bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pre-harvest food safety and conservation challenges facing US produce growers: results from a national survey
Authors: Adalja Aaron , Baur Patrick , Wiedmann Martin , Olimpi Elissa , Weller Daniel 
Published: December 2023

Abstract
Fruit and vegetable growers in the US face tradeoffs and synergies between on-farm conservation and pre-harvest food safety as a result of economic considerations, regulatory concerns, and external pressure from other stakeholders. However, detailed data on the frequency and extent of these tradeoffs across US regions remain sparse. We designed and implemented a national grower survey for the 2018 crop year to address this gap. Based on 209 responses, we examined usage of pre-harvest food safety and conservation practices with a particular emphasis on managing animal intrusion into growing areas and maintaining wildlife habitat. We also analyzed associations between farm characteristics and the probability that growers used different on-farm food safety and conservation practices. We did not find a simple biophysical or socio-economic explanation for why some farms adopted specific practices over others. Instead, our findings suggest that the adoption of particular food safety practices is influenced by a complex assemblage of factors that include environmental context, supply chain pressures, cost considerations, and growers' perceptions of risk. A better understanding of the diverse tradeoffs and synergies that US produce growers face between on-farm conservation and pre-harvest food safety is critical for effective policy design.
Isotope Constraints on Nitrate Exchanges Between Precipitation and Forest Canopy
Authors: Liu Xue‐Yan , Liu Mei‐Na , Qin Wan‐Xiao , Song Wei 
Published: December 2023

AbstractAtmospheric nitrogen (N) deposition is a key process influencing plant‐soil N processes and associated functions of forest ecosystems. However, the N deposition into soils based on open‐field precipitation observations remains inaccurate due to the unconstrained precipitation‐canopy N exchanges, which prevents a better evaluation of N deposition effects on forest N cycles and functions. Nitrate () is a major form of reactive N. Based on a data synthesis of fluxes and isotopes (15N, 17O, 18O) of atmospheric inputs in forests, here we constructed a new method to quantify fractions and fluxes of throughfall () contributors (nitrification () and particulates () in canopies, the original precipitation ()) and then constrain precipitation‐canopy exchanges (i.e., gains from canopy and losses due to canopy retention). Generally, was higher in fluxes but lower in N and O isotopes than , suggesting higher gains than losses and canopy nitrification as a gain contributor. 10%−18% and 40%−47% of were gained from canopy and , respectively, while 43% ± 25% and 20% ± 74% of the original were lost after passing through canopies of broadleaved and coniferous forests, respectively. Importantly, both gain and loss fluxes were found increasing with the fluxes. This work unlocked fractions and fluxes of major precipitation‐canopy exchange processes and revealed a stimulating mechanism of atmospheric pollution on precipitation‐canopy exchanges.
Dynamic Response to Ice Shelf Basal Meltwater Relevant to Explain Observed Sea Ice Trends Near the Antarctic Continental Shelf
Authors: Huneke Wilma G. C. , Hobbs William R. , Klocker Andreas , Naughten Kaitlin A. 
Published: December 2023

AbstractObserved Antarctic sea ice trends up to 2015 have a distinct regional and seasonal pattern, with a loss during austral summer and autumn in the Bellingshausen and Amundsen Seas, and a year‐round increase in the Ross Sea. Global climate models generally failed to reproduce the magnitude of sea ice trends implying that the models miss relevant mechanisms. One possible mechanism is basal meltwater, which is generally not included in the current generation of climate models. Previous work on the effects of meltwater on sea ice has focused on thermodynamic processes. However, local freshening also leads to dynamic changes, affecting ocean currents through geostrophic balance. Using a coupled ocean/sea‐ice/ice‐shelf model, we demonstrate that basal melting can intensify coastal currents in West Antarctica and the westward transport of sea ice. This change in transport results in sea ice anomalies consistent with observations, and may explain the disparity between climate models and observations.
Global and Regional Climate Feedbacks in Response to Uniform Warming and Cooling
Authors: Ringer Mark A. , Bodas‐Salcedo Alejandro , Webb Mark J. 
Published: December 2023

AbstractWe compare the radiative feedbacks in an ensemble of global climate models under uniform 4 K warming and cooling of sea surface temperatures. The global‐mean net feedback is less stabilizing under warming in all nine models. This results primarily from less stabilizing water vapor and extra‐tropical shortwave cloud feedbacks, partially offset by more stabilizing tropical cloud feedbacks. The zonal‐mean feedbacks are also robust across the ensemble. In the extra‐tropics, the less stabilizing shortwave cloud feedback under warming is associated with further poleward migration of the mean Southern Hemisphere jet in some models. However, additional experiments with an aquaplanet version of the HadGEM3 model suggest that the asymmetry of the jet shift is not driving the asymmetry in the cloud feedbacks at these latitudes. In the tropics, the stronger water vapor feedback under warming is offset by weaker shortwave cloud feedbacks. The result is that the ensemble spread in the differences between the global feedbacks under warming and cooling is mainly driven by their differences in the tropics. The spatial distribution of the feedbacks largely reflects the zonal‐mean behavior, although there is considerable model spread in the regional cloud feedbacks, particularly in the tropical shortwave cloud feedback. Comparison with CO2‐ and solar‐forced coupled experiments suggests that the global‐mean longwave cloud feedback is nearly invariant to warming and cooling, regardless of the nature of the forcing. The shortwave cloud feedback is generally more positive under warming in the coupled models, consistent with the uniform SST perturbation experiments.
Validating Ionospheric Models Against Technologically Relevant Metrics
Authors: Chartier A. T. , Steele J. , Sugar G. , Themens D. R. , Vines S. K. , Huba J. D. 
Published: December 2023

AbstractNew, open access tools have been developed to validate ionospheric models in terms of technologically relevant metrics. These are ionospheric errors on GPS 3D position, HF ham radio communications, and peak F‐region density. To demonstrate these tools, we have used output from Sami is Another Model of the Ionosphere (SAMI3) driven by high‐latitude electric potentials derived from Active Magnetosphere and Planetary Electrodynamics Response Experiment, covering the first available month of operation using Iridium‐NEXT data (March 2019). Output of this model is now available for visualization and download via https://sami3.jhuapl.edu. The GPS test indicates SAMI3 reduces ionospheric errors on 3D position solutions from 1.9 m with no model to 1.6 m on average (maximum error: 14.2 m without correction, 13.9 m with correction). SAMI3 predicts 55.5% of reported amateur radio links between 2–30 MHz and 500–2,000 km. Autoscaled and then machine learning “cleaned” Digisonde NmF2 data indicate a 1.0 × 1011 el. m3 median positive bias in SAMI3 (equivalent to a 27% overestimation). The positive NmF2 bias is largest during the daytime, which may explain the relatively good performance in predicting HF links then. The underlying data sources and software used here are publicly available, so that interested groups may apply these tests to other models and time intervals.
Investigation of the Physical Mechanisms of the Formation and Evolution of Equatorial Plasma Bubbles During a Moderate Storm on 17 September 2021
Authors: Wu Kun , Qian Liying , Wang Wenbin , Cai Xuguang , Mclnerney Joseph M. 
Published: December 2023

AbstractWe investigate in detail the occurrence and evolution of ionospheric equatorial plasma bubbles (EPBs) during a moderate storm on 17 September 2021, using Global‐scale Observations of the Limb and Disk (GOLD) observations and Whole Atmosphere Community Climate Model‐eXtended (WACCM‐X) simulations. GOLD observations show that there were no EPBs on 16 September before the storm but EPBs occurred after the storm commencement on 17 September. The EPBs extended to ∼30° magnetic latitude. A diagnostic analysis of WACCM‐X simulations reveals that the rapid enhancement of prompt penetration electric fields (PPEFs) after the sudden storm commencement is the main reason that triggered the occurrence of the EPBs. Further quantitative analysis shows that vertical plasma drifts, which are enhanced by the PPEF, played a dominant role in strengthening the Rayleigh‐Taylor instability, leading to the occurrence of the EPBs and the large latitudinal extension of the EPBs to ∼30° magnetic latitude during the night of 17 September.
Baseflow Statistics in Aggregated Catchments
Authors: Di Dato Mariaines , Bellin Alberto , Cvetkovic Vladimir , Dagan Gedeon , Dietrich Peter , Fiori Aldo , Teutsch Georg , Zech Alraune , Attinger Sabine 
Published: December 2023

AbstractThis paper employs stochastic analysis to investigate the combined effect of temporal and spatial variability on the temporal variance of baseflow in large catchments. The study makes use of the well‐known aggregated reservoir model, representing the catchment as a network of parallel linear reservoirs. Each reservoir models a sub‐catchment as an independent unit whose discharge temporal variation is characterized by a response time. By treating the rainfall‐generated recharge and the sub‐catchment response times as random variables, the statistical temporal moments of total baseflow are quantified. Comparisons are made between the temporal variance of baseflow in the aggregated reservoir model and that of a single homogeneous reservoir to define an upscaled response time. The analysis of the statistical moments of the random baseflow reveals that the number of reservoirs N has a weak impact on baseflow variance, with ergodic conditions achieved even with a small number of reservoirs. The study highlights that the ratio between the recharge correlation time and the geometric mean of the sub‐catchment response times plays a critical role in baseflow damping and the upscaled response. The results indicate that the dynamics of baseflow generation depend not only on the catchment hydro‐geological structure but also on the variability of the input signal. This research underscores the importance of understanding the combined influences of hydro‐geological factors and recharge input variability for baseflow prediction under uncertainty. The present study should be regarded as a first step, setting the theoretical framework for future research toward incorporating field data.
Prevalence and network structure of post-traumatic stress symptoms and their association with suicidality among Chinese mental health professionals immediately following the end of China’s Dynamic Zero-COVID Policy: a national survey
Authors: Chen Pan , Zhang Ling , Feng Yuan , An Feng-Rong , Su Zhaohui , Cheung Teris , Lok Ka-In , Ungvari Gabor S. , Jackson Todd , Xiang Yu-Tao , Zhang Qinge 
Published: December 2023

AbstractStudies on post-traumatic stress symptoms (PTSS) among mental health professionals (MHPs) are limited, particularly since restrictions due to coronavirus disease (COVID-19) have been lifted such as the recent termination of China’s Dynamic Zero-COVID Policy. The current study filled this gap by exploring the prevalence, correlates, and network structure of PTSS as well as its association with suicidality from a network analysis perspective. A cross-sectional, national survey was conducted using a convenience sampling method on MHPs between January 22 and February 10, 2023. PTSS were assessed using the Post-Traumatic Stress Disorder Checklist-Civilian version, while suicidality was assessed using standardized questions related to ideation, plans, and attempts. Univariate and multivariate analyses examined correlates of PTSS. Network analysis explored the structure of PTSS and suicidality. The centrality index of “Expected influence” was used to identify the most central symptoms in the network, reflecting the relative importance of each node in the network. The “flow” function was adopted to identify specific symptoms that were directly associated with suicidality. A total of 10,647 MHPs were included. The overall rates of PTSS and suicidality were 6.7% (n = 715; 95% CI = 6.2–7.2%) and 7.7% (n = 821; 95% CI = 7.2–8.2%), respectively. Being married (OR = 1.523; P < 0.001), quarantine experience (OR = 1.288; P < 0.001), suicidality (OR = 3.750; P < 0.001) and more severe depressive symptoms (OR = 1.229; P < 0.001) were correlates of more PTSS. Additionally, higher economic status (e.g., good vs. poor: OR = 0.324; P = 0.001) and health status (e.g., good vs. poor: OR = 0.456; P < 0.001) were correlates of reduced PTSS. PCL6 (“Avoiding thoughts”; EI = 1.189), PCL7 (“Avoiding reminders”; EI = 1.157), and PCL11 (“Feeling emotionally numb”; EI = 1.074) had the highest centrality, while PCL12 (“Negative belief”), PCL 16 (“Hypervigilance”) and PCL 14 (“Irritability”) had the strongest direct, positive associations with suicidality. A high prevalence of lingering PTSS was found among MHPs immediately after China’s “Dynamic Zero-COVID Policy” was terminated. Avoidance and hyper-arousal symptoms should be monitored among at-risk MHPs after the COVID-19 pandemic and serve as potential targets for the prevention and treatment of PTSS in this population.
Cross-linking polybutadiene rubber via a thiol-ene reaction with polycysteine as a degradable cross-linker
Authors: Tsuchiya Kousuke , Terada Kayo , Tsuji Yui , Law Simon Sau Yin , Masunaga Hiroyasu , Katashima Takuya , Sakai Takamasa , Numata Keiji 
Published: December 2023

AbstractCovalently cross-linked rubber materials are widely used in elastic applications due to their excellent mechanical properties. However, the irreversibility of covalent cross-linking suffers from poor material recyclability. As a degradable polypeptide-based cross-linker for polybutadiene, poly(l-cysteine) (polyCys) was synthesized via papain-catalyzed chemoenzymatic polymerization. The resulting polyCys had intact thiol groups that cross-linked polybutadiene via the thiol-ene reaction. The cross-linking reaction of polybutadiene was performed in the presence of polyCys and a radical initiator and resulted in insoluble polybutadiene gel formation. Based on Raman spectroscopy analysis, the cross-linking reaction was confirmed by the consumption of thiol groups of polyCys. From the dynamic viscoelastic analyses of the cross-linked polybutadienes, the viscoelasticity drastically changed from that of raw polybutadiene, with the disappearance of the slow relaxation mode at low frequencies. The complete network formation was confirmed by E′ and E′′ showing the power law over the whole frequency range, as determined by the time-course experiments of the dynamic viscoelastic properties. The cross-linked polybutadiene was degradable by acid hydrolysis, resulting in the regeneration of soluble polybutadiene. Polypeptide cross-linked polybutadiene materials are promising candidates for the application of polybutadiene-based rubber materials with the requirements of both material integrity and reusability.
Essential transcription factors for induced neuron differentiation
Authors: Lu Congyi , Garipler Görkem , Dai Chao , Roush Timothy , Salome-Correa Jose , Martin Alex , Liscovitch-Brauer Noa , Mazzoni Esteban O. , Sanjana Neville E. 
Published: December 2023

AbstractNeurogenins are proneural transcription factors required to specify neuronal identity. Their overexpression in human pluripotent stem cells rapidly produces cortical-like neurons with spiking activity and, because of this, they have been widely adopted for human neuron disease models. However, we do not fully understand the key downstream regulatory effectors responsible for driving neural differentiation. Here, using inducible expression of NEUROG1 and NEUROG2, we identify transcription factors (TFs) required for directed neuronal differentiation by combining expression and chromatin accessibility analyses with a pooled in vitro CRISPR-Cas9 screen targeting all ~1900 TFs in the human genome. The loss of one of these essential TFs (ZBTB18) yields few MAP2-positive neurons. Differentiated ZBTB18-null cells have radically altered gene expression, leading to cytoskeletal defects and stunted neurites and spines. In addition to identifying key downstream TFs for neuronal differentiation, our work develops an integrative multi-omics and TFome-wide perturbation platform to rapidly characterize essential TFs for the differentiation of any human cell type.
Uncertainties in critical slowing down indicators of observation-based fingerprints of the Atlantic Overturning Circulation
Authors: Ben-Yami Maya , Skiba Vanessa , Bathiany Sebastian , Boers Niklas 
Published: December 2023

AbstractObservations are increasingly used to detect critical slowing down (CSD) to measure stability changes in key Earth system components. However, most datasets have non-stationary missing-data distributions, biases and uncertainties. Here we show that, together with the pre-processing steps used to deal with them, these can bias the CSD analysis. We present an uncertainty quantification method to address such issues. We show how to propagate uncertainties provided with the datasets to the CSD analysis and develop conservative, surrogate-based significance tests on the CSD indicators. We apply our method to three observational sea-surface temperature and salinity datasets and to fingerprints of the Atlantic Meridional Overturning Circulation derived from them. We find that the properties of these datasets and especially the specific gap filling procedures can in some cases indeed cause false indication of CSD. However, CSD indicators in the North Atlantic are still present and significant when accounting for dataset uncertainties and non-stationary observational coverage.
Orphan quality control by an SCF ubiquitin ligase directed to pervasive C-degrons
Authors: Kong Ka-Yiu Edwin , Shankar Susmitha , Rühle Frank , Khmelinskii Anton 
Published: December 2023

AbstractSelective protein degradation typically involves substrate recognition via short linear motifs known as degrons. Various degrons can be found at protein termini from bacteria to mammals. While N-degrons have been extensively studied, our understanding of C-degrons is still limited. Towards a comprehensive understanding of eukaryotic C-degron pathways, here we perform an unbiased survey of C-degrons in budding yeast. We identify over 5000 potential C-degrons by stability profiling of random peptide libraries and of the yeast C‑terminome. Combining machine learning, high-throughput mutagenesis and genetic screens reveals that the SCF ubiquitin ligase targets ~40% of degrons using a single F-box substrate receptor Das1. Although sequence-specific, Das1 is highly promiscuous, recognizing a variety of C-degron motifs. By screening for full-length substrates, we implicate SCFDas1 in degradation of orphan protein complex subunits. Altogether, this work highlights the variety of C-degron pathways in eukaryotes and uncovers how an SCF/C-degron pathway of broad specificity contributes to proteostasis.
A manifold-based framework for studying the dynamics of the vaginal microbiome
Authors: Tsamir-Rimon Mor , Borenstein Elhanan 
Published: December 2023

AbstractThe vaginal microbiome plays a crucial role in our health. The composition of this community can be classified into five community state types (CSTs), four of which are primarily consisted of Lactobacillus species and considered healthy, while the fifth features non-Lactobacillus populations and signifies a disease state termed Bacterial vaginosis (BV), which is associated with various symptoms and increased susceptibility to diseases. Importantly, however, the exact mechanisms and dynamics underlying BV development are not yet fully understood, including specifically possible routes from a healthy to a BV state. To address this gap, this study set out to characterize the progression from healthy- to BV-associated compositions by analyzing 8026 vaginal samples and using a manifold-detection framework. This approach, inspired by single-cell analysis, aims to identify low-dimensional trajectories in the high-dimensional composition space. It further orders samples along these trajectories and assigns a score (pseudo-time) to each analyzed or new sample based on its proximity to the BV state. Our results reveal distinct routes of progression between healthy and BV states for each CST, with pseudo-time scores correlating with community diversity and quantifying the health state of each sample. Several BV indicators can also be successfully predicted based on pseudo-time scores, and key taxa involved in BV development can be identified using this approach. Taken together, these findings demonstrate how manifold detection can be used to successfully characterize the progression from healthy Lactobacillus-dominant populations to BV and to accurately quantify the health condition of new samples along the route of BV development.
Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix
Authors: Zhou Yilong , Bore Sigbjørn Løland , Tao Andrea R. , Paesani Francesco , Arya Gaurav 
Published: December 2023

AbstractMany-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.