cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.k6ypna
title: Occurrence Download

description: A dataset containing 8883030 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Amphibia"
 ]
}

 The dataset includes 8883030 records from 4970 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0161689-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28817729
title: TRAC Knockout in Primary Human Regulatory T cells

description: Flow cytometry data for TRAC knockout in Primary Human Regulatory T cells with electroporation parameters 550V, 2 ms, 2 pulses or 0V, 2 ms, 2 pulses.
DOI: 10.6084/m9.figshare.28817729.v1
title: TRAC Knockout in Primary Human Regulatory T cells

description: Flow cytometry data for TRAC knockout in Primary Human Regulatory T cells with electroporation parameters 550V, 2 ms, 2 pulses or 0V, 2 ms, 2 pulses.
DOI: 10.15468/dl.2vczx9
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sophora saxicola Proctor"
 ]
}

 The dataset includes 12 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015095-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b5f3s5
title: Occurrence Download

description: A dataset containing 681 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Europe",
 "Country is Netherlands",
 "DatasetKey is one of (Observation.org, Nature data from around the World, iNaturalist Research-grade Observations)",
 "OccurrenceStatus is Present",
 "TaxonKey is Cnaemidophorus Wallengren, 1862"
 ]
}

 The dataset includes 681 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015096-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5nhv7
title: Occurrence Download

description: A dataset containing 506 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Spain",
 "Geometry POLYGON((1.19535 42.60204,0.6107 41.91592,0.36427 41.09934,1.39828 40.78044,3.15707 41.59219,3.54845 42.06571,3.32019 42.41499,3.15168 42.46392,3.01397 42.48868,2.91432 42.48324,2.80258 42.46996,2.75305 42.43674,2.69386 42.43372,1.19535 42.60204))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Senecio lividus L."
 ]
}

 The dataset includes 506 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015093-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g57pvg
title: Occurrence Download

description: A dataset containing 921 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Month is one of (November, January)",
 "OccurrenceStatus is Present",
 "TaxonKey is Equus Linnaeus, 1758",
 "Year 2023-2024"
 ]
}

 The dataset includes 921 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015092-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88e67b
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Phalacronotus micronemus (Bleeker, 1846))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 41 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015094-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ha4vcn
title: Occurrence Download

description: A dataset containing 7498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "TaxonKey is Orchidaceae"
 ]
}

 The dataset includes 7498 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015097-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14163086
title: Dynamical ising dataset for the paper Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium

description: This dataset provide the evolution in time for the magnetizaion in the 2D Ising model evolved with Gluber dynamics for a lattice of size 64 x 64.
DOI: 10.5281/zenodo.14163087
title: Dynamical ising dataset for the paper Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium

description: This dataset provide the evolution in time for the magnetizaion in the 2D Ising model evolved with Gluber dynamics for a lattice of size 64 x 64.
DOI: 10.15468/dl.v4vvsq
title: Occurrence Download

description: A dataset containing 1187 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Aves de México I"
 ]
}

 The dataset includes 1187 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015098-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/1ftt-gr74
title: FIRED Northern Cyprus Nov 2000 - July 2024

description: This is event-level polygons for the fire event delineation (FIRED) product for Northern Cyprus from November 2000 to July 2024. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v061/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (https://github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. Daily polygons are included and the event identification numbers are the same for both files, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event. See the associated paper for more details on the methods and more:

Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498
DOI: 10.5517/ccdc.csd.cc2fp6n0
title: CCDC 2254712: Experimental Crystal Structure Determination

description: Related Article: Phoebe R. Hertler, Arturo Sauza-de la Vega, Andrea Darù, Arup Sarkar, Richard A. Lewis, Guang Wu, Laura Gagliardi, Trevor W. Hayton|2024|Chemical Science|15|16559|doi:10.1039/D4SC04880F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gln2t
title: CCDC 2282036: Experimental Crystal Structure Determination

description: Related Article: Chunyan Fang, Liping Zhang, Yongchao Wang, Weiliang Xiong, Zier Yan, Wenjun Zhang, Qingbo Zhang, Binju Wang, Yiguang Zhu, Changsheng Zhang|2024|J.Am.Chem.Soc.|146|16478|doi:10.1021/jacs.4c02841
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gmnj9
title: CCDC 2283011: Experimental Crystal Structure Determination

description: Related Article: Phathutshedzo Masithi, Ashlyn D. Bhana, Gerhard A. Venter, Hong Su, Christopher D. Spicer, Wade F. Petersen, Roger Hunter|2024|Org.Lett.|26|9162|doi:10.1021/acs.orglett.4c03650
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gmnkb
title: CCDC 2283012: Experimental Crystal Structure Determination

description: Related Article: Phathutshedzo Masithi, Ashlyn D. Bhana, Gerhard A. Venter, Hong Su, Christopher D. Spicer, Wade F. Petersen, Roger Hunter|2024|Org.Lett.|26|9162|doi:10.1021/acs.orglett.4c03650
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.t58pb6
title: Occurrence Download

description: A dataset containing 21209 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tissues Specimens"
 ]
}

 The dataset includes 21209 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015101-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14163303
title: Estimated field scale sediment loss on the North Wyke Farm Platform in typical and extreme wet winters

description: Based on monitored runoff and turbidity at 15-minute intervals from the North Wyke Fam Platform - a UK National Bioscience Research Infrastructure (NBRI), sediment loss during both typical and more extreme wet winters (December - February, inclusive) over the past decade (2012-2013, 2013-2014, 2015-2016, 2019-2020 and 2023-2024) from 5 grassland field catchments and 5 recently converted arable field catchments was estimated, including uncertainty ranges. Daily rainfall totals for the corresponding winter periods are also included.
DOI: 10.5281/zenodo.14163304
title: Estimated field scale sediment loss on the North Wyke Farm Platform in typical and extreme wet winters

description: Based on monitored runoff and turbidity at 15-minute intervals from the North Wyke Fam Platform - a UK National Bioscience Research Infrastructure (NBRI), sediment loss during both typical and more extreme wet winters (December - February, inclusive) over the past decade (2012-2013, 2013-2014, 2015-2016, 2019-2020 and 2023-2024) from 5 grassland field catchments and 5 recently converted arable field catchments was estimated, including uncertainty ranges. Daily rainfall totals for the corresponding winter periods are also included.
DOI: 10.15468/dl.hs4avh
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pachyodes ornataria Moore, 1888"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015102-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26513363
title: Optimization modeling and verification from problem specifications using a multi-agent multi-stage LLM framework

description: This paper explores the use of Large Language Models (LLMs) in modeling real-world optimization problems. We concretely define the task of translating natural language descriptions into optimization models (NL2OPT) and provide criteria for classifying optimization problems for the NL2OPT task. Our novel multi-agent modeling framework leverages relations identifier agents and a multi-agent verification mechanism, eliminating the need for solver execution. Additionally, we introduce a straightforward and practical evaluation framework, offering a more effective assessment method compared to traditional execution-based evaluations. We have created a unique dataset tailored for optimization modeling, featuring Problem Specifications as a structured representation of optimization problems. Through comprehensive experiments, our study compares our modeling framework with existing LLM reasoning strategies, highlighting their relative effectiveness in optimization modeling tasks. We also perform ablation studies to explore the effect of different components of our modeling framework. Experimental results demonstrate that our multi-agent framework outperforms many common LLM prompting strategies.
DOI: 10.6084/m9.figshare.26513363.v1
title: Optimization modeling and verification from problem specifications using a multi-agent multi-stage LLM framework

description: This paper explores the use of Large Language Models (LLMs) in modeling real-world optimization problems. We concretely define the task of translating natural language descriptions into optimization models (NL2OPT) and provide criteria for classifying optimization problems for the NL2OPT task. Our novel multi-agent modeling framework leverages relations identifier agents and a multi-agent verification mechanism, eliminating the need for solver execution. Additionally, we introduce a straightforward and practical evaluation framework, offering a more effective assessment method compared to traditional execution-based evaluations. We have created a unique dataset tailored for optimization modeling, featuring Problem Specifications as a structured representation of optimization problems. Through comprehensive experiments, our study compares our modeling framework with existing LLM reasoning strategies, highlighting their relative effectiveness in optimization modeling tasks. We also perform ablation studies to explore the effect of different components of our modeling framework. Experimental results demonstrate that our multi-agent framework outperforms many common LLM prompting strategies.
DOI: 10.6084/m9.figshare.26644203
title: Robust portfolio optimization model for electronic coupon allocation

description: Currently, many e-commerce websites issue online/electronic coupons as an effective tool for promoting sales of various products and services. We focus on the problem of optimally allocating coupons to customers subject to a budget constraint on an e-commerce website. We apply a robust portfolio optimization model based on customer segmentation to the coupon allocation problem. We also validate the efficacy of our method through numerical experiments using actual data from randomly distributed coupons. Main contributions of our research are twofold. First, we handle six type of coupons, thereby making it extremely difficult to accurately estimate the difference in the effects of various coupons. Second, we demonstrate from detailed numerical results that the robust optimization model achieved larger uplifts of sales than did the commonly-used multiple-choice knapsack model and the conventional mean–variance optimization model. Our results open up great potential for robust portfolio optimization as an effective tool for practical coupon allocation.
DOI: 10.6084/m9.figshare.26644203.v1
title: Robust portfolio optimization model for electronic coupon allocation

description: Currently, many e-commerce websites issue online/electronic coupons as an effective tool for promoting sales of various products and services. We focus on the problem of optimally allocating coupons to customers subject to a budget constraint on an e-commerce website. We apply a robust portfolio optimization model based on customer segmentation to the coupon allocation problem. We also validate the efficacy of our method through numerical experiments using actual data from randomly distributed coupons. Main contributions of our research are twofold. First, we handle six type of coupons, thereby making it extremely difficult to accurately estimate the difference in the effects of various coupons. Second, we demonstrate from detailed numerical results that the robust optimization model achieved larger uplifts of sales than did the commonly-used multiple-choice knapsack model and the conventional mean–variance optimization model. Our results open up great potential for robust portfolio optimization as an effective tool for practical coupon allocation.
DOI: 10.6084/m9.figshare.26663039
title: Diagnosing infeasible optimization problems using large language models

description: Decision-making problems can be represented as mathematical optimization models, finding wide applications in fields, such as economics, engineering, transportation, and health care. One of the primary barriers to deploying these models in practice is the challenge of helping practitioners understand and interpret such models, particularly when they are infeasible, meaning no decision satisfies all the constraints. Existing methods for diagnosing infeasible optimization models often rely on expert systems, necessitating significant background knowledge in optimization. In this paper, we introduce OptiChat, a first-of-its-kind natural language-based system equipped with a chatbot GUI for engaging in interactive conversations about infeasible optimization models. OptiChat can provide natural language descriptions of the optimization model itself, identify potential sources of infeasibility, and offer suggestions to make the model feasible. The implementation of OptiChat is built on GPT-4, which interfaces with an optimization solver to identify the minimal subset of constraints that render the entire optimization problem infeasible, known as the Irreducible Infeasible Subset (IIS). We utilize few-shot learning, expert chain-of-thought, key-retrieve, and sentiment prompts to enhance OptiChat’s reliability. Our experiments demonstrate that OptiChat assists both expert and non-expert users in improving their understanding of the optimization models, enabling them to quickly identify the sources of infeasibility.
DOI: 10.6084/m9.figshare.26663039.v1
title: Diagnosing infeasible optimization problems using large language models

description: Decision-making problems can be represented as mathematical optimization models, finding wide applications in fields, such as economics, engineering, transportation, and health care. One of the primary barriers to deploying these models in practice is the challenge of helping practitioners understand and interpret such models, particularly when they are infeasible, meaning no decision satisfies all the constraints. Existing methods for diagnosing infeasible optimization models often rely on expert systems, necessitating significant background knowledge in optimization. In this paper, we introduce OptiChat, a first-of-its-kind natural language-based system equipped with a chatbot GUI for engaging in interactive conversations about infeasible optimization models. OptiChat can provide natural language descriptions of the optimization model itself, identify potential sources of infeasibility, and offer suggestions to make the model feasible. The implementation of OptiChat is built on GPT-4, which interfaces with an optimization solver to identify the minimal subset of constraints that render the entire optimization problem infeasible, known as the Irreducible Infeasible Subset (IIS). We utilize few-shot learning, expert chain-of-thought, key-retrieve, and sentiment prompts to enhance OptiChat’s reliability. Our experiments demonstrate that OptiChat assists both expert and non-expert users in improving their understanding of the optimization models, enabling them to quickly identify the sources of infeasibility.
DOI: 10.15468/dl.9vxvdy
title: Occurrence Download

description: A dataset containing 736 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Emerita brasiliensis Schmitt, 1935"
 ]
}

 The dataset includes 736 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015104-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f4pt8g
title: Occurrence Download

description: A dataset containing 12146 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Melaleuca quinquenervia (Cav.) S.T.Blake"
 ]
}

 The dataset includes 12146 records from 158 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015105-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6cvhdg
title: Occurrence Download

description: A dataset containing 803 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (Spain, France, Italy, Portugal, Andorra)",
 "GbifRegion is Europe and Central Asia",
 "TaxonKey is Cetonia carthami Gory & Percheron, 1833"
 ]
}

 The dataset includes 803 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015107-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/stkt-bj43
title: FIRED Norway Nov 2000 - July 2024

description: This is event-level polygons for the fire event delineation (FIRED) product for NORWAY from November 2000  to July 2024. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v061/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (https://github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. Daily polygons are included and the event identification numbers are the same for both files, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event. See the associated paper for more details on the methods and more:

Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498