bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Influence of Weather Forecast Resolution on the Circulation of Lake George, NY
Authors: Auger Guillaume A. R. , Watson Campbell D. , Kolar Harry R. 
Published: September 2021

AbstractGlobal warming is expected to greatly impact the thermal conditions of inland water bodies. Publicly available weather forecasts sufficiently resolve weather patterns above large lakes to satisfactorily force a lake hydrodynamics model, we suspect this is not the case for smaller lakes. We address this issue using weather outputs from a numerical weather prediction model at three different resolutions (3 km, 1 and 0.33 km) to force a hydrodynamics model of Lake George, NY for the month of June 2017. We find that increasing the resolution of the weather model improves the accuracy of the simulation, in part through a significant increase in total heat content of the lake. This warming is linked to an increase in downward heat transfer from the atmosphere in the higher resolution experiment, especially in the northern part of the lake where the lake is less than 2 km wide and the simulated surface winds are stronger. Interrogation of the weather model shows the stronger winds originate from a better representation of the land‐lake interface (and thereby surface roughness length) at higher resolution. At the end of the one month simulation, we find the hypolimnetic volume of Lake George has reduced by 15% in the 0.33 km experiment compared to the 3 km experiment. If this discrepancy were systemic it would have obvious consequences for predicting the ecoysystem function over an extended period of small‐to‐medium sized lakes.
Observations of an Electron‐Cold Ion Component Reconnection at the Edge of an Ion‐Scale Antiparallel Reconnection at the Dayside Magnetopause
Authors: Zhao S. Q. , Zhang H. , Liu Terry Z. , Yan Huirong , Xiao C. J. , Liu Mingzhe , Zong Q.‐G. , Wang Xiaogang , Shi Mijie , Teng Shangchun , Wang Huizi , Rankin R. , Pollock C. , Le G. 
Published: September 2021

AbstractSolar wind parameters play a dominant role in reconnection rate, which controls the solar wind‐magnetosphere coupling efficiency at Earth's magnetopause. Besides, low‐energy ions from the ionosphere, frequently detected on the magnetospheric side of the magnetopause, also affect magnetic reconnection. However, the specific role of low‐energy ions in reconnection is still an open question under active discussion. In the present work, we report in situ observations of a multiscale, multi‐type magnetopause reconnection in the presence of low‐energy ions using NASA's Magnetospheric Multiscale data on September 11, 2015. This study divides ions into cold (10–500 eV) and hot (500–30,000 eV) populations. The observations can be interpreted as a secondary reconnection dominated by electrons and cold ions (mainly in plane) located at the edge of an ion‐scale reconnection (mainly in plane). This analysis demonstrates a dominant role of cold ions in the secondary reconnection without hot ions' response. Cold ions and electrons are accelerated and heated by the secondary process. The case study provides observational evidence for the simultaneous operation of antiparallel and component reconnection. Our results imply that the pre‐accelerated and heated cold ions and electrons in the secondary reconnection may participate in the primary ion‐scale reconnection affecting the solar wind‐magnetopause coupling and the complicated magnetic field topology could affect the reconnection rate.
Periodicities and Colors of Pulsating Auroras: DSLR Camera Observations From the International Space Station
Authors: Nanjo Sota , Hozumi Yuta , Hosokawa Keisuke , Kataoka Ryuho , Miyoshi Yoshizumi , Oyama Shin‐ichiro , Ozaki Mitsunori , Shiokawa Kazuo , Kurita Satoshi 
Published: September 2021

AbstractWe investigated the spatial characteristics of pulsating auroras (PsA) using digital camera measurements from the International Space Station. These measurements covered PsAs in 5‐h wide regions in the magnetic local time (MLT) direction in short time intervals (10 min). Analyses of two events suggested that the periodicity of the main pulsation of a PsA does not exhibit any clear dependence on the magnetic latitude (63–) and MLT (00–05). These results suggest that the periods are not controlled by the bounce time of trapped electrons but by local conditions such as gradients of temperature and/or density of electrons near the magnetospheric source region. We also analyzed the colors of PsAs as proxies for the energies of precipitating electrons. The blue and green channels of the digital camera are sensitive to the band emission of molecular nitrogen ions and the green line of oxygen atoms, respectively. Because the energy bands of precipitating electrons producing those two emissions are different, ratios of blue to green (B/G ratios) can be used as proxies for the energies of PsA electrons. The B/G ratio tends to be higher in the morning sector than in the midnight sector, which is consistent with the results of previous studies showing the MLT dependence of the energies of PsA electrons. This capability of estimating the energies of auroral electrons from digital camera images is expected to provide more opportunities for citizen scientists to contribute more deeply to auroral science.
Dancing Sprites Above a Lightning Mapping Array—An Analysis of the Storm and Flash/Sprite Developments
Authors: Tomicic Maja , Soula Serge , Defer Eric , Prieur Serge , Mlynarczyk Janusz , Farges Thomas , Chanrion Olivier , Köhn Christoph , Neubert Torsten 
Published: September 2021

AbstractOne of the most enigmatic types of sprites is the dancing sprite which appears to dance above the storm as sequential luminous emissions a few 100 ms or less apart. Dancing sprites occur in relatively small proportion and many aspects of their generation remain unknown. We present a multi‐instrumental analysis of a 20‐hr duration Mesoscale Convective System (MCS) over the northwestern Mediterranean Sea on September 21, 2019, that produced 21 sprites recorded with a video camera, of which 19 (90) were dancing sprites. The asymmetric trailing stratiform MCS developed in strong convective conditions having a CAPE of 3,500 J . It formed several convective cores (up to 2,900 with cloud top temperature −C) and exhibited a bow echo structure during the sprite production period. Using Lightning Mapping Array data, we show that the sprite producing positive cloud‐to‐ground (SP + CG) flashes mainly initiated at the edge of the convective line on the side of the stratiform region. The flashes propagated 100–200 km across it, producing both positive and negative CG strokes. The 19 dancing sprite events included 49 sequences, of which 46 were associated with distinct SP + CG strokes and 3 with surges during the continuing current. An especially bright and wide sprite sequence was produced by three distinct SP + CG strokes that occurred within 3 ms and spread over 54 km. This sprite sequence could be classified as a new sprite category resembling a "wall" but structured in three groups, each associated with one of the +CG strokes.
Circling in on Convective Self‐Aggregation
Authors: Nissen Silas Boye , Haerter Jan O. 
Published: September 2021

AbstractIn radiative‐convective equilibrium simulations, convective self‐aggregation (CSA) is the spontaneous organization into segregated cloudy and cloud‐free regions. Evidence exists for how CSA is stabilized, but how it arises favorably on large domains is not settled. Using large‐eddy simulations, we link the spatial organization emerging from the interaction of cold pools (CPs) to CSA. We systematically weaken simulated rain evaporation to reduce maximal CP radii, , and find reducing causes CSA to occur earlier. We further identify a typical rain cell generation time and a minimum radius, , around a given rain cell, within which the formation of subsequent rain cells is suppressed. Incorporating and , we propose a toy model that captures how CSA arises earlier on large domains: when two CPs of radii collide, they form a new convective event. These findings imply that interactions between CPs may explain the initial stages of CSA.
Dynamic Observations of the Densification of Polar Firn Under Compression Using a Micro‐Computed Tomograph
Authors: Li Yuan , Baker Ian 
Published: September 2021

AbstractThe present work is the first to undertake systematicin situobservations of the microstructural changes on samples taken at ∼10‐m intervals along the length of a 80‐m firn core, extracted at Summit, Greenland (72°35’ N, 38°25’ W) in June, 2017, under interrupted load and at a strain rate of ∼8 × 10−5s−1at −10°C, using a X‐ray micro‐computed tomograph. Several noteworthy features of the densification were found: the ice particle size increases, while the specific surface area, the total porosity, the pore size, and the structure model index (a measure of convexity/concavity of ice surface) decreases. The results were used to formulate semi‐empirical models (valid in the stress range of ∼0.05–2.15 MPa) that can be used to quantitatively assess the relative contributions of lattice diffusion (LD) and grain boundary diffusion (GBD) to the densification of polar firn. We found that 0.28 and 2.15 MPa are two critical stresses, which represent the start and end of LD as the dominant deformation mechanism to the densification of polar firn under the interrupted increasing loads. This bimodality when LD dominates implies that stress is not the only factor governing the densification of polar firn. On the other hand, GBD dominates the densification of polar firn both for stresses lower than 0.28 MPa and greater than 2.15 MPa. At stresses greater than 2.41 MPa, the firn specimens either fractured or other deformation mechanisms dominated, e.g., grain boundary sliding or power‐law dislocation creep.
Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines
Authors: Erdogan Eren , Schmidt Michael , Goss Andreas , Görres Barbara , Seitz Florian 
Published: September 2021

AbstractMonitoring the Vertical Total Electron Content (VTEC) of the ionosphere is important for applications ranging from navigation to detection of space weather events. Therefore, emerging efforts have been made by several analysis centers to estimate the VTEC using different approaches in real‐time. Global Navigation Satellite Systems (GNSS) is a crucial technology for ionosphere modeling due to its worldwide distributed receivers, high temporal resolution, and low latency data dissemination capability. The selection of a convenient approach to extract ionosphere information from GNSS and the representation of VTEC by an appropriate mathematical model are essential factors for providing fast and accurate ionosphere products. Contrarily to the widespread phase‐leveling method, which uses noisy and erroneous code measurements, the modeling concept in this paper utilizes pure carrier‐phase measurements. Measurements acquired through the International GNSS Service (IGS) real‐time service in Radio Technical Commission for Maritime Services format are from GPS, GLONASS, and GALILEO. The measurement biases, including the ambiguity of carrier‐phase measurements, are simultaneously estimated along with VTEC model parameters. In our approach, VTEC is represented by B‐spline expansions embedded into a Kalman filter. Due to their localizing feature, B‐splines form a highly sparse structure in the filter measurement model. Thus, matrix operations for large‐scale problems can be performed fast using sparse matrix operations, as is done in this study. The differential slant total electron content (dSTEC) analysis and the comparison with Jason‐3 altimetry VTEC were performed for validation within selected periods in 2019. The dSTEC analysis shows that the quality of the generated real‐time VTEC maps slightly outperforms those provided by the other IGS analysis centers.
Distributional Regression Forests Approach to Regional Frequency Analysis With Partial Duration Series
Authors: Kiran K. G. , Srinivas V. V. 
Published: September 2021

AbstractRegional flood frequency analysis (RFFA) is widely used to quantify flood risk at ungauged and sparsely gauged locations. There are minimal attempts to use partial duration series (PDS) for RFFA, though the use of PDS instead of widely used annual maximum series (AMS) can offer some advantages. This article contributes two novel random/regression forests (RFs)‐based methodologies, namely generalized pareto distribution (GPD)‐based distributional RFs (DRFs) and multivariate RFs (MVRFs), for RFFA with PDS. The RFs facilitate modeling interactions between predictors and their complex relationships with the predictands without explicitly specifying them. The DRFs and MVRFs comprise an ensemble of corresponding regression trees, each constructed by recursive binary partitioning of the feature space into meaningful segments. The proposed DRFs account for the sampling uncertainty of PDS in the partitioning and parameter estimation. In DRFs (MVRFs), quantile estimates for an ungauged site are obtained using maximum likelihood estimates (expected values) of GPD parameters corresponding to the segments to which the site belongs. The potential of DRFs and MVRFs relative to two recently proposed techniques (univariate RFs‐based quantile regression, generalized additive model based on GPD) is demonstrated through Monte‐Carlo simulation experiments and a study on 1,031 watersheds in the United States. The key features influencing scale and shape parameters of GPD fitted to PDS of the watersheds are identified as drainage area and 24‐hr rainfall intensity corresponding to 2‐year return period, respectively. Those identified for shape parameter differ from key features known based on analysis with AMS and generalized extreme value distribution.
Do shapes have feelings? Social attribution in children with autism spectrum disorder and attention-deficit/hyperactivity disorder
Authors: Vandewouw Marlee M. , Safar Kristina , Mossad Sarah I. , Lu Julie , Lerch Jason P. , Anagnostou Evdokia , Taylor Margot J. 
Published: September 2021

AbstractTheory of mind (ToM) deficits are common in children with neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), which contribute to their social and cognitive difficulties. The social attribution task (SAT) involves geometrical shapes moving in patterns that depict social interactions and is known to recruit brain regions from the classic ToM network. To better understand ToM in ASD and ADHD children, we examined the neural correlates using the SAT and functional magnetic resonance imaging (fMRI) in a cohort of 200 children: ASD (N = 76), ADHD (N = 74) and typically developing (TD; N = 50) (4–19 years). In the scanner, participants were presented with SAT videos corresponding to social help, social threat, and random conditions. Contrasting social vs. random, the ASD compared with TD children showed atypical activation in ToM brain areas—the middle temporal and anterior cingulate gyri. In the social help vs. social threat condition, atypical activation of the bilateral middle cingulate and right supramarginal and superior temporal gyri was shared across the NDD children, with between-diagnosis differences only being observed in the right fusiform. Data-driven subgrouping identified two distinct subgroups spanning all groups that differed in both their clinical characteristics and brain–behaviour relations with ToM ability.
Lenalidomide in combination with R-CHOP produces high response rates and progression-free survival in new, untreated diffuse large B-cell lymphoma transformed from follicular lymphoma: results from the Phase 2 MC078E study
Authors: Desai Sanjal H. , LaPlant Betsy , Macon William R. , King Rebecca L. , Wang Yucai , Inwards David J. , Micallef Ivana , Johnston Patrick B. , Porrata Luis F. , Ansell Stephen M. , Habermann Thomas M. , Witzig Thomas E. , Nowakowski Grzegorz S. 
Published: September 2021

AbstractDiffuse large B-cell lymphoma (DLBCL), either concurrent with or transformed from follicular lymphoma (FL) is often excluded from clinical trials. Lenalidomide has response rates of 45% in relapsed transformed DLBCL. Herein we present an analysis of MC078E, a phase II clinical trial testing lenalidomide plus R-CHOP (R2CHOP) for patients with untreated transformed/concurrent DLBCL (NCT00670358). Adult patients with transformed or concurrent DLBCL were included. Patients received six cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone (R-CHOP) with lenalidomide 25 mg days 1–10 of each cycle. The primary outcome was progression-free survival (PFS) at 24 months. Secondary outcomes were response rates, event-free survival (EFS), and overall survival (OS). Thirty-nine patients were accrued from August 5, 2013 to July 28, 2020 and 33 were eligible by central pathology review. The median age was 64 (24–80) years, 18 (54%) were male, 25 (76%) were concurrent and 8 (24%) were transformed DLBCL. The PFS, EFS, and OS rates at 24 months were 84.4% (CI95: 67.2–94.7%), 84.5% (CI95: 72.9–98%), and 97.0% (CI95: 91.3–100%), respectively. R2CHOP is effective in concurrent and transformed DLBCL. The study supports the inclusion of anthracycline-naive transformed and concurrent DLBCL in future clinical trials of novel immunomodulatory analogues.
Human tissue cultures of lung cancer predict patient susceptibility to immune-checkpoint inhibition
Authors: Junk David , Krämer Sebastian , Broschewitz Johannes , Laura Hennig , Massa Chiara , Moulla Yousef , Hoang Ngoc Anh , Monecke Astrid , Eichfeld Uwe , Bechmann Ingo , Lordick Florian , Seliger Barbara , Kallendrusch Sonja 
Published: September 2021

AbstractDespite novel immunotherapies being approved and established for the treatment of non-small cell lung cancer (NSCLC), ex vivo models predicting individual patients’ responses to immunotherapies are missing. Especially immune modulating therapies with moderate response rates urge for biomarkers and/or assays to determine individual prediction of treatment response and investigate resistance mechanisms. Here, we describe a standardized ex vivo tissue culture model to investigate individual tumor responses. NSCLC tissue cultures preserve morphological characteristics of the baseline tumor specimen for up to 12 days ex vivo and also maintain T-cell function for up to 10 days ex vivo. A semi-automated analysis of proliferating and apoptotic tumor cells was used to evaluate tissue responses to the PD-1 inhibitor nivolumab (n = 12), from which two cases could be successfully correlated to the clinical outcome. T-cell responses upon nivolumab treatment were investigated by flow cytometry and multispectral imaging. Alterations in the frequency of the Treg population and reorganization of tumor tissues could be correlated to nivolumab responsiveness ex vivo. Thus, our findings not only demonstrate the functionality of T cells in NSCLC slice cultures up to 10 days ex vivo, but also suggests this model for stratifying patients for treatment selection and to investigate in depth the tumor-associated T-cell regulation.
Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices
Authors: Lopez-Cruz Marco , Beyene Yoseph , Gowda Manje , Crossa Jose , Pérez-Rodríguez Paulino , de los Campos Gustavo 
Published: September 2021

AbstractGenomic prediction models are often calibrated using multi-generation data. Over time, as data accumulates, training data sets become increasingly heterogeneous. Differences in allele frequency and linkage disequilibrium patterns between the training and prediction genotypes may limit prediction accuracy. This leads to the question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Previous research on training set optimization has focused on identifying a subset of the available data that is optimal for a given prediction set. However, this approach does not contemplate the possibility that different training sets may be optimal for different prediction genotypes. To address this problem, we recently introduced a sparse selection index (SSI) that identifies an optimal training set for each individual in a prediction set. Using additive genomic relationships, the SSI can provide increased accuracy relative to genomic-BLUP (GBLUP). Non-parametric genomic models using Gaussian kernels (KBLUP) have, in some cases, yielded higher prediction accuracies than standard additive models. Therefore, here we studied whether combining SSIs and kernel methods could further improve prediction accuracy when training genomic models using multi-generation data. Using four years of doubled haploid maize data from the International Maize and Wheat Improvement Center (CIMMYT), we found that when predicting grain yield the KBLUP outperformed the GBLUP, and that using SSI with additive relationships (GSSI) lead to 5–17% increases in accuracy, relative to the GBLUP. However, differences in prediction accuracy between the KBLUP and the kernel-based SSI were smaller and not always significant.
Dynamic carbon flux network of a diverse marine microbial community
Authors: Mayerhofer Marvin M , Eigemann Falk , Lackner Carsten , Hoffmann Jutta , Hellweger Ferdi L 
Published: September 2021

Abstract
The functioning of microbial ecosystems has important consequences from global climate to human health, but quantitative mechanistic understanding remains elusive. The components of microbial ecosystems can now be observed at high resolution, but interactions still have to be inferred e.g., a time-series may show a bloom of bacteria X followed by virus Y suggesting they interact. Existing inference approaches are mostly empirical, like correlation networks, which are not mechanistically constrained and do not provide quantitative mass fluxes, and thus have limited utility. We developed an inference method, where a mechanistic model with hundreds of species and thousands of parameters is calibrated to time series data. The large scale, nonlinearity and feedbacks pose a challenging optimization problem, which is overcome using a novel procedure that mimics natural speciation or diversification e.g., stepwise increase of bacteria species. The method allows for curation using species-level information from e.g., physiological experiments or genome sequences. The product is a mass-balancing, mechanistically-constrained, quantitative representation of the ecosystem. We apply the method to characterize phytoplankton—heterotrophic bacteria interactions via dissolved organic matter in a marine system. The resulting model predicts quantitative fluxes for each interaction and time point (e.g., 0.16 µmolC/L/d of chrysolaminarin to Polaribacter on April 16, 2009). At the system level, the flux network shows a strong correlation between the abundance of bacteria species and their carbon flux during blooms, with copiotrophs being relatively more important than oligotrophs. However, oligotrophs, like SAR11, are unexpectedly high carbon processors for weeks into blooms, due to their higher biomass. The fraction of exudates (vs. grazing/death products) in the DOM pool decreases during blooms, and they are preferentially consumed by oligotrophs. In addition, functional similarity of phytoplankton i.e., what they produce, decouples their association with heterotrophs. The methodology is applicable to other microbial ecosystems, like human microbiome or wastewater treatment plants.