dataset use by researchers and practitioners, we also provide a set of development tools for the analysis and visualisation of the dataset.
DOI: 10.7910/dvn/eoygyy/vhzmms
title: replication.zip

description: :unav
DOI: 10.21227/kb29-9n65
title: The USyd Campus Dataset

description: Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation and deep-learning applications. Despite this success, the validation of algorithm robustness has recently been recognised as a major challenge for the massive deployment of these new technologies. It is well known that algorithms and models trained or tested with a particular dataset tend not to generalise well for other scenarios. For certain applications, autonomous vehicles in particular, algorithm failures can lead to potentially catastrophic consequences. To minimise this risk, it is essential to evaluate the robustness and reliability of algorithms before deploying them in real life applications. This paper presents a long-term, large-scale dataset collected over the period of 1.5 years on a weekly basis over the University of Sydney campus and surrounds. The USyd Campus Dataset has been designed to aid in the development, validation and testing of algorithm robustness under a wide variety of conditions. It includes multiple sensor modalities and covers various environmental conditions as well as diverse changes to illumination, scene structure, and pedestrian/vehicle traffic volumes. The dataset also includes a semantic segmentation dataset with different illumination conditions and camera perspectives, and a ‘Road’ class image dataset which is automatically generated using lidar. To facilitate the dataset use by researchers and practitioners, we also provide a set of development tools for the analysis and visualisation of the dataset.
DOI: 10.21227/eaf0-v645
title: Data Archive for Zhang, et al., “A Geophysical Model Function for S-band Reflectometry of Ocean Surface Winds in Tropical Cyclones,” accepted to Geophysical Research Letters

description: This is the data Archive for Zhang, et al., “A Geophysical Model Function for S-band Reflectometry of Ocean Surface Winds in Tropical Cyclones,” accepted by Geophysical Research Letters. This data set was generated from twelve (12) days of airborne S-band (2.3 GHz) reflectometry data collected during the 2014 hurricane season between 2 July 2014 and 17 September 2014. Cross-correlations between the direct and reflected S-band signals, commonly referred to as the “waveform” or delay-Doppler map (DDM) are provided with corresponding aircraft time and position data. An empirical model function, relating the sensed ocean surface mean square slope (MSS) to wind speed was then developed by fitting MSS estimates to comparison wind speed data from the Stepped-Frequency Microwave Radiometer (SFMR) on the same aircraft. This model function was applied for wind speed retrievals using an independent set of reflectometry measurements and validated against four (4) data sources: SFMR, HWFR, dropsondes, and flight-level winds. Estimated MSS and wind speeds are provided for both the training (calibration) and validation sets. Please refer to the GRL paper for more details. Figure numbers in the documentation refer to this paper.
DOI: 10.21227/hv4j-9t49
title: Data Archive for Zhang, et al., “A Geophysical Model Function for S-band Reflectometry of Ocean Surface Winds in Tropical Cyclones,” accepted to Geophysical Research Letters

description: This is the data Archive for Zhang, et al., “A Geophysical Model Function for S-band Reflectometry of Ocean Surface Winds in Tropical Cyclones,” accepted by Geophysical Research Letters. This data set was generated from twelve (12) days of airborne S-band (2.3 GHz) reflectometry data collected during the 2014 hurricane season between 2 July 2014 and 17 September 2014. Cross-correlations between the direct and reflected S-band signals, commonly referred to as the “waveform” or delay-Doppler map (DDM) are provided with corresponding aircraft time and position data. An empirical model function, relating the sensed ocean surface mean square slope (MSS) to wind speed was then developed by fitting MSS estimates to comparison wind speed data from the Stepped-Frequency Microwave Radiometer (SFMR) on the same aircraft. This model function was applied for wind speed retrievals using an independent set of reflectometry measurements and validated against four (4) data sources: SFMR, HWFR, dropsondes, and flight-level winds. Estimated MSS and wind speeds are provided for both the training (calibration) and validation sets. Please refer to the GRL paper for more details. Figure numbers in the documentation refer to this paper.
DOI: 10.25919/5d51639334622
title: Parkes observations for project P456 semester 2019APRS_43

description: The Parkes Pulsar Timing Array (PPTA) project has three primary goals: (a) detection of gravitational waves from astronomical sources, (b) establishment of a pulsar timescale, and (c) improvement of our understanding of Solar-system dynamics. The PPTA is the oldest of three international pulsar timing groups. We have the smallest telescope and the smallest group, but the best measurements and the best results. Our bound on the strength of the incoherent gravitational wave background is the only bound which significantly constrains theoretical models. We have maintained our leading position because: we have the southern sky; we have a small but well-focussed group; we have the best-calibrated receivers; and we have been able to observe with an almost regular cadence of 15 to 20 days over a wide bandwidth. With this proposal we aim to maintain our pre-eminent position in the field. Unlike most observing proposals, this is a continuing proposal for which the observations will continue to improve bounds on ultra-low-frequency gravitational waves until they are finally detected. Continued Parkes observations will remain valuable at least until the first stage of the SKA is able to improve on our sensitivity and observing cadence. Even after the gravitational wave background is detected we will want to continue observations in support of the nascent field of gravitational wave astronomy!
DOI: 10.18716/nmrshiftdb2/2329
title: NMR data for Nangustine
DOI: 10.6084/m9.figshare.9462446.v1
title: Depth-to-bedrock observations in China

description: This is a dataset of depth-to-bedrock observations in China. The dataset contains 6328 observations distributed all over the China.
DOI: 10.17632/wnsvtttzs8.1
title: Data for: Two arm weapon detection algorithm, using material test and fuzzy logic system for Global security system reliability

description: the data consists of two folders, namely Training and Test sets. each of these folders is made up of images from cameras which have been used in the analysis of the system in this article. the data is applied as training and test, and afterwards the test set is trained while the training set is tested. this is aimed at getting an average recognition rate for the system.
DOI: 10.18716/nmrshiftdb2/2353
title: NMR data for 3,8-Dimethyl-5-isopropyl-6-hydroxycoumarin; Mansorin B
DOI: 10.6073/pasta/3df6a253cf2c6bede9c8bc3992697c8e
title: Seed Bank in Hemlock Removal Experiment at Harvard Forest 2004-2015

description: The impending loss of hemlock trees due to hemlock woolly adelgid (Adelges tsugae) infestation prompted the need to identify species of plants able to colonize areas where hemlock has been removed. We investigated species present in the seed bank (in 2004 and 2010), the seedling bank (in 2004 and 2010), and seed rain (from 2005-2015) in the Harvard Forest Hemlock Removal Experiment. In 2004, Kelley Sullivan and Aaron Ellison determined the distribution of seeds buried in the soil in the six hemlock and two hardwood stands, before canopy treatments were applied (data files hf105-01, hf105-02). In 2010, Elizabeth Farnsworth and Aaron Ellison examined the distribution of plant species present five years after the simulated hemlock removal experiment was performed and six years after the baseline, pre-treatment study of the seedbank (data files hf105-03, hf105-04, hf105-05). In the 2010 study, we hypothesized that the composition of the seed and seedling banks and seed rain would diverge among the two treatments and the controls, based on the differential impacts of harvesting versus adelgid attack on the standing vegetation. We further hypothesized that the older (deeper) strata of the seedbanks of the treatment plots would have been exhausted over time, thus yielding poor germination relative to the top strata that continually receive seed rain. Identical methods of characterizing the composition of the seedbank and the aboveground vegetation at seedbank core locations were applied in both 2004 and 2010. Additional comparisons were made with long-term data collected on overall plant species composition in the Simes plots (datasets HF 106, HF126), and with data on seed rain (data file hf105-05). This study provides a unique temporal documentation of changes in the seedbank, seed rain, and vegetation under conditions of a changing overstory.
DOI: 10.18716/nmrshiftdb2/2356
title: NMR data for 5-(3-Buten-1-ynyl)-2,2'-bithiophene; BBT
DOI: 10.18716/nmrshiftdb2/2357
title: NMR data for Myricetin 3-O-(4''-O-acetyl-2''-O-galloyl)--L-rhamnopyranoside
DOI: 10.25919/5d5137ec0efaf
title: Parkes observations for project P958 semester 2019APRS_65

description: Fast radio bursts (FRBs) continue to raise more questions than they answer. Until a few months ago, only one burst – the only one known to repeat - had been localized to a bright radio nebula (either a young supernova remnant or pulsar wind nebulae) in a distant dwarf galaxy. Over the last year searches with the Australian Square Kilometre Array Pathfinder (ASKAP) have detected 28 bursts, two of which have been localised to host galaxies at redshifts &gt; 0.3. These bursts and their hosts are very unlike the repeater, suggesting there may be a dichotomy in the population. Over the next six months we expect to detect another 12 FRBs, which will also have sub-arcsecond localisations. Here we propose to search this population for repeats. Our comprehensive sample and a dense monitoring campaign of well localised bursts, at a fluence limit more than 60 times lower than that of their detections, will either confirm the presence of additional repeating FRBs or the uniqueness of FRB 121102 amongst the population.
DOI: 10.17632/57sh3m7c36.1
title: Data for: Carboniferous-Triassic felsic igneous rocks and typical mineral deposits in the Truong Son orogenic belt, SE Asia: implications for Paleo-Tethyan tectonic evolution and metallogeny

description: The detailed petrological, mineralogical, geochronological, geochemical, and isotopic data for typical igneous rocks and mineral deposits in the Truong Son orogenic belt.
DOI: 10.18716/nmrshiftdb2/2330
title: NMR data for Quercetin 3-O--(6''-E-p-coumaroylglucopyranoside)-7-O--glucopyranoside