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We treat the case of a flat stress-free surface (i.e., the ground in seismological applications) separating air from a homogeneous, isotropic, solid substratum overlain by a homogeneous, isotropic, solid layer (in contact with the ground)…
In this paper we introduce a new Python package, the Pulsar Signal Simulator, or PsrSigSim, which is designed to simulate a pulsar signal from emission at the pulsar, through the interstellar medium, to observation by a radio telescope, and…
The estimation of the signal location and intensity of a peak in a pulse height spectrum is important for x-ray and $\gamma$-ray spectroscopy, charged-particle spectrometry, liquid chromatography, and many other subfields. However, both the…
Background: Spatial transcriptomics have emerged as a powerful tool in biomedical research because of its ability to capture both the spatial contexts and abundance of the complete RNA transcript profile in organs of interest. However,…
We propose a new statistical test to identify non-stationary frequency-modulated stochastic processes from time series data. Our method uses the instantaneous phase as a discriminatory statistics with reliable critical values derived from…
Accurate and real-time monitoring of saturated oxygen level of the blood is an important clinical issue gaining great attention in recent years and during COVID 19 pandemic. Monitoring the patients` ventilation and respiration dynamic is…
Playing with amplitude, phase and frequency of both reference and signal arms, heterodyne holography is well adapted to vibration analysis. Vibration sidebands can be imaged and stroboscopic measurement sensitive to mechanical phase can be…
Aortic valve stenosis (AVS) presents challenges in asymptomatic detection, resulting in delayed intervention. This study aims to understand how AVS affects pulse wave (PW) morphology. A PW database of 16,038 virtual subjects aged 50 to 75…
We develop a framework to uncover and analyze dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive data sets to eliminate erroneous data segments,…
Object: It is increasingly popular to collect as much data as possible in the hospital setting from clinical monitors for research purposes. However, in this setup the data calibration issue is often not discussed and, rather, implicitly…
Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to…
On the microscopic level, biological signal transmission relies on coordinated structural changes in allosteric proteins that involve sensor and effector modules. The timescales and microscopic details of signal transmission in proteins are…
This paper presents a novel pulse-reconstruction method well suited to sparsely sampled repetitive data, such as commonly arise from trains of ultrashort laser-pulses. Typically waveforms in such traces are fully instrument-limited by the…
Computation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation…
The frequency-domain properties of nonstationary functional time series often contain valuable information. These properties are characterized through its time-varying power spectrum. Practitioners seeking low-dimensional summary measures…
We present a Bayesian dynamical inference method for characterizing cardiorespiratory (CR) dynamics in humans by inverse modelling from blood pressure time-series data. This new method is applicable to a broad range of stochastic dynamical…
An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related to the analysis of time-varying graph signals. This work…
A system's internal dynamics and its interaction with the environment can be determined by tracking how external perturbations affect its transition rates between states. Quantitative measurements of these rates are crucial for optimizing…
Stress is considered to be the epidemic of the 21st-century. Yet, mobile apps cannot directly evaluate the impact of their content and services on user stress. We introduce the Beam AI SDK to address this issue. Using our SDK, apps can…
Seizures are one of the defining symptoms in patients with epilepsy, and due to their unannounced occurrence, they can pose a severe risk for the individual that suffers it. New research efforts are showing a promising future for the…