cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/4syzhv
title: Replication Data for Post-Instrument Bias

description: When using instrumental variables, researchers often assume that causal effects are only identified conditional on covariates. We show that the role of these covariates is often unclear and that there exists confusion regarding their ability to mitigate violations of the exclusion restriction. We explain when and how existing adjustment strategies may lead to ``post-instrument'' bias. We then discuss assumptions that are sufficient to identify various treatment effects when adjustment for post-instrument variables is required. In general, these assumptions are highly restrictive, albeit they sometimes are testable. We also show that other existing tests are possibly misleading. Then, we introduce a sensitivity analysis that uses information on variables influenced by the instrument to gauge the effect of potential violations of the exclusion restriction. We illustrate it using a published study and summarize our results in easy-to-understand guidelines.
description: This dataset underwent an independent verification process, complying with the AJPS Verification Policy updated June 2023, which replicated the tables and figures in the primary article. For the supplementary materials, verification was performed solely for the successful execution of the code. The verification process was carried out by the Cornell Center for Social Sciences at Cornell University. 
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The associated article has been awarded the Open Materials Badge. Learn more about the Open Practice Badges from the Center for Open Science. 
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Open Materials Badge
DOI: 10.15156/bio/sh1203054.10fu
title: SH1203054.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203057.10fu
title: SH1203057.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203061.10fu
title: SH1203061.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203063.10fu
title: SH1203063.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203065.10fu
title: SH1203065.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203069.10fu
title: SH1203069.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203072.10fu
title: SH1203072.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1203076.10fu
title: SH1203076.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.emeeus
title: Occurrence Download

description: A dataset containing 83 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Platylomia Stål, 1870, Platylomia kohimaensis Hajong & Limatemjen, 2021, Platylomia lemoultii Lallemand, 1924, Platylomia flavida (Guérin-Méneville, 1834), Platylomia vibrans (Walker, 1850), Platylomia bivocalis (Matsumura, 1907), Platylomia plana Lei & Li, 1994, Platylomia larus (Walker, 1858), Platylomia bocki (Distant, 1882), Platylomia duffelsi Pham & Constant, 2014)"
 ]
}

 The dataset includes 83 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058159-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.39b79v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Halichoeres sazimai Luiz, Ferreira & Rocha, 2009",
 "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/0058160-241126133413365/datasets/export for details.
DOI: 10.21227/t0pa-t236
title: High-resolution millimeter wave pseudo-images collected using Vayyar's ECS2000, a commercial handheld scanner

description: In this study, MMW data are collected using a commercial handheld scanner (Vayyar's ECS2000), focusing on localized scans of the human body. The collected data are complex-valued (CV) high-resolution local 3D pseudo-images over a volume of 13×13×10 cm with spatial resolutions of 1.6 mm, 1.6 mm, and 4.3 mm in the x, y, and z directions, respectively.  The compact, portable ECS2000 Vayyar's MMW scanner is built around a single RF board working in the frequency range of [60.4-69.9] GHz, housing transmitting and receiving antennas in a multiple-input multiple-output (MIMO) setup. In particular, its 240 antennas are utilized for 3D CV data capturing where a localized part of a body can be scanned by that radar. The radar's receivers capture high-resolution 3D reflections, which are processed to generate granular imaging data containing both intensity and phase information. For each captured 3D snapshot, the resolutions in the x, y, and z directions are 1.6 mm, 1.6 mm, and 4.3 mm, respectively. The spatial range of captured data in these directions are [8.2–139.7] mm in x-direction, [8.2–139.7] mm in y-direction, and [151.3–249.4] mm in z-direction. The scanner is able to provide approximately 15 pseudo-images per second. Moreover, it is also capable of exporting raw IQ data of each antenna as well as the 3D pseudo-images. These high-resolution 3D pseudo images form the foundation for CV-based processing in this paper. The dimensions of the input for the CV-CNN are N×W×H×C, where N is the number of input samples, W and H show width and height of the input (pseudo) image and C shows the number of channels for each input. Based on the preprocessing parameters and experimental setup, W=H=81, and C=1. The dataset for the proposed CV-FL-based CO detection framework was meticulously designed to encompass diverse and representative scenarios. The data acquisition process involved the use of an MMW radar configured to generate CV pseudo-images of various concealed objects under multiple clothing configurations resulting in N=60,000. The inclusion of five different clothing sets resulted in five distinct datasets. Each local CV-CNN (four in total, corresponding to the four edge nodes) was independently trained by one of these datasets to maintain isolation during training. A fifth dataset, completely unseen by local models during training, was reserved exclusively for evaluating the final trained CV-FL model.
DOI: 10.34740/kaggle/dsv/10385631
title: Public Opinion on Climate Change (Updated Daily)
DOI: 10.48577/jpl.oxarpq
title: Nonlinear effects of loosely constrained deployable mass on instrument dynamic testing and analysis

description: Many instruments utilize launch locks (pin-pullers, frangibolts, etc) to restrain deployable assemblies during launch to survive launch vibration and acoustic environments. Non-linear responses have been observed during vibration testing for instruments where the restrained mass represents a significant portion of the total mass. The non-linearity is particularly notable when the mass is loosely constrained and sees large relative displacement compared to the primary structure of the instrument.
DOI: 10.48577/jpl.g2g3kf
title: 21cmLSTM: A Memory-based Emulator of the Global 21 cm Signal with Unprecedented Accuracy

description: Neural network (NN) emulators of the global 21 cm signal need an emulation error much less than the observational noise in order to be used to perform unbiased Bayesian parameter inference. To this end, we introduce 21cmLSTM—a long short-term memory (LSTM) NN emulator of the global 21 cm signal that leverages the intrinsic correlation between frequency channels to achieve exceptional accuracy compared to previous emulators, which are all feedforward, fully connected NNs. LSTM NNs are a type of recurrent NN designed to capture long-term dependencies in sequential data. When trained and tested on the same simulated set of global 21 cm signals as the best previous emulators, 21cmLSTM has an average relative rms error of 0.22%—equivalently 0.39 mK—and comparably fast evaluation time. We perform seven-dimensional Bayesian parameter estimation analyses using 21cmLSTM to fit global 21 cm signal mock data with different adopted observational noise levels, σ21. The posterior 1σ rms error is ≈three times less than σ21 for each fit and consistently decreases for tighter noise levels, showing that 21cmLSTM can sufficiently exploit even very optimistic measurements of the global 21 cm signal. We have made the emulator, code, and data sets publicly available so that 21cmLSTM can be independently tested and used to retrain and constrain other 21 cm models.
DOI: 10.48577/jpl.ybpjgg
title: Image Persistence Flagging for SPHEREx

description: Image persistence in HAWAII-2RG HgCdTe detectors has been observed by multiple parties. Also known as latent signal, this effect occurs when sensor images following an illumination show a decayed form of the illuminated image even though the source has been removed and the detector has been reset. Using data from an engineering grade detector delivered for SPHEREx testing illuminated with a wide range of fluxes, we demonstrate an interpretation and a working model from which the decaying signal can be estimated, providing the ability to flag pixels subject to excess persistence current beyond a user-defined threshold. Simulated persistence images allow validation of the module and prediction of its affect on flight data.
DOI: 10.48577/jpl.1qkcdy
title: Mars Soil Temperature and Thermal Properties from InSight HP3 Data

description: Diurnal and seasonal soil (and surface) temperature variations are reported, measured with the NASA InSight Mars mission’s HP3 thermal probe (and radiometer). At a representative depth of 10 – 20 cm, an average temperature of 217.5 K was found, varying by 5.3 – 6.7 K during a sol and by 13.3 K during the seasons. The damping of the surface temperature variation in the soil and the phase shift were used to derive a thermal diffusivity of 3.92 ± 0.39 × 10−8 m2/s for the top ∼10 cm from the diurnal variation and 3.63 ± 0.53 × 10−8 m2/s for the depth range of the mole of ∼40 cm from the annual temperature variation. The temperatures are conducive to the deliquescence of thin films of brine, which may explain the observed cemented duricrust. The thermal diffusivity suggests that published estimates of the depth to the cryosphere may need downward revision by around 5 %.
DOI: 10.15468/dl.d747kq
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brama japonica Hilgendorf, 1878",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 43 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058161-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48577/jpl.3dgoey
title: Effects of planetary mass uncertainties on the interpretation of the reflectance spectra of Earth-like exoplanets

description: Atmospheric characterization of Earth-like exoplanets through reflected light spectroscopy is a key goal for upcoming direct imaging missions. A critical challenge in this endeavor is the accurate determination of planetary mass, which may influence the measurement of atmospheric compositions and the identification of potential biosignatures. In this study, we used the Bayesian retrieval framework ExoReL-R to investigate the impact of planetary mass uncertainties on the atmospheric characterization of terrestrial exoplanets observed in reflected light. Our results indicate that precise prior knowledge of the planetary mass can be crucial for accurate atmospheric retrievals if clouds are present in the atmosphere. When the planetary mass is known within 10% uncertainty, our retrievals successfully identified the background atmospheric gas and accurately constrained atmospheric parameters together with clouds. However, with less constrained or unknown planetary mass, we observed significant biases, particularly in the misidentification of the dominant atmospheric gas. For instance, the dominant gas was incorrectly identified as oxygen for a modern-Earth-like planet or carbon dioxide for an Archean-Earth-like planet, potentially leading to erroneous assessments of planetary habitability and biosignatures. These biases arise because, the uncertainties in planetary mass affect the determination of surface gravity and atmospheric scale height, leading the retrieval algorithm to compensate by adjusting the atmospheric composition. Our findings emphasize the importance of achieving precise mass measurements—ideally within 10% uncertainty—through methods such as extreme precision radial velocity or astrometry, especially for future missions like the Habitable Worlds Observatory.
DOI: 10.48577/jpl.ev5vwt
title: Monitoring water from space: An illustration in Death Valley, California

description: Climate change and human activity are dramatically reshaping how water is distributed on Earth. High quality observations, as well as products that bridge the gap between low-level data and actionable information are needed to support the understanding of current and future water availability around the globe. Two new developments are now addressing these needs. The Surface Water and Topography Mission (SWOT) satellite mission is measuring water elevations with unprecedented detail, while the Observational Products for End-Users from Remote Sensing Analysis (OPERA) project is turning satellite observations into clear and interpretable maps of surface water extent. Together, these represent a paradigm shift in our ability to measure and monitor water from space. We demonstrate their capability by tracking the transformation of Badwater Basin in Death Valley, one of the driest, hottest places on Earth, into an ephemeral lake following extreme precipitation events starting with Hurricane Hilary in August of 2023.
DOI: 10.48577/jpl.buntpf
title: Vertical heat fluxes diagnosed from airborne observations

description: Submesoscale eddies (smaller than 50 km) are ubiquitous in all oceans, as revealed by satellite infrared images. Diagnosing their impact on the ocean energetics from observations remains a challenge. This study analyzes a turbulent field of submesoscale eddies using airborne observations of surface currents and sea surface temperature, with high spatial resolution, collected during the S-MODE experiment in October 2022. Assuming surface current divergence and temperature are homogeneous down to a given depth, we show that more than 80\% of the upward vertical heat fluxes, reaching $\sim$220 W~m$^{-2}$, is explained by the smallest eddies (with a size smaller than 15 km). This emphasizes the contribution of small-scale eddies, poorly taken into account in numerical models, to the ocean heat budget and, therefore, to the climate system.