bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dusty Mafic Rocks Along the Path of Chang'E‐4 Rover: Initial Analysis of the Image Cubes of the Onboard Visible and Near‐Infrared Imaging Spectrometer
Authors: Wang Xing , Liu Jianjun , Liu Dawei , Huang Hai , Guo Lin , Zhang Qing , Chen Yuan , Liu Bin , Chen Wangli , Ren Xin , Li Chunlai 
Published: January 2022

AbstractThe Yutu‐2 rover of Chang'E‐4 encountered four special rocks along its path. The onboard Visible and Near‐infrared Imaging Spectrometer (VNIS) collected their spectral data at close range. In this work, we focus on the visible/near‐infrared image cubes captured by the VNIS. Simple classification was performed using the K‐means algorithm based on the 750/900 nm spectral ratios to highlight the surface material variations. In the case of narrow measurements of phase angle, the classification results were not significantly affected by viewing geometry. Varying degrees of dust coverage on the rock surfaces were revealed, which may be attributed to ejecta deposition and dust electrostatic levitation. The spectral shapes of the less dust‐covered surfaces indicated that these rocks are dominated by mafic materials, suggesting they may not originate from the lunar upper crust. The influence of dust coverage on spectral measurement of rocks was also confirmed, which significantly attenuates the absorption depths.
Hydroclimate and ENSO Variability Recorded by Oxygen Isotopes From Tree Rings in the South American Altiplano
Authors: Rodriguez‐Caton Milagros , Andreu‐Hayles Laia , Daux Valérie , Vuille Mathias , Varuolo‐Clarke Arianna M. , Oelkers Rose , Christie Duncan A. , D’Arrigo Rosanne , Morales Mariano S. , Palat Rao Mukund , Srur Ana M. , Vimeux Françoise , Villalba Ricardo 
Published: January 2022

AbstractHydroclimate variability in tropical South America is strongly regulated by the South American Summer Monsoon (SASM). However, past precipitation changes are poorly constrained due to limited observations and high‐resolution paleoproxies. We found that summer precipitation and the El Niño‐Southern Oscillation (ENSO) variability are well registered in tree‐ring stable oxygen isotopes (δ18OTR) of Polylepis tarapacana in the Chilean and Bolivian Altiplano in the Central Andes (18–22°S, ∼4,500 m a.s.l.) with the northern forests having the strongest climate signal. More enriched δ18OTR values were found at the southern sites likely due to the increasing aridity toward the southwest of the Altiplano. The climate signal of P. tarapacana δ18OTR is the combined result of moisture transported from the Amazon Basin, modulated by the SASM, ENSO, and local evaporation, and emerges as a novel tree‐ring climate proxy for the southern tropical Andes.
Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning
Authors: Zhang Shuangshang , Xu Qing , Wang Haoyu , Kang Yanyan , Li Xiaofeng 
Published: January 2022

AbstractThis study presented an intuitive approach to derive large‐scale tidal flat's Digital Elevation Model (DEM). We first developed an automated method for accurately extracting the waterline from Synthetic Aperture Radar images acquired in Subei Sandbanks along the Yellow Sea coast of China between 2015 and 2020 based on deep convolutional neural networks. The statistical results show this method has appreciable accuracy for efficient waterline extraction even under complex imaging conditions with a mean recall and precision of 0.90 and 0.80, respectively. Then the pixel‐level extracted waterlines are calibrated with a global tide model to construct the large‐scale tidal flat's DEM in the study region. The comparison against in situ topographic data shows an error of 29 cm, demonstrating the usefulness of monitoring the morpho‐sedimentary evolution in intertidal areas. Furthermore, the Subei Sandbanks remained stable from 2015 to 2020, while the coastal region changed drastically due to human activities.
Acceleration of Electrons by Whistler‐Mode Hiss Waves at Saturn
Authors: Woodfield E. E. , Glauert S. A. , Menietti J. D. , Horne R. B. , Kavanagh A. J. , Shprits Y. Y. 
Published: January 2022

AbstractPlasmaspheric hiss waves at the Earth are well known for causing losses of electrons from the radiation belts through wave particle interactions. At Saturn, however, we show that the different plasma density environment leads to acceleration of the electrons rather than loss. The ratio of plasma frequency to electron gyrofrequency frequently falls below one creating conditions for hiss to accelerate electrons. The location of hiss at high latitudes (>25°) coincides very well with this region of very low density. The interaction between electrons and hiss only occurs at these higher latitudes, therefore the acceleration is limited to mid to low pitch angles leading to butterfly pitch angle distributions. The hiss is typically an order of magnitude stronger than chorus at Saturn and the resulting acceleration is rapid, approaching steady state in one day at 0.4 MeV at L = 7 and the effect is stronger with increasing L‐shell.
Impacts of the Unforced Pattern Effect on the Cloud Feedback in CERES Observations and Climate Models
Authors: Chao Li‐Wei , Muller Jacob C. , Dessler Andrew E. 
Published: January 2022

AbstractThe equilibrium climate sensitivity estimated from different sources is inconsistent due to its dependence on the surface warming pattern. Cloud feedbacks have been identified as the major contributor to this so‐called pattern effect. We find a large unforced pattern effect in CERES data, with cloud feedback estimated from two consecutive 125‐month periods (March 2000–July 2010 and August 2010–December 2020) changing from −0.45 ± 0.85 to +1.2 ± 0.78 W/m2/K. When comparing to models, 27% of consecutive 10‐year segments in CMIP6 control runs have differences similar to the observations. We also compare the spatial patterns in the CERES data to those in climate models and find they are similar, with the East Pacific playing a key role. This suggests that the impact of the unforced pattern effect can be significant and that models are capable of reproducing its global‐average magnitude.
Convective and Microphysical Characteristics of Extreme Precipitation Revealed by Multisource Observations Over the Pearl River Delta at Monsoon Coast
Authors: Yu Shuting , Luo Yali , Wu Chong , Zheng Dong , Liu Xiantong , Xu Weixin 
Published: January 2022

AbstractExtreme precipitation is an issue of worldwide concern, but its microphysics remain elusive. The convective and microphysical characteristics of extreme precipitation features (EPFs) in a monsoon coastal area (South China) are investigated mainly using 2‐year observations from a dual‐polarization radar and distrometers. The EPFs are accompanied by a broad range of convective intensity, and categorized into the “intense”, “moderate”, and “weak” convection accounting for 17.3%, 48.6% and 34.1% of the total population, respectively. The EPFs with weaker convection show weakened size sorting and less breakup of large raindrops, but a larger ratio of liquid water path to ice water path and more prominent coalescence warm‐rain process. All the three categories are dominated by the coalescence in the liquid‐phase processes, and have much more populous raindrops than the “continental” with a mean size larger than the “maritime” regime. These results improve our understanding of extreme precipitation from the microphysical perspective.
Crustal Structure of the Incoming Iquique Ridge Offshore Northern Chile
Authors: Myers E. K. , Roland E. C. , Tréhu A. M. , Davenport K. ,   the PICTURES group
Published: January 2022

AbstractThe Peru‐Chile subduction zone hosts M > 8 earthquakes as well as multiple ridges on the downgoing Nazca plate, making this region well suited for investigating the formation, evolution, and potential impacts of subducting features on seismogenesis. To evaluate the physical properties and structural variability of the Iquique Ridge offshore northern Chile, we present a P wave velocity model of the Nazca plate and Iquique Ridge outboard of the 2014 M 8.1 Iquique earthquake sequence. 2D tomographic inversions of P wave traveltime data from the 2016 PICTURES (Pisagua/Iquique Crustal Tomography to Understand the Region of the Earthquake Source) controlled‐source experiment indicate that the Iquique Ridge is characterized by significant crustal thickening relative to typical Nazca plate oceanic crust, with a maximum thickness of ∼13 km beneath the most prominent portion of the Iquique Ridge and outer rise. Reduced upper crustal seismic velocities extend from the ridge eastward to the trench, which may indicate increased fracturing and/or hydration during plate bending. Corresponding multi‐channel seismic reflection data show along‐profile structural variation as well, including an intermittent Moho reflector near the onset of crustal thickening and faulting along the landward slope. The structural heterogeneity entering the Peru‐Chile Trench has potential implications for slip behavior at depth assuming that the anomalous crustal structure continues beneath the forearc. We suggest that the increased buoyant normal force associated with discrete subducted Iquique Ridge seamounts similar to the zone of thick crust imaged here could lead to localized increased interplate coupling, while entrained sediment and fractured/altered crust could facilitate aseismic slip.
Supraglacial Drainage Efficiency of the Greenland Ice Sheet Estimated From Remote Sensing and Climate Models
Authors: Yang Kang , Smith Laurence C. , Andrews Lauren C. , Fettweis Xavier , Li Manchun 
Published: January 2022

AbstractSupraglacial stream/river catchments drain large volumes of surface meltwater off the southwestern Greenland Ice Sheet surface. Previous studies note a strong seasonal evolution of their drainage density (Dd), a classic measure of drainage efficiency defined as open channel length per unit catchment area, but a direct correlation between Dd and surface meltwater runoff (R) has not been established. We use 27 high‐resolution (∼0.5 m) satellite images to map seasonally evolving Dd for four GrIS supraglacial catchments, with elevations ranging from 1,100 m to 1,700 m. We find a positive linear correlation (r2 = 0.70, p < 0.01) between Dd and simulations of runoff production from two climate models (MAR v3.11 and MERRA‐2). Applying this R‐Dd empirical relationship to climate model output enables parameterization of spatial and temporal changes in supraglacial drainage efficiency continuously throughout the melt season, although temporal and spatial skewness of Dd observations likely affects the application of this R‐Dd relationship on crevasse fields and snow/firn surfaces. Incorporating this information into a simple surface routing model finds that high runoff leads to earlier, larger diurnal peaks of runoff transport on the ice surface, owing to increased Dd. This effect progressively declines from low (∼1,100 m) to high (∼1,700 m) elevation, causing a roughly order‐of‐magnitude reduction in diurnal runoff variability at the highest elevations relative to standard climate model output. Combining intermittent satellite Dd mapping with climate model output thus promises to improve characterization of supraglacial drainage efficiency to the benefit of supraglacial meltwater routing and subglacial hydrology models.
Evaluating Distributed Policies for Conjunctive Surface Water‐Groundwater Management in Large River Basins: Water Uses Versus Hydrological Impacts
Authors: Du Erhu , Tian Yong , Cai Ximing , Zheng Yi , Han Feng , Li Xin , Zhao Mohan , Yang Yi , Zheng Chunmiao 
Published: January 2022

AbstractIt is imperative to understand the interconnectedness of water use and hydrological impacts for water policy design underlying varying hydrological conditions across space and over time. However, such analysis remains difficult, constrained by the lack of appropriate modeling tools that fully integrate water policies, water use, and hydrological processes with high spatiotemporal resolutions. To address this challenge, this study proposes a distributed policy design scheme featuring spatially variable and temporally dynamic policies for conjunctive surface water‐groundwater management in large river basins. A fully integrated modeling framework is developed to tightly couple (a) an agent‐based model for farmers' water use under distributed water policies and (b) a physically based hydrological model for surface water‐groundwater processes. The modeling framework is applied to the Heihe River Basin to assess water use and hydrological impacts under distributed water policies. By using the distributed policy scheme to adjust a water policy (e.g., groundwater tax) across space and over time, we found that hydrological outcomes can be improved without adversely reducing agricultural water supply. For example, by shifting the implementation of a high groundwater tax from dry to wet years, a rise of the water table by 0.28 m (0.03–0.95 m across different irrigation districts) can be achieved while the total water supply is maintained at a similar level. Furthermore, hydrological externality effects among nearby districts can be explicitly identified and quantified based on assessments of spatially varying water policies. This study highlights the need for water policy design to consider spatiotemporal variations in the physical hydrological system.
Self-directed online machine learning for topology optimization
Authors: Deng Changyu , Wang Yizhou , Qin Can , Fu Yun , Lu Wei 
Published: January 2022

AbstractTopology optimization by optimally distributing materials in a given domain requires non-gradient optimizers to solve highly complicated problems. However, with hundreds of design variables or more involved, solving such problems would require millions of Finite Element Method (FEM) calculations whose computational cost is huge and impractical. Here we report Self-directed Online Learning Optimization (SOLO) which integrates Deep Neural Network (DNN) with FEM calculations. A DNN learns and substitutes the objective as a function of design variables. A small number of training data is generated dynamically based on the DNN’s prediction of the optimum. The DNN adapts to the new training data and gives better prediction in the region of interest until convergence. The optimum predicted by the DNN is proved to converge to the true global optimum through iterations. Our algorithm was tested by four types of problems including compliance minimization, fluid-structure optimization, heat transfer enhancement and truss optimization. It reduced the computational time by 2 ~ 5 orders of magnitude compared with directly using heuristic methods, and outperformed all state-of-the-art algorithms tested in our experiments. This approach enables solving large multi-dimensional optimization problems.
A Kerr polarization controller
Authors: Moroney N. , Del Bino L. , Zhang S. , Woodley M. T. M. , Hill L. , Wildi T. , Wittwer V. J. , Südmeyer T. , Oppo G.-L. , Vanner M. R. , Brasch V. , Herr T. , Del’Haye P. 
Published: January 2022

AbstractKerr-effect-induced changes of the polarization state of light are well known in pulsed laser systems. An example is nonlinear polarization rotation, which is critical to the operation of many types of mode-locked lasers. Here, we demonstrate that the Kerr effect in a high-finesse Fabry-Pérot resonator can be utilized to control the polarization of a continuous wave laser. It is shown that a linearly-polarized input field is converted into a left- or right-circularly-polarized field, controlled via the optical power. The observations are explained by Kerr-nonlinearity induced symmetry breaking, which splits the resonance frequencies of degenerate modes with opposite polarization handedness in an otherwise symmetric resonator. The all-optical polarization control is demonstrated at threshold powers down to 7 mW. The physical principle of such Kerr effect-based polarization controllers is generic to high-Q Kerr-nonlinear resonators and could also be implemented in photonic integrated circuits. Beyond polarization control, the spontaneous symmetry breaking of polarization states could be used for polarization filters or highly sensitive polarization sensors when operating close to the symmetry-breaking point.
Merging enzymes with chemocatalysis for amide bond synthesis
Authors: Bering Luis , Craven Elliott J. , Sowerby Thomas Stanley A. , Shepherd Sarah A. , Micklefield Jason 
Published: January 2022

AbstractAmides are one of the most fundamental chemical bonds in nature. In addition to proteins and other metabolites, many valuable synthetic products comprise amide bonds. Despite this, there is a need for more sustainable amide synthesis. Herein, we report an integrated next generation multi-catalytic system, merging nitrile hydratase enzymes with a Cu-catalysed N-arylation reaction in a single reaction vessel, for the construction of ubiquitous amide bonds. This synergistic one-pot combination of chemo- and biocatalysis provides an amide bond disconnection to precursors, that are orthogonal to those in classical amide synthesis, obviating the need for protecting groups and delivering amides in a manner unachievable using existing catalytic regimes. Our integrated approach also affords broad scope, very high (molar) substrate loading, and has excellent functional group tolerance, telescoping routes to natural product derivatives, drug molecules, and challenging chiral amides under environmentally friendly conditions at scale.
Ionic covalent organic framework based electrolyte for fast-response ultra-low voltage electrochemical actuators
Authors: Yu Fei , Ciou Jing-Hao , Chen Shaohua , Poh Wei Church , Chen Jian , Chen Juntong , Haruethai Kongcharoen , Lv Jian , Gao Dace , Lee Pooi See 
Published: January 2022

AbstractElectrically activated soft actuators with large deformability are important for soft robotics but enhancing durability and efficiency of electrochemical actuators is challenging. Herein, we demonstrate that the actuation performance of an ionic two-dimensional covalent-organic framework based electrochemical actuator is improved through the ordered pore structure of opening up efficient ion transport routes. Specifically, the actuator shows a large peak to peak displacement (9.3 mm, ±0.5 V, 1 Hz), a fast-response time to reach equilibrium-bending (~1 s), a correspondingly high bending strain difference (0.38%), a broad response frequency (0.1–20 Hz) and excellent durability (>99%) after 23,000 cycles. The present study ascertains the functionality of soft electrolyte as bionic artificial actuators while providing ideas for expanding the limits in applications for robots.
Modulus adaptive lubricating prototype inspired by instant muscle hardening mechanism of catfish skin
Authors: Zhang Yunlei , Zhao Weiyi , Ma Shuanhong , Liu Hui , Wang Xingwei , Zhao Xiaoduo , Yu Bo , Cai Meirong , Zhou Feng 
Published: January 2022

AbstractIn nature, living organisms evolve unique functional components with mechanically adaptive compatibility to cater dynamic change of interface friction/lubrication. This mechanism can be used for developing intelligent artificial lubrication-regulation systems. Inspired by the muscle hardening-triggered lubrication oflongsnout catfish, here we report a modulus adaptive lubricating hydrogel prototype consisting of top mucus-like hydrophilic lubricating layer and muscle-like bottom hydrogel that can stiffen via thermal-triggered phase separation. It exhibits instant switch from soft/high frictional state (~0.3 MPa,μ~0.37) to stiff/lubricating state (~120 MPa,μ~0.027) in water upon heating up. Such switchable lubrication is effective for wide range of normal loads and attributed to the modulus-dominated adaptive contact mechanism. As a proof-of-concept, switchable lubricating hydrogel bullets and patches are engineered for realizing controllable interface movements. These important results demonstrate potential applications in the fields of intelligent motion devices and soft robots.
The mitochondrial β-oxidation enzyme HADHA restrains hepatic glucagon response by promoting β-hydroxybutyrate production
Authors: Pan An , Sun Xiao-Meng , Huang Feng-Qing , Liu Jin-Feng , Cai Yuan-Yuan , Wu Xin , Alolga Raphael N. , Li Ping , Liu Bao-Lin , Liu Qun , Qi Lian-Wen 
Published: January 2022

AbstractDisordered hepatic glucagon response contributes to hyperglycemia in diabetes. The regulators involved in glucagon response are less understood. This work aims to investigate the roles of mitochondrial β-oxidation enzyme HADHA and its downstream ketone bodies in hepatic glucagon response. Here we show that glucagon challenge impairs expression of HADHA. Liver-specific HADHA overexpression reversed hepatic gluconeogenesis in mice, while HADHA knockdown augmented glucagon response. Stable isotope tracing shows that HADHA promotes ketone body production via β-oxidation. The ketone body β-hydroxybutyrate (BHB) but not acetoacetate suppresses gluconeogenesis by selectively inhibiting HDAC7 activity via interaction with Glu543 site to facilitate FOXO1 nuclear exclusion. In HFD-fed mice, HADHA overexpression improved metabolic disorders, and these effects are abrogated by knockdown of BHB-producing enzyme. In conclusion, BHB is responsible for the inhibitory effect of HADHA on hepatic glucagon response, suggesting that HADHA activation or BHB elevation by pharmacological intervention hold promise in treating diabetes.
Upcycling of dynamic thiourea thermoset polymers by intrinsic chemical strengthening
Authors: Feng Haijun , Zheng Ning , Peng Wenjun , Ni Chujun , Song Huijie , Zhao Qian , Xie Tao 
Published: January 2022

AbstractThermoset polymers are indispensable but their environmental impact has been an ever-increasing concern given their typical intractability. Although concepts enabling their reprocessing have been demonstrated, their practical potential is limited by the deteriorated performance of the reprocessed materials. Here, we report a thiourea based thermoset elastomer that can be reprocessed with enhanced mechanical properties. We reveal that the thiourea bonds are dynamic which leads to the reprocessibility. More importantly, they can undergo selective oxidation during high temperature reprocessing, resulting in significant chemical strengthening within certain reprocessing cycles. This is opposite to most polymers for which reprocessing typically results in material deterioration. The possibility of having materials with inherent reprocessing induced performance enhancement points to a promising direction towards polymer recycling.
Automated pipeline for superalloy data by text mining
Authors: Wang Weiren , Jiang Xue , Tian Shaohan , Liu Pei , Dang Depeng , Su Yanjing , Lookman Turab , Xie Jianxin 
Published: January 2022

AbstractData provides a foundation for machine learning, which has accelerated data-driven materials design. The scientific literature contains a large amount of high-quality, reliable data, and automatically extracting data from the literature continues to be a challenge. We propose a natural language processing pipeline to capture both chemical composition and property data that allows analysis and prediction of superalloys. Within 3 h, 2531 records with both composition and property are extracted from 14,425 articles, coveringγ′ solvus temperature, density, solidus, and liquidus temperatures. A data-driven model forγ′ solvus temperature is built to predict unexplored Co-based superalloys with highγ′ solvus temperatures within a relative error of 0.81%. We test the predictions via synthesis and characterization of three alloys. A web-based toolkit as an online open-source platform is provided and expected to serve as the basis for a general method to search for targeted materials using data extracted from the literature.