Multi-modal trajectory forecasting requires balancing predictive diversity and accuracy under a constrained sampling budget. Generative models with mode-structured priors provide strong global expressiveness; however, their instance-agnostic sampling strategies often distribute computation across trajectory modes that are weakly supported by the observed history. This paper presents a hierarchical generative framework that enables instance-adaptive sampling without modifying the underlying generative architecture. The proposed approach introduces a lightweight mode router that estimates an observation-conditioned categorical distribution over trajectory modes. This distribution is used to construct an uncertainty-adaptive feasible mode set via top-(p) selection, where the number of retained modes varies with the uncertainty of the predicted distribution. The retained probability mass is then renormalized into mode-specific sampling weights for downstream trajectory generation. By explicitly allocating the sampling budget at inference time, the proposed sampler concentrates samples on modes with higher posterior support while preserving multi-modal coverage. Experimental results show that the proposed sampler improves trajectory alignment under a fixed sampling budget. The advantage is particularly clear in the constrained Best-of-1 setting, where the prediction is limited to a single final trajectory; our method consistently outperforms MGF across ETH-UCY, SDD, and nuScenes, with additional nuScenes results showing similar gains for a DiffusionDrive-style predictor. The framework provides a practical mechanism for controlling the inference-time trade-off between diversity and accuracy, making it suitable for both real-time trajectory forecasting and decision-oriented trajectory generation in autonomous systems.
Orthopaedic infections are increasingly prevalent in the aging population, posing a significant clinical and economic burden. Despite progress in antimicrobial therapies, challenges such as antibiotic resistance and superbug emergence persist. Gas therapy has emerged as a promising strategy for managing orthopaedic infections. Classical gasotransmitters—including nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2S)—exhibit antibacterial and immunomodulatory effects at controlled concentrations, though improper dosing may induce adverse effects. This review critically examines the dual mechanisms through which gasotransmitters combat infection while promoting orthopaedic regeneration. We also survey advanced delivery platforms—such as smart scaffolds, nano-reservoirs, and on-demand release systems—engineered for targeted gasotransmitter delivery to infected bone tissue. Finally, we discuss current limitations and future prospects, aiming to inspire novel biomaterial designs for targeted therapeutic delivery and to advance gas therapy as a viable option for orthopaedic infection treatment.
Three-dimensional porous carbon materials were prepared from biomass waste sugarcane rind by pretreatment and controlled carbonization process, and their application properties in the field of microwave absorption were systematically investigated. SRC–700 shows excellent electromagnetic wave absorption characteristics in the frequency band of 2–18 GHz. When the matching thickness is 3.3 mm, the effective absorption bandwidth can reach 9.76 GHz (8.24–18.00 GHz). Its enhanced performance is mainly attributed to the unique chemical composition, multiple dielectric loss mechanisms, and the impedance matching optimization resulting from the three-dimensional porous structure. In contrast, when the structure of SRC–700 is damaged, it does not exhibit comparable performance under the same filling ratio (10 wt%) and similar electromagnetic parameters. This confirms that the three-dimensional porous structure plays a critical role in enhancing the multiple reflection/scattering of electromagnetic waves. This study demonstrates the conversion of agricultural waste into a high-performance microwave absorbing material, providing a promising strategy for biomass-derived functional applications.
We report a one-step electrodeposition of amorphous FeCoNi layered double hydroxide (LDH) on nickel foam (FeCoNi LDH/NF) as a cost-effective, robust electrocatalyst for the oxygen evolution reaction (OER) of the alkaline seawater splitting. The optimal Fe1CoNi LDH/NF catalyst exhibits outstanding electrochemical performance, achieving industrial-level current density of 500 mA cm(-2) at a low overpotential of 381 mV in alkaline natural seawater. Impressively, the catalyst demonstrates exceptional operational durability for over 325 h at the same current density in seawater with negligible activity decay, highlighting its superior resistance to chloride corrosion. When configured into an alkaline seawater electrolyzer (Fe1CoNi LDH/NF parallel to Pt/C/NF), the system requires a low cell voltage of 1.88 V to deliver 300 mA cm(-2) and retains excellent stability for more than 346 h. Density functional theory (DFT) calculations reveal that the synergistic electronic modulation among Fe, Co, and Ni sites in the amorphous LDH framework optimizes the local electronic structure and Gibbs free energy of oxygen intermediate adsorption, thereby significantly enhancing the intrinsic OER activity and long-term durability in seawater. This work provides a highly practical and industrially relevant catalyst design for energy-efficient hydrogen production from seawater.
Fruit development and ripening are complex, genetically programmed processes that determine yield, quality, and market value in horticultural crops. These processes rely on the precise temporal and spatial coordination of multiple plant hormones that regulate fruit initiation, growth, maturation, and senescence. Rather than acting independently, hormones operate through highly interconnected signaling networks that involve synergistic and antagonistic interactions at the molecular, cellular, and tissue levels. This review provides an integrated molecular perspective on the hormonal regulation of fruit development and ripening, with emphasis on the dynamic roles of auxin, gibberellins, cytokinins, abscisic acid, ethylene, brassinosteroids, jasmonate, and polyamines. We summarize current knowledge on hormone-driven control of fruit set, early growth, and morphology, followed by a detailed discussion of the hormonal promoters and inhibitors that govern ripening in both climacteric and non-climacteric fruits. Particular attention is given to hormonal crosstalk, key transcriptional regulators, and hormone-perception modules that function as central hubs of integration. Insights from transcriptomics, metabolomics, and tissue-specific studies are highlighted to illustrate how hormonal networks fine-tune developmental transitions. Finally, we discuss future perspectives, including high-resolution hormone mapping, integrative multi-omics approaches, and targeted manipulation of hormone pathways using precision breeding and genome editing to improve fruit quality, stress resilience, and postharvest performance.
