cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3w82ke
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Microstomus stelleri Schmidt, 1904",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026767-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dag7hj
title: Occurrence Download

description: A dataset containing 43301 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Insect specimens of Hokkaido University"
 ]
}

 The dataset includes 43301 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026766-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rhtmd4
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thunnus alalunga (Bonnaterre, 1788)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 18 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026768-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14335225
title: Plasma untargeted metabolomic analysis of circulating metabolites in night shift workers

description: Normal.tar, QC.tar and Shift.tar are the files of GCMS.

Normal_neg.tar, Shift_neg.tar, QC_neg.tar, Normal_pos.tar, Shift_pos.tar, and QC_pos.tar are the files of LCMS.
DOI: 10.5281/zenodo.14335228
title: Plasma untargeted metabolomic analysis of circulating metabolites in night shift workers

description: Normal.tar, QC.tar and Shift.tar are the files of GCMS.

Normal_neg.tar, Shift_neg.tar, QC_neg.tar, Normal_pos.tar, Shift_pos.tar, and QC_pos.tar are the files of LCMS.
DOI: 10.15468/dl.u36s84
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scomber alalunga Bonnaterre, 1788",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026769-241126133413365/datasets/export for details.
DOI: 10.15468/dl.dbgfks
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Flora del Bosque de los Guayupes Acacias, Meta, Colombia"
 ]
}

 The dataset includes 59 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026770-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p13scwnm
title: Data and Model Archive for Simulations of Seawater Restoration on Diked Salt Marshes

description: This dataset and model archive provides geochemical modeling input and selected output data used in simulations of seawater restoration on historically diked salt marshes. Biogeochemical changes resulting from seawater reintroduction were simulated using the computer program PHREEQC (Parkhurst and Appelo, 2013) to help support efforts to restore tidal flow and associated estuarine habitat to diked marshes, including the Herring River estuary in Wellfleet, Massachusetts, on Cape Cod. First, one-dimensional reactive transport models were developed and calibrated using data from Portnoy and Giblin (1997) microcosm experiments of sediment cores to better understand the associated timing and sequence of biogeochemical reactions and their implications to aquatic health. These cores included diked, flooded marsh sediments and subaerially exposed, diked, drained sediments representative of the Herring River diked marsh (Portnoy and Giblin, 1997). Solute concentrations measured in the microcosm experiment data were used to estimate sedimentary organic matter decay rates by matching the timing and magnitude of simulated dissolved ferrous iron and sulfide concentrations. Then, "basecase" models were used to simulate a single flow velocity to better understand biogeochemical conditions over longer time periods and with varying ferric iron source minerals.

This data release includes the metadata and the data and model archive folder "HerringR_PHRQC.zip", which contains the following files:

1. readme.txt — documents the work that was done, the structure of the model data release, the model files, and instructions on how to run the PHREEQC simulations.
2. HerringR_PHRQC_input.xlsx — a workbook of 14 PHREEQC model inputs as separate worksheets that can be copied and pasted into PHREEQCi input (pqi) files.
3. HerringR_PHRQC_seloutput.xlsx — a workbook of selected output for each model in separate worksheets.
4. data_dictionary_seloutput.csv — specific to "HerringR_PHRQC_seloutput.xlsx" providing the definitions for each column in selected output worksheets.
5. phreeqci.exe — executable file to run PHREEQC Interactive, the graphical users interface to PHREEQC, as described in the readme.txt file.
6. phreeqc.dat — the geochemical database used in simulations for this study.

References
Parkhurst, D.L., and Appelo, C.A.J., 2013, Description of input and examples for PHREEQC version 3: a computer program for speciation, batch-reaction, one-dimensional transport, and inverse     geochemical calculations: U. S. Geological Survey Techniques and Methods 6-A43 6-        A43, 519 p., http://pubs.er.usgs.gov/publication/tm6A43.
Portnoy, J.W., and Giblin, A.E., 1997, Biogeochemical effects of seawater restoration to diked salt marshes: Ecological applications, v. 7, no. 3, p. 1054-1063, https://doi.org/10.1890/1051-   0761(1997)007[1054:BEOSRT]2.0.CO;2.
DOI: 10.7274/27932310
title: Transceiver Technique in Large-Scale Low-Resolution MIMO Systems

description: Low-resolution communication systems are attracting significant attention due to their exceptionally low power consumption and cost, enabling the deployment of large numbers of fully digital transmit and receive chains. However, the extreme nonlinearity introduced by such systems necessitates a reevaluation of conventional transceiver techniques. For instance, the sharp transitions on the transmitter side present challenges in confining out-of-band emissions, while the coarse quantization on the receiver side renders many conventional detection schemes ineffective.

Therefore, we propose a set of simple yet effective techniques to address these challenges, thereby enabling the advantages of low-power, low-resolution, large-scale transceivers to achieve high data rate communication with significantly improved energy efficiency. Importantly, while achieving the optimal maximum likelihood (ML) performance, which is exponential in complexity with the number of transmitter antennas, the proposed techniques are designed to maintain much lower polynomial computational complexity, which is essential for systems with hundreds or thousands of antennas.

We first focus on receiver techniques in one-bit binary/quadrature phase-shift keying systems. When the channel is known at the receiver, one way to simplify the signal detection is to limit the search space to a small list. Inspired by successive interference cancellation, we propose a list creation method based on successive detection, whose performance is close to the optimal ML performance but with only cubic complexity. Moreover, we demonstrate that this method can also work in higher-resolution systems and in on-off keying systems, thus implying its broader applicability.

When the channel is unknown, a simple expression of the minimum mean square error estimator of the channel is derived. In this case, in order to limit the search space, we propose a correlation-based list creation method. Together with a slightly modified iterative detection and decoding process, we demonstrate that this receiver technique enables operation within 2-4 dB of capacity with hundreds of transmitter antennas.

Finally, for the transmitter side, we investigate transmission techniques under spectrum constraints. Specifically, the maximum entropy rate of the transmitted signal subject to the constraint that the fraction of power outside the allocated frequency band is smaller than a given threshold is considered, where the trade-off between the resolution of the digital-to-analog converter and the symbol rate is studied, and a lower bound of the entropy rate is derived. We further propose coding schemes based on a polar code that can shape the spectrum efficiently and effectively.
DOI: 10.7274/27932310.v1
title: Transceiver Technique in Large-Scale Low-Resolution MIMO Systems

description: Low-resolution communication systems are attracting significant attention due to their exceptionally low power consumption and cost, enabling the deployment of large numbers of fully digital transmit and receive chains. However, the extreme nonlinearity introduced by such systems necessitates a reevaluation of conventional transceiver techniques. For instance, the sharp transitions on the transmitter side present challenges in confining out-of-band emissions, while the coarse quantization on the receiver side renders many conventional detection schemes ineffective.

Therefore, we propose a set of simple yet effective techniques to address these challenges, thereby enabling the advantages of low-power, low-resolution, large-scale transceivers to achieve high data rate communication with significantly improved energy efficiency. Importantly, while achieving the optimal maximum likelihood (ML) performance, which is exponential in complexity with the number of transmitter antennas, the proposed techniques are designed to maintain much lower polynomial computational complexity, which is essential for systems with hundreds or thousands of antennas.

We first focus on receiver techniques in one-bit binary/quadrature phase-shift keying systems. When the channel is known at the receiver, one way to simplify the signal detection is to limit the search space to a small list. Inspired by successive interference cancellation, we propose a list creation method based on successive detection, whose performance is close to the optimal ML performance but with only cubic complexity. Moreover, we demonstrate that this method can also work in higher-resolution systems and in on-off keying systems, thus implying its broader applicability.

When the channel is unknown, a simple expression of the minimum mean square error estimator of the channel is derived. In this case, in order to limit the search space, we propose a correlation-based list creation method. Together with a slightly modified iterative detection and decoding process, we demonstrate that this receiver technique enables operation within 2-4 dB of capacity with hundreds of transmitter antennas.

Finally, for the transmitter side, we investigate transmission techniques under spectrum constraints. Specifically, the maximum entropy rate of the transmitted signal subject to the constraint that the fraction of power outside the allocated frequency band is smaller than a given threshold is considered, where the trade-off between the resolution of the digital-to-analog converter and the symbol rate is studied, and a lower bound of the entropy rate is derived. We further propose coding schemes based on a polar code that can shape the spectrum efficiently and effectively.
DOI: 10.15468/dl.7ejb4g
title: Occurrence Download

description: A dataset containing 531 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Etmopterus lucifer Jordan & Snyder, 1902",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 531 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026771-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bzhmat
title: Occurrence Download

description: A dataset listing the 4010764 species recorded in GBIF matching the query:
{ }

 The dataset's 4010764 records were derived from 69646 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026760-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7274/27949089
title: Environmental and Genetic Influences on Species Composition and Belowground Biomass Dynamics in Coastal Marshes

description: The relative abundance of Schoenoplectus americanus in coastal marsh systems plays a crucial role in regulating key processes such as marsh accretion, carbon sequestration, and methane production. Sea level rise, driving increasing salinization and inundation, and subsequent shifts in community composition affect these ecosystem functions. Further, it has been shown that evolutionary changes over the last century in the total root biomass of Schoenoplectus and in its distribution with sediment depth have been large enough to affect such ecosystem-level functions. Schoenoplectus commonly grows in competition with the C4 grass Spartina patens, and it is not known to what extent changes in belowground traits of one species (Schoenoplectus) affect plant community structure, such as the relative distribution of root biomass across species. Here, I explore the effects of intraspecific genetic variation and interspecific interactions on belowground traits by analyzing an experiment exposing 26 Schoenoplectus americanus genotypes, resurrected from century-long seedbanks, to different levels of flooding and salinity in pots with and without the presence of Spartina patens. The experimental environmental treatments drove large differences in species proportion, generating a spectrum of environmental contexts for observing the impact of evolution on the species composition of belowground biomass. Compared to plants grown in monospecific pots, competition greatly reduced belowground biomass and its variance. Within polyculture pots, the impact of a century of evolutionary change in plant traits became increasingly evident as environmental pressures increased: Under benign conditions, the upper sediments of pots grown under low inundation and low salinity, there was no detectable difference across seed age in the relative abundance of Schoenoplectus. With increasing sediment depth, inundation, and (especially) salinity, however, the belowground tissues of Schoenoplectus grown from seeds of older cohorts, dating back as early as the 1800s, made up a lower proportion of total biomass than plants grown from more recent seedbanks. While species proportion will be predominantly driven by the environment and community interactions, evolutionary changes at the margins have the potential to propagate to community-scale changes in species composition. This suggests that evolutionary change, along with changes to the environment and community composition, has the potential to affect predictions of ecosystem resilience
DOI: 10.7274/27949089.v1
title: Environmental and Genetic Influences on Species Composition and Belowground Biomass Dynamics in Coastal Marshes

description: The relative abundance of Schoenoplectus americanus in coastal marsh systems plays a crucial role in regulating key processes such as marsh accretion, carbon sequestration, and methane production. Sea level rise, driving increasing salinization and inundation, and subsequent shifts in community composition affect these ecosystem functions. Further, it has been shown that evolutionary changes over the last century in the total root biomass of Schoenoplectus and in its distribution with sediment depth have been large enough to affect such ecosystem-level functions. Schoenoplectus commonly grows in competition with the C4 grass Spartina patens, and it is not known to what extent changes in belowground traits of one species (Schoenoplectus) affect plant community structure, such as the relative distribution of root biomass across species. Here, I explore the effects of intraspecific genetic variation and interspecific interactions on belowground traits by analyzing an experiment exposing 26 Schoenoplectus americanus genotypes, resurrected from century-long seedbanks, to different levels of flooding and salinity in pots with and without the presence of Spartina patens. The experimental environmental treatments drove large differences in species proportion, generating a spectrum of environmental contexts for observing the impact of evolution on the species composition of belowground biomass. Compared to plants grown in monospecific pots, competition greatly reduced belowground biomass and its variance. Within polyculture pots, the impact of a century of evolutionary change in plant traits became increasingly evident as environmental pressures increased: Under benign conditions, the upper sediments of pots grown under low inundation and low salinity, there was no detectable difference across seed age in the relative abundance of Schoenoplectus. With increasing sediment depth, inundation, and (especially) salinity, however, the belowground tissues of Schoenoplectus grown from seeds of older cohorts, dating back as early as the 1800s, made up a lower proportion of total biomass than plants grown from more recent seedbanks. While species proportion will be predominantly driven by the environment and community interactions, evolutionary changes at the margins have the potential to propagate to community-scale changes in species composition. This suggests that evolutionary change, along with changes to the environment and community composition, has the potential to affect predictions of ecosystem resilience
DOI: 10.15468/dl.djcchc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Etmopterus sculptus Ebert, Compagno & De Vries, 2011",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026774-241126133413365/datasets/export for details.
DOI: 10.15468/dl.c949rq
title: Occurrence Download

description: A dataset containing 27393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Buteo brachyurus Vieillot, 1816"
 ]
}

 The dataset includes 27393 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026773-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z57vtk
title: Occurrence Download

description: A dataset containing 385 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Caracterización de fauna y flora en ecosistemas sensibles del área de perforación exploratoria Sabanero, Meta (LAM4649)"
 ]
}

 The dataset includes 385 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026775-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7274/27914880
title: Cost-Effective Machine Learning Techniques for Graphs

description: Graph-structured data is prevalent in various domains, including social, commercial, and molecular networks. To capture the underlying complexity of such data, graph neural networks (GNNs) have emerged as a powerful tool, delivering exceptional performance across tasks like node classification, link prediction, and node clustering. However, applying GNNs in large-scale industrial settings presents significant challenges, particularly when dealing with graphs with massive numbers of nodes and edges. Additionally, despite the high computational costs, GNNs often struggle to achieve consistently strong performance across all tasks and node cohorts, highlighting the need for more cost-effective approaches. This dissertation addresses these challenges by improving the cost-effectiveness of GNNs through four key dimensions: optimization, model design, task alignment, and data handling. In terms of optimization, we developed methods that substantially accelerate GNN training without compromising performance. From model, task, and data perspectives, we proposed frameworks that enable GNNs to perform effectively across multiple tasks and diverse node cohorts simultaneously. These contributions collectively enhance the scalability and practicality of GNNs, offering solutions to make them more efficient and applicable to real-world social network mining.
DOI: 10.7274/27914880.v1
title: Cost-Effective Machine Learning Techniques for Graphs

description: Graph-structured data is prevalent in various domains, including social, commercial, and molecular networks. To capture the underlying complexity of such data, graph neural networks (GNNs) have emerged as a powerful tool, delivering exceptional performance across tasks like node classification, link prediction, and node clustering. However, applying GNNs in large-scale industrial settings presents significant challenges, particularly when dealing with graphs with massive numbers of nodes and edges. Additionally, despite the high computational costs, GNNs often struggle to achieve consistently strong performance across all tasks and node cohorts, highlighting the need for more cost-effective approaches. This dissertation addresses these challenges by improving the cost-effectiveness of GNNs through four key dimensions: optimization, model design, task alignment, and data handling. In terms of optimization, we developed methods that substantially accelerate GNN training without compromising performance. From model, task, and data perspectives, we proposed frameworks that enable GNNs to perform effectively across multiple tasks and diverse node cohorts simultaneously. These contributions collectively enhance the scalability and practicality of GNNs, offering solutions to make them more efficient and applicable to real-world social network mining.
DOI: 10.15468/dl.tnbnc2
title: Occurrence Download

description: A dataset containing 354 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Seriola quinqueradiata Temminck & Schlegel, 1845",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 354 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026779-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ucdyce
title: Occurrence Download

description: A dataset containing 22812 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (BRA.13.824_2, BRA.13.44_2, BRA.13.661_2, BRA.25.491_2)",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 22812 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026778-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.