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Reconstructing near-wall turbulence from wall-based measurements is a critical yet inherently ill-posed problem in wall-bounded flows, where limited sensing and spatially heterogeneous flow–wall coupling challenge deterministic estimation strategies. To address this, we introduce a novel generative modelling framework based on conditional flow matching for synthesising instantaneous velocity fluctuation fields from wall observations, with explicit quantification of predictive uncertainty. Our method integrates continuous-time flow matching with a probabilistic forward operator trained using stochastic weight-averaging Gaussian, enabling zero-shot conditional generation without model re-training. We demonstrate that the proposed approach not only recovers physically realistic, statistically consistent turbulence structures across the near-wall region but also effectively adapts to various sensor configurations, including sparse, incomplete and low-resolution wall measurements. The model achieves robust uncertainty-aware reconstruction, preserving flow intermittency and structure even under significantly degraded observability. Compared with classical linear stochastic estimation and deterministic convolutional neural network methods, our stochastic generative learning framework exhibits superior generalisation for unseen realisations under same flow conditions and resilience under measurement sparsity with quantified uncertainty. This work establishes a robust semi-supervised generative modelling paradigm for data-consistent flow reconstruction and lays the foundation for uncertainty-aware, sensor-driven modelling of wall-bounded turbulence.
Subject personal pronouns are highly variable in Spanish but nearly obligatory in many contexts in English, and regions of Latin America differ significantly in rates and constraints on use. We investigate language and dialect contact by analyzing these pronouns in a corpus of 63,500 verbs extracted from sociolinguistic interviews of a stratified sample of 142 members of the six largest Spanish-speaking communities in New York City. A variationist approach to rates of overt pronouns and variable and constraint hierarchies, comparing speakers from different dialect regions (Caribbeans vs. Mainlanders) and different generations (those recently arrived vs. those born and/or raised in New York), reveals the influence of English on speakers from both regions. In addition, generational changes in constraint hierarchies demonstrate that Caribbeans and Mainlanders are accommodating to one another. Both dialect and language contact are shaping Spanish in New York City and promoting, in the second generation, the formation of a New York Spanish speech community.