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The scattering of charged particles by oxygen ion cyclotron harmonic (OCH) waves in the inner magnetosphere is investigated by evaluating the relevant quasi‐linear diffusion coefficients. Recent studies demonstrated that OCH waves are oxygen ion Bernstein modes and their complex kinetic dispersion relation has made it challenging to assess their role in scattering charged particles. The present study calculates the quasi‐linear diffusion coefficients for the scattering of electrons and ions by OCH waves using their kinetic dispersion relation. The results show that OCH waves can effectively scatter electrons between ∼100 eV and 100s keV via Landau resonance. They are also capable of heating cold helium and oxygen ions through cyclotron resonances. Specially, it is found that the 4th harmonic of OCH waves can lead to effective heating of helium ions, while oxygen ions would interact more efficiently with lower harmonics of OCH waves. Plain Language Summary Oxygen ion cyclotron harmonic (OCH) waves observed in the inner magnetosphere often have multiple spectral peaks at harmonics of the local oxygen ion cyclotron frequency. They have been shown to be excited by hot oxygen ion loss‐cone or ring/ring‐like distributions and follow a complicated kinetic dispersion relation for oxygen ion Bernstein waves. Since OCH waves cannot be described by the relatively simple cold plasma dispersion relation, it has been difficult to calculate their diffusion coefficients in scattering charged particles in quasi‐linear theory. The present study numerically solves the kinetic dispersion relation for OCH waves and then uses the results to calculate the corresponding quasi‐linear diffusion coefficients for electrons and ions. The diffusion coefficients obtained show that OCH waves can effectively interact with ∼100 eV to 100s keV electrons and are capable of heating cold helium and oxygen ions. Thus, OCH waves have their own unique contribution to the particle dynamics in the inner magnetosphere. Key Points Quasi‐linear diffusion coefficients are evaluated for particle scattering by oxygen ion cyclotron harmonic (OCH) waves for the first time OCH waves can scatter electrons in a wide energy range (∼100 eV–100s keV) via Landau resonance OCH waves are capable of heating cold helium and oxygen ions through cyclotron resonance

We discuss the situations under which Brownian yet non-Gaussian (BnG) diffusion can be observed in the model of a particle's motion in a random landscape of diffusion coefficients slowly varying in space (quenched disorder). Our conclusion is that such behavior is extremely unlikely in the situations when the particles, introduced into the system at random at t = 0, are observed from the preparation of the system on. However, it indeed may arise in the case when the diffusion (as described in Ito interpretation) is observed under equilibrated conditions. This paradigmatic situation can be translated into the model of the diffusion coefficient fluctuating in time along a trajectory, i.e. into a kind of the 'diffusing diffusivity' model.

Chorus waves are intense electromagnetic emissions critical in modulating electron dynamics. In this study, we perform two‐dimensional particle‐in‐cell simulations to investigate self‐consistent wave‐particle interactions with oblique chorus waves. We first analyze the electron dynamics sampled from cyclotron and Landau resonances with waves, and then quantify the advection and diffusion coefficients through statistical studies. It is found that phase‐trapped cyclotron resonant electrons satisfy the second‐order resonance condition and gain energy from waves. While phase‐bunched cyclotron resonant electrons cannot remain in resonance for long periods. They transfer energy to waves and are scattered to smaller pitch angles. Landau resonant electrons are primarily energized by waves. For both types of resonances, advection coefficients are greater than diffusion coefficients when the wave amplitude is large. Our study highlights the important role of advection in electron dynamics modulation resulting from nonlinear wave‐particle interactions. Plain Language Summary Wave‐particle interactions can modulate electron distributions through advection and diffusion. Previous studies focusing on advection and diffusion primarily relied on test particle simulations, which uses a simplified model of wave evolution. In this study, we perform self‐consistent simulations to investigate the wave‐particle interactions with chorus waves and quantify the advection and diffusion coefficients of resonant electrons. It is found that advection coefficients are greater than diffusion coefficients in both cyclotron and Landau resonances, indicating the significant role of nonlinear wave‐particle interactions. The quantification of advection and diffusion coefficients in a self‐consistent system is important for understanding and predicting the loss and energization processes in radiation belt electrons. This study complements previous diffusion models that regarded the evolution of electron dynamics in wave‐particle interactions as a slow diffusive process. Key Points Electron advection and diffusion in wave‐particle interactions with chorus waves are investigated through self‐consistent simulations The second‐order time derivative of gyrophase angle is nearly zero for phase‐trapped electrons but is negative for phase‐bunched electrons The advection and diffusion coefficients for cyclotron and Landau resonant electrons interacting with chorus waves are quantified

Oceanographic observations are limited by sampling rates, while ocean models are limited by finite resolution and high viscosity and diffusion coefficients. Therefore, both data from observations and ocean models lack information at small and fast scales. Methods are needed to either extract information, extrapolate, or upscale existing oceanographic data sets, to account for or represent unresolved physical processes. Here we use machine learning to leverage observations and model data by predicting unresolved turbulent processes and subsurface flow fields. As a proof of concept, we train convolutional neural networks on degraded data from a high‐resolution quasi‐geostrophic ocean model. We demonstrate that convolutional neural networks successfully replicate the spatiotemporal variability of the subgrid eddy momentum forcing, are capable of generalizing to a range of dynamical behaviors, and can be forced to respect global momentum conservation. The training data of our convolutional neural networks can be subsampled to 10–20% of the original size without a significant decrease in accuracy. We also show that the subsurface flow field can be predicted using only information at the surface (e.g., using only satellite altimetry data). Our results indicate that data‐driven approaches can be exploited to predict both subgrid and large‐scale processes, while respecting physical principles, even when data are limited to a particular region or external forcing. Our in‐depth study presents evidence for the successful design of ocean eddy parameterizations for implementation in coarse‐resolution climate models. Plain Language Summary Models of the ocean and ocean observations are imperfect. Due to this imperfection, simulations of the ocean and our observations are not quite the same as the true ocean currents. We, therefore, need ways to make our ocean data more realistic and complete and to make it more similar to the actual ocean. Scientists have traditionally approached this problem in a pen‐and‐paper style, considering physical theories and mechanisms. This study instead uses machine learning, which focuses on data as opposed to equations on a black board. We successfully use a particular type of machine learning algorithm, called a convolutional neural network, to make the most of current oceanographic data. This type of neural network works well even if ocean data are limited to a particular area. Future work will involve combining machine learning with physical theories of the ocean. Key Points We successfully use convolutional neural networks to predict unresolved turbulent processes and subsurface velocities The neural networks generalize to different regions, dynamical regimes, and forcing Global momentum conservation for eddy parameterization can be respected without sacrificing accuracy

Using the statistical wave power spectral profiles obtained from CRRES wave data within the 0000–0600 MLT sector under different levels of geomagnetic activity and a modeled latitudinal variation of wave normal angle distribution, we examine quantitatively the effects of lower band and upper band chorus on resonant diffusion of plasma sheet electrons for diffuse auroral precipitation in the inner magnetosphere. Whistler mode chorus‐induced resonant scattering of plasma sheet electrons is geomagnetic activity dependent, varying from above the strong diffusion limit (timescale of an hour) during active times (AE* > 300 nT) with peak wave amplitudes of >50 pT to weak scattering (timescale of a day) during quiet conditions (AE* < 100 nT) with typical wave amplitudes of ≤10 pT. Chorus waves present at different magnetic latitudes make distinct contributions to the net diffusion rates of plasma sheet electrons, largely depending on the latitudinal variation of wave power. Upper band chorus is the controlling scattering process for electrons from ∼100 eV to ∼2 keV, and lower band chorus is most effective for precipitating the higher energy (>∼2 keV) plasma sheet electrons in the inner magnetosphere. Efficient scattering by the combination of active time lower band and upper band chorus can cover a wide energy range from ∼100 eV to >100 keV and a broad interval of equatorial pitch angle, thereby accounting for the formation of observed electron pancake distribution. Decreased chorus scattering during less disturbed times can also modify the magnetic local time distribution of plasma sheet electrons. Compared to the effects of chorus waves, electron cyclotron harmonic wave‐induced resonant diffusion coefficients are at least 1 order of magnitude smaller and are negligible under any geomagnetic condition, indicating that chorus waves act as the major contributor dominantly responsible for diffuse auroral precipitation in the inner magnetosphere. Chorus‐driven momentum diffusion and mixed diffusion are also important. Lower band and upper band chorus can cause strong momentum diffusion of plasma sheet electrons in the energy ranges of ∼500 eV to ∼2 keV and ∼2 keV to ∼3 keV, respectively, which can significantly result in energization of the electrons and attenuation of the waves. Key Points Chorus can cause both efficient pitch angle scattering and momentum diffusion Chorus dominates over ECH waves to account for diffuse auroral precipitation Chorus scattering can also explain the formation of electron pancake distribution

ObjectiveTo develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting apparent diffusion coefficient (ADC) radiomics features.MethodsThis retrospective study involved analysis of MR images from 169 patients with cervical cancer stage IB–IVA captured; among them, diffusion-weighted (DW) images from 144 patients were used for training, and another 25 patients were recruited for testing. A U-Net convolutional network was developed to perform automated tumor segmentation. The manually delineated tumor region was used as the ground truth for comparison. Segmentation performance was assessed for various combinations of input sources for training. ADC radiomics were extracted and assessed using Pearson correlation. The reproducibility of the training was also assessed.ResultsCombining b0, b1000, and ADC images as a triple-channel input exhibited the highest learning efficacy in the training phase and had the highest accuracy in the testing dataset, with a dice coefficient of 0.82, sensitivity 0.89, and a positive predicted value 0.92. The first-order ADC radiomics parameters were significantly correlated between the manually contoured and fully automated segmentation methods (p < 0.05). Reproducibility between the first and second training iterations was high for the first-order radiomics parameters (intraclass correlation coefficient = 0.70–0.99).ConclusionU-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images. First-order radiomics features extracted from whole tumor volume demonstrate the potential robustness for longitudinal monitoring of tumor responses in broad clinical settings.SummaryU-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images.Key Points• U-Net-based deep learning can perform accurate fully automated localization and segmentation of cervical cancer in diffusion-weighted MR images.• Combining b0, b1000, and apparent diffusion coefficient (ADC) images exhibited the highest accuracy in fully automated localization.• First-order radiomics feature extraction from whole tumor volume was robust and could thus potentially be used for longitudinal monitoring of treatment responses.

PURPOSETo evaluate the diagnostic efficacy of apparent diffusion coefficient (ADC) measurements and semiquantitative dynamic contrast enhancement (DCE) parameters in predicting the differentiation between low- and high-grade tumors in non-muscle invasive bladder cancers (NMIBC).METHODSPatients with NMIBC, who were histopathologically confirmed between August 2020 and July 2023, were analyzed by 2 radiologists with different levels of experience. DCE semi-quantitative parameters such as wash-in rate (WiR), wash-out ratio (WoR), time to peak (TTP), and peak enhancement (PE) were calculated. ADC measurements were performed using the three-region-of-interest (ADCt) and whole volume (ADCw) methods; ADCt ratio (ADCtR) and ADCw ratio (ADCwR) were also calculated. Receiver operating characteristic curve analysis was performed to demonstrate the cut-off values of ADCt, ADCw, ADCtR, and ADCwR to differentiate low- and high-grade tumors. The intraclass correlation coefficient was used to evaluate inter-reader agreement.RESULTSA total of 89 patients were included in this study. Of these patients, 48 had low-grade NMIBC, and 41 had high-grade NMIBC. There was no significant difference in mean WoR, WiR, TTP, and PE values between low- and high-grade NMIBC (P > 0.05). The ADCt, ADCw, ADCtR, and ADCwR values of high-grade NMIBC were significantly lower than those of low-grade NMIBC (P < 0.001). With cut-off values of 0.449 and 0.435, ADCtR had the best diagnostic value for both readers, showing better accuracy, sensitivity, specificity, and area under the curve (85.4%–83.1%, 87.5%–85.4%, 82.9%–80.4%, and 0.879–0.857, respectively, with confidence intervals). Additionally, ADCtR and ADCt showed acceptable diagnostic performance for both readers, with cut-off values of 0.439 and 0.431, respectively, for differentiating Ta- and T1-stages. The inter-reader agreement was almost perfect for ADC measurements.CONCLUSIONWhile DCE semiquantative parameters did not yield significant outcomes in distinguishing between low and high grades, ADCtR holds promise for enhancing patient management in NMIBC cases and stands as a potential preoperative radiological asset.CLINICAL SIGNIFICANCEIndividuals diagnosed with NMIBC may require different treatment approaches; therefore, it is very important to distinguish between low- and high-grade cases preoperatively. The differentiation between the Ta- and T1-stages is recognized as crucial in patient treatment strategies. Furthermore, ADCtR shows promise for improving patient management in NMIBC cases.

In multispecies electrolyte solutions, even in the absence of an external electric field, differences in ion diffusivities induce an electric potential and generate additional fluxes for each species. This electro-diffusion process is well-described by the advection Nernst–Planck equation. This study aims to analyse the long-time behaviour of the governing equation under electroneutrality and zero current conditions, and to investigate how the diffusion-induced electric potential and shear flow enhance the effective diffusion coefficients of each species in channel domains. The exact solutions of the effective equation with certain special parameters, as well as the asymptotic analyses for ions with large diffusivity discrepancies, are presented. Furthermore, there are several interesting properties of the effective equation. First, it is a generalization of the Taylor dispersion, with a nonlinear diffusion tensor replacing the scalar diffusion coefficient. Second, the effective equation exhibits a scaling relation, revealing that the system with a weak flow is equivalent to the system with a strong flow under scaled physical parameters. Third, in the case of injecting an electrolyte solution into a channel containing well-mixed buffer solutions or electrolyte solutions with the same ion species, if the concentration of the injected solution is lower than that of the pre-existing solution, then the effective equation simplifies to a multi-dimensional diffusion equation. However, when introducing the electrolyte solution into a channel filled with deionized water, the ion–electric interaction results in several phenomena not present in the advection–diffusion equation, including upstream migration of some species, spontaneous separation of ions, and non-monotonic dependence of the effective diffusivity on Péclet numbers. Finally, the dependence of effective diffusivity on concentration and ion diffusivity suggests a method to infer the concentration ratio of each component and ion diffusivity by measuring the effective diffusivity.

By constructing an empirical model of the spectral and latitudinal distribution of ion cyclotron waves on the basis of Cassini datasets, we investigate the resonant interactions between ion cyclotron waves and radiation belt electrons at Saturn. Calculations based on quasi‐linear bounce‐averaged diffusion coefficients show that at Saturn ion cyclotron waves can efficiently pitch angle scatter >∼1 MeV to tens of MeV electrons into the loss cone thereby inducing precipitation loss, while the mixed and momentum scattering effects are typically negligible. The resultant electron loss timescales range from a few to tens of minutes, which in fact decrease significantly with increasing L‐shell at L = 4–6. We also find that the kinetic effects introduced by pick‐up ring particles cause distinct changes in pitch angle scattering efficiency for lower energy electrons (<3 MeV at L = 5). Our results demonstrate that ion cyclotron waves play a significant role in the dynamics of Saturn's radiation belt electrons. Plain Language Summary Ion cyclotron waves are a common electromagnetic wave mode in the planetary magnetospheres. At Saturn, ion cyclotron waves are usually observed with wave frequencies near the gyro‐frequency of water‐group ions (e.g., O+, OH+, and H2O+). They are known to be excited by a ring distribution of the pick‐up water‐group ions which are extracted from the extended neutral clouds. In this paper, we investigate the resonant interactions between ion cyclotron waves and radiation belt electrons at Saturn. By constructing an empirical model of the spectral and latitudinal distribution of ion cyclotron waves based on Cassini observations, we calculate the bounce‐averaged electron diffusion coefficients and resultant electron loss timescales. Our results suggest that Saturn's ion cyclotron waves can cause efficient precipitation loss of radiation belt electrons by scattering them into the loss cone. The corresponding loss timescales range from a few to tens of minutes, decreasing with increasing radial distance from Saturn. Our results confirm the important role of ion cyclotron waves in the dynamics of Saturnian radiation belt electrons. Key Points The resonant interactions between ion cyclotron waves and radiation belt electrons at Saturn are investigated Ion cyclotron waves can efficiently pitch angle scatter >∼1 MeV to tens of MeV electrons into the loss cone for precipitation loss The resultant electron loss timescales range from a few to tens of minutes, which decrease significantly with increasing L‐shell over L = 4–6

An accurate mechanistic understanding of solute diffusion in partially saturated clays is critical for assessing the safety of deep geological repositories for radioactive waste. In this study, a pore‐scale numerical framework is developed to simulate water and ion diffusion in partially saturated clays. First, the two‐phase Shan‐Chen Lattice Boltzmann method is employed to establish the liquid‐gas distribution in a reconstructed three‐dimensional pore geometry of a clay. An equivalent solute method is also developed and validated to improve the numerical stability of the solution at the liquid/gas interface corresponding to steep variations of the concentration and diffusion coefficient of the water tracer. By using a mobility‐distance relationship from molecular simulations, Fick's law is numerically solved to simulate water diffusion in nanopores, while the coupled Poisson‐Boltzmann‐Nernst‐Planck equations are solved to simulate ion diffusion under the influence of the electrical double layer (EDL). Our model reveals that the decrease of relative effective diffusion coefficients during the desaturation is more pronounced for ions than for water, due to the additional transport pathway of water tracers in the gas phase. The obtained effective diffusion coefficients of tritiated water and ions agree well with reported data from compacted sedimentary rocks. By comparing the local electric potential and the distribution of ion concentrations in single pores, the simulation results suggest that the EDL in unsaturated clays has a more complex influence on ion distribution than under fully water‐saturated conditions. This study provides critical insights into the coupled transport processes of solutes in partially saturated clays. Key Points Development of a pore‐scale numerical framework to simulate water and ion diffusion in partially saturated clays Derivation of an equivalent solute method to improve the numerical stability caused by the discontinuities at the water/vapor interface The electrical double layer has a stronger effect on ion transport under unsaturated conditions than under water saturated conditions