Annals of the New York Academy of Sciences最新文献

Weakly supervised semantic segmentation plays a pivotal role in domains such as autonomous driving and medical image analysis. However, existing approaches often rely on limited semantic cues from single images or paired samples, leading to underutilized intraclass information and entangled interclass features—both of which significantly impair segmentation performance. To address these challenges, we propose a novel dual-dimensional contrastive learning (D2CL) framework that explores fine-grained feature attributes both across and within views, thereby promoting intraclass compactness and interclass discriminability in the feature space. Specifically, the interclass prototype contrastive learning module constructs a cross-view dynamic prototype memory bank and imposes a contrastive loss to enhance category-level distinctiveness. In parallel, the intraclass pixel contrastive learning module focuses on pixel-wise variations within the same category from a single view, enabling the model to capture more refined semantic details and better handle intraclass diversity. Extensive experiments conducted on the PASCAL VOC 2012 and MS COCO 2014 datasets demonstrate that D2CL consistently boosts the performance of multiple baseline models. For instance, the mean intersection over union of the baseline model SEAM is improved from 64.5% to 67.7%, while another model AMN sees an increase from 69.6% to 71.8%, highlighting the general applicability and effectiveness of our method.

This study investigated how auditory stimuli and optokinetic stimulation modulate functional Head Impulse Test (fHIT) correct response rate (CR%) across semicircular canals (SCCs) and the associated cognitive load in healthy adults. Fifty participants (20–57 years) completed repeated-measures fHIT under four conditions: silence, music, white noise, and optokinetic stimulation. The CR% from all SCCs were recorded and workload was assessed with the NASA Task Load Index (NASA-TLX). Optokinetic stimulation produced the most significant CR% decrement (e.g., right lateral 90 vs. 100 in silence; p<0.001) and the highest workload (median NASA-TLX = 50). Auditory conditions produced minimal CR% changes. Across conditions, lateral SCCs were less affected than vertical SCCs by sensory and cognitive interference. Visual–vestibular conflict markedly reduced CR%, whereas auditory effects appeared indirect and attention mediated. These findings provide normative benchmarks for multisensory fHIT assessment.

The rapid formation of methane hydrates in subsea pipelines threatens flow safety, while conventional inhibitors face environmental and efficiency limitations. This study investigates a poly(N-vinylcaprolactam)-glycine (PVCap-glycine) composite system for synergistic methane hydrate inhibition. Experimental results demonstrate superior performance: the composite system extends induction time to 672 min (135% and 37% longer than the single PVCap and glycine, respectively), reduces gas consumption by 72.6%, and lowers peak gas consumption rates by 25–45.5% compared to the blank system. Mechanistically, glycine disrupts water's hydrogen-bond network through carboxyl groups, delaying quasi-clathrate nucleation, while PVCap's hydrophobic chains adsorb on crystal nuclei, forming mass-transfer barriers. Their hydrophobic association generates composite micelles, increasing interfacial resistance by approximately 40% and elevating nucleation energy barriers. Notably, substituting glycine for partial PVCap reduces environmental burdens while achieving 135% longer induction time and 45.2% lower gas consumption than the single PVCap, overcoming the performance limitations of individual inhibitors at their optimal concentrations. The synergy originates from glycine's molecular-scale water perturbation and PVCap's interfacial regulation, coupled with wax-induced physicochemical barriers, enabling dual thermodynamic-kinetic inhibition. This synergistic strategy enables high-performance, low-environmental-impact inhibitors for deep-sea pipeline safety.

Two multilayer chiral three-dimensional (3D) polymers exhibiting aggregation-induced emission (AIE) properties were successfully synthesized through Suzuki–Miyaura crosslinking reactions. Deliberately designed with different terminal functional groups (bromine vs. boronic ester), these polymers served as a model system to probe the profound influence of molecular structure on nanoscale aggregation and macroscopic function. Both polymers demonstrated significant AIE behavior, but the variant with less sterically hindered termini formed more uniform aggregates, leading to superior AIE performance. This property enabled their application as ultrasensitive fluorescent probes for the detection of Fe³⁺ and Cr⁶⁺ ions in tetrahydrofuran (THF), achieving detection limits at the nanomolar (nM) level. The materials exhibited outstanding selectivity against competing ions: binding of Fe³⁺ or Cr⁶⁺ inhibited electron transfer, resulting in fluorescence quenching. The distinct terminal groups were found to influence the sensing mechanism, with the boronic ester functionality introducing an additional redox-based pathway for enhanced Fe³⁺ sensitivity. This study establishes a comprehensive design paradigm for AIE-active materials, linking precise structural engineering to extended sensing functions. These multifunctional polymers show great potential for applications in environmental monitoring, biomedical diagnostics, and the development of advanced smart sensors.