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High-grade gliomas (HGGs, WHO grades 3–4) are highly aggressive, with a poor prognosis and treatment resistance. Immune evasion may contribute to their progression, but the role of cytotoxic T-lymphocyte immune evasion (CTLE) is not well-validated. This study analyzed the transcriptomic data of 525 patients from TCGA-GBM-HG_U133A. Two molecular subtypes were identified based on 182 CTLE-associated genes, with 238 differentially expressed genes between them. A prognostic model was developed, identifying BST2 and DIRAS3 as key risk factors, and validated in multiple cohorts. The subtypes had distinct immune profiles, with Cluster 2 showing higher immune infiltration but a poorer prognosis. The model had a good predictive performance. High-risk patients had upregulated BST2 and DIRAS3, linked to immunosuppression and shorter survival. Knockdown experiments confirmed their roles in GBM cell migration and invasion. Mechanistically, they promote immune evasion. BST2 and DIRAS3 could be therapeutic targets for HGG immunotherapy.

Materials following Murray’s law are of significant interest due to their unique porous structure and optimal mass transfer ability. However, it is challenging to construct such biomimetic hierarchical channels with perfectly cylindrical pores in synthetic systems following the existing theory. Achieving superior mass transport capacity revealed by Murray’s law in nanostructured materials has thus far remained out of reach. We propose a Universal Murray’s law applicable to a wide range of hierarchical structures, shapes and generalised transfer processes. We experimentally demonstrate optimal flow of various fluids in hierarchically planar and tubular graphene aerogel structures to validate the proposed law. By adjusting the macroscopic pores in such aerogel-based gas sensors, we also show a significantly improved sensor response dynamics. In this work, we provide a solid framework for designing synthetic Murray materials with arbitrarily shaped channels for superior mass transfer capabilities, with future implications in catalysis, sensing and energy applications. Improving mass transfer through hierarchically porous synthetic materials is a great challenge. Here the authors address this by expanding the original Murray’s law, a biomimetic principle defining the branching of veins in living structures.

Strategically improving carbon emission efficiency (CEE) through digital intelligence technology innovation (DITI) is imperative to capitalize on emerging opportunities for economic decarbonization and low-carbon green development. This study employs panel data from 283 Chinese cities from 2011 to 2021 to examine the influence of DITI on urban CEE. The findings suggest the following: ① DITI is crucial in enhancing CEE, and it exerts spatial spillover effects on neighboring areas. ② Following the transition to a low-carbon energy system, DITI is instrumental in enhancing CEE by reducing the energy consumption scale, optimizing the energy consumption structure, and controlling the energy consumption intensity. ③ DITI has varying effects on CEE when subjected to multidimensional regulations, including fiscal pressure, fiscal decentralization, private economics, and entrepreneurial vitality. ④ The beneficial impact of DITI on CEE is more pronounced in regions with high economic growth, low natural resource endowments, high digital resource endowments, and in cities in central China. This study emphasizes DITI’s crucial role in promoting a low-carbon, green circular, and energy-efficient digital economy.

Strategically improving carbon emission efficiency (CEE) through digital intelligence technology innovation (DITI) is imperative to capitalize on emerging opportunities for economic decarbonization and low-carbon green development. This study employs panel data from 283 Chinese cities from 2011 to 2021 to examine the influence of DITI on urban CEE. The findings suggest the following: (D DITI is crucial in enhancing CEE, and it exerts spatial spillover effects on neighboring areas. 2) Following the transition to a low-carbon energy system, DITI is instrumental in enhancing CEE by reducing the energy consumption scale, optimizing the energy consumption structure, and controlling the energy consumption intensity. 3) DITI has varying effects on CEE when subjected to multidimensional regulations, including fiscal pressure, fiscal decentralization, private economics, and entrepreneurial vitality. O The beneficial impact of DITI on CEE is more pronounced in regions with high economic growth, low natural resource endowments, high digital resource endowments, and in cities in central China. This study emphasizes DITI's crucial role in promoting a low-carbon, green circular, and energy-efficient digital economy.

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Building upon these attributes, their additive manufacturing on sustainable substrates further offers unique advantages for future electronics, including low environmental impact. Here, exploiting the structure–property relationship of inkjet‐printed MoS2 nanoflake‐based resistive layer, we present paper‐based reconfigurable memristors. We demonstrate a sustainable process covering material exfoliation, device fabrication, and device recycling. With >90% yield from a 16 × 65 device array, our memristors demonstrate robust resistive switching, with >105 ON–OFF ratio and <0.5 V operation in non‐volatile state. Through modulation of compliance current, the devices transition into a volatile state, with only 50 pW switching power consumption. These performances rival state‐of‐the‐art metal oxide‐based counterparts. We show device recyclability and stable, reconfigurable operation following disassembly, material collection and re‐fabrication. We further demonstrate synaptic plasticity and neuronal leaky integrate‐and‐fire functionality, with disposable applications in smart packaging and simulated medical image diagnostics. Our work shows a sustainable pathway toward printable, reconfigurable neuromorphic devices, with minimal environmental footprints. In this work, we focus on using sustainable production and additive manufacturing processes to fabricate high‐yield, recyclable, multifunctional, and reconfigurable memristors on paper‐based substrates. Reconfigurable memristors can mimic the functions of neurons and synapses, thereby simplifying the structure of neuromorphic computing systems. This approach unlocks potential for environmentally friendly neuromorphic electronics with applications in artificial intelligence and smart packaging.

The China‐France Oceanography Satellite (CFOSAT) launched in 2018 is equipped with the Chinese Scatterometer (CSCAT), which is designed to measure high‐precision sea surface wind fields in the global ocean. This study aims to validate the CFOSAT wind fields with moored buoy‐measured ground truth data from August 2019 to July 2021. The test area was chosen as the Taiwan Strait, which is an important navigation channel and rich fishery grounds in the East Asia. It is also a high wind speed area particularly during typhoons and cold air passages. Thus, the accurate wind forecasts are crucially needed to avoid capsizing and casualties. The validation results give the correlation coefficient (R2) of 0.92, the root mean square error (RMSE) of 1.75 m s−1, and the absolute deviation (AD) of 1.10 m s−1 for the wind speeds, and R2 of 0.96, the RMSE of 21.87°, and the AD of 1.17° for the wind directions. During cold air passages, the AD of wind speeds decreases to 1.03 m s−1, which is smaller than 1.17 m s−1 during typhoons. Using the CFOSAT wind as historical observation data for refining of forecast work was tested by model output statistics revised method. The test results show that the refined forecast results of wind fields are improved up to 4%–17%. Thus, the validation and test results obtained in this study indicate that updating satellite winds would have great contributions to refined forecasting of local sea surface winds. Plain Language Summary The China‐France Oceanography Satellite (CFOSAT) is a China‐France joint mission launched in 2018, which aims to update satellite remote sensing technologies of the sea surface winds and waves. This paper reports the validation results of the CFOSAT winds with moored buoy measurements. The test area is chosen as the Taiwan Strait, which is an important navigation channel in the East Asia and a rich fishery ground. Total 467 satellite‐buoy spatiotemporal matching data pairs were collected during 8 typhoons and 8 cold air passage processes over the Taiwan Strait. Statistical calibration analyses give the correlation coefficients as high as 0.92 for the wind speeds and 0.96 for the wind directions, implying that the CFOSAT wind data are of high quality and satisfy the requirements for the operational applications. Furthermore, test results to use the CFOSAT winds for operational ocean forecasts in the Taiwan Strait and adjacent waters show that the accuracies of forecasting work are raised up to 4%–17% during the typhoon and cold air passage processes. Thus, the validation and test results provided by this study indicate that it is expectable that updating satellite winds would have great contributions to refined forecasting of local sea surface winds. Key Points China‐France Oceanography Satellite (CFOSAT) scatterometer wind data are validated by buoy measurements deployed in the Taiwan Strait Calibration analyses of 467 spatiotemporal matching data pairs give correlation coefficients of 0.92 for wind speed and 0.96 for direction Applications of CFOSAT winds improve refined operational forecasts up to 4%–17% under the extreme weather conditions

The (k,n)-threshold Secret Image Sharing scheme (SISS) is a solution to image protection. However, the shadow images generated by traditional SISS are noise-like, easily arousing deep suspicions, so that it is significant to generate meaningful shadow images. One solution is to embed the shadow images into meaningful natural images and visual quality should be considered first. Limited by embedding rate, the existing schemes have made concessions in size and visual quality of shadow images, and few of them take the ability of anti-steganalysis into consideration. In this paper, a meaningful SISS that is based on Natural Steganography (MSISS-NS) is proposed. The secret image is firstly divided into n small-sized shadow images with Chinese Reminder Theorem, which are then embedded into RAW images to simulate the images with higher ISO parameters with NS. In MSISS-NS, the visual quality of shadow images is improved significantly. Additionally, as the payload of cover images with NS is larger than the size of small-sized shadow images, the scheme performs well not only in visual camouflage, but also in other aspects, like lossless recovery, no pixel expansion, and resisting steganalysis.

Surface currents measured by High Frequency (HF) radar are used to investigate the dynamics in the coastal waters of Qingdao, China, on the western coast of the Yellow Sea. Different factors affecting the surface currents are revealed by dynamical analysis. Harmonic tidal analysis shows that the coastal tidal currents are barotropic and their temporal evolution is mainly influenced by the semidiurnal tidal constitutes, topography and geometry. It is also found that their horizontal distribution represents the effect of local topography. At sub‐tidal frequencies, the high correlation between winds and the sub‐tidal surface currents indicates a crucial role of wind‐forcing in driving the currents. Varying wind direction coupled with small‐scale features of the coastal geometry results in complicated sub‐mesoscale circulation. In addition, the monthly coastal circulation is characterized by an eddy structure and is primarily determined by the outflow which is closely associated with the sea level slope along the coast. The variability of the residual currents is studied by analyzing the cross‐shore momentum equation with wind stress, sea level records, and HF radar currents. It is shown that both the barotropic pressure gradient and the nonlinear tidal stress contribute to the variations of the residual currents near the bay mouth and further govern the coastal monthly circulation in August, 2008. Key Points Describes surface current pattern over Qingdao coastal water from observations Study the coastal dynamics about tide, local wind, alongshore pressure gradient Reveal the evolution of Qingdao coastal eddy circulation in August 2008

A 30-d current numerical simulation is running for the Yangshan Port,the Changjiang Estuary,the Hangzhou Bay and their adjacent seas using a finite volume coastal ocean model （FVCOM）,with Changjiang River runoff and wind effect being considered.At the open boundary,this model is driven by the water level obtained from prediction including eight main partial tides.After the harmonic analysis,the cotidal chart and the iso-amplitude line as well as the current ellipse distribution map are displayed to illustrate the propagation property of a tidal wave.Horizontal velocity of both the U and V components coincides with the actual measurement,which shows that the model result is credible to describe the hydrodynamic pattern in this sea area.On this basis,real-time current data from high-frequency radar is assimilated with the implementation of quick ensemble Kalman filter,which takes the variation tendency of the state vector to compute the analysis field,instead of integrating the field for N （the number of ensemble） times as it used to in the standard EnKF,aiming at raising the efficiency of computation,reducing the error of prediction and at the same time,improving the forecast effect.

Surface currents measured by high frequency （HF） radar arrays are assimilated into a regional ocean model over Qingdao coastal waters based on Kalman filter method. A series of numerical experiments are per- formed to evaluate the performance of the data assimilation schemes. In order to optimize the analysis pro- cedure in the traditional ensemble Kalman filter （ENKF）, a different analysis scheme called quasiensemble Kaman filter （QENKF） is proposed. The comparisons between the ENKF and the QENKF suggest that both them can improve the simulated error and the spatial structure. The estimations of the background error covariance （BEC） are also assessed by comparing three different methods： Monte Carlo method; Canadian quick covariance （CQC） method and data uncertainty engine （DUE） method. A significant reduction of the root-mean-square （RMS） errors between model results and the observations shows that the CQC method is able to better reproduce the error statistics for this coastal ocean model and the corresponding external forcing. In addition, the sensibility of the data assimilation system to the ensemble size is also analyzed by means of different scales of the ensemble size used in the experiments. It is found that given the balance of the computational cost and the forecasting accuracy, the ensemble size of 50 will be an appropriate choice in the Qingdao coastal waters.