Distribution shift mitigation at test time with performance guarantees

Due to inappropriate sample selection and limited training data, a distribution shift often exists between the training and test sets. This shift can adversely affect the test performance of Graph Neural Networks (GNNs). Existing approaches mitigate this issue by either enhancing the robustness of GNNs to distribution shift or reducing the shift itself. However, both approaches necessitate retraining the model, which becomes unfeasible when the model structure and parameters are inaccessible. To address this challenge, we propose FR-GNN, a general framework for GNNs to conduct feature reconstruction. FRGNN constructs a mapping relationship between the output and input of a well-trained GNN to obtain class representative embeddings and then uses these embeddings to reconstruct the features of labeled nodes. These reconstructed features are then incorporated into the message passing mechanism of GNNs to influence the predictions of unlabeled nodes at test time. Notably, the reconstructed node features can be directly utilized for testing the well-trained model, effectively reducing the distribution shift and leading to improved test performance. This remarkable achievement is attained without any modifications to the model structure or parameters. We provide theoretical guarantees for the effectiveness of our framework. Furthermore, we conduct comprehensive experiments on various public datasets. The experimental results demonstrate the superior performance of FRGNN in comparison to mainstream methods

Dynamical tunneling-assisted coupling of high-Q deformed microcavities using a free-space beam

We investigate the efficient free-space excitation of high-Q resonance modes in deformed microcavities via dynamical tunneling-assisted coupling. A quantum scattering theory is employed to study the free-space transmission properties, and it is found that the transmission includes the contribution from (1) the off-resonance background and (2) the on-resonance modulation, corresponding to the absence and presence of high-Q modes, respectively. The theory predicts asymmetric Fano-like resonances around high-Q modes in background transmission spectra, which are in good agreement with our recent experimental results. Dynamical tunneling across Kolmogorov-Arnold-Moser tori, which plays an essential role in the Fano-like resonance, is further studied. This efficient free-space coupling holds potential advantages to simplify experimental conditions and excite high-Q modes in higher-index-material microcavities

Chaos-assisted broadband momentum transformation in optical microresonators

The law of momentum conservation rules out many desired processes in optical microresonators. We report broadband momentum transformations of light in asymmetric whispering gallery microresonators. Assisted by chaotic motions, broadband light can travel between optical modes with different angular momenta within a few picoseconds. Efficient coupling from visible to near-infrared bands is demonstrated between a nanowaveguide and whispering gallery modes with quality factors exceeding 10 million. The broadband momentum transformation enhances the device conversion efficiency of the third-harmonic generation by greater than three orders of magnitude over the conventional evanescent-wave coupling. The observed broadband and fast momentum transformation could promote applications such as multicolor lasers, broadband memories, and multiwavelength optical networks

Crowd modeling and simulation technologies

As a collective and highly dynamic social group, the human crowd is a fascinating phenomenon that has been frequently studied by experts from various areas. Recently, computer-based modeling and simulation technologies have emerged to support investigation of the dynamics of crowds, such as a crowd's behaviors under normal and emergent situations. This article assesses the major existing technologies for crowd modeling and simulation. We first propose a two-dimensional categorization mechanism to classify existing work depending on the size of crowds and the time-scale of the crowd phenomena of interest. Four evaluation criteria have also been introduced to evaluate existing crowd simulation systems from the point of view of both a modeler and an end-user. We have discussed some influential existing work in crowd modeling and simulation regarding their major features, performance as well as the technologies used in this work. We have also discussed some open problems in the area. This article will provide the researchers with useful information and insights on the state of the art of the technologies in crowd modeling and simulation as well as future research directions.</jats:p

Association of specific biotypes in patients with Parkinson disease and disease progression

Objective: To identify biotypes in patients with newly diagnosed Parkinson disease (PD) and to test whether these biotypes could explain interindividual differences in longitudinal progression. Methods: In this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson's Progression Markers Initiative (n = 314, age 61.0 ± 9.5, years 34.1% female, 5 years of follow-up). Voxel-level neuroanatomic features were estimated with deformation-based morphometry (DBM) of T1-weighted MRI. Voxels with deformation values that were significantly correlated (p < 0.01) with clinical scores (Movement Disorder Society–sponsored revision of the Unified Parkinson’s Disease Rating Scale Parts I–III and total score, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomic features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomic pattern were compared between different biotypes. Results: Two neuroanatomic biotypes were identified: biotype 1 (n = 114) with subcortical brain volumes smaller than heathy controls and biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease durations at the initial visit and follow-up were similar between biotypes, patients with PD with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of 5 years. Conclusion: Robust neuroanatomic biotypes exist in PD with distinct clinical and neuroanatomic patterns. These biotypes can be detected at diagnosis and predict the course of longitudinal progression, which should benefit trial design and evaluation

Chaos-assisted broadband momentum transformation in optical microresonators

The law of momentum conservation rules out many desired processes in optical microresonators. We report broadband momentum transformations of light in asymmetric whispering gallery microresonators. Assisted by chaotic motions, broadband light can travel between optical modes with different angular momenta within a few picoseconds. Efficient coupling from visible to near-infrared bands is demonstrated between a nanowaveguide and whispering gallery modes with quality factors exceeding 10 million. The broadband momentum transformation enhances the device conversion efficiency of the third-harmonic generation by greater than three orders of magnitude over the conventional evanescent-wave coupling. The observed broadband and fast momentum transformation could promote applications such as multicolor lasers, broadband memories, and multiwavelength optical networks

Hearing impairment is associated with cognitive decline, brain atrophy and tau pathology.

Hearing impairment was recently identified as the most prominent risk factor for dementia. However, the mechanisms underlying the link between hearing impairment and dementia are still unclear. We investigated the association of hearing performance with cognitive function, brain structure and cerebrospinal fluid (CSF) proteins in cross-sectional, longitudinal, mediation and genetic association analyses across the UK Biobank (N = 165,550), the Chinese Alzheimer's Biomarker and Lifestyle (CABLE, N = 863) study, and the Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 1770) database. Poor hearing performance was associated with worse cognitive function in the UK Biobank and in the CABLE study. Hearing impairment was significantly related to lower volume of temporal cortex, hippocampus, inferior parietal lobe, precuneus, etc., and to lower integrity of white matter (WM) tracts. Furthermore, a higher polygenic risk score (PRS) for hearing impairment was strongly associated with lower cognitive function, lower volume of gray matter, and lower integrity of WM tracts. Moreover, hearing impairment was correlated with a high level of CSF tau protein in the CABLE study and in the ADNI database. Finally, mediation analyses showed that brain atrophy and tau pathology partly mediated the association between hearing impairment and cognitive decline. Hearing impairment is associated with cognitive decline, brain atrophy and tau pathology, and hearing impairment may reflect the risk for cognitive decline and dementia as it is related to bran atrophy and tau accumulation in brain. However, it is necessary to assess the mechanism in future animal studies. A full list of funding bodies that supported this study can be found in the Acknowledgements section. [Abstract copyright: Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.