cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.8bdc4810e824472682cd3650a2411515
title: CUAHSI LTAW: The Little-Known Tale of the Thirsty Chips

description: The Little-Known Tale of the Thirsty Chips documentary was created with the sole purpose of education, creating awareness, and starting a well-informed conversation about water usage in the semiconductor industry. It is the winning pitch of the Lets Talk About Water (LTAW) Grant 2023 and is funded by the Consortium of Universities for Advancement of Hydrologic Sciences Inc. (CUAHSI). This documentary was created by three graduate students, Ayobami Oluwadunsin Oladapo, Srilani Wickramasinghe, and Shivika Aggrawal.

Given the current atmosphere where chips and AI are making headlines every day, there is already much ongoing discussion about the challenges for resource acquisition (skilled-labor, rare earth metals, etc.) in these industries. Water, which is a critical resource for the sustenance of these high-tech industries, rarely made it to the discussion table. Recognizing this gap, this documentary aims to bring the water story to the forefront, reaching a wider audience, beyond the scientific academic audience, and help educate and raise awareness about water use in the semiconductor industry. 

The documentary addresses crucial questions, such as: Why is the recent semiconductor boom important to the United States?  Are people aware of water usage in the semiconductor industry/chip manufacturing? Is the current planning & policy framework related to the chips-water scenario sufficient? What can be done to improve? How can it be done? What are the current water-related best practices within the chip industry? What is the way forward & what role can research & innovation play in this regard? Is it the right time to start this dialogue about water use in the semiconductor industry?

The interview-driven documentary offers a comprehensive narrative that stimulates critical evaluation through a multidisciplinary lens, including insights from hydrogeologists, semiconductor experts, students, and water utility professionals. This multidisciplinary engagement approach provided a comprehensive and nuanced view of the topic, thus encouraging critical thinking and reflection among the audience based on the evidence presented. The goal of the documentary is to encourage water-efficient chip innovation and emphasize the role of chip R&D in this regard while also advocating for informed resource planning. With “The Little-Known Tale of Thirsty Chips”, we aspire to bring water as a resource to the table where discussions about improving resource efficiency in the semiconductor industry take place.
DOI: 10.4211/hs.975ae49ca7c7428caa38746e5f4a7038
title: Changes in hyporheic chemistry due to streambed alteration by macro-roughness elements project

description: Dissolved oxygen (DO), dissolved organic carbon (DOC), temperature (temp), boulder coordinates, and other data collected at the Center for Ecohydraulics Research, University of Idaho, Boise. Experiments were conducted to measure the impact of macroroughness elements (MRE), like boulders, and MRE-induced topographical changes on hyporheic chemistry. DO was measured using the system described in Reeder et al. (2019). The DOC was measured using a Shimadzu TOC-VCSH total organic carbon analyzer (CAT NO. 638-91062-22).
DOI: 10.17632/g8chhgjsyr
title: Source code, cron job scripts, and database schema for the predictive chatbot for student success

description: This dataset contains the full source code, cron job scripts, and database schema used in the study “Early detection and personalized academic support using a predictive chatbot for student success” (submitted to PeerJ Computer Science). The system integrates a high-performance LightGBM predictive model with an AI-powered WhatsApp® chatbot based on the GPT-4o-mini model to identify at-risk students and deliver early, personalized academic support.
DOI: 10.4211/hs.4c6424e5569a4ff89841a7b5b47d31bd
title: Water Bottle River Video for Computer Vision and Detection

description: This dataset contains a total of 12 videos. Six are raw input videos intended for testing, and the other six are output generated by the botell.ai model. The videos capture various perspectives, including drone footage, views from a pedestrian bridge, a weir, and side views. All files are in mp4 format. The computer vision program is located on github at the following link: https://github.com/AnthroHydro/botell.ai
DOI: 10.17632/g8chhgjsyr.2
title: Source code, cron job scripts, and database schema for the predictive chatbot for student success

description: This dataset contains the full source code, cron job scripts, and database schema used in the study “Early detection and personalized academic support using a predictive chatbot for student success” (submitted to PeerJ Computer Science). The system integrates a high-performance LightGBM predictive model with an AI-powered WhatsApp® chatbot based on the GPT-4o-mini model to identify at-risk students and deliver early, personalized academic support.
DOI: 10.17632/yr4fyf5chj
title: Research productivity and secular stagnation: Is there a correlation between research productivity and economic growth in OECD countries?

description: Recent papers have documented a reduction in research productivit over time. We estimate the relationship between research productivity and economic growth using a panel of OECD economies between 1981 and 2019. For countries in the G7, we find a strong correlation between these twoariables. The effect is both statistically significant and quantitatively relevant.
DOI: 10.4211/hs.6a0a63daaa4e4540b9fdef00975c55a7
title: Dataset for: "Trajectories of River-Floodplain Adjustments Following Compounding Wildfire-Flood Disturbances "

description: Wide, low-gradient segments within river networks (i.e., beads) play a critical role in absorbing and morphologically adapting to disturbances, including wildfires and debris flows. However, the magnitude and rate of morphological adjustment and subsequent hydraulic conditions provided by beads compared to pre-disturbance conditions are not well understood. This study analyzed trajectories of river morphology, flood attenuation, and fish habitat following the 2020 Cameron Peak Fire and July 2022 debris flow and flood at Little Beaver Creek, Colorado, USA. Using repeat aerial imagery, ground-based surveys, and hydrodynamic modeling, we assessed morphological changes in a 600-m-long bead of Little Beaver Creek. We used remotely sensed imagery for pre- and post-disturbance geomorphic metrics in rates of floodplain destruction and formation, changes in channel width, and channel migration. Metrics of floodplain destruction and formation and channel migration greatly increased in magnitude after the first post-fire runoff season but returned to the historical range of these metrics three years after the fire. The 2022 flood deposited sediment, infilled side channels, reduced pool area, and increased the area of bars and islands. The assessed functions of the system did not show clear improvement or impairment despite more rapid changes in system geometry, geomorphic unit abundance, and geomorphic unit location. The ability of the site to attenuate peak flows changed minimally and inconsistently over the studied floods. Various lotic habitat conditions changed—namely a reduction in floodplain access and deepening of certain pools—but the overall flow-type diversity of the system was not largely impacted. The resilience of the active channel of Little Beaver Creek to the fire and flood disturbances while retaining key services demonstrates the importance of river beads for enhancing river-floodplain resilience to large disturbance events and highlights river beads as key areas for preservation and restoration.
DOI: 10.17632/yr4fyf5chj.2
title: Research productivity and secular stagnation: Is there a correlation between research productivity and economic growth in OECD countries?

description: Recent papers have documented a reduction in research productivit over time. We estimate the relationship between research productivity and economic growth using a panel of OECD economies between 1981 and 2019. For countries in the G7, we find a strong correlation between these twoariables. The effect is both statistically significant and quantitatively relevant.
DOI: 10.4211/hs.65ccb3e358834424a2a7204b99bcc642
title: 1D-analytical framework for saltwater intrusion analysis

description: Saltwater intrusion is a critical concern for coastal communities due to its impacts on fresh ecosystems and civil infrastructure. Declining recharge and rising sea level are the two dominant drivers of saltwater intrusion along the land-ocean continuum, but there are currently no global estimates of future saltwater intrusion that synthesize these two spatially variable processes. Here, for the first time, we provide a novel assessment of global saltwater intrusion risk by integrating future recharge and sea level rise while considering the unique geology and topography of coastal regions. We show that nearly 77% of global coastal areas below 60° north will undergo saltwater intrusion by 2100, with different dominant drivers. Climate-driven changes in subsurface water replenishment (recharge) is responsible for the high-magnitude cases of saltwater intrusion, whereas sea level rise and coastline migration are responsible for the global pervasiveness of saltwater intrusion and have a greater effect on low-lying areas.
DOI: 10.4211/hs.127d1b944fce46caaa89bac236627ed4
title: Supporting data for publication (Prediction of flow duration curve for ungauged basins: Machine learning and deep learning approach)

description: The flow duration curve characterizes streamflow variability, crucial for river management. Constructing FDCs is challenging in areas without gauging stations. This study explores machine learning and deep learning models, including random forest, deep neural network, support vector regression, and elastic net regression, to predict FDCs in ungauged basins. Using data from streamflow stations, we predict streamflow percentiles . The models utilize various combinations of accumulated precipitation and topographic features to improve prediction accuracy.
DOI: 10.5281/zenodo.17916318
title: NASA GSFC Firn Densification Model version 1.2.1 (GSFC-FDMv1.2.1) for the Greenland and Antarctic Ice Sheets: Jan 1980 - Jul 2024

description: Overview

The NASA GSFC-FDM v1.2.1 provides the evolution of firn air content (FAC), surface mass balance (SMB) (and its individual components), and total firn height change over the Greenland and Antarctic Ice Sheets from January 1, 1980 to July 30, 2024 at 5-day temporal resolution.  The model uses atmospheric forcing from NASA GMAO's  Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) global atmospheric reanalysis, combined with a higher resolution replay (see Medley et al., 2022) as input into the Community Firn Model (CFMv1.1.6) to simulate the evolution of firn properties across the ice sheets.  The GSFC-FDMv1.2.1 is provided on a 12.5 km x 12.5 km North/South Polar Stereographic Grid, depending on the ice sheet.

For a thorough description of how the GSFC-FDMv1.2.1 was generated see Medley et al. (2022) in The Cryosphere.  Release 2 contains model output up through June 30, 2022, whereas the initial release only extended through September 30, 2021.  Release 3 contains model output up through July 31, 2024 and uses CFMv2.3.1, but access is restricted due to incorrectly mapped variables.  Release 4 contains model output up through July 31, 2024 and uses CFMv2.3.1.  The model set up is identical between releases.
description: This work was funded by NASA's ICESat-2 Project Science Office (PSO) as part of efforts to generate ice-sheet mass change estimates from NASA's ICESat-2.
DOI: 10.17632/3s8w9kr5hz
title: A titin missense variant drives atrial electrical remodeling and is associated with atrial fibrillation

description: Rare and common genetic variants contribute to the risk of atrial fibrillation (AF). Although ion channels were among the first AF candidate genes identified, rare loss-of-function variants in structural genes, such as TTN, have also been implicated in AF pathogenesis, partly through the development of atrial myopathy; however, the underlying mechanisms are poorly understood. While TTN truncating variants (TTNtvs) have been causally linked to arrhythmia and cardiomyopathy syndromes, the role of missense variants (mvs) remains unclear. We show that rare TTNmvs are associated with worse clinical outcomes in a single-center ethnic minority clinical cohort and uncover a pathogenic mechanism by which the T32756I variant drives AF. Modeling the TTN-T32756I variant using human induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-aCMs) revealed that the mutant cells display aberrant contractility, increased activity of a cardiac potassium channel (KCNQ1, Kv7.1), and dysregulated calcium homeostasis without compromising the sarcomeric integrity of the atrial cardiomyocytes. We also show that a titin-binding protein, the Four-and-a-Half Lim domains 2 (FHL2), has increased binding with KCNQ1 and its modulatory subunit KCNE1 in the TTN-T32756I-iPSC-aCMs, enhancing the slow delayed rectifier potassium current (Iks). Suppression of FHL2 in mutant iPSC-aCMs normalized the Iks, supporting FHL2 as an Iks modulator. Our findings demonstrate that a single amino acid substitution in titin not only impairs its function but also remodels ion channels, contributing to AF. These findings underscore the importance of high-throughput screening to assess the pathogenicity of TTNmvs and establish a mechanistic connection between titin, potassium ion channels, and sarcomeric proteins, which may represent a novel therapeutic target.
DOI: 10.5281/zenodo.7054573
title: NASA GSFC Firn Densification Model version 1.2.1 (GSFC-FDMv1.2.1) for the Greenland and Antarctic Ice Sheets: Jan 1980 - Jul 2024

description: Overview

The NASA GSFC-FDM v1.2.1 provides the evolution of firn air content (FAC), surface mass balance (SMB) (and its individual components), and total firn height change over the Greenland and Antarctic Ice Sheets from January 1, 1980 to July 30, 2024 at 5-day temporal resolution.  The model uses atmospheric forcing from NASA GMAO's  Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) global atmospheric reanalysis, combined with a higher resolution replay (see Medley et al., 2022) as input into the Community Firn Model (CFMv1.1.6) to simulate the evolution of firn properties across the ice sheets.  The GSFC-FDMv1.2.1 is provided on a 12.5 km x 12.5 km North/South Polar Stereographic Grid, depending on the ice sheet.

For a thorough description of how the GSFC-FDMv1.2.1 was generated see Medley et al. (2022) in The Cryosphere.  Release 2 contains model output up through June 30, 2022, whereas the initial release only extended through September 30, 2021.  Release 3 contains model output up through July 31, 2024 and uses CFMv2.3.1, but access is restricted due to incorrectly mapped variables.  Release 4 contains model output up through July 31, 2024 and uses CFMv2.3.1.  The model set up is identical between releases.
description: This work was funded by NASA's ICESat-2 Project Science Office (PSO) as part of efforts to generate ice-sheet mass change estimates from NASA's ICESat-2.
DOI: 10.4211/hs.4b455c9ac1864e1ba7a3bc90e91e8e0e
title: Parameters of multi-linear regressions for reconstructing peak flow in Contiguous United States (CONUS)

description: This dataset contains multi-regressions for 672 gauges across Contiguous United States (CONUS) to extend the peak dataset for enhanced Flood Frequency Analysis (FFA).

Flooding is a recurrent natural disaster causing substantial damage and casualties worldwide. A critical task to prevent and mitigate the negative impacts of these natural hazards is to characterize the frequency of flood peaks – a process known as flood frequency analysis (FFA). However, the short records of peak flow observations often limit the FFA accuracy. Here, we developed a statistical method to expand peak flow records at 672 undisturbed gauges across the United States using observations of daily mean flow, available over relatively long periods. We also quantified how FFA reliability improves by adding these expanded datasets of peak flows. This work provides datasets and benchmarks for increasing FFA accuracy, which are helpful for practitioners and government agencies responsible for flood mitigation, infrastructure design, and water management in the United States.
DOI: 10.17632/3s8w9kr5hz.1
title: A titin missense variant drives atrial electrical remodeling and is associated with atrial fibrillation

description: Rare and common genetic variants contribute to the risk of atrial fibrillation (AF). Although ion channels were among the first AF candidate genes identified, rare loss-of-function variants in structural genes, such as TTN, have also been implicated in AF pathogenesis, partly through the development of atrial myopathy; however, the underlying mechanisms are poorly understood. While TTN truncating variants (TTNtvs) have been causally linked to arrhythmia and cardiomyopathy syndromes, the role of missense variants (mvs) remains unclear. We show that rare TTNmvs are associated with worse clinical outcomes in a single-center ethnic minority clinical cohort and uncover a pathogenic mechanism by which the T32756I variant drives AF. Modeling the TTN-T32756I variant using human induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-aCMs) revealed that the mutant cells display aberrant contractility, increased activity of a cardiac potassium channel (KCNQ1, Kv7.1), and dysregulated calcium homeostasis without compromising the sarcomeric integrity of the atrial cardiomyocytes. We also show that a titin-binding protein, the Four-and-a-Half Lim domains 2 (FHL2), has increased binding with KCNQ1 and its modulatory subunit KCNE1 in the TTN-T32756I-iPSC-aCMs, enhancing the slow delayed rectifier potassium current (Iks). Suppression of FHL2 in mutant iPSC-aCMs normalized the Iks, supporting FHL2 as an Iks modulator. Our findings demonstrate that a single amino acid substitution in titin not only impairs its function but also remodels ion channels, contributing to AF. These findings underscore the importance of high-throughput screening to assess the pathogenicity of TTNmvs and establish a mechanistic connection between titin, potassium ion channels, and sarcomeric proteins, which may represent a novel therapeutic target.
DOI: 10.4211/hs.6c9217f8d84b4558a321eaee65e395dd
title: Neural network soil thermal conductivity prediction

description: The uploaded dataset comprises two folders:

1. “Model Prediction” Folder: This folder contains the complete dataset utilized in this study, along with the trained neural network. It enables users to reproduce the results presented in Figure 8 (training and testing outcomes) and facilitates the application of the model to additional soil datasets.
2. “Global Map of Model Parameters” Folder: This folder demonstrates an example application of the trained model, where the authors used SSCBD data from a global hydraulic properties dataset to generate and visualize the global distribution of the MLD model parameters.
DOI: 10.4211/hs.5b7f7c870eed4f8591bc8be01b34ee54
title: Carbon Evasion Dynamics in a Tropical, High-Elevation, Peatland Ecosystem are Mediated by Watershed Morphology

description: Inland waters emit large amounts of carbon and are key players in the global carbon budget. Particularly high rates of carbon emissions have been reported in streams draining mountains, tropical regions, and peatlands. However, few studies have examined the spatial variability of CO2 concentrations and fluxes occurring within these systems, particularly as a function of catchment morphology. Here we evaluated spatial patterns of CO2 in three tropical, headwater catchments in relation to the river network and stream geomorphology. We measured dissolved carbon dioxide (pCO2), aquatic CO2 emissions, discharge, and stream depth and width at high spatial resolutions along multiple stream reaches. Confirming previous studies, we found that tropical headwater streams are an important source of CO2 to the atmosphere. More notably, we found marked, predictable spatial organization in aquatic carbon fluxes as a function of landscape position. For example, pCO2 was consistently high (>10,000 ppm) at locations close to groundwater sources and just downstream of hydrologically connected wetlands, but consistently low (<1,000 ppm) in high gradient locations or river segments with larger drainage areas. Taken together, our findings suggest that catchment area and stream slope are important drivers of pCO2 and gas transfer velocity (k) in mountainous streams, and as such they should be considered in catchment-scale assessments of CO2 emissions. Furthermore, our work suggests that accurate estimation of CO2 emissions requires understanding of dynamics across the entire stream network, from the smallest seeps to larger streams.
DOI: 10.17632/pgyttykpjv
title: Traffic fatalities by Brazilian municipality from 2010 to 2023

description: Traffic fatality rates by Brazilian municipality from 2010 to 2023 with explanatory variables for modeling.
DOI: 10.17632/pgyttykpjv.1
title: Traffic fatalities by Brazilian municipality from 2010 to 2023

description: Traffic fatality rates by Brazilian municipality from 2010 to 2023 with explanatory variables for modeling.
DOI: 10.4211/hs.5cbece3ef6ad4e08a08d611681e1f800
title: Recovering head and flux distributions at the sediment-water interface for arbitrary, transient bedforms by inversion of photographic time series: supporting data

description: This is supporting data for the manuscript "Recovering head and flux distributions at the sediment-water interface for arbitrary, transient bedforms by inversion of photographic time series". The data set includes raw video of bed form and dye motion for three tracer tests conducted in a glass-sided flume which are discussed in the manuscript. Also contained are digital feature representations for those tests, including sediment-water interface (SWI) location, SWI head distribution, and dye front locations.
DOI: 10.17632/dfmtgtg55w
title: Eco-Routing Database Project

description: This dataset contains OpenStreetMap (OSM) road network data for the Southeast region of Brazil in Protocol Buffer Binary Format (PBF). The file includes comprehensive geospatial information about the road infrastructure, including street networks, road types, speed limits, one-way restrictions, and road geometries. This dataset was used in the Ecological Route Optimization System project to enable route calculation algorithms (Dijkstra and A*) for comparing ecological (fuel-efficient) versus shortest distance routes.

The PBF format is a compressed, efficient binary format for storing OpenStreetMap data. This dataset can be used for transportation research, route optimization studies, urban planning, and geographic information system (GIS) applications.

Data includes:
- Road network topology (nodes and edges)
- Road names and classifications
- Speed limit information
- One-way street restrictions
- Road segment lengths and geometries
- Geographic coordinates for all network nodes