Gradient Components Research Articles

Causal Hierarchy in the Financial Market Network-Uncovered by the Helmholtz-Hodge-Kodaira Decomposition.

Granger causality can uncover the cause-and-effect relationships in financial networks. However, such networks can be convoluted and difficult to interpret, but the Helmholtz-Hodge-Kodaira decomposition can split them into rotational and gradient components which reveal the hierarchy of the Granger causality flow. Using Kenneth French's business sector return time series, it is revealed that during the COVID crisis, precious metals and pharmaceutical products were causal drivers of the financial network. Moreover, the estimated Granger causality network shows a high connectivity during the crisis, which means that the research presented here can be especially useful for understanding crises in the market better by revealing the dominant drivers of crisis dynamics.

Machine learning based analysis of entropy production and wall shear stress in blood flow through stenosed artery

The building up of cholesterol and various substances on the inner boundary of arterial walls forms a plaque (stenosis), which results in the narrowing of walls of arteries, and this exerts additional stress on the walls. Shear stress at the wall of arteries may cause the formation of plaque, plaque growth, and expansive arterial remodeling, and it may also result in an increased risk of plaque rupture. The purpose of this research work is to use machine learning approaches to analyze the wall shear stress and entropy generation through irreversible processes of blood flow in a porous stenosed artery within the context of magnetohydrodynamic consideration. As a way of illustrating blood’s non-Newtonian behavior, the Casson fluid model is used. A blood flow model in the context of mild stenosis has been developed, and it has subsequently been computationally addressed using an explicit finite difference method. The velocity, temperature, entropy generation, Bejan number, and wall shear stress are visualized for different values of pertinent variables. The result reflects the increased velocity in the stenosed region. A hybrid machine learning method using artificial neural network and particle swarm optimization is implemented to optimize the entropy generation and wall shear stress. The network is trained using Stochastic gradient–descent training procedure as well as Levenberg–Marquardt training procedure, and the outcomes of both training procedures are compared. Using this machine learning process, the minimum entropy production has been found for specific values of the Hartmann number, dimensionless temperature difference, and pulsatile component of pressure gradient. This machine learning-based optimization approach enhances the ability to forecast quantitative changes in affecting parameters, which will contribute to minimized damage to the arterial wall, improved blood flow efficiency and the delivery of necessary components to tissues.

Feasibility of Induced Magnetic Gradient Surveying for Seepage Detection in Earth-filled Dams: Insights from Synthetic and Field Studies

Seepage is a common hydrogeological hazard in engineering. Determining the seepage paths is vital for de-risking the instability of embankment structures. With the improvement of the acquisition accuracy of magnetic sensors, the magnetometric resistivity method has become an emerging technology for detecting seepage paths through earth-filled dams. This technique is non-destructive and gives prominent signals. However, the resulting magnetic data have seen ambiguity in fully determining the targets. We propose an induced magnetic gradient surveying approach to monitor seepage paths in earth-filled dams. First, we briefly review the electromagnetic theory for the magnetic gradient tensor based on Maxwell’s equations. To match against the measurements, we present an accurate modeling framework using the third-order finite element method and a novel compact difference scheme. We verify our approach on both semi-analytical 1D and 3D models. Systematic modeling studies are then carried out to investigate the spatial distribution characteristics and sensitivities of the induced magnetic gradient to the seepage in typical dam scenarios. In addition, we conducted two field experiments in the Zhongmou experimental base and Xixiayuan Reservoir in Henan Province, China,respectively. The induced magnetic field vector and its gradient components were both acquired. Cross-validation with a-priori geological information shows that the seepage path can be spatially identified by the induced magnetic gradient components Byy, Byz, Bzy, and Bzz while the field components failed to locate the seepage pathways. This successful application indicates that the proposed approach could be a promising solution for seepage path discrimination in earth-filled dams with high resolution.

A Quantitative Study of How Effective the Transformed Gravity Gradient Tensor is for Subway Tunnel Imaging

We investigate the efficacy of spatial frequency filtering in improving gravity inversion when gravity gradient data are unavailable. The technique simulates gravity gradient data from gravity readings by extracting distinct frequency components. Previous research shows that the joint inversion of gravity and gradient data derives accurate density models. Given the lack of gradient instruments, the potential of frequency filtering to enhance inversions is explored. A series of inversion experiments are conducted using synthetic and field-measured gravity data. The research aims to determine if filtered gradient data, transformed from gravity data, can enhance inversion results compared to using gravity alone. Synthetic models assess the filter, showing that low-pass filtering at an optimal cutoff enhances the correlation between transformed and forward-modeled gradient components. Inversions using transformed gradients consistently outperform those with only gravity. Component combinations and cutoff wavelengths must be optimized to achieve the best reconstruction. Applying the method to Beijing subway tunnel gravity readings, gravity and transformed Uzz gradient data are combined to detail underground double tunnels. The information agrees with engineering data, validating the approach for improving inversions, especially for shallow, large targets. This work establishes the practicality of frequency filtering when direct gradients cannot be measured, contributing valuable insights into better characterizing geology through enhanced inversion. Findings imply improved interpretation; particularly where gradient acquisition proves difficult.

A new approach to explaining nano-bubbles paradoxical longevity

It has been established experimentally that nano-bubbles exist in water for weeks, even months. This contradicts the theory that predicts life span for such small bubbles being on the scale of milliseconds. Nano-bubbles are charged due to adsorption of OH- ions, which creates electric double layers (EDL) at their interfaces. Suggestion has been made that EDL could be responsible for nano-bubbles longevity, but the mechanism remains unknown. We propose such a mechanism here. There is one overlooked feature of the EDL – water molecules in the first layer at interface are oriented, which is supported by many experiments and theory overviewed here. EDL electric field has a gradient component, which exerts force on these oriented molecules dipole moments. We show that it is practically equal to the Young-Laplace force but opposite in direction. It ensures balance of normal forces at interface and creates a pressure gradient that prevents leakage diffusion flux from the stable bubble. In addition, oriented water dipole moments repel each other. This effect is similar to the repulsion of surfactant polar groups, which are known to counterbalance surface tension in tangential direction and stabilize bubbles. Oriented water molecules should cause the same effect. Balance of forces acting on the bubble interface leads to the equation for the stable bubble size that agrees with experimental trends.

Quantitative characterization of bubble stability of foam concrete throughout extrusion process: From yield stress, viscosity and surface tension point of view

Foam concrete (FC) is suitable to be used as printing ink for drones in extreme environment because of its light weight, it can reduce the load of drones and improve printing efficiency. Furthermore, since the FC density and thermal insulation performance can be flexibly changed by changing the bubble content, it can be used to print functional gradient components and special-shaped insulation walls. The stability of bubbles is crucial as it directly impacts the performance of 3D printed FC (3DPFC). Here, we examined the bubble destabilization and deformation of FC throughout the mixing process, resting period prior to extrusion, and extrusion process based on three parameters, i.e., yield stress, viscosity, and surface tension. The results indicate that increasing the yield stress from 1406 Pa to 13379 Pa of the precursor leads to a decrease in bubble volume fraction after mixing from 38.26 % to 27.24 %, while increasing viscosity from 2.16 Pa s to 6.65 Pa s and decreasing surface tension from 72.4 mN/m to 33.5 mN/m are favorable for improving the sphericity of bubbles with the diameter between 300 and 800 μm in FC. In the resting stage, the yield stress of the interstitial paste is the primary factor controlling bubble stability. When the initial yield stress of the equivalent interstitial paste is 5212 Pa, the bubble volume fraction decreases by only 0.8 % within 60 min. During extrusion, high yield stress leading to bubble deformation and instability, whereas viscosity and pore solution surface tension act as sources of bubble compression resistance. There exists a suitable diameter interval for bubble pressure-bearing limit under different paste environment during extrusion.

Improved gravity field estimation by incorporating the Tiangong Space Station and next-generation CAI satellite gravity mission

The next-generation gravity satellite mission equipped with the Cold Atom Interferometry (CAI) gradiometer has great potential for the Earth's gravity field estimation. Deploying a CAI gradiometer on the Chinese Tiangong Space Station launched for long-term Earth science research not only reduces the cost compared to a dual-satellite constellation but also enhances interdisciplinary collaboration in the Earth's gravity field detection. In this study, we conducted gravity gradient-based simulations to assess the contribution of deploying a CAI gradiometer on the Tiangong Space Station to collaboratively observe the Earth's gravity field with a polar-orbit gravity satellite. The simulation results demonstrate that whether utilizing Vyy component, three diagonal components or full components, the derived gravity field models show significant improvements within 100 degree and above 200 degree after incorporating Tiangong Space Station. In particular, the gravity field solution recovered from three diagonal components achieves the best accuracy. In the case of using diagonal components, the collaboration observation scheme effectively reduced the cumulative geoid height error by approximately 5.3cm (300 d/o). In the spatial domain, the incorporation of the Tiangong Space Station primarily impacts the estimated gravity field within the orbital coverage area of the space station, and this effect is particularly pronounced when just employing Vyy component. However, due to the limitation of angular velocity observation inaccuracy associated with the CAI gradiometer in nadir mode, there is no substantial accuracy improvement observed above 200 degree when adding gradient components.

Crystal plasticity finite element study on the microstructure and orientations evolution of {100} columnar grains in electrical steels

Most of the electrical steel slabs are composed of {100} columnar grains. After hot rolling, there is a texture gradient across the thickness. The surface shear textures (Goss texture{110}<100>, Brass texture{110}<112>, Copper texture{112}<111>) and certain <001>//ND fiber textures after hot rolling can be inherited into the finished sheet. The volume fraction and distribution of these textures after cold rolling significantly influence the magnetic properties. Therefore, a full-field crystal plasticity finite element method (CPFEM) was employed to simulate the evolution of microstructure and orientations of {100} columnar grains under plane strain compression and an additional displacement gradient component L13. Through qualitative and quantitative analysis of the simulated microstructure, it was found that under plane strain compression, {100}<110> grains were the most stable, followed by {100}<001> grains. Nearly {100}<021> orientation rotated towards {114}<481> orientation at the extremities of the simulation block. The additional displacement gradient component L13 enhanced the rotational effect. At the 45° shear direction and ends of the simulation block, the {110}<110> orientation originated from {100}<001> grains, the nearly {110}<112> orientation formed from {100}<021> grains, and the {112}<111> Copper orientation derived from {100}<110> grains. However, the simulation did not demonstrate the development of Goss shear orientation.

A possible relation between global CO excitation and massive molecular outflows in local ULIRGs

Local ultra-luminous infrared galaxies (ULIRGs) have been observed to host ubiquitous molecular outflows, including the most massive and powerful ever detected. These sources have also exceptionally excited global, galaxy-integrated CO ladders. A connection between outflows and molecular gas excitation has however never been established, since previous multi-J CO surveys were limited in spectral resolution and sensitivity and so they could only probe the global molecular gas conditions. In this work, we address this question using new, ground-based, sensitive heterodyne spectroscopy of multiple CO rotational lines (up to CO(7−6)) in a sample of 17 local ULIRGs. We used the Atacama Pathfinder Experiment (APEX) telescope to survey the CO(Jup ≥ 4) lines at a high signal-to-noise ratio, and complemented these data with CO(Jup ≤ 3) APEX and Atacama Large Millimeter Array (ALMA and ACA) observations presented in Montoya Arroyave et al. (2023, A&amp;A, 673, A13). We detected a total of 74 (out of 75) CO lines, with up to six transitions per source. The resulting CO spectral line energy distributions (SLEDs) show a wide range in gas excitation, in agreement with previous studies on ULIRGs. Some CO SLEDs peak at Jup ∼ 3, 4, which we classify as “lower excitation”, while others plateau or keep increasing up to the highest-J CO transition probed, and we classify these as “higher excitation”. Our analysis includes for completeness the results of CO SLED fits performed with a single large velocity gradient component, but our main focus is the investigation of possible links between global CO excitation and the presence of broad and/or high-velocity CO spectral components that can contain outflowing gas. We discovered an increasing trend of line width as a function of Jup of the CO transition, which is significant at the 4σ level and appears to be driven by the eight sources that we classified as higher excitation. We further analyzed such higher-excitation ULIRGs, by performing a decomposition of their CO spectral profiles into multiple components, and we derived CO ladders that are clearly more excited for the spectral components characterized by higher velocities and/or velocity dispersion. Because these sources are known to host widespread molecular outflows, we favor an interpretation whereby the highly excited CO-emitting gas in ULIRGs resides in galactic-scale massive molecular outflows whose emission fills a large fraction of the beam of our APEX high-J CO observations. On the other hand, our results challenge alternative scenarios for which the high CO excitation in ULIRGs can be explained by classical component of the interstellar medium, such as photon- or X-ray dominated regions around the nuclear sources.

Linear dynamics of a thick liquid layer subjected to an oblique temperature gradient

The present study aims to demonstrate the application of the oblique temperature gradient (OTG) to manipulate the buoyancy instabilities and resulting mixing. To accomplish this, we consider a model consisting of a liquid layer supported by a perfectly conducting bottom wall from below and the upper surface is exposed to ambient inert gas in a shallow container. The stability analysis employs the pseudospectral method and perturbation energy budget approach. The imposed OTG consists of a negative vertical temperature gradient (VTG), which leads to unstable density stratification, and a negative horizontal temperature gradient (HTG) component responsible for the Hadley circulation, which can be utilised to control instabilities. Without the HTG, a Rayleigh–Bénard mode of instability exists due to the imposed VTG termed as a VTG mode. The imposed HTG induces a linear VTG term and a quintic polynomial VTG term in the bottom wall-normal coordinate $y$ . The induced linear VTG term reinforces the imposed VTG, while the induced quintic polynomial VTG term opposes the imposed VTG. For the vanishing Biot number ( $Bi$ ), the induced quintic VTG term stabilises the VTG mode for the Prandtl number, $Pr=7$ . However, for $Pr=0.01$ , the Reynolds stresses associated with the Hadley circulation destabilise the VTG mode. For non-zero $Bi$ , new streamwise and spanwise instability modes arise for $Pr=7$ due to the induced linear VTG term. Physical arguments show that the unstable density stratification near the gas–liquid interface caused by the synergistic effect of the imposed VTG and the induced linear VTG term lead to the existence of the predicted new modes. The present study thus shows that the strength of the HTG can be utilised to control the instability modes and critical parameters, thereby demonstrating the utility of the OTG in manipulating the buoyancy instabilities.

Submodels of 2-d model of the motion of fluid or gas in a porous medium with an external non-stationary source or absorption

The motion of fluid or gas in a porous medium is the main object of investigation of underground hydromechanics. The model describing this motion was called “Porous medium”.In our paper, we study a general 2-d model of the motion of fluid or gas in porous medium with an external non-stationary source or absorption. As the main research method, we use the method of group (symmetry) analysis, which is one of the most effective ways to obtain information about the properties of solutions to differential equations that define a physical model. A group classification of the differential equation defining studied physical model is carried out. As a result, all basic models with different symmetry properties are obtained. For the basic model, which admits the widest group a classification of all its invariant submodels is performed and all invariant submodels, defined by invariant solutions of rank 1 are studied. All solutions found have physical meaning.The set of explicitly found solutions forms a 47-parametric family of exact solutions. Each solution in this family depends on an arbitrary function defining an external non-stationary source or absorption. For each solution, for the specific values of the parameters on which it depends and for this specific function, we obtained a graph of the pressure distribution.Other solutions are used to describe the movement of a liquid or gas if either the pressure and its rate of change, or the pressure and one of its gradient components, are given at an initial time at a fixed point. The set of these solutions depends on 13 parameters and a function defining an external non-stationary source or absorption. For specific values of this function and specific values of the parameters on which each solution depends, the existence and uniqueness of a solution to the corresponding boundary value problem under some additional conditions has been established. Each such problem is solved numerically. The results of these decisions we reflected in the graphs.The significance of obtained solutions lies in the fact that we have obtained a database consisting of two multiparameter families of invariant solutions of rank 1 of the equation describing the motion of fluid or gas in a porous medium in the presence of an external non-stationary source or absorption. Every solution depends on an empirically determined function. These solutions describe specific physical processes. They can also be used as test solutions in numerical calculations related to the study of the motion of fluid or gas in a porous medium during fluids filtering, engineering surveys in the construction of building structures and in the extraction of shale oil or gas.

ADHD classification with cross-dataset feature selection for biomarker consistency detection

Objective. Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children. While numerous intelligent methods are applied for its subjective diagnosis, they seldom consider the consistency problem of ADHD biomarkers. In practice, these data-driven approaches lead to varying learned features for ADHD classification across diverse ADHD datasets. This phenomenon significantly undermines the reliability of identified biomarkers and hampers the interpretability of these methods. Approach. In this study, we propose a cross-dataset feature selection (FS) module using a grouped SVM-based recursive feature elimination approach (G-SVM-RFE) to enhance biomarker consistency across multiple datasets. Additionally, we employ connectome gradient data for ADHD classification. In details, we introduce the G-SVM-RFE method to effectively concentrate gradient components within a few brain regions, thereby increasing the likelihood of identifying these regions as ADHD biomarkers. The cross-dataset FS module is integrated into an existing binary hypothesis testing (BHT) framework. This module utilizes external datasets to identify global regions that yield stable biomarkers. Meanwhile, given a dataset which waits for implementing the classification task as local dataset, we learn its own specific regions to further improve the performance of accuracy on this dataset. Main results. By employing this module, our experiments achieve an average accuracy of 96.7% on diverse datasets. Importantly, the discriminative gradient components primarily originate from the global regions, providing evidence for the significance of these regions. We further identify regions with the high appearance frequencies as biomarkers, where all the used global regions and one local region are recognized. Significance. These biomarkers align with existing research on impaired brain regions in children with ADHD. Thus, our method demonstrates its validity by providing enhanced biological explanations derived from ADHD mechanisms.

Функционально-воксельное моделирование задачи Коши

The paper considers an approach to solving the Cauchy problem for an example of a partial differential equation of the first order under given boundary conditions by the functional voxel method (FVM). The proposed approach uses the accumulated experience of differentiation and integration into FV- modeling to obtain local geometric characteristics of triangular elements on the surface of the resulting function in the process of linear approximation. The analytical solution of a simple example of a partial differential equation of the first order for the Cauchy problem is analyzed. Based on the obtained analytical solution, FV-model is constructed for further comparison with the results obtained by means of FV-modeling. The algorithm for solving the example is described by means of FV-modeling. A visual and numerical comparative analysis is carried out to determine the difference between the obtained results of FV-modeling and the accepted standard. The main difference between solving such a problem by numerical methods is the results obtained. In numerical methods, the result is the value of the function at the approximation nodes, and the FV-model at the nodes contains local geometric characteristics (gradient components in a space enlarged by one), which makes it possible to obtain a nodal local function of an implicit form, as well as a differential local function of an explicit form. The proposed graphical representation of the function area on a computer provides not only visual visibility, but also compact storage compared to a traditional array of real numbers.

Continental Hotspots Tracks From an Analysis of GOCE Gravity Gradients Data

AbstractThis study aims to detect residual thermal anomalies along the path of a hotspot beneath the continental lithosphere using gradiometry data. We calculate perturbations in gravity vectors and gradients by employing a simple thermal anomaly model. The results highlight that the horizontal components of Bouguer gravity gradients, sensitive to source structure and elongation, exhibit substantial magnitudes, exceeding current detection levels. To improve signals from sources of different sizes and orientations, we apply a filtering approach involving wavelet transforms and rotated local frames. We also assess the impact of lateral crustal variations on the gravity field by introducing random density anomalies and a seismic crustal model, testing the method's ability to distinguish between these anomalies and thermal sources. Using Gravity field and steady‐state Ocean Circulation Explorer satellite data, we generated scale‐orientation diagrams aiming to identify signals aligned with the direction of plate movement and with a spatial scale of a few hundred kilometers (scale of the plumes). Maps of filtered Bouguer gravity gradients aligned with hotspot trajectories are generated for all continental hot plumes, with the position and the age of the intraplate volcanism to support the interpretation. While we do not show a clear signal in regions that are too tectonically complex or with lateral variations in the crust or at the lithospheric boundary correlated with the hotspot trace, we found observed signals with expected sign and amplitude over Hoggar, Tibesti, Darfour and Cameroon tracks in Africa and over Iceland and Jan Mayen in Greenland. However, determining corresponding mass source depths remains a complex task.

PaintHuman: Towards High-Fidelity Text-to-3D Human Texturing via Denoised Score Distillation

Recent advances in zero-shot text-to-3D human generation, which employ the human model prior (e.g., SMPL) or Score Distillation Sampling (SDS) with pre-trained text-to-image diffusion models, have been groundbreaking. However, SDS may provide inaccurate gradient directions under the weak diffusion guidance, as it tends to produce over-smoothed results and generate body textures that are inconsistent with the detailed mesh geometry. Therefore, directly leveraging existing strategies for high-fidelity text-to-3D human texturing is challenging. In this work, we propose a model called PaintHuman to addresses the challenges from two perspectives. We first propose a novel score function, Denoised Score Distillation (DSD), which directly modifies the SDS by introducing negative gradient components to iteratively correct the gradient direction and generate high-quality textures. In addition, we use the depth map as a geometric guide to ensure that the texture is semantically aligned to human mesh surfaces. To guarantee the quality of rendered results, we employ geometry-aware networks to predict surface materials and render realistic human textures. Extensive experiments, benchmarked against state-of-the-art (SoTA) methods, validate the efficacy of our approach.Project page: https://painthuman.github.io/.

Gradient-Guided Modality Decoupling for Missing-Modality Robustness

Multimodal learning with incomplete input data (missing modality) is very practical and challenging. In this work, we conduct an in-depth analysis of this challenge and find that modality dominance has a significant negative impact on the model training, greatly degrading the missing modality performance. Motivated by Grad-CAM, we introduce a novel indicator, gradients, to monitor and reduce modality dominance which widely exists in the missing-modality scenario. In aid of this indicator, we present a novel Gradient-guided Modality Decoupling (GMD) method to decouple the dependency on dominating modalities. Specifically, GMD removes the conflicted gradient components from different modalities to achieve this decoupling, significantly improving the performance. In addition, to flexibly handle modal-incomplete data, we design a parameter-efficient Dynamic Sharing (DS) framework which can adaptively switch on/off the network parameters based on whether one modality is available. We conduct extensive experiments on three popular multimodal benchmarks, including BraTS 2018 for medical segmentation, CMU-MOSI, and CMU-MOSEI for sentiment analysis. The results show that our method can significantly outperform the competitors, showing the effectiveness of the proposed solutions. Our code is released here: https://github.com/HaoWang420/Gradient-guided-Modality-Decoupling.

Rayleigh–Bénard Convection With Multiple Solutions in Trapezoidal Closed Cavities

Abstract Rayleigh–Bénard convection (RBC) in symmetric trapezoidal closed cavities with cavity angle ϕ=70°−110°, filled with air, is studied using numerical simulations where inclined side walls are adiabatic. In contrast to rectangular cavities, where no flow exists below a threshold value, there is a weak convection even at a low Rayleigh number (Ra) due to the fact that there is a component of thermal gradient in the horizontal direction in these cavities. Interestingly, these cavities show sudden and significant jumps in the convection, similar to square cavities (Rac = 2585.02 for ϕ=90°), as Ra increases beyond a critical value (Rac). It is noted here that these Rac represent symmetry-breaking pitchfork bifurcations. These bifurcations are seen in both acute (Rac = 8000 for ϕ=70°) and obtuse (Rac = 2300 for ϕ=110°) angle trapezoidal cavities. Moreover, it is observed that multiple steady-state solutions (MSSS) exist as Ra is further increased. A forward and backward continuation approach for numerical simulations is used to track the co-existence of MSSS. These steady-states have co-existing one-roll and two-roll convective patterns beyond another threshold value of Ra. Here, two types of critical Ra have been identified for different cavity angles; one shows the sudden jump in the convection, and the other is the one beyond which MSSS co-exist. Furthermore, a codimension two bifurcation analysis is carried out with Ra and ϕ as two parameters. The bifurcation analysis divides the parameter space into different regions based on the multiplicity of the solutions.

Plant–mycorrhizal associations may explain the latitudinal gradient of plant community assembly

Biogeographical variation in community assembly processes forms the basis of the latitudinal gradient of biodiversity by driving β‐diversity. Classical studies on community assembly predict environmental filtering affecting β‐diversity more strongly at higher latitudes, where productivity is lower and abiotic stress is stronger. Contrary to this prediction, recent evidence indicates that plant community composition at higher latitudes exhibits more spatially clustered distributions independently of background environments, suggesting the importance of spatial processes, such as priority effects. In this study, we propose a hypothesis that resolves this paradox by considering plant–soil feedback and biogeographic variations in the dominant mycorrhizal type: we predict that the increasing prevalence of ectomycorrhizal (EcM) trees with latitude contributes to the spatially clustered distribution of plants, as EcM trees tend to exhibit positive plant–soil feedback. We analyzed a large‐scale standardized dataset of Japanese forests covering a latitudinal gradient of &gt;10° and found that 1) the proportion of EcM trees was higher at higher latitudes, and 2) EcM tree‐rich communities exhibited more spatially clustered distributions likely due to positive plant–soil feedback. Consequently, 3) tree species composition at higher latitudes was better explained by spatial variables suggesting the importance of priority effects. Consistent with the predictions of the plant–soil feedback theory, these patterns were more pronounced in understory than in canopy communities. Taken together, our results lend support to our hypothesis that biogeographic variation in tree community assembly patterns is defined by mycorrhizal types and plant–soil feedback, thereby resolving a paradox in the latitudinal gradient of plant community assembly. Our work highlights that plant mycorrhizal type underlies the determinants of β‐diversity which is a critical component of the latitudinal gradient of diversity.

Comparative Analysis of Type III Radio Bursts and Solar Flares: Spatial Localization and Correlation with Solar Flare Intensity

We present a comprehensive study of type III radio bursts and their association with solar flares of magnitude M1.0 and larger, as observed by four widely separated spacecraft (Parker Solar Probe, Solar Orbiter, STEREO-A, and Wind). Our main focus is the introduction and validation of two methods for localizing radio bursts using the available multispacecraft data. The first method utilizes intensity fitting with a circular Gaussian distribution, while the second method is based on the time arrival of radio bursts. We demonstrate the effectiveness of these methods through the analysis of a single type III burst event and compare their results with the traditional radio triangulation technique. Furthermore, we conduct a statistical study of 17 type III bursts associated with M- and X-class solar flares in years 2020–2022. Our findings suggest a possible correlation between solar flare intensities and longitudes, with east limb flares tending to be weaker than west limb flares. We also observe a systematic drift of radio burst longitudes toward the east, potentially explained by a poleward component of the local density gradient. Our results suggest a strong correlation between solar flare intensities and radio burst properties, enhancing our understanding of the relationship between solar flares and type III radio bursts.

The role of the primary sensorimotor system in generalized epilepsy: Evidence from the cerebello-cerebral functional integration.

The interaction between cerebellum and cerebrum participates widely in function from motor processing to high-level cognitive and affective processing. Because of the motor symptom, idiopathic generalized epilepsy (IGE) patients with generalized tonic-clonic seizure have been recognized to associate with motor abnormalities, but the functional interaction in the cerebello-cerebral circuit is still poorly understood. Resting-state functional magnetic resonance imaging data were collected for 101 IGE patients and 106 healthy controls. The voxel-based functional connectivity (FC) between cerebral cortex and the cerebellum was contacted. The functional gradient and independent components analysis were applied to evaluate cerebello-cerebral functional integration on the voxel-based FC. Cerebellar motor components were further linked to cerebellar gradient. Results revealed cerebellar motor functional modules were closely related to cerebral motor components. The altered mapping of cerebral motor components to cerebellum was observed in motor module in patients with IGE. In addition, patients also showed compression in cerebello-cerebral functional gradient between motor and cognition modules. Interestingly, the contribution of the motor components to the gradient was unbalanced between bilateral primary sensorimotor components in patients: the increase was observed in cerebellar cognitive module for the dominant hemisphere primary sensorimotor, but the decrease was found in the cerebellar cognitive module for the nondominant hemisphere primary sensorimotor. The present findings suggest that the cerebral primary motor system affects the hierarchical architecture of cerebellum, and substantially contributes to the functional integration evidence to understand the motor functional abnormality in IGE patients.