Developed by a research team, the DEA coating boasts strong erosion–corrosion resistance thanks to its multi-layer gradient structure and amylose hydrogel layer. The coating can fully repair cracks up to 50 μm wide, significantly reducing erosion rates and offering enhanced protection for underwater pipeline systems.
Researchers develop a novel method, VMPLN, to analyze scRNA-seq data and infer gene regulatory networks (GRNs) of mixed populations. The approach outperforms state-of-the-art methods in scenarios with high cell type mixing, providing accurate network estimation.
The study reveals that increasing pressure decreases lattice constants and narrows band gaps, but also enhances optical absorption in these perovskites. This analysis underscores their potential for advanced optoelectronic and photovoltaic technologies.
Researchers develop a cotransporter system that combines autonomous harvesting, unloading, and transportation operations for fully efficient rice harvesting. The proposed dual-unloading mode significantly enhances operational efficiency by minimizing downtime and optimizing resource use.
Researchers engineered β-sheet regions in IsPETase to enhance its depolymerization performance and thermostability. The best variant, DepoPETase β, exhibited superior activity and was found to have enhanced hydrogen bonds and salt bridges, as well as improved binding of PET to active sites.
A new dataset called TV100 reveals that pre-trained CLIP models cannot recognize classes of images released after 2021. However, fine-tuning the model improves its performance significantly, indicating that the dataset is learnable and separable.
Researchers have introduced a novel concept called hybrid-layer optical data storage (ODS) that uses high-orthogonality random meta-channels to encode data into both physical and virtual layers. This approach has shown promising results, achieving a storage density of 2.5 Tbit cm⁻³.
Researchers developed RA-CFGPT, a novel approach to improve Large Language Models' generative capabilities for complex financial tasks. The system incorporates a comprehensive hybrid knowledge base and fine-tuning of a Chinese LLM for task-specific precision.
The new compression-casting technology improves concrete properties without chemical additives, promoting sustainable construction and reducing CO2 emissions. The study reveals superior mechanical properties, durability, and resistance to environmental factors, making it a game-changer for the construction industry.
A team of researchers developed a novel approach to categorize eigencurrents and eigenmodes based on symmetry features, revealing the topological invariants protected by symmetries. This discovery paves the way for synthesizing complex singularities with predictable properties.
A novel method for evaluating real-time dynamic reliability of composite power systems integrated with renewable energy sources (RES) has been introduced. The proposed method significantly reduces computational complexity by using a uniform design-based contingency screening and modified stochastic response surface method.
A recent study optimizes industrial park energy systems with hybrid energy storage to enhance economic performance, reliability, and carbon reduction. The research team developed a detailed model for the system and proposed an active operation strategy that uses energy storage output as decision variables.
Nanofluidic devices overcome challenges in manipulating tiny objects by suppressing random motion and enabling precise control. This enables the transport and control of individual nanoscale objects, paving the way for transformative advancements in science and engineering.
Researchers developed an innovative approach using deep learning to detect Mini-LED backlight quality, achieving high precision and accuracy. This advancement enhances production efficiency and ensures higher quality control standards.
The study investigates organic amendments' decomposition in soils, revealing that mass loss patterns and microbial community characteristics impact carbon retention. Organic amendments enhance humification processes, affecting soil carbon storage.
A recent study highlights the importance of deep soil health in improving crop productivity on low-yielding farmland. Researchers found that improving surface soil health can increase wheat yield, while a complex microbial network is essential for maintaining soil health and crop productivity.
A new ZrO2/Al2O3 catalyst has been developed to significantly enhance CO2 desorption efficiency, reducing energy consumption by 27.56% and optimizing costs. The catalyst's porous structure and active Zr–O–Al coordination promote proton transfer, accelerating CO2 desorption kinetics.
Researchers developed a new ultrafine-grained W-Cu bimetal with spatially connected Cu and specific W islands, achieving outstanding integrated mechanical properties and electric conductivity. The unique microstructure enhances stress distribution and strain response in each phase.
Researchers propose Pro-Aging Metabolic Reprogramming (PAMRP) as a unified theory of aging, suggesting that metabolic changes drive cellular and genetic reprogramming. This new perspective has implications for preventing or reversing aging, with potential therapeutic targets identified.
This special issue aims to present the latest advancements in 3D reconstruction and generation technologies, focusing on virtual/augmented reality, gaming, film production, and more. The topics cover key techniques for fostering breakthroughs and addressing critical problems within this domain.
A new authentication scheme is proposed to address the security challenges in wireless body area networks (WBANs), which guarantee timely data processing and secure information preservation. The proposed scheme requires fewer communication and computation resources, while having stronger security attributes than existing research.
The article presents SS-Pro, a simplified siamese contrastive learning approach for protein surface representation. The method leverages large unlabeled datasets for pre-training and fine-tuning downstream networks, achieving performance enhancements across various protein surface networks.
Intracellular checkpoint molecules in NK cells, such as FBP-1 and EZH2, contribute to exhaustion, while TIPE2 and HIF-1α negatively regulate IL-15 signaling. Targeting these checkpoints may improve cancer immunotherapy outcomes.
A novel thermal dome concept has been proposed to overcome limitations in traditional thermal cloaking devices. The design features an open functional area, enabling usability and applicability for objects with heat sources, and a reconfigurable structure inspired by Lego blocks.
Agricultural water scarcity in China worsens due to climate change, with AWSI increasing during droughts and hot years. Regional scale effects are crucial for forecasting water scarcity, suggesting the need for finer spatial scales in water management strategies.
Researchers developed a tunable plasma photonic crystal 'kaleidoscope' with adjustable geometric configurations, enabling real-time control of structural parameters. The system provides a platform for investigating tunable plasma metamaterials with potential applications in integrated optical components and precision radiolocation.
Researchers propose HATree, utilizing inner node space for in-node hotspot cache and eADR technology for instant log persistence. Experimental results show improved search and update performance compared to previous works.
Droplet-based microfluidics combined with mass spectrometry enhances sensitivity in single-cell proteomics, minimizing sample loss and enabling complex tasks like cell culture and analytes enrichment. This technology has been instrumental in characterizing cellular heterogeneity and discovering new biomarkers.
A research team proposes a dynamic periodic synchronization strategy that adapts to different workloads, reducing synchronization costs. The strategy uses a quantitative analysis model and achieves the best tradeoff between consistency and synchronization cost.
Researchers have developed a novel noise correction method for crowdsourcing that considers both instance features and multiple noisy labels. The method, called LDSNC, outperforms existing competitors in reducing noise impact on integrated labels.
Researchers developed a compound metalens that enables distortion-free imaging across a wide field of view. The device demonstrated diffraction-limited performance and low barrel distortion, outperforming reference metalens.
Research highlights the importance of human and material capital in promoting sustainable tourism, while acknowledging unequal access to opportunities. The study recommends investing in public infrastructure and financial support for families to ensure equitable benefits.
Researchers developed a dual-layer optimization framework that integrates electricity and heat demand response, increasing revenue by 5.09% and consumer surplus by 2.46%. The strategy also reduced carbon trading costs by 5.23% and emissions by 2.54%, promoting environmental sustainability.
Graph convolutional networks improve collaborative patterns but exacerbate popularity bias, recommending more popular than lesser-known items. A new method corrects this by identifying and removing influential nodes' effects, improving recommendations for both popular and lesser-known items.
A recent study found that CIDEC/FSP27 enhances PVAT inflammation and macrophage infiltration, exacerbating AAA formation induced by high-fat diet and Ang II. FSP27 deficiency attenuates HFD-induced PVAT inflammation and prevents AAA formation.
Researchers report two cases of acquired immune thrombotic thrombocytopenic purpura (TTP) after administration of inactivated COVID-19 vaccine CoronaVac. TTP incidence increased in years following COVID-19 vaccination campaigns, suggesting a possible correlation between the vaccines and the condition.
Researchers propose a Graph-Segmenter using graph transformer and boundary-aware attention for simultaneous global and local view modeling. The approach enhances backbone capabilities by addressing issues in sliding window-based semantic segmentation.
A recent study by researchers from Zhejiang University and Nankai University estimates that AI systems could emit more than 102 million tons of CO₂ annually. The study analyzes energy consumption from 79 major AI systems between 2020 and 2024, highlighting the need for regulatory measures and standardized emissions caps.
A large body of research has been dedicated to automated issue classification for Issue Tracking Systems (ITSs). The team proposed an advanced approach called DeepLabel, which achieved better performance compared to existing approaches.
A recent study has identified the pivotal role of CD39 expression in modulating CAR-T cell function. Moderate CD39 expression levels displayed superior antitumor activity compared to those with high or low CD39 levels. The combination strategy of mdivi-1 and CD39 knockdown significantly enhanced the antitumor response.
Researchers evaluated four M-protease inhibitors against SARS-CoV-2 variants and other coronaviruses. LTV demonstrated superior inhibitory activity against M-protease mutants, while ETV showed limited impact on α-coronaviruses.
Delegable zk-SNARKs with proxies enable secure proof generation by sharing partial witnesses among multiple parties, achieving computational soundness and perfect zero knowledge.
Researchers discovered epigenetic silencing of BEND4 as a synthetic lethal marker for ATM inhibitors in pancreatic cancer. This approach targets the tumor suppressor gene, enhancing treatment efficacy. The study found significant association between BEND4 methylation and poor tumor differentiation.
Researchers successfully fabricate subwavelength nanostructures on Au nanofilm using laser direct-writing system, achieving minimum linewidth of 83.6 nm and repeatable linewidth of approximately 167.8 nm. The mechanism involves melting of the Au nanofilm due to locally excited surface plasmon polaritons.
A recent study using single-cell RNA sequencing has identified a 'starter' subpopulation of tumor cells responsible for initiating metastasis in neuroblastoma. The research also uncovered a 150-gene signature associated with poor prognosis, which may inform future therapeutic strategies.
A new research has proposed a Byzantine-Resilient and Verifiable Aggregation for Differentially Private Federated Learning, addressing the limitations of existing protocols. The approach achieves privacy-preservation, byzantine-resilience and verifiability through three primary methods: DPFA, DPLoss, and DPVeri.
A research team has proposed a distributed federated intrusion detection method using a blockchain-based architecture, which ensures secure training and discovery of new attack types. The proposed method outperforms existing methods in guaranteeing training security and discovering new attack types.
Researchers develop ReRAM-based PIM architecture ARCHER to process compressed recommendation systems on monolithic ReRAM chips. The approach enables large practical models on resource-constrained devices while outperforming existing solutions in terms of performance and energy savings.
A groundbreaking study reveals lncRNA Gm20257's regulatory role in pathological cardiac hypertrophy through its interaction with PGC-1α and the mitochondrial complex IV axis. Overexpression of Gm20257 reduces hypertrophic responses and improves cardiac function.
A new method, MLP-Mixer and Mixture of Expert model, predicts lithium-ion battery lifespan with high accuracy by handling varying contributions of different time steps. The proposed model outperforms existing methods on NASA and CALCE public datasets, providing reliable RUL predictions.