Correlation matrices serve as fundamental representations of functional brain networks in neuroimaging. Conventional analyses often treat pairwise interactions independently within Euclidean space, neglecting the underlying geometry of correlation structures. Although recent efforts have leveraged the quotient geometry of the correlation manifold, they suffer from computational inefficiency and numerical instability, especially in high-dimensional settings. We propose a novel geometric framework that uses diffeomorphic transformations to embed correlation matrices into a Euclidean space while preserving critical manifold characteristics. This approach enables scalable, geometry-aware analyses and integrates seamlessly with standard machine learning techniques, including regression, dimensionality reduction, and clustering. Moreover, it facilitates population-level inference of brain networks. Simulation studies demonstrate significant improvements in both computational speed and predictive accuracy over existing manifold-based methods. Applications to real neuroimaging data further highlight the framework’s versatility, improving behavioral score prediction, subject fingerprinting in resting-state fMRI, and hypothesis testing in EEG analyses. To support community adoption and reproducibility, we provide an open-source MATLAB toolbox implementing the proposed techniques. Our work opens new directions for efficient and interpretable geometric modeling in large-scale functional brain network research.

The development of subunit vaccines that mimic the molecular complexity of attenuated vaccines has been limited by the difficulty of intracellular co-delivery of multiple chemically diverse payloads at controllable concentrations. We report on hierarchical hydrogel depots employing simple poly(propylene sulfone) homopolymers to enable ratiometric loading of a protein antigen and four physicochemically distinct adjuvants in a hierarchical manner. The optimized vaccine consisted of immunostimulants either adsorbed to or encapsulated within nanogels, which were capable of noncovalent anchoring to subcutaneous tissues. In female BALB/c and C57BL/6 mice, these 5-component nanogel vaccines demonstrated enhanced humoral and cell-mediated immune responses compared to formulations with standard single adjuvant and antigen pairing. The use of a single simple homopolymer capable of rapid and stable loading and intracellular delivery of diverse molecular cargoes holds promise for facile development and optimization of scalable subunit vaccines and complex therapeutic formulations for a wide range of biomedical applications.

In the United States, even though national guidelines for allocating scarce healthcare resources are lacking, 26 states have specific ventilator allocation guidelines to be invoked in case of a shortage. While several states developed their guidelines in response to the recent COVID-19 pandemic, New York State developed these guidelines in 2015 as "pandemic influenza is a foreseeable threat, one that we cannot ignore." The primary objective of this study is to assess the existing procedures and priority rules in place for allocating/rationing scarce ventilator capacity and propose alternative (and improved) priority schemes. We first build machine learning models using inpatient records of COVID-19 patients admitted to New York-Presbyterian/Columbia University Irving Medical Center and an affiliated community health center to predict survival probabilities as well as ventilator length-of-use. Then, we use the resulting point estimators and their uncertainties as inputs for a multiclass priority queueing model with abandonments to assess three priority schemes: (i) SOFA-P (Sequential Organ Failure Assessment based prioritization), which most closely mimics the existing practice by prioritizing patients with sufficiently low SOFA scores; (ii) ISP (incremental survival probability), which assigns priority based on patient-level survival predictions; and (iii) ISP-LU (incremental survival probability per length-of-use), which takes into account survival predictions and resource use duration. Our findings highlight that our proposed priority scheme, ISP-LU, achieves a demonstrable improvement over the other two alternatives. Specifically, the expected number of survivals increases and death risk while waiting for ventilator use decreases. We also show that ISP-LU is a robust priority scheme whose implementation yields a Pareto-improvement over both SOFA-P and ISP in terms of maximizing saved lives after mechanical ventilation while limiting racial disparity in access to the priorityqueue.

This study aimed to identify distinct profiles of investigators based on their exposure to child sexual abuse material (CSAM) and associated mental health symptomatology. Specifically, the study seeks to differentiate resilient profiles from those exhibiting psychopathologies. Additionally, this research explores resilience as a transdiagnostic and distal factor, examining individual- and agency-level coping and resiliency factors. An analytic sample of 500 police investigators and forensic examiners exposed to CSAM comprised the current sample. Latent profile analysis identified five profiles based on CSAM exposure and psychopathology. Profiles were compared across various individual- and agency-level factors. Distinct profiles emerged, including low exposure and psychopathology, average exposure and low psychopathology, low exposure and high psychopathology, high exposure and low psychopathology (representing resilience), and high exposure and high psychopathology. Resilient profiles demonstrated higher scores in general resiliency, future orientations, and purpose in life. Noteworthy differences were found in individual- and agency-level factors, emphasizing the role of appreciation, support, and a positive work climate. The study underscores the diversity of experiences among law enforcement professionals conducting CSAM investigations. Resilient profiles highlight the importance of factors like mattering, appreciation, support, and a positive work climate. These findings have implications for wellness training and agency practices to enhance the well-being of investigators dedicated to protecting children. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

ABSTRACT We provide evidence that banks classify fixed-rate debt investment securities as held to maturity (HTM) rather than as available for sale (AFS) when HTM classification provides preferred financial accounting and regulatory capital treatments, not because they have a distinct economically motivated intent and ability to hold the securities to maturity. Specifically, we document predictably divergent security classifications by three categories of banks that differ in whether the regulatory accumulated other comprehensive income (AOCI) filter, which removes AOCI from Tier 1 capital, applies in four subperiods of our 2012–2022 sample period. The boundaries of the subperiods reflect changes in the AOCI filter’s applicability in 2014 and 2019 and the sharp rise in interest rates beginning in late 2021. We further find that the bank categories differ in the interest rate risk of their AFS securities and the extents to which they economically hedge that risk using derivatives and uninsured deposits. JEL Classifications: G21; G28; M41; M48.

ABSTRACT Ball and Brown (1968) introduce a method to measure accounting earnings’ contribution to price discovery toward the end-of-period price. Building on this method, we examine a comprehensive set of corporate disclosures and document a large gap in their contribution to annual price discovery between bad and good news years (40 percent versus over 60 percent), despite no such difference in stock return variance (partial R2). These patterns are consistent with managers proactively releasing good news to counteract negative news during bad news years. Our finding broadens the concept of news bundling from concurrent releases to intertemporal dynamics within an annual window. Voluntary press releases are a key driver of this disparity in price discovery, adding 3 percent in bad times while being the top contributor in good times (27 percent). Investor private information acquisition contributes to bridging the gap left by corporate disclosures in price discovery during bad news years. Data Availability: Data are available from public sources cited in the text. JEL Classifications: G10; G12; M41.

Abstract COVID‐19 sparked a global public health crisis, to which countries around the world responded differently. However, the critical reasons behind governments' slow or stringent responses to COVID‐19 remain understudied. Leveraging multiple global databases on COVID‐19 policies, trust, and national cultural orientation, this study spotlights the crucial roles of institutional trust and individualism in shaping the speed and stringency of early COVID‐19 policy responses across 120 countries. Using necessary condition analysis (NCA), the study unveils that low institutional trust is necessary for high first‐response delay, while both low institutional trust and low individualism are necessary for high first‐response stringency. A mediating necessity relationship is established: “low institutional trust—high first‐response delay—high first‐response stringency.” These findings underscore the critical need to improve institutional trust, enabling a crisis response policy of “responding quickly with low stringency,” thus minimizing early‐phase health and socioeconomic repercussions. By highlighting the imperative of institutional trust and individualistic culture in crisis policymaking, this study provides new insights into how and why informal institutions matter most for early crisis responses.

We provide novel evidence that aggregate investor attention to stocks predicts marketwide returns, but with a striking difference across investor clienteles. Daily aggregate retail attention (ARA) negatively predicts one-week-ahead market returns, is associated with aggregate retail order imbalance and flows to equity mutual funds, and exhibits a stronger predictability during periods of high marketwide uncertainty, poor liquidity, or more costly short selling. In contrast, aggregate institutional attention (AIA), when observed before major news announcements, positively predict future marketwide returns. In cross-sectional analysis, we show that the predictability is stronger for ARA among illiquid stocks and for AIA among high-beta stocks. The predictability results are robust out-of-sample and correspond to meaningful expected utility gains even for diversified investors. The findings are consistent with the idea that attention-driven retail buying can generate an aggregate price pressure on the stock market, whereas institutional attention precedes the resolution of marketwide uncertainty and the accrual of risk premiums. This paper was accepted by Will Cong, finance. Funding: J. Hua acknowledges the Professional Staff Congress-City University of New York Research Foundation for financial support. L. Peng acknowledges the Wasserman Summer Research Grant and the Krell Research Fund for financial support. T.C.-C. Hung acknowledges research support from the Ministry of Science and Technology, Taiwan [Grants 110-2410-H-002-245 and 111-2410-H-002-197], and the E. Sun Academic Award. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.01294 .

Inspired by ideas stemming from the analysis of the Boltzmann equation, in this article, we expand the well-posedness theory of the spatially inhomogeneous 4-wave kinetic equation and also analyze an infinite hierarchy of PDEs associated with this nonlinear equation. More precisely, we show global in time well-posedness of the spatially inhomogeneous 4-wave kinetic equation for polynomially decaying small initial data. For the associated infinite hierarchy, we construct global in time solutions using the solutions of the wave kinetic equation and the Hewitt-Savage theorem. The uniqueness of these solutions is proved by using a combinatorial board game argument tailored to this context, which allows us to control the factorial growth of the Dyson series.

ABSTRACT This study explores how five conditions – a delayed public-health response, the risk of healthcare capacity being overwhelmed, trust in government, individualistic cultural orientation, and population density – have jointly contributed to high versus low older adults’ mortality rates during the early phase of the COVID-19 pandemic across 39 ageing countries. A fuzzy-set qualitative comparative analysis (fsQCA) identifies four configurations associated with high and an additional five configurations linked to low older adults’ mortality rates. The study underscores the absence of a one-size-fits-all ‘playbook’ that ageing countries can adopt to protect their seniors. They must customize their pandemic response policies to align with their specific cultural and demographic circumstances.