bluuebunny/crossref_metadata_2025_split huggingface dataset:
Can Gauss‐Newton Algorithms Outperform Stochastic Optimization Algorithms When Calibrating a Highly Parameterized Hydrological Model? A Case Study Using SWAT
Authors: Qin Youwei , Kavetski Dmitri , Kuczera George , McInerney David , Yang Tao , Guo Yuan 
Published: September 2022

AbstractThe calibration of highly parameterized hydrological models is a major computational challenge, especially for models with long run times. This challenge motivates the reconsideration of gradient‐based algorithms often overlooked for their perceived lack of robustness. Our study evaluates two Gauss‐Newton algorithms, robust Gauss‐Newton (RGN), and Levenberg‐Marquardt (PEST), and two stochastic algorithms, Shuffled Complex Evolution (SCE), and Dynamically Dimensioned Search (DDS), on a 38‐parameter SWAT model calibration problem. Algorithm performance is comprehensively assessed using trajectory plots from 100 invocations and by analyzing the distribution of estimated optima at fixed budgets of 200, 500, 1,000, 2,000, 3,000, and 5,000 objective function evaluations (model runs). Empirical results indicate that: (a) Gauss‐Newton algorithms are more likely than stochastic algorithms to locate good solutions for the budgets considered in this work, and more likely to locate satisfactory solutions when budget is tight (200–500 model runs) and (b) RGN shows the fastest initial convergence amongst the algorithms under consideration and has the highest chance of finding satisfactory solutions when the budget is tight. The results indicate that Gauss‐Newton algorithms offer an attractive choice for the calibration of highly parameterized hydrological models.
Imaging the Absorbing Feeding and Eruptive Pathways of Deception Island, Antarctica
Authors: Guardo R. , De Siena L. , Prudencio J. , Ventura G. 
Published: September 2022

AbstractDeception Island is one of the most active and best‐documented volcanoes in Antarctica. Since its last eruption in 1970, several geophysical surveys have targeted reconstructing its magmatic systems. However, geophysics fails to reconstruct the pathways magma and fluids follow from depth to erupt at the surface. Here, novel data selection strategies and multi‐frequency absorption inversions have been framed in a Geographical Information System, using all available geological (vents and faults distribution), geochemical and geophysical knowledge of the volcano. The result is the detection of these eruptive pathways. The model offers the first image of the magma and associated fluids pathways feed the 1967, 1969, and 1970 eruptions. Results suggest that future ascending paths might lead to active research bases and zones of planned helicopter rescue. The connection between seismic absorption, temperature, and fluid content makes it a promising attribute for detecting and monitoring eruptions at active calderas.
Recognizing the Role of Tropical Seaways in Modulating the Pacific Circulation
Authors: Tan N. , Zhang Z. S. , Guo Z. T. , Guo C. C. , Zhang Z. J. , He Z. L. , Ramstein G. 
Published: September 2022

AbstractVarious modeling studies have examined the climatic effects of either the Central American Seaway or the Indonesian seaway. The co‐existence of these two tropical seaways may have a greater influence than the existence of a single seaway. Although the dual seaway situation is closer to that reconstructed during Miocene/Pliocene, relevant studies remain scarce. Here, we investigate the co‐effects of dual tropical seaway changes on the Pacific circulation through a set of sensitivity experiments. Our results show that the combined shallow opening of tropical seaways can generate an active Pacific meridional overturning circulation and maintain strong upwelling conditions along the equatorial Pacific, which may have helped favor a “biogenic bloom” during the late Miocene and early Pliocene. Moreover, the logically successive closure of the tropical seaways can provide patterns of zonal sea surface temperature gradients that are similar to those recorded in the equatorial Pacific from the late Miocene to the Pliocene.
Energy Flux Through the Magnetopause During Flux Transfer Events in Hybrid‐Vlasov 2D Simulations
Authors: Ala‐Lahti Matti , Pulkkinen Tuija I. , Pfau‐Kempf Yann , Grandin Maxime , Palmroth Minna 
Published: September 2022

AbstractSolar wind—magnetosphere coupling drives magnetospheric dynamic phenomena by enabling energy exchange between magnetospheric and solar wind plasmas. In this study, we examine two‐dimensional noon‐midnight meridional plane simulation runs of the global hybrid‐Vlasov code Vlasiator with southward interplanetary magnetic field driving. We compute the energy flux, which consists of the Poynting flux and hydrodynamic energy flux components, through the Earth's magnetopause during flux transfer events (FTEs). The results demonstrate the spatiotemporal variations of the energy flux along the magnetopause during an FTE, associating the FTE leading (trailing) edge with an energy injection into (escape from) the magnetosphere on the dayside. Furthermore, FTEs traveling along the magnetopause transport energy to the nightside magnetosphere. We identify the tail lobes as a primary entry region for solar wind energy into the magnetosphere, consistent with results from global magnetohydrodynamic simulations and observations.
Relating a Large‐Scale Variation of Waves in the Indian Ocean to the IOD
Authors: Li Rui , Wu Kejian , Li Jingkai , Dong Xianghui , Sun Jian , Zhang Wenqing , Liu Qingxiang 
Published: September 2022

AbstractThis study used the ERA‐5 40‐year reanalysis data set from the European Centre for Medium‐Range Weather Forecasts to analyze the spatial characteristics of wind waves and swells in the Indian Ocean. Although swells from the Southern Ocean can propagate into the Bay of Bengal, the zonal surface Stokes drift has been shown to correlate well with wind waves. Investigation of the relationship between the Indian Ocean Dipole (IOD) and the surface Stokes drift revealed strong correlation in the tropical Indian Ocean. The surface Stokes drift plays a positive role in maintaining sea surface temperature stability by transporting more (less) abnormally cold water during periods of positive (negative) IOD events. The depth‐integrated wave transport is quantified by the spectra and bulk parameters, respectively. Although two methods provide estimates of the same order of magnitude, the transport value is larger when wave spectra are used. With this approach, the estimated wave transport is comparable to the Ekman transport and its zonal component is even greater for more than 80% of the sea areas in the Indian Ocean; thus, it would have substantial effect on sea surface temperature. This paper proposes a new idea for studying this climatic phenomenon by considering the large‐scale wave effect, which builds a bridge for energy transport between the eastern and western boundaries of the Indian Ocean.
Positive and Negative Surface Feedback and Atmospheric Control of Land Surface Conditions on Convective Organization Over the Tibetan Plateau
Authors: Yang Chenyi , Ma Yaoming , Yuan Yuan , Zuo Hongchao 
Published: September 2022

AbstractThe dependence of the feedback signal on atmospheric conditions is still poorly understood and may lead to an underestimation of feedback strength due to opposite responses of precipitation to soil moisture. Based on data from observation stations on the Tibetan Plateau and from satellites, this study evaluated the response of convective clouds to the change of evaporation fraction (EF) and analyzed how surface conditions affect the initiation and development of convection in different coupling regimes. After considering coupling regimes classified by the tropospheric state, the afternoon convective cloud showed a strong response to EF, which is negative feedback in the dry coupling regime and positive feedback in the wet coupling regime. Organized deep convection defined by both the cloud properties and the afternoon precipitation displayed this phenomenon. This shows that the lack of a strong response of convection to EF is due to the dependence of this response on the coupling regime, rather than on the method of defining convection. We also found that the difference in surface heat flux between the two regimes is more significant in the afternoon, while the difference of meteorological elements is most significant before noon. These results provide support for the use of ground‐based meteorological data to determine coupling regimes. We also used a regression tree to decompose the effects of coupling regimes and EF into basic near‐surface meteorological elements, the results of which provide support for some of our conclusions.
Intermediate‐Volatility Organic Compounds Observed in a Coastal Megacity: Importance of Non‐Road Source Emissions
Authors: Fang Hua , Huang Xiaoqing , Xiao Shaoxuan , Lowther Scott , Fu Xuewei , Zhang Yanli , Wu Ting , Hu Weiwei , Zhang Guohua , Ding Xiang , Tang Mingjin , Bi Xinhui , Jones Kevin C. , Wang Xinming 
Published: September 2022

AbstractIntermediate‐volatility organic compounds (IVOCs) are among the most important precursors to secondary organic aerosol (SOA), yet their sources and contributions to SOA in ambient air are poorly constrained. In this study, IVOCs were collected with sorption tubes in a coastal city in southern China during September–October 2019 and were analyzed by gas chromatography‐mass selective detector after thermo‐desorption. The measured average concentration of IVOCs was 25.0 ± 0.95 μg m−3 (mean ± 95% C.I.), and residual unresolved complex mixtures shared 79.8% ± 1.91% of IVOCs. The estimated SOA production, even only from speciated IVOCs and unspeciated branch‐alkane IVOCs, reached 2.44 ± 1.46 μg m−3, approximately five times that from VOCs during the photochemically active period (12:00–15:00 local time). Based on the positive matrix factorization model with a photochemical‐age‐based parameterization, diesel‐related emission was the largest contributor (46.6%) of IVOCs, followed by ship emission (23.0%), gasoline exhaust (16.8%), and biomass/coal burning (13.6%). Non‐road diesel engines accounted for a dominant part in diesel‐related emission. Ship emission was found to contribute SOA formation potentials (SOAFPs) comparable to that of diesel‐related emission, while biomass/coal burning showed higher SOAFPs than gasoline exhaust. Our results revealed that non‐road sources, such as ship emission, non‐road diesel engines, and biomass/coal burning contributed substantially to IVOCs, and will be of greater importance in producing ambient SOA with the increasingly stringent control on emissions from on‐road vehicles.
A Comprehensive Model for Pickup Ion Formation at the Moon
Authors: Poppe A. R. , Halekas J. S. , Harada Y. 
Published: September 2022

AbstractThe lunar exosphere is an ensemble of multiple overlapping, noninteracting neutral distributions that reflect the primary physical processes acting on the lunar surface. While previous observations have detected and constrained the behavior of some species, many others have only circumstantial evidence or theoretical modeling suggesting their presence. Many species are so tenuous as to be unobservable by direct neutral sampling, yet in comparison, measurements in their ionized form provide a particularly sensitive method of detection. To better aid the interpretation of past measurements and planning of future observations, we present a model for the production of lunar pickup ions from the Moon consisting of two components: An analytic model for the distributions of 18 neutral species produced by various mechanisms and an analytic model for the ionization and subsequent acceleration of 20 exospheric and surface‐sputtered pickup ion species. The dominant lunar pickup ions in the model are , He+, CO+, 40Ar+, Al+, Na+, K+, Si+, Ca+, and O+ with an asymmetric distribution favoring the positive interplanetary electric field hemisphere of the Moon. We compare the model predictions to statistically averaged pickup ion fluxes around the Moon as observed by the ARTEMIS spacecraft over the past decade. By filtering for interplanetary electric field‐aligned, high‐energy observations, we find that the pickup ion model lacks an additional source of heavy species. We suggest that a dense CO2 exosphere of 3 × 104 − 1 × 105 cm−3 could account for the missing pickup ion flux as part of the recycling of solar wind carbon ions incident to the Moon.
Hydrodynamic Simulations of Millimeter‐Scale Cambrian Sedentary Medusozoans
Authors: Liu Ping , Zhang Yiheng , Yang Xiaoguang , Wang Bin , Zhang Tao , Sun Jie , Tang Qingqin , He Kaiyue , Hao Wenjing , Yue Ning , He Xiaowei , Han Jian 
Published: September 2022

AbstractModern medusae are primarily macroscopic, free‐swimming marine organisms with a tetraradial symmetry. But the early Cambrian medusozoans, such as biradial Hexaconularia sichuanensis and tetraradial Quadrapyrgites quadratacris from the basal Cambrian Kuanchuanpu Formation in South China, were millimeter‐scale and sedentary forms. Although well‐documented as common components in a shelf environment, little is known about their in situ life conditions since they are easily transported by tidal flow before burial. Specifically, the interactions between their exoskeleton shapes and the hydrodynamic conditions are poorly known. Here we use fluid–structure interaction computational fluid dynamics to analyze the functional performance of the two taxa using 3D mesh models constructed from scanned fossils. The simulation experiments reveal that: (a) due to their millimeter‐scale size, most sedentary small shelly fossils (SSFs), including those of medusozoans lived within the viscous sublayer range of tidal flow; (b) the biradial symmetry of Hexaconularia was more structurally stable than the tetraradial symmetry of Quadrapyrgites; (c) different orientations of Hexaconularia, relative to the water flow, resulted in different force distributions on the surface. This research provides quantitative data of the hydrodynamic conditions of SSFs in shelf environments and critical insights into the biotic replacement of the early Cambrian benthic medusozoan community.
Drivers of Phytoplankton Variability in and Near the Pearl River Estuary, South China Sea During Typhoon Hato (2017): A Numerical Study
Authors: Feng Yang , Huang Jingwen , Du Yan , Balaguru Karthik , Ma Weiwei , Feng Qingyu , Wan Xiuquan , Zheng Youchang , Guo Xianghui , Cai Shuqun 
Published: September 2022

AbstractThe Pearl River Estuary and adjacent seas in South China Sea are frequently affected by tropical cyclones (TCs). Previous in situ and remote sensing studies have found that typhoons can enhance phytoplankton biomass and induce blooms in this region. However, the mechanistic links between phytoplankton blooms and typhoons have not been well understood due to the interplay of multiple complex processes along the land‐ocean‐atmosphere interface. Here, we constructed an integrated modeling system with the marine ecosystem and sediment components for the China Great Bay Area. By using the integrated modeling system, we quantitatively investigated the phytoplankton response to hydrological conditions variations under Typhoon Hato (2017), a strong typhoon case. Passive tracer experiments showed that with high river discharge induced by heavy rainfall, the residence time within Lingding Bay is as short as 15 days, less than half of that under the climatological discharge. The increase in freshwater pulse washes out the phytoplankton biomass within Lingding Bay. While for the offshore region, the analysis of various source and sink terms for the offshore region's post‐typhoon response showed that the increase of phytoplankton biomass in the first week was because of the uplift of nutrient‐rich subsurface water, while in the second week, it was due to the seaward propagation of nearshore high phytoplankton biomass water. While riverine nutrients support phytoplankton growth in the third week, a large part of phytoplankton biomass was lost to zooplankton grazing, showing the system shifted from the bottom‐up control to the top‐down control.
Energetic Electron Flux Predictions in the Near‐Earth Plasma Sheet From Solar Wind Driving
Authors: Swiger B. M. , Liemohn M. W. , Ganushkina N. Y. , Dubyagin S. V. 
Published: September 2022

AbstractSuprathermal electrons in the near‐Earth plasma sheet are important for inner magnetosphere considerations. They are the source population for outer radiation belt electrons and they pose risks to geosynchronous satellites through their contribution to surface charging. We use empirical modeling to address relationships between solar driving parameters and plasma sheet electron flux. Using Time History of Events and Macroscale Interactions during Substorms, OMNI, and Flare Irradiance Spectral Model Version 2 data, we develop a neural network model to predict differential electron flux from 0.08 to 93 keV in the plasma sheet, at distances from 6 to 12 RE. Driving parameters include solar wind (SW) density and speed, interplanetary magnetic field (IMF) BZ and BY, solar extreme ultraviolet flux, IMF BZ ultra‐low frequency (ULF) wave power, SW‐magnetosphere coupling functions Pα1 and NXCF, and the 4‐hr time history of these parameters. Our model predicts overall plasma sheet electron flux variations with correlation coefficients of between 0.59 and 0.77, and median symmetric accuracy in the 41%–140% range (depending on energy). We find that short time‐scale electron flux variations are not reproduced using short time‐scale inputs. Using a recently published technique to extract information from neural networks, we determine the most important drivers impacting model prediction are VSW, VBS, and IMF BZ. SW‐magnetosphere coupling functions that include IMF clock angle, IMF BZ ULF wave power, and IMF BY have little impact in our model of electron flux in the near‐Earth plasma sheet. The new model, built directly on differential flux, outperforms an existing model that derives fluxes from plasma moments, with the performance improvement increasing with increasing energy.
Using Mutual Information for Global Sensitivity Analysis on Watershed Modeling
Authors: Jiang Peishi , Son Kyongho , Mudunuru Maruti K. , Chen Xingyuan 
Published: September 2022

AbstractGlobal sensitivity analysis (GSA) often is applied to assess the sensitivity of model outputs to their inputs using ensemble simulations. However, increasing model complexity and the associated computational cost have limited the use of most GSA approaches for process‐based watershed models. We propose to use mutual information (MI) as a computationally efficient GSA method for watershed modeling. Such MI computed from several hundred realizations usually can capture nonlinear relationships between inputs and outputs of interest. We perform MI‐based watershed sensitivity analyses in studies of the Portage River Watershed in Ohio and the American River Watershed in Washington. In these studies, MI is used to evaluate the sensitivity of river discharges simulated by the Soil and Water Assessment Tool to no less than 20 SWAT parameters for each watershed. Our MI‐based sensitivity analyses achieved convergence with about 300–500 realizations, a small fraction of the ensemble size (i.e., several thousands) required by the Sobol method. Nevertheless, the two‐dimensional MI yields similar sensitivity ranking compared to Sobol's total‐order sensitivity indices, especially for sensitive parameters. Our study thus sheds new light on the use of MI as an affordable GSA method for computationally intensive models such as the hyperresolution, watershed hydrobiogeochemical models.
Machine-learning algorithms for asthma, COPD, and lung cancer risk assessment using circulating microbial extracellular vesicle data and their application to assess dietary effects
Authors: McDowell Andrea , Kang Juwon , Yang Jinho , Jung Jihee , Oh Yeon-Mok , Kym Sung-Min , Shin Tae-Seop , Kim Tae-Bum , Jee Young-Koo , Kim Yoon-Keun 
Published: September 2022

AbstractAlthough mounting evidence suggests that the microbiome has a tremendous influence on intractable disease, the relationship between circulating microbial extracellular vesicles (EVs) and respiratory disease remains unexplored. Here, we developed predictive diagnostic models for COPD, asthma, and lung cancer by applying machine learning to microbial EV metagenomes isolated from patient serum and coded by their accumulated taxonomic hierarchy. All models demonstrated high predictive strength with mean AUC values ranging from 0.93 to 0.99 with various important features at the genus and phylum levels. Application of the clinical models in mice showed that various foods reduced high-fat diet-associated asthma and lung cancer risk, while COPD was minimally affected. In conclusion, this study offers a novel methodology for respiratory disease prediction and highlights the utility of serum microbial EVs as data-rich features for noninvasive diagnosis.
Parsing genetically influenced risk pathways: genetic loci impact problematic alcohol use via externalizing and specific risk
Authors: Barr Peter B. , Mallard Travis T. , Sanchez-Roige Sandra , Poore Holly E. , Linnér Richard Karlsson ,   COGA Collaborators, Porjesz Bernice , Hesselbrock Victor , Foroud Tatiana , Agrawal Arpana , Dick Danielle , Edenberg Howard J. , Nurrnberger John , Liu Yunlong , Kuperman Samuel , Kramer John , Meyers Jacquelyn , Kamarajan Chella , Pandey Ashwini , Bierut Laura , Rice John , Bucholz Kathleen , Schuckit Marc , Tischfield Jay , Hart Ronald , Salvatore Jessica , Almasy Laura , Goate Alison , Kapoor Manav , Slesinger Paul , Scott Denise , Bauer Lance , Wetherill Leah , Xuei Xiaolong , Lai Dongbing , O’Connor Sean , Plawecki Martin , Acion Laura , Chan Grace , Chorlian David B. , Zhang Jian , Kinreich Sivan , Pandey Gayathri , Chao Michael , Anokhin Andrey , McCutcheon Vivia , Saccone Scott , Aliev Fazil , Chin Hemin , Parsian Abbas , Waldman Irwin D. , Palmer Abraham A. , Harden K. Paige , Dick Danielle M. 
Published: September 2022

AbstractGenome-wide association studies (GWAS) identify genetic variants associated with a trait, regardless of how those variants are associated with the outcome. Characterizing whether variants for psychiatric outcomes operate via specific versus general pathways provides more informative measures of genetic risk. In the current analysis, we used multivariate GWAS to tease apart variants associated with problematic alcohol use (ALCP-total) through either a shared risk for externalizing (EXT) or a problematic alcohol use-specific risk (ALCP-specific). SNPs associated with ALCP-specific were primarily related to alcohol metabolism. Genetic correlations showed ALCP-specific was predominantly associated with alcohol use and other forms of psychopathology, but not other forms of substance use. Polygenic scores for ALCP-total were associated with multiple forms of substance use, but polygenic scores for ALCP-specific were only associated with alcohol phenotypes. Polygenic scores for both ALCP-specific and EXT show different patterns of associations with alcohol misuse across development. Our results demonstrate that focusing on both shared and specific risk can better characterize pathways of risk for substance use disorders. Parsing risk pathways will become increasingly relevant as genetic information is incorporated into clinical practice.