Search

Highly concentrated aqueous electrolytes (termed water-in-salt electrolytes, WiSEs) at solid-liquid interfaces are ubiquitous in myriad applications including biological signaling, electrosynthesis, and energy storage. This interface, known as the electrical double layer (EDL), has a different structure in WiSEs than in dilute electrolytes. Here, we investigate how divalent salts [zinc bis(trifluoromethylsulfonyl)imide, Zn(TFSI)2], as well as mixtures of mono- and divalent salts [lithium bis(trifluoromethylsulfonyl)imide (LiTFSI) mixed with Zn(TFSI)2], affect the short- and long-range structure of the EDL under confinement using a multimodal combination of scattering, spectroscopy, and surface forces measurements. Raman spectroscopy of bulk electrolytes suggests that the cation is closely associated with the anion regardless of valency. Wide-angle X-ray scattering reveals that all bulk electrolytes form ion clusters; however, the clusters are suppressed with increasing concentration of the divalent ion. To probe the EDL under confinement, we use a Surface Forces Apparatus and demonstrate that the thickness of the adsorbed layer of ions at the interface grows with increasing divalent ion concentration. Multiple interfacial layers form following this adlayer; their thicknesses appear dependent on anion size, rather than cation. Importantly, all electrolytes exhibit very long electrostatic decay lengths that are insensitive to valency. It is likely that in the WiSE regime, electrostatic screening is mediated by the formation of ion clusters rather than individual well-solvated ions. This work contributes to understanding the structure and charge-neutralization mechanism in this class of electrolytes and the interfacial behavior of mixed-electrolyte systems encountered in electrochemistry and biology.

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. The soil carbon dioxide (CO2) efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation phenology, climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, our research demonstrates an efficient method of employing various open-source remote sensing and GIS datasets to comprehend the spatial variability and soil respiration mechanisms in coastal TAI. There is no one-size-fits-all approach to modeling carbon fluxes released by soil respiration in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

Abstract The primary immune constituents in the brain, microglia and macrophages, are the target for HIV in people and simian immunodeficiency virus (SIV) in nonhuman primates. This infection can lead to neurological dysfunction, known as HIV-associated neurocognitive disorder (HAND). Given the gaps in our knowledge on how these cells respond in vivo to CNS infection, we perform single-cell multiomic sequencing, including gene expression and ATAC-seq, on myeloid cells from the brains of rhesus macaques with SIV-induced encephalitis (SIVE) as well as uninfected controls. We find that SIVE significantly changes the myeloid cell populations. In SIVE, microglia-like cells express high levels of chemoattractants capable of recruiting highly activated CAM-like cells to the site of infection/inflammation. A unique population of microglia-like cells is found in which the chromatin accessibility of genes diverges from their RNA expression. Additionally, we observe a dramatic shift of upstream gene regulators and their targets in brain myeloid cells during SIVE. This study further uncovers the transcriptome, gene regulatory events, and potential roles of different brain myeloid phenotypes in SIVE. This might deepen the understanding of SIVE/HIVE and enlighten the therapeutic development.

Societal Impact Statement Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net‐zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi‐automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net‐zero motivated future. Abstract Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well‐documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi‐automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground‐based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground‐based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

Abstract Coastal ecosystems are at the nexus of many high priority challenges in environmental sciences, including predicting the influences of compounding disturbances exacerbated by climate change on biogeochemical cycling. While research in coastal science is fundamentally transdisciplinary—as drivers of biogeochemical and ecological processes often span scientific and environmental domains—traditional place–based approaches are still often employed to understand coastal ecosystems. We argue that a macrosystems science perspective, including the integration across distributed research sites, is crucial to understand how compounding disturbances affect coastal ecosystems. We suggest that many grand challenge questions, such as advancing continental‐scale process understanding of extreme events and global change, will only be addressed in coastal ecosystems using a network‐of‐networks approach. We identify specific ways that existing research efforts can maximize benefit across multiple interested parties, and where additional infrastructure investments might increase return‐on‐investment along the coast, using the coastal continental United States as a case study.

Vehicle trajectory data have become essential for many research fields, such as traffic flow, traffic safety, and automated driving. To make trajectory data useable for researchers, an overview of the included road section and traffic situation as well as a description of the data processing methodology is necessary. In this paper, we present a trajectory dataset from a German highway with two lanes per direction, an off-ramp and congested traffic in one direction, and an on-ramp in the other direction. The dataset contains 8,648 trajectories and covers 87 ​min and an ∼1,200 ​m long section of the road. The trajectories were extracted from drone videos using a posttrained YOLOv5 object detection model and projected onto the road surface via three-dimensional (3D) camera calibration. The postprocessing methodology can compensate for most false detections and yield accurate speeds and accelerations. The trajectory data are also compared with induction loop data and vehicle-based smartphone sensor data to evaluate the plausibility and quality of the trajectory data. The deviations of the speeds and accelerations are estimated at 0.45 ​m/s and 0.3 ​m/s2, respectively. We also present some applications of the data, including traffic flow analysis and accident risk analysis.

Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities.

ABSTRACT Objective: The aim of this study was to analyze the association between participation in fitness-related exercises (FRE) and body image dissatisfaction (BID) in adolescents and evaluate the interaction between physical exercise and nutritional status in this association. Methods: A cross-sectional study was conducted in 2015 involving 799 adolescents (10–16 years old) from 14 public schools in Curitiba (PR), Brazil. BID was assessed using the Body Shape Questionnaire and the Silhouette Scale. The FRE was classified as “does not practice,” “practices ≤300 min/week,” and “practices >300 min/week” by the Physical Activity Questionnaire for Adolescents. Poisson and multinomial logistic regressions, adjusted for sex, sexual maturation, and nutritional status analyzed the association of FRE and BID. Results: The BID prevalence was 28.3%; 52.4% of the adolescents wanted to reduce their silhouettes; and 48.7% did not practice FRE. Adolescents who practiced FRE >300 min/week had a 28% higher prevalence for some level of BID (PR 1.28; 95%CI 1.08–1.52) and a 46% lower chance of wanting to reduce silhouettes (OR 0.54; 95%CI 0.35–0.82), compared to nonpractitioners. There was no interaction between FRE and nutritional status in association with BID. Conclusions: The adolescents who practice FRE >300 min/week are likely to have some level of BID and are less likely to report the desire to increase their silhouettes, regardless of their nutritional status.

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

Weigh-in-motion (WIM) systems aim to estimate a vehicle’s weight by measuring static wheel loads as it passes at highway speed over roadway-embedded sensors. Vehicle oscillations and the resulting dynamic load components are critical factors affecting measurements and limiting accuracy. As of now, a satisfactory solution has yet to be found. This paper discusses a novel correction approach that fuses WIM sensor data with wheel oscillation captured by cameras. In an experiment, a hard plastic speed bump was placed ahead of a piezoelectric WIM sensor to induce oscillation in trucks crossing the WIM sensor. Three high-speed cameras captured the motion of the wheels. The results show that the proposed method improved the accuracy of the measured gross weight for significant wheel oscillations, while no improvement is observed for smaller oscillation amplitudes.

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research-from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology-from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

Cryogenic opto-electronic interconnects are gaining increasing interest as a means to control and readout cryogenic electronic components. The challenge is to achieve sufficient signal integrity with low heat load processing. In this context, we demonstrate the opto-electronic bias and readout of a commercial four-pixel superconducting nanowire single-photon detector array using a cryogenic photodiode and laser. We show that this approach has a similar system detection efficiency to a conventional bias. Furthermore, multi-pixel detection events are faithfully converted between the optical and electrical domains, which allows reliable extraction of amplitude multiplexed photon statistics. Our device has a latent heat load of 2.6 mW, maintains a signal rise time of 3 ns, and operates in free-running (self-resetting) mode at a repetition rate of 600 kHz. This demonstrates the potential of high-bandwidth, low noise, and low heat load opto-electronic interconnects for scalable cryogenic signal processing and transmission.

Abstract AGU Publications encourages research collaborations between regions, countries, and communities. When well‐resourced researchers complete research or field work in low‐resourced settings while excluding local communities or researchers from the process, this can be referred to as parachute science or helicopter research. To help address concerns of parachute science and to promote greater equity and transparency in global research collaborations, AGU Publications has updated its authorship policy across its scholarly journals. The implementation of this policy follows a successful 18‐month pilot at JGR: Biogeosciences. For research completed in low‐resourced regions, authors are encouraged to include a disclosure statement pertaining to the ethical and scientific considerations of their research collaborations.

Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats-instructions, templates, and tools for consistently formatting data within a discipline-can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

Numerous plant hydrodynamic models have started to be implemented in vegetation dynamics models, reflecting the central role of plant hydraulic traits in driving water, energy, and carbon cycles, as well as plant adaptation to climate change. Different numerical approximations of the governing equations of the hydrodynamic models have been documented, but the numerical accuracy of these models and its subsequent effects on the simulated vegetation function and dynamics have rarely been evaluated. Using different numerical solution methods (including implicit and explicit approaches) and vertical discrete grid resolutions, we evaluated the numerical performance of a plant hydrodynamic module in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES-HYDRO version 0.1) based on single-point and global simulations. Our simulation results showed that when near-surface vertical grid spacing is coarsened (grid size >10 cm), the model significantly overestimates aboveground biomass (AGB) in most of the temperate forest locations and underestimates AGB in the boreal forest locations, as compared to a simulation with finer vertical grid spacing. Grid coarsening has a small effect on AGB in the tropical zones of Asia and South America. In particular, coarse surface grid resolution should not be used when there are large and prolonged water content differences among soil layers at depths due to long dry-season duration and/or well-drained soil or when soil evaporation is a dominant fraction of evapotranspiration. Similarly, coarse surface grid resolution should not be used when there is lithologic discontinuity along the soil depth. This information is useful for uncertainty quantification, sensitivity analysis, or the training of surrogate models to design the simulations when computational cost limits the use of ensemble simulations.

Abstract Isotopic pool dilution is a powerful approach to quantify gross biogeochemical transformation rates, but remains seldom used despite its potential. To facilitate broader implementation of pool dilution methods, we present a user‐friendly R package that optimizes gross production and consumption rates (and optionally fractionation constants as well) based on standard pool dilution time series data. This package features extensive documentation and example analyses, and is easily integrated into analytical pipelines. With this open‐source tool, the biogeochemistry community will be able to readily apply isotope pool dilution to a wide range of processes.

Abstract Guidelines regulate how many (tumour-bearing) tissue particles should be sampled during gastric cancer biopsy to obtain representative results in predictive biomarker testing. Little is known about how well these guidelines are applied, how the number of tissue particles correlates with the actual tumour-infiltrated area and how many absolute tumour cells are captured. The study included endoscopic biopsies of untreated carcinomas of the upper gastrointestinal (GI)-tract during the 2016–2020 review period. Archival (H&E)-stained histological sections were digitised and the tumour areas were manually annotated. The tumour-bearing tissue area and absolute carcinoma cell count per case were determined by image analysis and compared with a reference primary surgical specimen. Biopsies from 253 patients were analysed. The following mean values were determined: (a) tumour tissue particle number: 6.5 (range: 1–25, standard deviation (SD) = 3.33), (b) number of tumour-bearing tissue particles: 4.7 (range: 1–20, SD = 2.80), (c) tumour-infiltrated area: 7.5 mm2 (range: 0.18–59.46 mm2, SD = 6.67 mm2), (d) absolute tumour cell count: 13,492 (range: 193–92,834, SD = 14,185) and (e) tumour cell count in a primary surgical specimen (tumour size: 6.7 cm): 105,200,176. The guideline-recommended tissue particle count of 10 was not achieved in 208 patients (82.2%) and the required tumour-bearing tissue particle count of 5 was not achieved in 133 patients (52.6%). Tissue particle count, tumour-infiltrated area and tumour cell count were only weakly correlated. Most cases featured an infiltrated area ≥ 4.5 mm2 (156, 61.7%). Cases with more tissue particles showed only a moderate increase in infiltrated area and tumour cells compared to cases with fewer particles. Biopsies are often used to determine predictive biomarkers, particularly Her2/neu and PD-L1. Diagnostic standards to ensure representative material have been suggested in guidelines to reduce false-negative predictions. However, the real-world practice seems to substantially deviate from recommended standards. To the best of our knowledge, this is the first systematic study describing the relationships between endoscopic tissue fragment number, actual infiltrated tumour area and carcinoma cell number. The data question the tissue particle number as a quality assessment parameter. We advocate histopathological reports indicating on which basis statements on therapy-relevant biomarkers were made. Digital pathology has the potential to objectively quantify the tissue for documentation, quality assessment and future clinical studies.

Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community-driven standard development and associated documentation on GitHub based on a systematic review of existing practices.

Field observations of the soil-to-atmosphere CO2 flux—soil respiration, RS—are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the earth and ecological sciences as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g., FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. With input from the research community, we have also developed research data and metadata templates to support data collection adhering to the reporting format. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. This proposed RS reporting format is openly available online and is intended to be a dynamic document, subject to further community feedback and/or change.

Field observations of the soil-to-atmosphere CO2 flux—soil respiration, RS—are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the earth and ecological sciences as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g., FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. With input from the research community, we have also developed research data and metadata templates to support data collection adhering to the reporting format. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. This proposed RS reporting format is openly available online and is intended to be a dynamic document, subject to further community feedback and/or change.

IntroductionIn the 21st century, digital devices have become integral to our daily lives. Still, practical assessments designed to evaluate an individual’s digital tool competencies are absent. The present study introduces the “Digital Tools Test” (“DIGI”), specifically designed for the evaluation of one’s proficiency in handling common applications and functions of smartphones and tablets. The DIGI assessment has been primarily tailored for prospective use among older adults and neurological patients with the latter frequently suffering from so-called apraxia, which potentially also affects the handling of digital tools. Similar to traditional tool use tests that assess tool-selection and tool-action processes, the DIGI assessment evaluates an individual’s ability to select an appropriate application for a given task (e.g., creating a new contact), their capacity to navigate within the chosen application and their competence in executing precise and accurate movements, such as swiping.MethodsWe tested the implementation of the DIGI in a group of 16 healthy adults aged 18 to 28 years and 16 healthy adults aged 60 to 74 years. All participants were able to withstand the assessment and reported good acceptance.ResultsThe results revealed a significant performance disparity, with older adults displaying notably lower proficiency in the DIGI. The DIGI performance of older adults exhibited a correlation with their ability to employ a set of novel mechanical tools, but not with their ability to handle a set of familiar common tools. There was no such correlation for the younger group.ConclusionIn conclusion, this study introduces an innovative assessment tool aimed at evaluating common digital tool competencies. Our preliminary results demonstrate good acceptance and reveal expected group differences. For current cohorts of older adults, the results seem to indicate that the ability to use novel tools may aid digital tool use. In the next step, the psychometric properties of the DIGI assessment should be evaluated in larger and more diverse samples. The advancement of digital tool competency assessments and rehabilitation strategies is essential when we aim at facilitating societal inclusion and participation for individuals in affected populations.