bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbon 13 Isotopes Reveal Limited Ocean Circulation Changes Between Interglacials of the Last 800 ka
Authors: Bouttes N. , Vazquez Riveiros N. , Govin A. , Swingedouw D. , Sanchez‐Goni M. F. , Crosta X. , Roche D. M. 
Published: April 2020

AbstractIce core data have shown that atmospheric CO2 concentrations during interglacials were lower before the Mid‐Brunhes Event (MBE, ~430 ka), than after the MBE by around 30 ppm. To explain such a difference, it has been hypothesized that increased bottom water formation around Antarctica or reduced Atlantic Meridional Overturning Circulation (AMOC) could have led to greater oceanic carbon storage before the MBE, resulting in less carbon in the atmosphere. However, only few data on possible changes in interglacial ocean circulation across the MBE have been compiled, hampering model‐data comparison. Here we present a new global compilation of benthic foraminifera carbon isotopic (δ13C) records from 31 marine sediment cores covering the last 800 ka, with the aim of evaluating possible changes of interglacial ocean circulation across the MBE. We show that a small systematic difference between pre‐ and post‐MBE interglacial δ13C is observed. In pre‐MBE interglacials, northern source waters tend to have slightly higher δ13C values and penetrate deeper, which could be linked to an increased northern sourced water formation or a decreased southern sourced water formation. Numerical model simulations tend to support the role of abyssal water formation around Antarctica: Decreased convection there associated with increased sinking of dense water along the continental slopes results in increased δ13C values in the Atlantic in agreement with pre‐MBE interglacial data. It also yields reduced atmospheric CO2 as in pre‐MBE records, despite a smaller simulated amplitude change compared to data, highlighting the need for other processes to explain the MBE transition.
Physical Constraints for Improved Soil Hydraulic Parameter Estimation by Pedotransfer Functions
Authors: Lehmann Peter , Bickel Samuel , Wei Zhongwang , Or Dani 
Published: April 2020

AbstractGlobal land surface models use spatially distributed soil information for the parameterization of soil hydraulic properties (SHP). Parameters of measured SHP are correlated with easy‐to‐measure soil properties to construct general pedotransfer functions (PTFs) used to predict SHP from spatial soil information. Global PTFs are based on a limited number of samples yielding highly variable and poorly constrained SHP. The study implements a physical constraint, soil‐specific capillary length, to reduce unphysical combinations of SHP. The procedure fits concurrently soil water retention and capillary length using the same parameters. Results suggest that meeting the capillary length constraint has minor effects on the goodness of fit to soil water retention data. Constrained SHP were applied to represent 4 years of lysimeter fluxes yielding evapotranspiration values in close agreement with measurements relative to slight overestimation by unconstrained SHP. The procedure was applied for testing constraint SHP at a regional scale in New Zealand using the surface evaporation capacitance model and Noah‐MP for detailed simulations of land surface processes. The use of constrained SHP in both models yields higher surface runoff in agreement with observations (unconstrained SHP severely underestimated runoff generation). The concept of constrained SHP could be extended to include other physical constraints to improve PTFs, for example, by consideration of vegetation cover and soil structure effects on infiltration.
Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems
Authors: Tartakovsky A. M. , Marrero C. Ortiz , Perdikaris Paris , Tartakovsky G. D. , Barajas‐Solano D. 
Published: April 2020

AbstractWe present a physics‐informed deep neural network (DNN) method for estimating hydraulic conductivity in saturated and unsaturated flows governed by Darcy's law. For saturated flow, we approximate hydraulic conductivity and head with two DNNs and use Darcy's law in addition to measurements of hydraulic conductivity and head to train these DNNs. For unsaturated flow, we approximate unsaturated conductivity function and capillary pressure with DNNs and train these DNNs using measurements of capillary pressure and the Richards equation. Because it is difficult to measure unsaturated conductivity in the field, we assume that no measurements of unsaturated conductivity are available. The proposed approach enforces the partial differential equation (PDE) (Darcy or Richards equation) constraints by minimizing the PDE residual at select points in the simulation domain. We demonstrate that physics constraints increase the accuracy of DNN approximations of sparsely observed functions and allow for training DNNs when no direct measurements of the functions of interest are available. For the saturated conductivity estimation problem, we show that the physics‐informed DNN method is more accurate than the state‐of‐the‐art maximum a posteriori probability method. For the unsaturated flow in homogeneous porous media, we find that the proposed method can accurately estimate the pressure‐conductivity relationship based on the capillary pressure measurements only, even in the presence of measurement noise.
A Technical Evaluation of Lidar‐Based Measurement of River Water Levels
Authors: Paul Jonathan D. , Buytaert Wouter , Sah Neeraj 
Published: April 2020

AbstractMeasuring river water level (stage) is key for a variety of applications including discharge estimation and flood prediction. Although a variety of in situ and noncontact methods are available, there is an urgent need for new and more cost‐efficient methods. Rapid technological progress has accelerated the use of noncontact methods and development of time‐of‐flight distance sensors. Among available techniques, the use of lidar for distance measurement is promising because of its low cost, high energy efficiency, and small measurement footprint. However, lidar has rarely been used to measure water levels. Here we test a near‐infrared (905 nm) lidar sensor to determine its suitability for stage measurements under a range of environmental conditions. Using different laboratory and field setups, we assess sensor performance as a function of measurement distance, surface roughness, air temperature, water turbidity, and measurement angle. Despite the low reflectivity of water for infrared radiation, we find that the tested sensor is able to take measurements under all tested conditions, up to an incidence angle of ∼40°. The accuracy of the sensor is within the technical specifications of the device and is characterized by a relative error of around 0.1%. We find a strong dependence of the accuracy on sensor temperature, which we attribute to suboptimal internal compensation of the electronics. The precision of the sensor decreases with increasing measured distance and increases with surface roughness of the water body. We did not find any significant impact of water turbidity on the measurements.
An Automatic Framework of Region‐of‐Interest Detection and Classification for Networked X‐Band Weather Radar System
Authors: Xu Zi‐Xin , Yang Ling , Lei Bo , Li Xuehua , Zhen Xiaoqiong 
Published: April 2020

AbstractNowadays, S‐band weather radars are designed to observe weather conditions within large area. However, S‐band radars suffer from large blind zone at low elevation and fixed scan strategy so that they are not efficient for surveillance of convective weathers such as tornado. Networked X‐band weather radars are thereby proposed to overcome this issue. One key problem of networked radar is to automatically determine the type and the precise position of convective cells that are worthwhile to detect. In this paper, a tailor‐made framework is proposed to automatically find the convective cells and retrieve information of them from reflectivity product of networked X‐band weather radars. The framework consists of three substeps: convection pixel retrieval by Back Propagation Neural Network (BPNN), convection cell construction by Density‐Based Spatial Clustering of Applications with Noise (DBSCAN), and convection cell classification by Convolutional Neural Network (CNN). Evaluation results show that the proposed algorithm is capable to identify isolated single‐cell and multicell convective storms from the reflectivity image accurately. Therefore, the proposed framework is capable to provide information for networked X‐band weather radars so that they can track harmful convective weathers. The proposed framework has been embedded in the meteorological command and control (MCC) center of networked X‐band radar system in Chengdu.
Ductility and Compressibility Accommodate High Magma Flux Beneath a Silicic Continental Rift Caldera: Insights From Corbetti Caldera (Ethiopia)
Authors: Gottsmann J. , Biggs J. , Lloyd R. , Biranhu Y. , Lewi E. 
Published: April 2020

AbstractLarge silicic magma reservoirs preferentially form in the upper crust of extensional continental environments. However, our quantitative understanding of the link between mantle magmatism, silicic reservoirs, and surface deformation during rifting is very limited. Here, we focus on Corbetti, a peralkaline caldera in the densely populated Main Ethiopian Rift, which lies above a focused zone of upper mantle partial melt and has been steadily uplifting at a maximum rate of 6.6±1.2 cm yr−1 for more than 10 yr. Numerical modeling shows that a maximum concomitant residual gravity increase of 9±3 μGal yr−1 by the intrusion of mafic magma at ∼7 km depth into a compressible and inelastic crystal mush best explains the observed deformation and gravity changes. The derived magma mass flux of ∼1011 kg yr−1 is anomalously high and at least 1 order of magnitude greater than the mean long‐term mass eruption rate. This study demonstrates that periodic and high‐rate magmatic rejuvenation of upper‐crustal mush is a significant and rapid contributor to mature continental rifting.
Magnetospheric Multiscale (MMS) Observations of Magnetic Reconnection in Foreshock Transients
Authors: Liu Terry Z. , Lu San , Turner Drew L. , Gingell Imogen , Angelopoulos Vassilis , Zhang Hui , Artemyev Anton , Burch James L. 
Published: April 2020

AbstractMagnetic reconnection is a fundamental process of energy conversion in plasmas between electromagnetic fields and particles. Magnetic reconnection has been observed directly in a variety of plasmas in the solar wind and Earth's magnetosphere. Most recently, electron magnetic reconnection without ion coupling was observed for the first time in the turbulent magnetosheath and within the transition region of Earth's bow shock. In the ion foreshock upstream of Earth's bow shock, there may also be magnetic reconnection especially around foreshock transients that are very turbulent and dynamic. With observations from the National Aeronautics and Space Administration's Magnetospheric Multiscale mission inside foreshock transients, we report two events of magnetic reconnection with and without a strong guide field, respectively. In both events, a super‐ion‐Alfvénic electron jet was observed within a current sheet with thickness less than or comparable to one ion inertial length. In both events, energy was converted from the magnetic field to electrons, manifested as an increase in electron temperature. Weak or no ion coupling was observed in either event. Results from particle‐in‐cell simulations of magnetic reconnection with and without a strong guide field are qualitatively consistent with observations. Our results imply that magnetic reconnection is another electron acceleration/heating process inside foreshock transients and could play an important role in shock dynamics.
New Observations of Large‐Scale Waves Coupling With the Ionosphere Made by the GOLD Mission: Quasi‐16‐Day Wave Signatures in the F‐Region OI 135.6‐nm Nightglow During Sudden Stratospheric Warmings
Authors: Gan Quan , Eastes Richard W. , Burns Alan G. , Wang Wenbin , Qian Liying , Solomon Stanley C. , Codrescu Mihail V. , McClintock William E. 
Published: April 2020

AbstractThe recently launched Global‐scale Observations of the Limb and Disk (GOLD) Mission observed prominent quasi‐16‐day oscillations (Q16DOs) in the OI 135.6‐nm nightglow from the equatorial ionization anomaly (EIA) region during 26 November 2018 to 25 January 2019. Meanwhile, the enhanced and concurrent quasi‐16‐day wave (Q16DW) activity was observed in the middle atmosphere by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument. This implies that the F‐region ionosphere couples with the lower atmosphere through large‐scale waves. A noteworthy phenomenon was that the Q16DOs displayed an asymmetric behavior between the northern and southern EIA crests. This asymmetry indicates that the ionospheric Q16DOs might be driven by the Q16DW‐modulated tides, which not only modulated the E‐region dynamo winds but also modulated the F‐region field‐aligned neutral winds via vertical penetration, producing the oscillations in plasmas densities.
Numerical Investigation of Baroclinic Channel‐Shoal Interaction in Partially Stratified Estuaries
Authors: Zhou Jian , Stacey Mark T. , Holleman Rusty C. , Nuss Emma , Senn David B. 
Published: April 2020

AbstractThe internal, density‐driven channel‐shoal interaction in partially stratified estuaries is numerically investigated. Idealized General Estuarine Transport Model (GETM) simulations with the rigid‐lid assumption are performed in a two‐dimensional cross‐sectional mode forced by a constant longitudinal salinity gradient and an M2 tidal current. Simulation results show that within each tide cycle, the abrupt flattening of bathymetry at the channel‐shoal interface leads to the trapping of a patch of high‐salinity water mass on the shoal. The resulting local salinity maximum near the interface interacts with the differential advection by the gentle slope of shoal, driving complex density‐driven on‐shoal lateral circulations. Next, it is found that the presence of the shoal in turn enhances the longitudinal residual circulation in the channel. As a storage of estuarine water that is partially isolated from the main stream, the shoal traps saltier water that originates from the channel during slack after ebb (thus a less stratified flood), while injects fresher water into the surface of the channel during slack after flood (thus a more stratified ebb). These lateral baroclinic exchanges across the channel‐shoal interface give rise to a new mechanism for generating tidal asymmetry of eddy viscosity and shear in the channel (i.e., tidal straining circulation), which has the same orientation with the classical estuarine circulation. The interfacial salt trapping and the accompanied shoal‐induced modification of channel residual circulation are demonstrated to possess a highly localized nature, with their characteristics largely independent of shoal bathymetry far away from the channel‐shoal interface.
Biomarker Fingerprint of Debris Flow Deposits as a Paleoproxy for IRD Sources in the Last Glacial North Atlantic
Authors: Wary Mélanie , Kornilova Oksana , Russell Marie , Rosell‐Melé Antoni 
Published: April 2020

AbstractInvestigating the spatiotemporal dynamics of iceberg discharges during the last glacial period constitutes a major challenge for paleoclimate research. In recent decades, many ice‐rafted debris (IRD) provenance studies, mostly based on the comparison of the inorganic signature of IRD‐rich layers and surrounding continental bedrock, have differentiated main subareas of individual ice sheets as iceberg sources and gauged their dynamic interplay. Diagnosis of specific source ice streams has nonetheless remained limited. Here we propose a new IRD provenance methodology to refine the identification of iceberg sources. It relies on the organic geochemical characterization of glacigenic debris flow (GDF) deposits to obtain the biomarker fingerprint of IRD sources. To test its potential, we analyze the composition of n‐alkanes and chlorophyll‐derived pigments in sediments deposited within six major North Atlantic GDF depocenters fed by ice streams draining the surrounding ice sheets. The biomarker fingerprint of GDF deposits appears to (1) be consistent with a common origin of IRD and GDF deposits through erosion of outcrops and transport by ice streams, (2) differ significantly from that of ambient hemipelagic sediments, (3) be specific and unique to each GDF depocenter, making it possible to distinguish the corresponding specific ice streams, (4) be imprinted in IRD‐bearing marine sediments, and (5) have remained homogeneous enough through the last glacial to be used as a proxy for IRD sources. The biomarker fingerprint of GDF deposits thus shows strong potential to track the specific source ice streams that delivered IRD to the last glacial North Atlantic.
Improved LDMOS‐SCR for high‐voltage electrostatic discharge (ESD) protection applications
Authors: Song Wenqiang , Hou Fei , Du Feibo , Liu Jizhi , Liu Zhiwei , Liou Juin J. 
Published: April 2020

An improved lateral double‐diffused MOS silicon‐controlled rectifier (ILDMOS‐SCR) for high‐voltage electrostatic discharge (ESD) protection applications has been proposed and verified in a 0.18 µm 5 V/24 V BCD process. The proposed improved lateral double‐diffused MOS silicon‐controlled rectifier (LDMOS‐SCR) is constructed by adding a gated P‐type/intrinsic/N‐type (PIN) diode into a conventional LDMOS‐SCR. With part of the ESD current discharges from the surface gated PIN diode path, the proposed ILDMOS‐SCR achieves a high holding voltage of 30 V as well as a high failure current of 10.04 A, which is evaluated to pass 15 KV Human Body Model (HBM) ESD stress.
Motion boundary emphasised optical flow method for human action recognition
Authors: Peng Cheng , Huang Haozhi , Tsoi Ah‐Chung , Lo Sio‐Long , Liu Yun , Yang Zi‐yi 
Published: April 2020

This study proposes a three‐stream model using two different types of deep convolutional neural networks (CNNs): (i) a spatial stream with a CNN on images; (ii) a ResNet (residual network) on optical flows; and, (iii) a ResNet on the concatenation of motion features. This model is applied to four datasets: (i) UCF Sports; (ii) Youtube Sports; (iii) SBU action interaction; and (iv) a subset of the UCF‐1M Sports. Using two optical flow estimation methods: (i) a motion boundary emphasised Epicflow (Edge Preserving Interpolation Correspondences for Optical Flow) method, (MBEpicflow); and (ii) the Flownet 2 method, a learning optical flow estimation method. It was found that (i) the proposed MBEpicflow outperforms the Flownet 2 method on the SBU dataset, while the Flownet 2 performs equally well or better than the MBEpicflow method on the other three datasets, and these results are the best when compared with those obtained using other approaches on all datasets evaluated. These results showed the importance of accurate optical flow plays in human action recognition, an aspect which has been seldom addressed. Moreover, it showed that if some measure of the global behaviours of motion is incorporated, the generalisation performance is often improved by 1–2%.
Accurate and fast single shot multibox detector
Authors: Guo Lie , Wang Dongxing , Li Linhui , Feng Jindun 
Published: April 2020

With the development of deep learning, the performance of object detection has made great progress. However, there are still some challenging problems, such as the detection accuracy of small objects and the efficiency of the detector. This study proposes an accurate and fast single shot multibox detector, which includes context comprehensive enhancement (CCE) module and feature enhancement module (FEM). To integrate more efficient information when aggregating context information, the conv4_3 and fc_7 feature maps are merged to design the CCE module. To obtain more fine‐grained feature information, this study presents a FEM and special feature enhancement module (FEM‐s) module that can fuse different receptive field sizes to better adapt to the scale change of the object. Compared to existing methods based on deep learning, the proposed method helps to gradually produce more detailed feature maps with better performance. Under the premise of ensuring real‐time speed, the authors network can achieve 81.2 mean average precision on the PASCAL VOC 2007 test with an input size of 320 × 320 on a single Nvidia 2080Ti GPU.
Use of Graph Based Descriptors for Determination of Structural Features Causing Modulation of Fructose-1,6-Bisphosphatase
Authors: Kumar Ashwani , Bagri Kiran , Kumar Parvin ,   Manisha
Published: April 2020

AbstractFructose-1,6-bisphosphatase performs a significant function in regulating the blood glucose level in type 2 diabetes by controlling the process gluconeogenesis. In this research work optimal descriptor (graph) based quantitative structural activity relationship studies of a set of 203 fructose-1,6-bisphosphatase has been performed with the help of Monte Carlo optimization. Distribution of compounds into different sets such as training set, invisible training set, calibration set and validation sets resulted in formation of splits. Statistical parameters obtained from quantitative structural activity relationship modeling were good for various designed splits. The statistical parameters such as R2 and Q2 for calibration and validation sets of best split developed were found to be 0.8338, 0.7908 & 0.7920 and 0.7036 respectively. Based on the results obtained for correlation weights, different structural attributes were described as promoters and demoters of the endpoint. Further these structural attributes were used in designing of new fructose-1,6-bisphosphatase inhibitors and molecular docking study was accomplished for the determination of interactions of designed molecules with the enzyme.
Epileptic Spasms in an Infant with Incontinentia Pigmenti: Report of a Rare Case with Brief Review of the Literature
Authors: Sharawat Indar Kumar , Panda Prateek Kumar 
Published: April 2020

Abstract
Incontinentia pigmenti (IP) or Bloch–Sulzberger’s disease is a rare neurocutaneous syndrome with dermatological, neurologic, and systemic manifestations including retinal, dental and hair abnormalities. It follows X-linked dominant inheritance and predominantly affects female children. The characteristic evolution of skin lesions in four stages is a hallmark diagnostic feature of the disease. The pigmented lesions of IP are usually distributed in linear streaks, macular whorls, reticulated patches, and flecks along the Blaschko lines. Neurologic morbidities are found in a considerable proportion of affected children, and the spectrum includes seizures, neuromotor impairment, microcephaly, developmental delay, and intellectual disability. Seizures are reported in 10% to 25% of children with IP in various previous clinical studies. The majority of these children had seizures in the neonatal period or early infancy, and focal–clonic seizure is the commonest observed semiology. However, there are only a few case reports of infants with IP with epileptic spasms. In this report, the clinical course of a 6-month-old girl with IP and epileptic spasms has been described, who responded favorably to treatment with adrenocorticotropic hormone injection. Clinicians managing children with IP should be aware of their predisposition to develop epileptic spasms and consider neuroimaging, electroencephalogram, and other investigations accordingly.
Thermoelasticplastic deformation of a functionally graded spherical layer
Authors: Akinlabi E. T. , Dats E. P. , Murashkin E. V. 
Published: April 2020

Abstract
The paper deals with the problem of calculation of residual stresses and displacements in functionally graded material under thermal treatment. The investigated multilayered object has a spherical form. The model of thermoelastic plastic deformation is used. The method of construction of analytical solution is proposed and discussed. The distributions of stresses and displacements in the one-dimensional problem of heating a multilayer sphere are obtained and graphically analysed.