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The ability to accurately estimate room impulse responses (RIRs) is integral to many applications of spatial audio processing. Regrettably, estimating the RIR using ambient signals, such as speech or music, remains a challenging problem due to, e.g., low signal-to-noise ratios, finite sample lengths, and poor spectral excitation. Commonly, in order to improve the conditioning of the estimation pro
In this work, we introduce a spatio-temporal kernel for Gaussian process (GP) regression-based sound field estimation. Notably, GPs have the attractive property that the sound field is a linear function of the measurements, allowing the field to be estimated efficiently from distributed microphone measurements. However, to ensure analytical tractability, most existing kernels for sound field estim
Despite advancements, the prevalence of HIV-associated neurocognitive impairment remains at approximately 40%, attributed to factors like pre-cART (combination antiretroviral therapy) irreversible brain injury. People with HIV (PWH) treated with cART do not show significant neurocognitive changes over relatively short follow-up periods. However, quantitative neuroimaging may be able to detect ongo
Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates
The land surface temperature (LT) is a crucial variable that governs the energy and radiation budget of the earth's atmosphere and influences land-atmosphere interactions. The LT plays a crucial role mainly in the short-range forecast of a numerical weather prediction (NWP) model. The primary research goal in this research work undertaken is to assess the impact of assimilation of LT data from the
In this work, we consider the problem of localizing multiple signal sources based on time-difference of arrival (TDOA) measurements. In the blind setting, in which the source signals are not known, the localization task is challenging due to the data association problem. That is, it is not known which of the TDOA measurements correspond to the same source. Herein, we propose to perform joint local
Purpose: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial data from North American men with localized prostate cancer treated with definitive radiation, using biopsy digital pathology images and key clinical information (age, PSA, and T-stage) to generate prognostic scores. This study externally validates the biomarker in a prospective, real-world dataset of
We propose data-driven surrogate models to solve systems of time-dependent differential equations coupled with noise. Using a feedforward neural network, we separately learn the noise and solution, tackling approximations across regimes with bifurcations and rare events. Focusing on irregular data generated by a stochastic noise model on a one-dimensional spatial lattice coupled to a differential
The decline in areal BMD (aBMD) in men may start as early as age 19, but it is debated whether proximal femoral strength follows the same pattern. We measured FN aBMD in a cross-sectional cohort of 1101 men aged 18-28 yr with two-dimensional DXA. Body height, weight, jump height, grip strength, and maximum knee extension torque muscle strength were measured with standard tests, after which BMI was
Solvent cage-escape dynamics of bimolecular photoredox products in solution has been investigated computationally through a combination of molecular dynamics simulations and quantum chemical calculations. The present work focuses on the photoinduced oxidation of the organic electron donor dimethylaniline (DMA) by a Fe(III) N-heterocyclic carbene photosensitizer (Fe(III)NHC+) in two different solve
A general formulation for the distribution problem is presented, which is applicable to frequency distributions of subgrid-scale variables and hydrometeor size distributions, as well as to probability distributions characterizing data uncertainties. The general formulation is presented based upon two well-known basic principles: the maximum-entropy principle and the Liouville equation. The maximum
During 2024, an intensive 114CO2 flask sampling campaign was conducted at 12 sampling stations across Europe as part of the CO2MVS Research on Supplementary Observations (CORSO) project. These 114CO2 samples, combined with CO2 atmospheric measurements, are intended to enhance the estimation of fossil CO2 emissions over Europe through inverse modeling. In this study, we perform a series of Observin
Background: In cardiovascular magnetic resonance, late gadolinium enhancement (LGE) is the standard method to visualize myocardial infarction (MI). Many algorithms quantifying infarct size in LGE images exist. However, only few algorithms have been validated, i.e., benchmarked against an ex-vivo measurement. Furthermore, the reported algorithm performance varies considerably between studies. Objec
Power required to fly for a bird generally follows a U-shaped function of airspeed, with higher cost at both low and high speeds. Because power required increases with body mass faster than power available from flight muscles, larger birds may experience restricted flight speed ranges and climbing capabilities. Previous studies found limited flight performance in cormorants. Adapted for both fligh
Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafau
Purpose: Cardiac diffusion tensor imaging (cDTI) can investigate the microstructure of heart tissue. At sufficiently high b-values, additional information on microstructure can be observed, but the data require a representation such as diffusion kurtosis imaging (DKI). cDTI is prone to image corruption, which is usually treated with shot rejection but which can be handled more generally with robus
The perivascular space (PVS) is integral to glymphatic function, facilitating fluid exchange and waste clearance in the brain. Diffusion tensor imaging along the perivascular space (DTI-ALPS) has been proposed as a noninvasive marker of perivascular diffusion, yet its specificity remains unclear. ALPS measures assume radial symmetry in white matter (characterized by equal transverse diffusion eige
Tropical cyclones (TCs) pose significant threats to life and property across global ocean basins, and forecasting their structural evolution, track, and intensity remains a major scientific challenge. This review synthesizes the current understanding of TCs across major basins, that is, the Pacific, Atlantic, and North Indian Oceans, with a focus on the key environmental factors influencing TC beh
Background and Aims. While the rationale for coronavirus disease 2019 (COVID-19) vaccination is to reduce complications and overall mortality, some cardiovascular complications from the vaccine itself have been demonstrated. Myocarditis and pericarditis are recognized as rare acute adverse events after mRNA vaccines in young males, while evidence regarding other cardiovascular events remains limit
