A new critical review published in Materials Futures traces the rapid evolution of Refractory High-Entropy Alloys (RHEAs), a revolutionary class of materials engineered for extreme environments. The review, led by researchers from Shanghai Jiao Tong University, highlights a paradigm shift from traditional alloy design towards computational- and microstructurally-guided strategies. It details how advanced tools like machine learning, quantum mechanics simulations, and phase diagram calculations are accelerating the discovery of new compositions. A central focus is on innovative microstructural designs, including metastable engineering, heterogeneous structures, and atomic-scale chemical ordering, that are successfully overcoming the long-standing trade-off between strength and ductility. The authors conclude that the integration of multi-scale modeling, in-situ characterization, and closed-loop data analysis is poised to transition RHEAs from laboratory breakthroughs to critical components in aerospace, energy, and nuclear applications.

Recently, Associate Professor Xiaolong Feng from the College of Economics and Management at China Agricultural University, together with researchers from the Alliance for a Green Revolution in Africa (AGRA), has addressed these questions through a comparative analysis of agricultural subsidy policies in China and Africa. The related article has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025624).

Recently, an in-depth study addressing this question was jointly conducted by Associate Professor Ting Meng from the College of Economics and Management at China Agricultural University, in collaboration with researchers from the Research Institute for Eco-civilization of the Chinese Academy of Social Sciences and the Alliance of Biodiversity International and International Center for Tropical Agriculture (Senegal). The study offers systematic solutions for developing countries, and the related article was published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025646).

We systematically review 34 relevant studies between 2015 and 2025 following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, focusing on the combination of multimodal wearable sensing with learning models.

Human action recognition (HAR) is crucial for the development of efficient computer vision, where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces. However, the absence of interactions among versatile biomimicking functionalities within a single device, which was developed for specific vision tasks, restricts the computational capacity, practicality, and scalability of in-sensor vision computing. Here, we propose a bioinspired vision sensor composed of a GaN/AlN-based ultrathin quantum-disks-in-nanowires (QD-NWs) array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing. By simply tuning the applied bias voltage on each QD-NW-array-based pixel, we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency, respectively. Strikingly, the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4% to 81.4% owing to the integrated artificial vision system. The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.

The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision. While flexible pressure-sensing insoles show clinical potential, their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity (R² > 0.99 up to 1 MPa) in conventional designs. Inspired by the tactile sensing mechanism of human skin, where dermal stratification enables wide-range pressure adaptation and ion-channel-regulated signaling maintains linear electrical responses, we developed a dual-mechanism flexible iontronic pressure sensor (FIPS). This innovative design synergistically combines two bioinspired components: interdigitated fabric microstructures enabling pressure-proportional contact area expansion (∝ P^1/3) and iontronic film facilitating self-adaptive ion concentration modulation (∝ P^2/3), which together generate a linear capacitance-pressure response (C ∝ P). The FIPS achieves breakthrough performance: 242 kPa⁻¹ sensitivity with 0.997 linearity across 0–1 MPa, yielding a record linear sensing factor (LSF = 242,000). The design is validated across various substrates and ionic materials, demonstrating its versatility. Finally, the FIPS-driven design enables a smart insole demonstrating 1.8% error in tibial load assessment during gait analysis, outperforming nonlinear counterparts (6.5% error) in early fracture-risk prediction. The biomimetic design framework establishes a universal approach for developing high-performance linear sensors, establishing generalized principles for medical-grade wearable devices.

Emerging ferroptosis–immunotherapy strategies, integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics, demonstrate significant potential in managing primary, recurrent, and metastatic malignancies. Mechanistically, ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death (ICD), eliciting damage-associated molecular patterns (DAMPs) release to activate partial antitumor immunity. However, standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations: low tumor immunogenicity, immunosuppressive microenvironment constraints, and tumor microenvironment (TME)-associated physiological barriers (e.g., hypoxia, dense extracellular matrix). To address these challenges, synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance, encompassing (1) direct amplification of antitumor immunity, (2) disruption of immunosuppressive tumor niches, and (3) biophysical hallmark remodeling in TME. Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy. Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy, this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis–immunotherapy strategies. It advances multidimensional nanoplatform design principles for material selection, structural configuration, physicochemical modulation, multifunctional integration, and artificial intelligence-enabled design, providing a scientific basis for efficacy optimization. Moreover, it examines translational challenges of ferroptosis–immunotherapy nanoplatforms across preclinical and clinical stages, proposing actionable solutions while envisioning future onco-immunotherapy directions. Collectively, it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies, offering a roadmap for accelerating clinical translation in onco-immunotherapy research.