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In scenarios where a sustained energetic particle source strongly drives toroidal Alfvén eigenmodes (TAE), and phase-space transport is insufficient to saturate TAE, this novel theory of TAE-zonal mode (ZM)-turbulence—self-regulated by cross-scale interactions (including collisionless ZF damping) – merits consideration. Zonal modes are driven by Reynolds and Maxwell stresses, without the onset of modulational instability. TAE evolution in the presence of ZMs conserves energy and closes the system feedback loop. The saturated zonal shears can be sufficient to suppress ambient drift-ion temperature gradient (ITG) turbulence, achieving an enhanced core confinement regime. The saturated state is regulated by linear and turbulent zonal flow drag. This regulation leads to bursty TAE spectral oscillations, which overshoot while approaching saturation. Heating by both collisional and collisionless ZM damping deposits alpha particle energy into the thermal plasma, achieving effective alpha channeling. This theory offers a mechanism for EP-induced transport barrier formation, and predicts a novel thermal ion heating mechanism.

Organic framework membranes (OFMs) have emerged as transformative materials for separation technologies due to their tunable porosity, structural diversity, and stability, yet their design and optimization face challenges in navigating vast chemical spaces and complex performance trade-offs. This review highlights the pivotal role of machine learning (ML) in overcoming these limitations by integrating multi-source data, constructing quantitative structure–property relationships, and enabling the cross-scale optimization of OFMs. Methodologically, ML workflows—spanning data construction, feature engineering, and model optimization—accelerate candidate screening, inverse design, and mechanistic interpretation, as demonstrated in gas separations and nascent liquid-phase applications. Key findings reveal that ML identifies critical structural descriptors and environmental parameters, guiding the development of high-performance membranes that surpass traditional selectivity–permeability limits. Challenges persist in liquid separations due to dynamic operational complexities and data scarcity, while emerging frameworks offer untapped potential. The integration of interpretable ML, in situ characterization, and industrial scalability strategies is essential to transition OFMs from laboratory innovations to sustainable, adaptive separation systems. This review underscores ML’s transformative capacity to bridge computational insights with experimental validation, fostering next-generation membranes for carbon neutrality, water security, and energy-efficient industrial processes.

Previous research has shown that microbes play a role in immune-related diseases. Our study reveals that children with Henoch-Schönlein purpura nephritis have distinct and altered tongue coating microbiota, characterized by significant changes in species richness, diversity, and specific microbial compositions compared with healthy controls. Nevertheless, the particular involvement of tongue coating microbiota in Henoch-Schönlein Purpura remains unclear. A total of 26 children were enrolled, including 13 patients with HSP and 13 healthy children. Tongue coating samples were collected for DNA extraction and 16S rRNA gene sequencing. Alpha diversity indices, including ACE, Chao1, Shannon, and Simpson indices, revealed significantly lower richness and diversity of tongue coating microbiota in children with Henoch-Schönlein purpura compared to healthy controls. Beta diversity analysis demonstrated distinct clustering of microbial communities between HSP and healthy children, with significant compositional differences. 16S rRNA gene sequencing showed that the relative abundance of key genera, such as Veillonella and Prevotella , differed between the two groups. A random forest algorithm identified five genera as potential diagnostic biomarkers for HSP. Co-occurrence analysis revealed different hub microbes in HSP and healthy children. BugBase predicted an increased proportion of stress-tolerant bacteria in the HSP group compared to the healthy controls group. PICRUSt analysis indicated alterations in metabolic functions of tongue coating microbiota between HSP and healthy children, with 25 KEGG pathways exhibiting significant differences. Children with HSP exhibit marked differences in their tongue coating microbiota when contrasted with their healthy counterparts.

Aiming to investigate the transient four-quadrant hydrodynamics on blades under the circumferential motion of the steering center, an efficient three-dimensional (3D) model with half blades was established in this paper. The 3D model with half blades accounts for the hydrodynamic loss induced by the complicated mechanical structure, predicting the hydrodynamic performance of the high-load cycloidal propeller with high accuracy. On this basis, the open water manoeuvering performance of the cycloidal propellers in fully azimuth angle was simulated by Reynolds-averaged Navier-Stokes (RANS) solver, and the hydrodynamic loads and flow field characteristics were analyzed in detail. The research shows that the variation of azimuth angle φ induces the rapid response of hydrodynamic loads, which directly affects the direction of ship motion. Compared with φ = 0°, the increase in the azimuth angle of the steering center will enhance the negative impact of the inflow velocity on the wake flow field and the internal flow field within the blades. Additionally, the non-uniform flow in the main thrust direction leads to a significant increase in the undesired net lateral force. Our primary findings revealed in present paper should contribute to accurate prediction of hydrodynamic performance for high-load cycloidal propellers during maneuvering process.

Yuan, H.; Li, F.; Yan, Q.; Zhang, W., and Hu, J., 2023. Investigating pressure fluctuations on marine vessel rudders: Numerical results from propeller–rudder–hull interactions. Journal of Coastal Research, 39(2), 284–295. Charlotte (North Carolina), ISSN 0749-0208. Severe pressure fluctuations induced by propeller wake enhance rudder vibrations. In the present study, the pressure fluctuations on the rudder are numerically investigated by using k-ω Menter's shear stress transport turbulence model. The pressure fluctuations on the port and starboard sides of the rudder are compared in time and frequency domains. Furthermore, the impact of the advance coefficient on the displacement of propeller wake and pressure fluctuations is also discussed. The numerical results indicate that the propeller wake displacement is oriented upward and downward at the port and starboard sides, respectively. The most intense pressure fluctuation occurs at the propeller blade passage frequency. As a result of vortex displacement, the suction-side fluctuations are weaker than those on the pressure side at frequencies of 100–300 Hz over an advance coefficient range of J = 0.75–0.925. The displacement of the propeller wake weakens when the advance coefficient decreases.

We report on comprehensive experimental studies of turbulence spreading in edge plasmas. These studies demonstrate the relation of turbulence spreading and entrainment to intermittent convective density fluctuation events or bursts (i.e. blobs and holes). The non-diffusive character of turbulence spreading is thus elucidated. The turbulence spreading velocity (or mean jet velocity) manifests a linear correlation with the skewness of density fluctuations, and increases with the auto-correlation time of density fluctuations. Turbulence spreading by positive density fluctuations is outward, while spreading by negative density fluctuations is inward. The degree of symmetry breaking between outward propagating blobs and inward propagating holes increases with the amplitude of density fluctuations. Thus, blob-hole asymmetry emerges as crucial to turbulence spreading. These results highlight the important role of intermittent convective events in conveying the spreading of turbulence, and constitute a fundamental challenge to existing diffusive models of spreading.

Experimental studies of the dynamics of shear flow and turbulence spreading at the edge of tokamak plasmas are reported. Scans of line-averaged density and plasma current are carried out while approaching the Greenwald density limit on the J-TEXT tokamak. In all scans, when the Greenwald fraction fG=n¯/nG=n¯/(Ip/πa2) increases, a common feature of enhanced turbulence spreading and edge cooling is found. The result suggests that turbulence spreading is a good indicator of edge cooling, indeed better than turbulent particle transport is. The normalized turbulence spreading power increases significantly when the normalized E×B shearing rate decreases. This indicates that turbulence spreading becomes prominent when the shearing rate is weaker than the turbulence scattering rate. The asymmetry between positive/negative (blobs/holes) spreading events, turbulence spreading power and shear flow are discussed. These results elucidate the important effects of interaction between shear flow and turbulence spreading on plasma edge cooling.

We study the concentration field in a prescribed 2D Cahn-Hilliard Navier-Stokes (CHNS) system. We formulate a description for the target pattern formation and pattern merging processes, and compare this description with simulation results. Shear-augmented diffusion along streamlines causes a separation of time scales, thus 2D CHNS system can be simplified to a 1D system. In this 1D system, target pattern formation is induced by linear instability. The waveform of patterns are described by Jacobi Elliptic Functions. The interface (of pattern) migration or coarsening velocity is determined by the derivative of interface curvature. The anomalous migration of inner pattern can be explained by the singularity at the origin and therefore the boundary motion in the quasi-one-dimension system. Finally we derive a simple criterion for when CHNS system becomes dynamic by following similar cases in MHD.

In scenarios where a sustained energetic particle source strongly drives toroidal Alfvén eigenmodes (TAE), and phase-space transport is insufficient to saturate TAE, this novel theory of TAE-zonal mode (ZM)-turbulence -- self-regulated by cross-scale interactions (including collisionless ZF damping) -- merits consideration. Zonal modes are driven by Reynolds and Maxwell stresses, without the onset of modulational instability. TAE evolution in the presence of ZMs conserves energy and closes the system feedback loop. The saturated zonal shears can be sufficient to suppress ambient drift-ITG turbulence, achieving an enhanced core confinement regime. The necessary mechanism is identified. The saturated state is regulated by linear and turbulent zonal flow drag. This regulation leads to bursty TAE spectral oscillations, which overshoot while approaching saturation. Heating by both collisional and collisionless ZM damping deposits alpha particle energy into the thermal plasma, achieving effective alpha channeling. This theory offers a mechanism for EP-induced transport barrier formation, and predicts a novel thermal ion heating mechanism.

CD8 + T cell exhaustion is a stable dysfunctional state driven by chronic antigen stimulation in the tumor microenvironment (TME). Differentiation of exhausted CD8 + T cells (CD8 + TEXs) is accompanied by extensive transcriptional, epigenetic and metabolic reprogramming. CD8 + TEXs are mainly characterized by impaired proliferative and cytotoxic capacity as well as the increased expression of multiple co-inhibitory receptors. Preclinical tumor studies and clinical cohorts have demonstrated that T cell exhaustion is firmly associated with poor clinical outcomes in a variety of cancers. More importantly, CD8 + TEXs are regarded as the main responder to immune checkpoint blockade (ICB). However, to date, a large number of cancer patients have failed to achieve durable responses after ICB. Therefore, improving CD8 + TEXs may be a breakthrough point to reverse the current dilemma of cancer immunotherapy and eliminate cancers. Strategies to reinvigorate CD8 + TEXs in TME mainly include ICB, transcription factor-based therapy, epigenetic therapy, metabolism-based therapy and cytokine therapy, which target on different aspects of exhaustion progression. Each of them has its advantages and application scope. In this review, we mainly focus on the major advances of current strategies to reinvigorate CD8 + TEXs in TME. We summarize their efficacy and mechanisms, identify the promising monotherapy and combined therapy and propose suggestions to enhance the treatment efficacy to significantly boost anti-tumor immunity and achieve better clinical outcomes.