bluuebunny/crossref_metadata_2025_split huggingface dataset:
Partitioning the Export of Distinct Biogenic Carbon Pools in the Northeast Pacific Ocean Using a Biogeochemical Profiling Float
Authors: Huang Yibin , Fassbender Andrea J. , Long Jacqueline S. , Johannessen Sophia , Bernardi Bif Mariana 
Published: January 2022

AbstractWe leverage observations from chemical and bio‐optical sensors mounted on a biogeochemical profiling float in the Northeast Pacific Ocean to quantify the cycling and export potential of distinct biogenic carbon pools, including particulate inorganic carbon (PIC), particulate organic carbon (POC), and dissolved organic carbon (DOC). Year‐round observations reveal complex carbon cycle dynamics among these carbon pools. Net DOC production peaked during bloom initiation, about 3 months prior to the summer peak in POC production. We validate the float estimates of DOC cycling with seasonal accumulation and removal rates derived from ship‐board DOC observations over the same period. By combining chemical and bio‐optical tracers of POC cycling, we estimate the instantaneous POC sinking flux (). The cooccurrence of DOC consumption and POC production and sinking during fall and winter resolves the regional conundrum of a persistent particle sinking flux observed by sediment traps during a season that is known to be heterotrophic. PIC production is small, and uncertainties are large. By combining float‐based estimates of instantaneous net primary production (NPP) and , we quantify a real‐time carbon export ratio ([/NPP] × 100%) for the euphotic zone. Elevated export ratios during summer are associated with an increase in the fraction of particles larger than 100 μm in size. Elevated export ratios during winter are associated with the physical redistribution of particles through seasonal deep mixing. Our study demonstrates how the combined use of multiple sensors on biogeochemical profiling floats can provide more nuanced information about upper ocean carbon cycle dynamics.
Volcanism‐Triggered Climatic Control on Late Cretaceous Oceans
Authors: Sun Ruiyang , Yao Hanwei , Deng Changzhou , Grasby Stephen E. , Wang Chengshan , Chen Xi , Yin Runsheng 
Published: January 2022

AbstractDuring the Late Cretaceous, Earth's climate oscillated between warm and cool states, and global oceans changed between anoxic and oxic conditions, resulting in black/gray shales and oceanic red beds (ORBs) deposition, respectively. To understand such climate/ocean dynamics, this study investigated bulk Hg and Hg isotopes, as well as Fe3+/Fe2+ in Upper Cretaceous sediments deposited in southern Tibet and the North Atlantic. In both areas, black/gray shales show much higher Hg concentrations than ORBs, indicating enhanced Hg flux to global oceans during time of black/gray shale deposition. Black/gray shales show lower Fe3+/Fe2+ and positive Δ199Hg, suggesting a significant input of Hg into the anoxic/dysoxic ocean via atmospheric deposition. The isotope values are consistent with a volcanic source for this excess Hg. ORBs show high Fe3+/Fe2+ and negative shifts of Δ199Hg, suggesting that the dominant source of Hg into the oxic oceans was via terrestrial runoff. This study suggests that volcanism was an important driver of the climate/ocean dynamics during the Late Cretaceous.
The Source of Auroral Omegas
Authors: Weygand J. M. , El‐Alaoui M. , Nykyri H. K. 
Published: January 2022

AbstractThe auroral wave‐like structures called “omega bands” appear within the post‐midnight sector auroral oval with shapes resembling the Greek letter omega, and are typically associated with the recovery phase of substorms. Prior work and MHD simulations suggest both high speed earthward flows and post‐midnight flow shears are possible omega band source mechanisms. However, what produces omega bands is not well understood. It is most likely that the paucity of concurrent magnetospheric data has limited our ability to understand fully the mechanism responsible for the generation of the omega bands. We have identified about 263 auroral omegas in seven different THEMIS all sky cameras (ASCs) over a 10 year period. A fraction appear to form from north‐south streamers, but some appear to form from east‐west auroral arcs. Fifty‐one of the 263 Ω also have conjugate or near conjugate THEMIS and GOES spacecraft data. There is evidence in about 80% of these events that high speed earthward flows have occurred prior to or at about the same time as the auroral omega observation. This evidence consists of high speed earthward flows, magnetic field dipolarizations, particle injections into the inner magnetosphere, and auroral streamers. 11 events also show plasma flow data azimuthally along the inner magnetosphere, but for six of these events the Vy component is inconsistent with the auroral omega direction of motion. Of the remaining five events, four have Vy flow shear events but also show evidence of magnetic field dipolarizations, particle injections into the inner magnetosphere, and auroral streamers. Our observations suggest high speed earthward flows are more likely to be the source of auroral omega bands.
The Effect of Fault Roughness and Earthquake Ruptures on the Evolution and Scaling of Fault Damage Zones
Authors: Tal Yuval , Faulkner Daniel 
Published: January 2022

AbstractFault damage zones dominate the mechanical, hydraulic and seismological properties of faults yet the relative contributions from processes leading to their development and growth is obscure. In this study, we investigate the damage development related to slip on rough faults and passage of earthquake ruptures. We compare the cumulative damage with slip and damage distribution from numerical models against field data from exhumed faults with slip less than 3.5 m within the Atacama Fault Zone in northern Chile. Models are constrained by experimentally determined mechanical properties of the host rock. We perform simulations of damage accumulation during quasistatic slip on rough faults and during sequences of earthquakes on planar and rough faults governed by rate and state friction laws. Both sets of simulations include Drucker–Prager rheology of the bulk to identify off‐fault damage where the yield stress is exceeded. Our results indicate that the extent and distribution of damage depend on the characteristics of fault roughness, amount of slip, and, when present, the intensity and variability of dynamic ruptures. When typical values for fault roughness are used, the scaling of damage zone width versus slip during quasistatic slip is comparable to that observed in the field data. Earthquake rupture on smooth faults by itself does not explain the field data. Simulations of earthquake sequences on rough faults leads to significantly larger damage zone widths with slip than that observed in the field data, suggesting the development of damage for small displacement is dominated by quasistatic slip on rough faults.
On the Groupiness and Intermittency of Oceanic Whitecaps
Authors: Malila M. P. , Thomson J. , Breivik Ø. , Benetazzo A. , Scanlon B. , Ward B. 
Published: January 2022

AbstractThe enhancement of wave breaking activity during wave group passage is investigated using coherent field observations of the instantaneous sea surface elevation and whitecap coverage from platform‐based stereo video measurements in the central North Sea. Passing wave groups are shown to be associated with a two to threefold enhancement in the probability distribution of total whitecap coverage W whereas the enhancement of active whitecap coverage WA is approximately fivefold. Breaking time scales and intermittency characteristics are also investigated with the inclusion of a secondary data set of W and WA observations collected during a research cruise in the North Pacific. The time scale analysis suggests a universal periodicity in wave breaking activity within a representative sea‐surface area encompassing approximately one dominant wave crest. The breaking periodicity is shown to be closely linked to the peak period of the dominant wave components, suggesting that long‐wave modulation of wave breaking is a predominant mechanism controlling the intermittency of wave breaking across scales.
Depthwise Soil CO2 Production Is Controlled by Freeze‐Thaw Processes in a Tibetan Alpine Steppe
Authors: Zhang Jianxin , Wei Da , Hong Jiangtao , Wang Xiaodan 
Published: January 2022

AbstractCold ecosystems in regions of high‐latitude and altitude with vast stores of soil organic carbon suffer strong freeze‐thaw cycles, which can greatly affect soil CO2 release. However, on the Tibetan Plateau, where altitude is >4,000 m, it remains unknown how freeze‐thaw processes regulate CO2 production across the soil profile. In this study, we used the gradient method to explore impacts of freeze‐thaw processes on depthwise soil CO2 production in an alpine steppe. We found almost all soil CO2 was produced in the root‐zone layer (<30 cm), while the root‐free layer (>30 cm) frequently alternated between being a source and sink of CO2 and thus acted largely as a buffer. The surface layer (0–15 cm) and subsurface layer (15–30 cm) had a similar CO2 production rate in the thawed period. However, during the freezing‐frozen‐thawing period, the subsurface layer consistently functioned as a weak CO2 source, although parts were trapped in frozen soil, resulting in a weaker CO2 sink in the surface layer. Soil CO2 production in subsurface layer is thus more sensitive to temperature variability compared with surface layer. Furthermore, our results suggest water content plays a more important role than temperature in regulating soil CO2 production. For the first time, our data set reveals the vertical production of CO2 within the seasonally frozen soils on the Tibetan Plateau, which will benefit understanding of belowground carbon processes and modeling of soil CO2 release in the region.
Influences of 3D Sub‐Grid Terrain Radiative Effect on the Performance of CoLM Over Heihe River Basin, Tibetan Plateau
Authors: Zhang Xindan , Huang Anning , Dai Yongjiu , Li Weiping , Gu Chunlei , Yuan Hua , Wei Nan , Zhang Yanlin , Qiu Bo , Cai Shuxin 
Published: January 2022

AbstractSurface solar radiation (SSR), as a primary component of heat budget between land and atmosphere, controls both water and energy exchanges. However, the sub‐grid terrain radiative effect (STRE) which exerts critical influences on SSR simulation is usually extremely simplified or even ignored in most current land surface models (LSMs) due to the heavy computational burden. In this study, we developed a physically realistic and computationally efficient three dimensional (3D) STRE scheme and implemented it into the Common Land Model (CoLM) to indicate its quantitative influences on surface energy budget, land surface temperature (LST), soil temperature, and moisture simulations over the Heihe River Basin, Tibetan Plateau. Results show that the CoLM coupled with 3D‐STRE scheme shows more realistic description of SSR and improves the simulation of soil thermal and moist features at both single‐point and regional scales. Compared to the results without 3D‐STRE, the inclusion of 3D‐STRE scheme efficiently diminishes the overestimation of SSR, which leads to the root mean square error (RMSE) of LST simulation reduced by 17.1% due to significant improvements in valley areas. Adopting 3D‐STRE scheme also improves the pattern and amplitude of temporal variability of simulated soil temperature (moisture) at 37 sites with the mean Taylor score increased by 3.6–3.7% (14.0–14.3%). These results emphasize the importance of considering the 3D‐STRE scheme in LSMs and are significantly helpful to deepen our understanding of surface heat exchanges and improve the representations of land surface processes over complex terrain.
Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients
Authors: Liu Yichuan , Qu Hui-Qi , Mentch Frank D. , Qu Jingchun , Chang Xiao , Nguyen Kenny , Tian Lifeng , Glessner Joseph , Sleiman Patrick M. A. , Hakonarson Hakon 
Published: January 2022

AbstractMental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to complete questionnaires or standardized rating scales for diagnosis. In the past decade, multiple genomic association signals have been reported for mental disorders, some of which present attractive drug targets. Concurrently, machine learning algorithms, especially deep learning algorithms, have been successful in the diagnosis and/or labeling of complex diseases, such as attention deficit hyperactivity disorder (ADHD) or cancer. In this study, we focused on eight common mental disorders, including ADHD, depression, anxiety, autism, intellectual disabilities, speech/language disorder, delays in developments, and oppositional defiant disorder in the ethnic minority of African Americans. Blood-derived whole genome sequencing data from 4179 individuals were generated, including 1384 patients with the diagnosis of at least one mental disorder. The burden of genomic variants in coding/non-coding regions was applied as feature vectors in the deep learning algorithm. Our model showed ~65% accuracy in differentiating patients from controls. Ability to label patients with multiple disorders was similarly successful, with a hamming loss score less than 0.3, while exact diagnostic matches are around 10%. Genes in genomic regions with the highest weights showed enrichment of biological pathways involved in immune responses, antigen/nucleic acid binding, chemokine signaling pathway, and G-protein receptor activities. A noticeable fact is that variants in non-coding regions (e.g., ncRNA, intronic, and intergenic) performed equally well as variants in coding regions; however, unlike coding region variants, variants in non-coding regions do not express genomic hotspots whereas they carry much more narrow standard deviations, indicating they probably serve as alternative markers.
Multi‐scale attention encoder for street‐to‐aerial image geo‐localization
Authors: Li Songlian , Tu Zhigang , Chen Yujin , Yu Tan 
Published: January 2022

AbstractThe goal of street‐to‐aerial cross‐view image geo‐localization is to determine the location of the query street‐view image by retrieving the aerial‐view image from the same place. The drastic viewpoint and appearance gap between the aerial‐view and the street‐view images brings a huge challenge against this task. In this paper, we propose a novel multiscale attention encoder to capture the multiscale contextual information of the aerial/street‐view images. To bridge the domain gap between these two view images, we first use an inverse polar transform to make the street‐view images approximately aligned with the aerial‐view images. Then, the explored multiscale attention encoder is applied to convert the image into feature representation with the guidance of the learnt multiscale information. Finally, we propose a novel global mining strategy to enable the network to pay more attention to hard negative exemplars. Experiments on standard benchmark datasets show that our approach obtains 81.39% top‐1 recall rate on the CVUSA dataset and 71.52% on the CVACT dataset, achieving the state‐of‐the‐art performance and outperforming most of the existing methods significantly.
A low‐power fast‐switching write‐and‐standby shared assist circuit for low‐voltage SRAMs
Authors: Wang Jinn‐Shyan , Liu Chien‐Tung , Liu Zhi‐Rong , Wang Shao‐Zhi , Kang Jyun‐Jiea 
Published: January 2022

AbstractAssist circuitry helps the SRAM to lower the supply voltage VDD to reduce power consumption. Separately designed read, write, and standby assists for low voltage (LV) are not area‐ and power‐efficient. This paper proposes a fast‐switching VDD‐lowering circuit without inducing direct current to achieve a single low‐power write‐and‐standby shared assist circuit. Experimental results verify that the proposed assist can achieve significant power reduction no matter in the write or the standby modes.
Semantically guided self‐supervised monocular depth estimation
Authors: Lu Xiao , Sun Haoran , Wang Xiuling , Zhang Zhiguo , Wang Haixia 
Published: January 2022

AbstractDepth information plays an important role in the vision‐related activities of robots and autonomous vehicles. An effective method to obtain 3D scene information is self‐supervised monocular depth estimation, which utilizes large and diverse monocular video datasets during the training process without the need for ground‐truth data. A novel multi‐task learning strategy that uses semantic information to guide the monocular depth estimation method while maintaining self‐supervision is proposed. An improved differential direct visual odometer (DDVO) combined with Pose‐Net is applied for achieving better pose prediction. Minimum reprojection loss with auto‐masking and semantic masking is used to remove the effects of low‐texture areas and moving dynamic‐class objects within scenes. Concurrently, the semantic masking is introduced into the DDVO pose predictor to filter moving objects and reduce the matching error between monocular sequence frames. In addition, PackNet is employed as the backbone of multi‐task learning to further improve the accuracy of deep prediction. The proposed method produces state‐of‐the‐art results for monocular depth estimation on the KITTI Eigen split benchmark, even outperforming supervised methods that have been trained using ground‐truth depth.
One‐shot learning‐based driver's head movement identification using a millimetre‐wave radar sensor
Authors: Nguyen Hong Nhung , Lee Seongwook , Nguyen Tien‐Tung , Kim Yong‐Hwa 
Published: January 2022

AbstractConcentration of drivers on traffic is a vital safety issue; thus, monitoring a driver being on road becomes an essential requirement. The key purpose of supervision is to detect abnormal behaviours of the driver and promptly send warnings to him/her for avoiding incidents related to traffic accidents. In this paper, to meet the requirement, based on radar sensors applications, the authors first use a small‐sized millimetre‐wave radar installed at the steering wheel of the vehicle to collect signals from different head movements of the driver. The received signals consist of the reflection patterns that change in response to the head movements of the driver. Then, in order to distinguish these different movements, a classifier based on the measured signal of the radar sensor is designed. However, since the collected data set is not large, in this paper, the authors propose One‐shot learning to classify four cases of driver's head movements. The experimental results indicate that the proposed method can classify the four types of cases according to the various head movements of the driver with a high accuracy reaching up to 100%. In addition, the classification performance of the proposed method is significantly better than that of the convolutional neural network (CNN) model.
Green Synthesis of Diaryl Selenides from Arylboronic Acids and Arylseleninic Acids
Authors: Redon Sébastien , Vanelle Patrice , Remusat Vincent 
Published: January 2022

AbstractA new method of deborylative selanylation using arylboronic acids and arylseleninic acids gave diaryl selenoethers and diarylselenoxide. The present approach requires only equimolar arylseleninic acid and led selectively to selenoethers or selenoxides depending on the solvent. The method is metal-free, base- or oxidant-free, efficient, and environmentally friendly.
Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match‐play
Authors: Collins Neil , White Ryan , Palczewska Anna , Weaving Dan , Dalton‐Barron Nicholas , Jones Ben 
Published: January 2022

ABSTRACTThis study aims to (a) quantify the movement patterns during rugby league match‐play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular‐SL), three Super League (semi‐)Finals (final‐SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal–Wallis rank‐sum and Dunn post‐hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of “walk” and “jog” based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal–Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular‐SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match‐play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands.Highlights
This study shows that movement patterns and movement units can be used to investigate team sports through the application of the SMP framework
One hundred and twenty‐one movement patterns were found to be present within rugby league match‐play, with the walk‐ and jog‐based movement units most prevalent. No movement pattern was unique to a single competition level.
Further analysis revealed that the majority of movement units analysed had significant differences between international and domestic rugby league, whereas only four movement units (i.e. f,m,n,q) had significant differences within the two domestic rugby league levels.
International rugby league had higher occurrences of the movement patterns consisting of higher velocity movement units (ie. T,S,y). This suggests that international rugby league players may need greater high velocity exposure in training.