Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified blueprint for researchers to navigate classification, clustering, incomplete views and hybrid techniques.

DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification accuracy for streaming irregular multivariate time series.

A research paper by scientists from Liaoning Cancer Hospital & Institute, The First Affiliated Hospital of Ningbo University, and other institutions proposed a hollow mesoporous carbon (HMC) nanoparticle prepared via the sacrificial template method, featuring a porphyrin-like structure that enables efficient singlet oxygen generation and synergistic sono-immunotherapy for pancreatic cancer.

The new research paper, published on May 9 in the journal Cyborg and Bionic Systems, presented the preparation, characterization, and therapeutic application of MOF-derived HMC nanoparticles, and demonstrated their potential to enhance sono-immunotherapy efficacy by inducing tumor cell apoptosis and activating the immune

 Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the representation performance.

The complex fluid–structure interaction underlying blood flow through vessels has proved challenging to analyze both numerically and experimentally. Addressing this gap, researchers developed a new experimental platform that uses polarized light to directly visualize stress fields in artificial blood vessels and in the flowing blood analogue in real time. Their findings reveal how stress is distributed during pulsating flow and could help design safer devices and improve the diagnosis and treatment of cardiovascular diseases.

This review systematically summarizes recent research on co-processing biomass with petroleum streams via fluid catalytic cracking and hydrotreating, addressing feedstock properties, catalyst performance, and pilot-scale projects.

Researchers from Xi'an Jiaotong University have developed a groundbreaking compressed carbon dioxide (CO₂) energy storage system that achieves unprecedented efficiency while simultaneously generating electricity and cooling energy. The study, published in Frontiers in Energy, introduces a novel gas-liquid phase change approach that eliminates geographical constraints and reduces operating pressures, potentially transforming how commercial facilities and power grids manage renewable energy storage.

Developing environmentalyl friendly and energy-efficient CO₂ adsorbents for post-combustion capture is a critical step toward achieving toward carbon neutrality. While aqueous amines and metal oxides have play pivotal roles in CO₂ capture, their application is limited by issues such as secondary pollution and high energy consumption. In contrast, Zn-based metal-organic frameworks (Zn-based MOFs) have emerged as a green alternative, offering low toxicity reduced regeneration temperatures, and high efficiency in both CO₂ adsorption and catalytic conversion into valuable fuels and chemicals. This mini review begins with a general introduction to MOFs in CO₂ capture and conversion, followed by an overview of early studies on Zn-based MOFs for CO₂ capture. It then summarizes recent research advancements in Zn-based MOFs for integrated CO₂ capture and conversion. Finally, it discusses key challenges and future research directions for post-combustion CO₂ capture and conversion using Zn-based MOFs.