bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geochemistry π: Automated Machine Learning Python Framework for Tabular Data
Authors: ZhangZhou J. , He Can , Sun Jianhao , Zhao Jianming , Lyu Yang , Wang Shengxin , Zhao Wenyu , Li Anzhou , Ji Xiaohui , Agarwal Anant 
Published: January 2024

AbstractAlthough machine learning (ML) has brought new insights into geochemistry research, its implementation is laborious and time‐consuming. Here, we announce Geochemistry π, an open‐source automated ML Python framework. Geochemists only need to provide tabulated data and select the desired options to clean data and run ML algorithms. The process operates in a question‐and‐answer format, and thus does not require that users have coding experience. After either automatic or manual parameter tuning, the automated Python framework provides users with performance and prediction results for the trained ML model. Based on the scikit‐learn library, Geochemistry π has established a customized automated process for implementing classification, regression, dimensionality reduction, and clustering algorithms. The Python framework enables extensibility and portability by constructing a hierarchical pipeline architecture that separates data transmission from the algorithm application. The AutoML module is constructed using the Cost‐Frugal Optimization and Blended Search Strategy hyperparameter search methods from the A Fast and Lightweight AutoML Library, and the model parameter optimization process is accelerated by the Ray distributed computing framework. The MLflow library is integrated into ML lifecycle management, which allows users to compare multiple trained models at different scales and manage the data and diagrams generated. In addition, the front‐end and back‐end frameworks are separated to build the web portal, which demonstrates the ML model and data science workflow through a user‐friendly web interface. In summary, Geochemistry π provides a Python framework for users and developers to accelerate their data mining efficiency with both online and offline operation options.
Explainable Offline‐Online Training of Neural Networks for Parameterizations: A 1D Gravity Wave‐QBO Testbed in the Small‐Data Regime
Authors: Pahlavan Hamid A. , Hassanzadeh Pedram , Alexander M. Joan 
Published: January 2024

AbstractThere are different strategies for training neural networks (NNs) as subgrid‐scale parameterizations. Here, we use a 1D model of the quasi‐biennial oscillation (QBO) and gravity wave (GW) parameterizations as testbeds. A 12‐layer convolutional NN that predicts GW forcings for given wind profiles, when trained offline in abig‐dataregime (100‐year), produces realistic QBOs once coupled to the 1D model. In contrast, offline training of this NN in asmall‐dataregime (18‐month) yields unrealistic QBOs. However, online re‐training of just two layers of this NN using ensemble Kalman inversion and only time‐averaged QBO statistics leads to parameterizations that yield realistic QBOs. Fourier analysis of these three NNs' kernels suggests why/how re‐training works and reveals that these NNs primarily learn low‐pass, high‐pass, and a combination of band‐pass filters, potentially related to the local and non‐local dynamics in GW propagation and dissipation. These findings/strategies generally apply to data‐driven parameterizations of other climate processes.
Improving Estimates of Land–Atmosphere Coupling Through a Novel Framework of Land Aridity Classification
Authors: Shan Yufeng , Wei Jiangfeng , Zan Beilei 
Published: January 2024

AbstractThe evapotranspiration (ET) regime is an illustration of the water‐energy interactions at the land surface and is important for regional climate. In this study, we propose a revised framework for land aridity classification based on the ET regime and the conditional mutual information method. The proposed framework effectively captures the influences of short‐term water and energy supply on ET and highlights their potential roles in extreme events. This framework can be a supplement to the traditional classification schemes that rely on long‐term mean climate. Furthermore, we examine the sensitivity of this land aridity framework to different model physics parameterization schemes. The cumulus schemes are found to have the most important impact, followed by the radiation and microphysics schemes, while the planetary boundary layer schemes have the weakest impact. These findings provide valuable insights for the identification of land aridity and its relationship with land–atmosphere interactions.
Detection of Earthquake Infragravity and Tsunami Waves With Underwater Distributed Acoustic Sensing
Authors: Xiao Han , Spica Zack J. , Li Jiaxuan , Zhan Zhongwen 
Published: January 2024

AbstractUnderwater Distributed Acoustic Sensing (DAS) utilizes optical fiber as a continuous sensor array. It enables high‐resolution data collection over long distances and holds promise to enhance tsunami early warning capabilities. This research focuses on detecting infragravity and tsunami waves associated with earthquakes and understanding their origin and dispersion characteristics through frequency‐wavenumber domain transformations and beamforming techniques. We propose a velocity correction method based on adjusting the apparent channel spacing according to water depth to overcome the challenge of detecting long‐wavelength and long‐period tsunami signals. Experimental results demonstrate the successful retrieval of infragravity and tsunami waves using a subsea optical fiber in offshore Oregon. These findings underscore the potential of DAS technology to complement existing infragravity waves detection systems, enhance preparedness, and improve response efforts in coastal communities. Further research and development in this field are crucial to fully utilize the capabilities of DAS for enhanced tsunami monitoring and warning systems.
A New Post‐Hoc Method to Reduce the Energy Imbalance in Eddy Covariance Measurements
Authors: Zhang Weijie , Nelson Jacob A. , Miralles Diego G. , Mauder Matthias , Migliavacca Mirco , Poyatos Rafael , Reichstein Markus , Jung Martin 
Published: January 2024

AbstractLatent and sensible heat flux observations are essential for understanding land–atmosphere interactions. Measurements from the eddy covariance technique are widely used but suffer from systematic energy imbalance problems, partly due to missing large eddies from sub‐mesoscale transport. Because available energy drives the development of large eddies, we propose an available energy based correction method for turbulent flux measurements. We apply our method to 172 flux tower sites and show that we can reduce the energy imbalance from −14.99 to −0.65 W m−2 on average, together with improved consistency between turbulent fluxes and available energy and associated increases in r2 at individual sites and across networks. Our results suggest that our method is conceptually and empirically preferable over the method implemented in the ONEFlux processing. This can contribute to the efforts in understanding and addressing the energy imbalance issue, which is crucial for the evaluation and calibration of land surface models.
Pn Velocity and Anisotropy Tomography With Nonuniform Grid Beneath the Ryukyu–Taiwan–Philippines Region
Authors: He Yuhui , Lü Yan 
Published: January 2024

AbstractTo enhance our comprehension of the dynamic processes associated with complex plate subduction, volcanic magmatism, and lithosphere deformation beneath the Ryukyu–Taiwan–Philippines region, we utilized nonuniform inversion grids for Pn velocity and anisotropy tomography, and obtained the uppermost mantle structure of this area. The results demonstrate remarkable characteristics: cold oceanic subducting plates display high Pn velocities, whereas volcanic arcs, the extinct mid‐ocean ridge in the South China Sea, and the Palawan region exhibit low Pn velocities. The extinct mid‐ocean ridge also displays a low‐velocity anomaly, indicating that residual heat persists even after approximately 15 million years since seafloor spreading. The occurrence of a discontinuous low‐velocity beneath the Ryukyu arc supports the presence of a slab window at approximately 123°E. The volcanic arcs of all subduction zones within the study area displayed trench‐parallel Pn anisotropy. The observed Pn fast directions beneath the Taiwan orogenic belt are consistent with crustal anisotropy, providing evidence for the crust–mantle coupled deformation. Moreover, our results shed light on the deep structural characteristics of the complex subduction zones beneath the Philippines region. Plate subduction causes partial melting due to dehydration; then, the melt ascends and accumulates at the uppermost mantle, showing low Pn velocities. However, the low‐velocity anomaly is not widely distributed but corresponds to a narrow band. In particular, the east–west bidirectional subduction of the Philippines and Negros formed separate low‐velocity anomalies. Low Pn velocities and trench‐parallel anisotropy indicate the location of different subduction zones and finely characterize their impact on the uppermost mantle structure.
The Global Overturning Circulation and the Role of Non‐Equilibrium Effects in ECCOv4r4
Authors: Monkman Tatsu , Jansen Malte F. 
Published: January 2024

AbstractWe quantify the volume transport and watermass transformation rates of the global overturning circulation using the Estimating the Circulation and Climate of the Ocean version 4 release 4 (ECCOv4r4) reanalysis product. The ECCO solution shows large rates of intercell exchange between the mid‐depth and abyssal cells, consistent with other recent inferences. About 10 Sv of North Atlantic deep water enters the abyssal cell in the Southern Ocean and is balanced by a similar amount of apparrent diapycnal upwelling in the Indo‐Pacific. However, much of the upwelling in ECCO's deep ocean is not associated with irreversible watermass transformations, as typically assumed in theoretical models. Instead, a dominant portion of the abyssal circulation in ECCO is associated with isopycnal volume tendencies, reflecting a deep ocean in a state of change and a circulation in which transient tendencies play a leading role in the watermass budget. These volume tendencies are particularly prominent in the Indo‐Pacific, where ECCO depicts a cooling and densifying deep ocean with relatively little mixing‐driven upwelling, in disagreement with recent observations of deep Indo‐Pacific warming trends. Although abyssal ocean observations are insufficient to exclude the trends modeled by ECCO, we note that ECCO's parameterized diapycnal mixing in the abyssal ocean is much smaller than observational studies suggest and may lead to an under‐representation of Antarctic Bottom Water consumption in the abyssal ocean. Whether or not ECCO's tendencies are realistic, they are a key part of its abyssal circulation and hence need to be taken into consideration when interpreting the ECCO solution.
A Comparison of Laboratory and Field Measurements of Whitecap Foam Evolution From Breaking Waves
Authors: Callaghan A. H. , Deane G. B. , Stokes M. Dale 
Published: January 2024

AbstractSufficiently energetic breaking ocean waves produce distinctive visible foam signatures on the water surface called whitecaps. The mixture of surface whitecap foam cells, and sub‐surface bubbles, results in the broad‐band scattering of light that allow whitecaps to be measured with optical cameras. In this paper the temporal evolution of whitecap foam area from laboratory and oceanic breaking waves is compared. When appropriately scaled, the foam area time series for both laboratory and oceanic breaking waves follow similar trends, despite occurring in vastly different settings. Distinct similarities of the signature of foam stabilization due to the presence of surfactants in the controlled laboratory experiments are also found in the field suggesting foam stabilization may be a means to remotely sense the presence/absence or concentration of surfactants in the ocean. In addition, probability density distributions of key whitecap variables such as foam area growth and decay timescales and maximum foam area are compared between laboratory and oceanic whitecaps. The oceanic whitecaps are much larger in scale than the laboratory breaking waves, whereas the whitecap growth and decay timescales are similar in magnitude, the latter suggesting that the depths to which bubbles are injected during active air entrainment in the field are relatively shallow. The aggregated whitecap statistics are used to estimate the energy dissipation of individual whitecaps in a novel manner.
Radiative and Microphysical Impacts of the Saharan Dust on Two Concurrent Tropical Cyclones: Danielle and Earl (2010)
Authors: Pan Bowen , Wang Yuan , Lin Yun , Hsieh Jen‐Shan , Lavallee Michael , Zhao Lijun , Zhang Renyi 
Published: January 2024

AbstractSaharan dust exerts profound impacts on the genesis and intensification of tropical cyclones (TCs). Such impacts on various stages of the TCs have yet to be explored. In this study, we utilize the Cloud‐Resolving weather research and forecasting model (WRF) to investigate the relative importance of the microphysical and radiative effects of dust on two hurricanes (Earl and Danielle) at different life stages under similar dynamical conditions in 2010. Both TCs were embedded in a dusty environment throughout their lifetime. A new dust ice nucleation scheme was implemented into the aerosol‐aware Texas A&M University two‐moment microphysical scheme in WRF. Moreover, the dust radiative effect was included in the Goddard Shortwave Scheme of WRF. Our sensitivity experiments show that the radiative effect of dust (DRAD) amplified the mid‐level ridge in the Central Atlantic Ocean through temperature perturbation, changing the tracks of Danielle and Earl. Further analyses reveal an early shift of Danielle's maximum intensity for 12 hours but a significantly suppressed Earl in DRAD. In addition, the microphysical effect of dust had little impact on the large‐scale dynamical fields and storm tracks. The inclusion of dust as ice nucleation particles results in more variations in the intensity of Danielle and Earl than in other scenarios. This is owing to the higher maximum diabatic heating rate in the rainband region that perturbs the size of the TC. This study shows the dominant dust radiative effects on both intensity and track of the storm. In addition, there is evidence that dust suppresses the early stage TC but provides favorable conditions for matured TC. Both findings have profound implications for hurricane forecast and address the importance of accounting for detailed cloud microphysics and aerosol‐TC interactions in the operational forecasting models.
Designing a Convection‐Cloud Chamber for Collision‐Coalescence Using Large‐Eddy Simulation With Bin Microphysics
Authors: Wang Aaron , Ovchinnikov Mikhail , Yang Fan , Schmalfuss Silvio , Shaw Raymond A. 
Published: January 2024

AbstractCollisional growth of cloud droplets is an essential yet uncertain process for drizzle and precipitation formation. To improve the quantitative understanding of this key component of cloud‐aerosol‐turbulence interactions, observational studies of collision‐coalescence in a controlled laboratory environment are needed. In an existing convection‐cloud chamber (the Pi Chamber), collisional growth is limited by low liquid water content and short droplet residence times. In this work, we use numerical simulations to explore various configurations of a convection‐cloud chamber that may intensify collision‐coalescence. We employ a large‐eddy simulation (LES) model with a size‐resolved (bin) cloud microphysics scheme to explore how cloud properties and the intensity of collision‐coalescence are affected by the chamber size and aspect ratio, surface roughness, side‐wall wetness, side‐wall temperature arrangement, and aerosol injection rate. Simulations without condensation and evaporation within the domain are first performed to explore the turbulence dynamics and wall fluxes. The LES wall fluxes are used to modify the Scalar Flux‐budget Model, which is then applied to demonstrate the need for non‐uniform side‐wall temperature (two side walls as warm as the bottom and the two others as cold as the top) to maintain high supersaturation in a tall chamber. The results of LES with full cloud microphysics reveal that collision‐coalescence is greatly enhanced by employing a taller chamber with saturated side walls, non‐uniform side‐wall temperature, and rough surfaces. For the conditions explored, although lowering the aerosol injection rate broadens the droplet size distribution, favoring collision‐coalescence, the reduced droplet number concentration decreases the frequency of collisions.
Effects of Along‐Trench Asymmetric Subduction Initiation on Plate Rotation and Trench Migration: A Laboratory Modeling Perspective
Authors: Wang Chunyang , Ding Weiwei , Schellart Wouter P. , Tong Zhengyi , Dong Chongzhi , Fang Yinxia , Li Jiabiao 
Published: January 2024

AbstractThe impact of along‐trench asymmetric subduction on plate kinematic evolution (e.g., plate rotation and trench migration) remains enigmatic. In this study, analog experiments were performed to investigate the effects of symmetric and asymmetric subduction initiation on slab kinematics and trench migration. In cases when subduction was started with a cylindric slab perturbation, the plate showed little rotation during the entire subduction process, resulting in a trench shape that was symmetric with respect to the center‐line of the plate. However, if subduction started with a non‐cylindrical slab perturbation, the trench shape changed substantially. During the free sinking stage, the more deeply subducted part of the slab had a higher trench‐normal retreat velocity (VT⊥) and subduction velocity (VS⊥) than the shallow part, which induced trench and plate rotations in the same direction. This along‐trench gradient in VT⊥ increased until the deeper portion of the slab tip first touched the bottom, after which a marked decrease in VS⊥ occurred at this location; the other side of the slab had not yet reached the bottom, so experienced no recorded reduction of subduction velocity at this time. This along‐strike diachronous arrival of the slab tip could induce a marked along‐strike reversal in magnitude of the subduction velocity and a rotation torque centered on the point of first contact between slab and 660‐km discontinuity. This could lead to instability and rotation of the subducting slab, potentially causing a reversal in the direction of trench rotation direction, but rarely in the direction of plate rotation. Our modeling results may provide useful understanding for the processes driving the rotations of the trench and plate in natural subduction zones.
Underthrusting of Tarim Lower Crust Beneath the Tibetan Plateau Revealed by Receiver Function Imaging
Authors: Wu Chenglong , Xu Tao , Tian Xiaobo , Mitchell Ross N. , Lin Jiyan , Yang Jianfeng , Wang Xin , Lu Zhanwu 
Published: January 2024

AbstractThe left‐lateral Altyn Tagh Fault (ATF) system is the northern boundary of the Tibetan Plateau resulted from the India–Eurasia continental collision. How intracontinental deformation across the central ATF responds to the distal collision remains elusive, primarily due to unclear crustal structure. We obtained detailed crustal structure across the central ATF using receiver functions recorded by ∼NW–SE oriented linear dense array. The images reveal the Tarim lower crust is underthrusting beneath the Tibetan Plateau and reaches to a maximum depth of ∼75 km and undergoing partial eclogitization. The two south‐dipping interfaces imaged beneath the Altyn Tagh Range (ATR) represent the thrusting Northern Altyn Fault and its branch fault. Oblique convergent forces extruded upper crustal materials along the thrust faults, creating the pop‐up structure of ATR, supported by low Vp/Vs ratios. Our balanced cross‐section for the Moho suggests intracontinental deformation in the ATR has accelerated since the late Miocene.
Data-driven connectivity profiles relate to smoking cessation outcomes
Authors: Murray Laura , Frederick Blaise B. , Janes Amy C. 
Published: January 2024

AbstractAt a group level, nicotine dependence is linked to differences in resting-state functional connectivity (rs-FC) within and between three large-scale brain networks: the salience network (SN), default mode network (DMN), and frontoparietal network (FPN). Yet, individuals may display distinct patterns of rs-FC that impact treatment outcomes. This study used a data-driven approach, Group Iterative Multiple Model Estimation (GIMME), to characterize shared and person-specific rs-FC features linked with clinically-relevant treatment outcomes. 49 nicotine-dependent adults completed a resting-state fMRI scan prior to a two-week smoking cessation attempt. We used GIMME to identify group, subgroup, and individual-level networks of SN, DMN, and FPN connectivity. Regression models assessed whether within- and between-network connectivity of individual rs-FC models was associated with baseline cue-induced craving, and craving and use of regular cigarettes (i.e., “slips”) during cessation. As a group, participants displayed shared patterns of connectivity within all three networks, and connectivity between the SN-FPN and DMN-SN. However, there was substantial heterogeneity across individuals. Individuals with greater within-network SN connectivity experienced more slips during treatment, while individuals with greater DMN-FPN connectivity experienced fewer slips. Individuals with more anticorrelated DMN-SN connectivity reported lower craving during treatment, while SN-FPN connectivity was linked to higher craving. In conclusion, in nicotine-dependent adults, GIMME identified substantial heterogeneity within and between the large-scale brain networks. Individuals with greater SN connectivity may be at increased risk for relapse during treatment, while a greater positive DMN-FPN and negative DMN-SN connectivity may be protective for individuals during smoking cessation treatment.
Electrophysiological signatures of anxiety in Parkinson’s disease
Authors: Yassine Sahar , Almarouk Sourour , Gschwandtner Ute , Auffret Manon , Fuhr Peter , Verin Marc , Hassan Mahmoud 
Published: January 2024

AbstractAnxiety is a common non-motor symptom in Parkinson’s disease (PD) occurring in up to 31% of the patients and affecting their quality of life. Despite the high prevalence, anxiety symptoms in PD are often underdiagnosed and, therefore, undertreated. To date, functional and structural neuroimaging studies have contributed to our understanding of the motor and cognitive symptomatology of PD. Yet, the underlying pathophysiology of anxiety symptoms in PD remains largely unknown and studies on their neural correlates are missing. Here, we used resting-state electroencephalography (RS-EEG) of 68 non-demented PD patients with or without clinically-defined anxiety and 25 healthy controls (HC) to assess spectral and functional connectivity fingerprints characterizing the PD-related anxiety. When comparing the brain activity of the PD anxious group (PD-A, N = 18) to both PD non-anxious (PD-NA, N = 50) and HC groups (N = 25) at baseline, our results showed increased fronto-parietal delta power and decreased frontal beta power depicting the PD-A group. Results also revealed hyper-connectivity networks predominating in delta, theta and gamma bands against prominent hypo-connectivity networks in alpha and beta bands as network signatures of anxiety in PD where the frontal, temporal, limbic and insular lobes exhibited the majority of significant connections. Moreover, the revealed EEG-based electrophysiological signatures were strongly associated with the clinical scores of anxiety and followed their progression trend over the course of the disease. We believe that the identification of the electrophysiological correlates of anxiety in PD using EEG is conducive toward more accurate prognosis and can ultimately support personalized psychiatric follow-up and the development of new therapeutic strategies.