bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three times lucky: in dialogue with Rein Müllerson
Authors: Menéndez Agustín José , Müllerson Rein 
Published: August 2022

AbstractThe publication in 2017 of Dawn of a New World (I B Tauris) confirmed Rein Müllerson as one of the great international lawyers of his generation. His career is deeply marked by the recent history of Europe. He was a young director of the Department of International Law of the Academy of Sciences of Moscow in the 1980s, doubling down as legal advisor to Gorbachev during the decisive years of perestroika and glasnost. It is not an exaggeration to say that, in those hectic days, Müllerson saw history unfolding from the machine room of the Kremlin. In the 1990s, after a brief but very intense period as secretary of state of the newborn Estonian Republic, Müllerson joined academia again as professor of international law at the LSE first, then at King’s College. His inexhaustible stamina allowed him to wear a second hat as adviser on human rights to the United Nations, spending quite some time in Central Asia. After his retirement from King’s College, he returned in the 2010s to Tallinn as dean of the newly established School of Governance. The following text is the result of a number of conversations, some in Tallinn, others forced by circumstances through video connection. The range of issues is as wide as Müllerson’s interests, hopefully offering the reader views which are out of the common road. Not only because of the multiplicity of perspectives he is privy to, thanks to his extremely rich academic and personal trajectory, but also because of his commitment to diversity and pluralism.
Ecology and effects of metazoan parasites of fish in transitional waters
Authors: Giari Luisa , Castaldelli Giuseppe , Timi Juan Tomás 
Published: August 2022

AbstractGiven the abundance, heterogeneity and ubiquity of parasitic organisms, understanding how they influence biodiversity, evolution, health and ecosystem functionality is crucial, especially currently when anthropogenic pressures are altering host–parasite balances. This review describes the features, roles and impacts of metazoan parasites of fish occurring in transitional waters (TW). These aquatic ecosystems are highly productive and widespread around the globe and represent most favourable theatres for parasitism given the availability of hosts (invertebrates, fishes and birds) and an increased probability of parasite transmission, especially of those having complex life cycles. Fascinating examples of how parasitism can influence different hierarchical levels of biological systems, from host individuals and populations to entire aquatic communities, through effects on food webs come from this kind of ecosystem. Edible fish of commercial value found in TW can harbour some parasite species, significantly reducing host health, marketability and food safety, with possible economic and public health consequences. Many TW are historically exploited by humans as sources of relevant ecosystem services, including fisheries and aquaculture, and they are highly vulnerable ecosystems. Alteration of TW can be revealed through the study of parasite communities, contributing, as bioindicators, for assessing environmental changes, health and restoration. Fish parasites can provide much information about TW, but this potential appears to be not fully exploited. More studies are necessary to quantify the ecological, economic and medical impacts fish parasites can have on these important ecosystems.
Spatiotemporal Distributions and Source Apportionment of PM2.5‐Bound Antimony in Beijing, China
Authors: Yang Chenmeng , Wu Yunjie , Zhang Leiming , Sun Guangyi , Yao Heng , Li Zhonggen , Bi Xiangyang , Huang Qiang , Feng Xinbin 
Published: August 2022

AbstractAntimony (Sb) is a toxic heavy metal, and PM2.5‐bound Sb (SbPM2.5) in the air impacts human health via inhalation pathways. In this study, we analyzed multiyear measurements of ambient SbPM2.5 in Beijing to characterize its spatiotemporal distributions, identify main sources, and predict future trends. The results show that ambient SbPM2.5 has been decreasing with fluctuations from 2005 to 2012 and decreased rapidly after 2013, which was likely a result of the government's enhanced air pollution control plan that targeted main sources of industrial Sb. Across the city, average SbPM2.5 concentrations were relatively higher at nonemission locomotive traffic sampling sites and in densely populated areas (9.45–19.45 ng/m3) and lower in background areas (0.6–0.9 ng/m3). Regional‐scale emissions and local human activities both affected the spatial distributions of SbPM2.5. Notably, SbPM2.5 concentration increased by 58.3% from 2006 to 2013 in one suburban background area, indicating the changing emission distributions and intensities over the study period. A neural network model was developed and tested to predict future SbPM2.5 levels, results from which showed that with simulated massive reductions in coal supplies and a rapid boom in the waste incineration industry, SbPM2.5 concentration would vary in a smaller range (from 4.08 to 4.38 ng/m3) over the next decade as compared to the observed range during 2011–2018 (19.0–5.44 ng/m3). The impact of the continued expansion of the waste incineration industry on SbPM2.5 pollution needs to be considered in future emission control policies.
Incorporating Uncertainty Into a Regression Neural Network Enables Identification of Decadal State‐Dependent Predictability in CESM2
Authors: Gordon Emily M. , Barnes Elizabeth A. 
Published: August 2022

AbstractPredictable internal climate variability on decadal timescales (2–10 years) is associated with large‐scale oceanic processes, however these predictable signals may be masked by the noisy climate system. One approach to overcoming this problem is investigating state‐dependent predictability—how differences in prediction skill depend on the initial state of the system. We present a machine learning approach to identify state‐dependent predictability on decadal timescales in the Community Earth System Model version 2 pre‐industrial control simulation by incorporating uncertainty estimates into a regression neural network. We leverage the network's prediction of uncertainty to examine state dependent predictability in sea surface temperatures by focusing on predictions with the lowest uncertainty outputs. In particular, we study two regions of the global ocean—the North Atlantic and North Pacific—and find that skillful initial states identified by the neural network correspond to particular phases of Atlantic multi‐decadal variability and the interdecadal Pacific oscillation.
Revisiting the 1959 Hebgen Lake Earthquake Using Optical Image Correlation; New Constraints on Near‐Field 3D Ground Displacement
Authors: Andreuttiova Lucia , Hollingsworth James , Vermeesch Pieter , Mitchell Thomas M. , Bergman Eric 
Published: August 2022

AbstractNear‐field surface displacement measurements allow us to quantify the on‐ and off‐fault proportion of earthquake‐related deformation. The Hebgen Lake earthquake was a large normal event with a complex surface rupture, which broke across mountainous terrain. This study takes advantage of high‐resolution historical aerial stereo‐imagery to measure three‐dimensional displacement from correlation of the orthorectified pre‐ and post‐earthquake image mosaics. The results reveal new strike‐slip ruptures which are possibly associated with the aftershocks from 18th August 1959. These structures likely reflect internal block deformation induced by the complex geometry of the mainshock. Additionally, comparison of our results with the existing displacement data shows that the optical image correlation‐derived offsets often exceed the field measurements by >50%. We attribute this difference to inelastic off‐fault deformation.
Autocyclic Secondary Channels Stabilize Deltaic Islands Undergoing Relative Sea Level Rise
Authors: Salter Gerard , Lamb Michael P. 
Published: August 2022

AbstractUnderstanding what sets the size and stability of deltaic islands is critical for predicting how deltas will respond to sea level rise. Models of overbank sedimentation produce an exponentially decaying sedimentation profile, seemingly incompatible with island stability, which requires uniform sedimentation balancing sea level rise. However, secondary channels provide a mechanism for delivering sediment deeper into island interiors, potentially stabilizing islands. Using a 1D morphodynamic model, we found that autogenic secondary channels allow islands or parts of islands to maintain a stable profile dynamically through cycles of channel incision and aggradation. However, when islands are too large, secondary channels grow to become stable, primary channels, thereby bisecting the island, resulting in smaller, stable islands with more connectivity to the channel network. Rather than passively drowning, our results indicate that deltaic islands can respond to sea level rise through morphodynamic feedbacks that act to enhance island accretion.
Single‐Crystal Elasticity of Antigorite at High Pressures and Seismic Detection of Serpentinized Slabs
Authors: Satta Niccolò , Grafulha Morales Luiz Fernando , Criniti Giacomo , Kurnosov Alexander , Boffa Ballaran Tiziana , Speziale Sergio , Marquardt Katharina , Capitani Gian Carlo , Marquardt Hauke 
Published: August 2022

AbstractThe subduction of serpentinized slabs is the dominant process to transport “water” into Earth's mantle, and plays a pivotal role for subduction dynamics. Antigorite, the most abundant serpentine mineral in subduction settings, may imprint a seismic signature on serpentinized slabs, making them seismically distinguishable from the dry, non‐serpentinized ones. However, the complete single‐crystal elasticity of antigorite has not been experimentally constrained at high pressures, hindering the use of seismological approaches to detect serpentinization in subducting slabs. Here, we report the full elastic stiffness tensor of antigorite by single‐crystal Brillouin spectroscopy and X‐ray diffraction up to 7.71(5) GPa. We use our results to model seismic properties of antigorite‐bearing rocks and show that their seismological detectability depends on the geometrical relation between seismic wave paths and foliation of serpentinized rocks. In particular, we demonstrate that seismic shear anisotropy shows low sensitivity to serpentinization for a range of relevant geometries.
Global Spectrum of Vegetation Light‐Use Efficiency
Authors: He Mingzhu , Chen Shaoyuan , Lian Xu , Wang Xuhui , Peñuelas Josep , Piao Shilong 
Published: August 2022

AbstractVegetation light‐use efficiency (LUE) is a critical parameter of vegetation photosynthesis, but its global variations and the drivers remain poorly understood. Here, we used data from 172 flux tower sites to characterize the global distribution of ecosystem‐level LUE spanning various vegetation and climate. The global growing season average LUE was 1.30 ± 0.55 g C MJ−1 for 2000–2014. The main factors driving LUE variations included environmental conditions (e.g., temperature), plant traits (e.g., foliar nitrogen concentration and isohydricity) and their interactions, which together accounted for about 76% of the observed global variations in LUE. However, an ensemble of 11 dynamic global vegetation models largely underestimated LUE, and hardly captured the key drivers. Our results highlight that a paradigm shift from vegetation functional type‐based scheme to trait‐climate spectrum‐based scheme is necessary for the next‐generation models to accurately simulate the response of vegetation carbon uptake to climate change.
Explosive Eruption of the Tonga Underwater Volcano Modulates the Ionospheric E‐Region Current on 15 January 2022
Authors: Sun Yang‐Yi , Chen Chieh‐Hung , Zhang Pengyu , Li Sheng , Xu Hui‐Ru , Yu Tao , Lin Kai , Mao Zhiqiang , Zhang Dixin , Lin Chi‐Yen , Liu Jann‐Yenq 
Published: August 2022

AbstractThe sudden eruption of the Tonga underwater volcano (20.53°S, 175.38°W) on 15 January 2022 generated explosions that triggered blast waves traveling away from the eruption. In this study, the analysis of the geomagnetic field observations on the ground shows that the eruption perturbed the E‐region current density by 22–55 mA/m within a radius of 8,000 km away from the eruption. The perturbation evolved into large scales of ∼5 hr and thousands of kilometers as it traveled away. The traveling speed of the leading front is ∼740 m/s that is near acoustic in the ionosphere. The magnetic fields and total electron content observations suggest that the dynamics changes further induced significant ionospheric disturbances that lasted ∼10 hr after the eruption. The examination of the Tonga volcanic eruption inspires us that a near‐surface perturbation can change the dynamics of the upper atmosphere.
First Synoptic Images of FUV Discrete Aurora and Discovery of Sinuous Aurora at Mars by EMM EMUS
Authors: Lillis Robert J. , Deighan Justin , Brain David , Fillingim Matthew , Jain Sonal , Chaffin Michael , England Scott , Holsclaw Greg , Chirakkil Krishnaprasad , Al Matroushi Hessa , Lootah Fatma , Al Mazmi Hoor , Thiemann Ed , Eparvier Frank , Schneider Nick , Curry Shannon 
Published: August 2022

AbstractWe present the first measurements of Mars discrete aurora in the extreme ultraviolet (<110 nm) and the first synoptic aurora images in the far ultraviolet (110–180 nm). Auroral emission is detected in >75% of nightside images, with patterns shifting visibly over 15–20 min. Aurora is observed most frequently in regions of open magnetic topology (where crustal magnetic fields are very weak and/or vertical), with the brightest aurora where crustal fields are strongest. We present the first disk‐averaged spectrum of discrete aurora, with several O, C, and CO features as expected for electron impact primarily on CO2. We categorize discrete auroral morphology into three types: crustal field aurora, non‐crustal field patchy aurora, and a new type we call “sinuous” aurora, an elongated serpentine structure that stretches thousands of kilometers into the nightside from near midnight in the northern hemisphere. These observations point to a highly dynamic environment in Mars' magnetotail.
Isotopic Evidence That Alkyl Nitrates Are Important to Aerosol Nitrate Formation in the Equatorial Pacific
Authors: Joyce Emily E. , Balint Sawyer J. , Hastings Meredith G. 
Published: August 2022

AbstractConcentrations and the stable isotopic composition of bulk aerosol nitrate (NO3−) were quantified from two GEOTRACES cruises: (a) Alaska–Tahiti (GP15; n = 22) and (b) Peru–Tahiti (GP16; n = 17) to explore the hypothesis that a marine source influences aerosol NO3− in the equatorial Pacific. The δ15N‐NO3− ranged from −14.5‰–0.5‰, with lowest values furthest from the coast, primarily reflecting a shift in sources. The δ18O‐ and Δ17O‐NO3− were both relatively high (65.2‰–85.4‰ and 21.4‰–30.7‰, respectively) and decreased away from continental regions, reflecting a shift in the oxidants that influence the formation of NO3−. Transport modeling and co‐occurrence of low δ15N, δ18O and Δ17O provided evidence for an important influence of marine‐derived alkyl nitrates (RONO2) on aerosol NO3− formation. Based on the Δ17O, we quantified that the contribution of RONO2 to aerosol NO3− can be as high as 47.5% (range 7.5%–47.5%). We also estimate an average δ15N‐RONO2 of −27.8‰ ± 23.3‰.
A Rotation Procedure to Improve Seasonally Varying Empirical Orthogonal Function Bases for MJO Indices
Authors: Weidman Sarah , Kleiner Ned , Kuang Zhiming 
Published: August 2022

AbstractVarious indices have been defined to characterize the phase and amplitude of the Madden‐Julian oscillation (MJO). One widely used index is the outgoing longwave radiation (OLR) based MJO index (OMI), which is calculated using the spatial pattern of 30–96‐day eastward‐filtered OLR. The empirical orthogonal functions (EOFs) used to calculate the OMI in observations are prone to degeneracy and exhibit oscillations on the order of 10–20 days, despite initial filtering of the OLR. We propose a simple modification to the OMI that involves aligning the EOFs between neighboring days while retaining the spatial pattern described by the EOFs. This rotation method is implemented as a postprocessing procedure of the current OMI calculation and cleanly removes the spurious oscillations and degeneracy issues seen in the standard method. A similar rotation procedure can be implemented in calculations of other MJO indices.
Carbon Isotopic Constraints on Basin‐Scale Vertical and Lateral Particulate Organic Carbon Dynamics in the Northern South China Sea
Authors: Zhang Jingjing , Li Hongliang , Wiesner Martin G. , Eglinton Timothy I. , Haghipour Negar , Jian Zhimin , Chen Jianfang 
Published: August 2022

AbstractLateral particle transport in shelf/slope settings of marginal sea systems may potentially supply allochthonous particulate organic carbon (POC) to the ocean interior. The magnitude and prevalence of such processes has implications for our understanding of the functioning and efficiency of modern biological carbon pump processes, as well as for interpretation of deep ocean sediment records. Yet, ages and relative contribution of POC from different sources to deep ocean basins are much less understood. Here, based on radiocarbon (Fm, fraction modern), stable carbon (δ13Corg), and other geochemical analysis of particles intercepted by time‐series sediment traps deployed at three different depths (1,000, 2,150, and 3,200 m), we constrain the source of the sinking POC in the deep basin of northern South China Sea (SCS). The results show that the modern POC derived from surface ocean productivity, acting as the vertical vector, accounts for 87% ± 4% of sinking POC on average, while the lateral vector (aged POC hosted on resuspended sediment) comprises the remainder (13%). The contribution of laterally supplied POC increases with depth and is composed of aged POC derived from several sources. The majority stems from sediment resuspension of the northeastern SCS slope, that entrains aged marine POC (dominant), fossil OC, and soil OC (least significant). The diminished proportion of fossil OC in deep basin sinking POC relative to Taiwan‐proximal areas is likely due to its dispersion via resuspension–deposition loops and dilution by POC stemming from modern surface ocean productivity during the delivery.
Training Physics‐Based Machine‐Learning Parameterizations With Gradient‐Free Ensemble Kalman Methods
Authors: Lopez‐Gomez Ignacio , Christopoulos Costa , Langeland Ervik Haakon Ludvig , Dunbar Oliver R. A. , Cohen Yair , Schneider Tapio 
Published: August 2022

AbstractMost machine learning applications in Earth system modeling currently rely on gradient‐based supervised learning. This imposes stringent constraints on the nature of the data used for training (typically, residual time tendencies are needed), and it complicates learning about the interactions between machine‐learned parameterizations and other components of an Earth system model. Approaching learning about process‐based parameterizations as an inverse problem resolves many of these issues, since it allows parameterizations to be trained with partial observations or statistics that directly relate to quantities of interest in long‐term climate projections. Here, we demonstrate the effectiveness of Kalman inversion methods in treating learning about parameterizations as an inverse problem. We consider two different algorithms: unscented and ensemble Kalman inversion. Both methods involve highly parallelizable forward model evaluations, converge exponentially fast, and do not require gradient computations. In addition, unscented Kalman inversion provides a measure of parameter uncertainty. We illustrate how training parameterizations can be posed as a regularized inverse problem and solved by ensemble Kalman methods through the calibration of an eddy‐diffusivity mass‐flux scheme for subgrid‐scale turbulence and convection, using data generated by large‐eddy simulations. We find the algorithms amenable to batching strategies, robust to noise and model failures, and efficient in the calibration of hybrid parameterizations that can include empirical closures and neural networks.
Biomonitoring of inorganic arsenic species in pregnancy
Authors: Ashley-Martin Jillian , Fisher Mandy , Belanger Patrick , Cirtiu Ciprian Mihai , Arbuckle Tye E. 
Published: August 2022

AbstractExposure assessment of inorganic arsenic is challenging due to the existence of multiple species, complexity of arsenic metabolism, and variety of exposure sources. Exposure assessment of arsenic during pregnancy is further complicated by the physiological changes that occur to support fetal growth. Given the well-established toxicity of inorganic arsenic at high concentrations, continued research into the potential health effects of low-level exposure on maternal and fetal health is necessary. Our objectives were to review the value of and challenges inherent in measuring inorganic arsenic species in pregnancy and highlight related research priorities. We discussed how the physiological changes of pregnancy influence arsenic metabolism and necessitate the need for pregnancy-specific data. We reviewed the biomonitoring challenges according to common and novel biological matrices and discussed how each matrix differs according to half-life, bioavailability, availability of laboratory methods, and interpretation within pregnancy. Exposure assessment in both established and novel matrices that accounts for the physiological changes of pregnancy and complexity of speciation is a research priority. Standardization of laboratory method for novel matrices will help address these data gaps. Research is particularly lacking in contemporary populations of pregnant women without naturally elevated arsenic drinking water concentrations (i.e. <10 µg/l).
Tumor-derived miR-130b-3p induces cancer-associated fibroblast activation by targeting SPIN90 in luminal A breast cancer
Authors: Ahn Suyeon , Kwon Ahreum , Huh Yun Hyun , Rhee Sangmyung , Song Woo Keun 
Published: August 2022

AbstractCancer-associated fibroblasts (CAFs) in the tumor microenvironment (TME) interact closely with cancer cells to promote tumor development. Downregulation of SPIN90 in CAFs has been reported to facilitate breast cancer progression, but the underlying mechanism has not been elucidated. Here, we demonstrate that miR-130b-3p directly downregulates SPIN90 in stromal fibroblasts, leading to their differentiation into CAFs. As the decrease of SPIN90 in CAFs was shown to be more prominent in estrogen receptor (ER)-positive breast tumors in this study, miR-130b-3p was selected by bioinformatics analysis of data from patients with ER-positive breast cancer. Ectopic expression of miR-130b-3p in fibroblasts accelerated their differentiation to CAFs that promote cancer cell motility; this was associated with SPIN90 downregulation. We also found that miR-130b-3p was generated in luminal A-type cancer cells and activated fibroblasts after being secreted via exosomes from cancer cells. Finally, miR-130b-3p increased in SPIN90-downregulated tumor stroma of luminal A breast cancer patients and MCF7 cell-xenograft model mice. Our data demonstrate that miR-130b-3p is a key modulator that downregulates SPIN90 in breast CAFs. The inverse correlation between miR-130b-3p and SPIN90 in tumor stroma suggests that the miR-130b-3p/SPIN90 axis is clinically significant for CAF activation during breast cancer progression.