Data-driven Identification of Parametric Governing Equations of Dynamical Systems Using the Signed Cumulative Distribution Transform.

This paper presents a novel data-driven approach to identify partial differential equation (PDE) parameters of a dynamical system. Specifically, we adopt a mathematical "transport" model for the solution of the dynamical system at specific spatial locations that allows us to accurately estimate the model parameters, including those associated with structural damage. This is accomplished by means of a newly-developed mathematical transform, the signed cumulative distribution transform (SCDT), which is shown to convert the general nonlinear parameter estimation problem into a simple linear regression.

An evidence-based approach to assessing the effectiveness of training regimen on athlete performance: Youth soccer as a case study.

Athletic performance data are modeled in an effort to better understand the relationship between both hours spent training and a measurement of "commitment" to that training, and improvements in performance. Both increased training time and greater commitment were predicted to produce larger increases in performance improvement, and commitment was predicted to be the more important determinant of improvement. The performance of 108 soccer players (ages 9-18) was quantified over a 10-week training program.

Radon Cumulative Distribution Transform Subspace Modeling for Image Classification.

We present a new supervised image classification method applicable to a broad class of image deformation models. The method makes use of the previously described Radon Cumulative Distribution Transform (R-CDT) for image data, whose mathematical properties are exploited to express the image data in a form that is more suitable for machine learning. While certain operations such as translation, scaling, and higher-order transformations are challenging to model in native image space, we show the R-CDT can capture some of these variations and thus render the associated image classification problems easier to solve.

Transport-based pattern recognition versus deep neural networks in underwater OAM communications.

Comparisons between machine learning and optimal transport-based approaches in classifying images are made in underwater orbital angular momentum (OAM) communications. A model is derived that justifies optimal transport for use in attenuated water environments. OAM pattern demultiplexing is performed using optimal transport and deep neural networks and compared to each other.

Parametric Signal Estimation Using the Cumulative Distribution Transform.

We present a new method for estimating signal model parameters using the Cumulative Distribution Transform (CDT). Our approach minimizes the Wasserstein distance between measured and model signals. We derive some useful properties of the CDT and show that the resulting estimation problem, while nonlinear in the original signal domain, becomes a linear least squares problem in the transform domain.

Linear transfer function estimation using the photodiode impulse response.

In this Letter, we implement a model-based auto-regressive estimator of the frequency response for a high-speed photodiode (PD). A transfer function is developed, and the associated coefficients representing the PD model and frequency response are solved for using a two-stage least-squares approach. The model is implemented for a modified uni-traveling carrier PD and experimentally compared to measured impulse response data.

Sediment starvation destroys New York City marshes' resistance to sea level rise.

New York City (NYC) is representative of many vulnerable coastal urban populations, infrastructures, and economies threatened by global sea level rise. The steady loss of marshes in NYC's Jamaica Bay is typical of many urban estuaries worldwide. Essential to the restoration and preservation of these key wetlands is an understanding of their sedimentation.

Surveying silicon nitride nanopores for glycomics and heparin quality assurance.

Polysaccharides have key biological functions and can be harnessed for therapeutic roles, such as the anticoagulant heparin. Their complexity-e.g.

De-multiplexing vortex modes in optical communications using transport-based pattern recognition.

Free space optical communications utilizing orbital angular momentum beams have recently emerged as a new technique for communications with potential for increased channel capacity. Turbulence due to changes in the index of refraction emanating from temperature, humidity, and air flow patterns, however, add nonlinear effects to the received patterns, thus making the demultiplexing task more difficult. Deep learning techniques have been previously been applied to solve the demultiplexing problem as an image classification task.

Conductance-based profiling of nanopores: Accommodating fabrication irregularities.

Solid-state nanopores are nanoscale channels through otherwise impermeable membranes. Single molecules or particles can be passed through electrolyte-filled nanopores by, e.g.

The impact of an ICME on the Jovian X-ray aurora.

We report the first Jupiter X-ray observations planned to coincide with an interplanetary coronal mass ejection (ICME). At the predicted ICME arrival time, we observed a factor of ∼8 enhancement in Jupiter's X-ray aurora. Within 1.

Solar cycles or random processes? Evaluating solar variability in Holocene climate records.

Many studies have reported evidence for solar-forcing of Holocene climate change across a range of archives. These studies have compared proxy-climate data with records of solar variability (e.g.

"Store-operated" cAMP signaling contributes to Ca2+-activated Cl- secretion in T84 colonic cells.

Apical cAMP-dependent CFTR Cl(-) channels are essential for efficient vectorial movement of ions and fluid into the lumen of the colon. It is well known that Ca(2+)-mobilizing agonists also stimulate colonic anion secretion. However, CFTR is apparently not activated directly by Ca(2+), and the existence of apical Ca(2+)-dependent Cl(-) channels in the native colonic epithelium is controversial, leaving the identity of the Ca(2+)-activated component unresolved.

Order and disorder in irreversible decay processes.

Dynamical disorder motivates fluctuating rate coefficients in phenomenological, mass-action rate equations. The reaction order in these rate equations is the fixed exponent controlling the dependence of the rate on the number of species. Here, we clarify the relationship between these notions of (dis)order in irreversible decay, n A → B, n = 1, 2, 3, …, by extending a theoretical measure of fluctuations in the rate coefficient.

Estimating detection and identification probabilities in maritime target acquisition.

This work describes several approaches to the estimation of target detection and identification probabilities as a function of target range. A Bayesian approach to estimation is adopted, whereby the posterior probability distributions associated with these probabilities are analytically derived. The parameter posteriors are then used to develop credible intervals quantifying the degree of uncertainty in the parameter estimates.

The auroral footprint of Enceladus on Saturn.

Although there are substantial differences between the magnetospheres of Jupiter and Saturn, it has been suggested that cryovolcanic activity at Enceladus could lead to electrodynamic coupling between Enceladus and Saturn like that which links Jupiter with Io, Europa and Ganymede. Powerful field-aligned electron beams associated with the Io-Jupiter coupling, for example, create an auroral footprint in Jupiter's ionosphere. Auroral ultraviolet emission associated with Enceladus-Saturn coupling is anticipated to be just a few tenths of a kilorayleigh (ref.

Jupiter's nightside airglow and aurora.

Observations of Jupiter's nightside airglow (nightglow) and aurora obtained during the flyby of the New Horizons spacecraft show an unexpected lack of ultraviolet nightglow emissions, in contrast to the case during the Voyager flybys in 1979. The flux and average energy of precipitating electrons generally decrease with increasing local time across the nightside, consistent with a possible source region along the dusk flank of Jupiter's magnetosphere. Visible emissions associated with the interaction of Jupiter and its satellite Io extend to a surprisingly high altitude, indicating localized low-energy electron precipitation.

A unified approach to attractor reconstruction.

In the analysis of complex, nonlinear time series, scientists in a variety of disciplines have relied on a time delayed embedding of their data, i.e., attractor reconstruction.

Bragg grating-based fibre optic sensors in structural health monitoring.

This work first considers a review of the dominant current methods for fibre Bragg grating wavelength interrogation. These methods include WDM interferometry, tunable filter (both Fabry-Perot and acousto-optic) demultiplexing, CCD/prism technique and a newer hybrid method utilizing Fabry-Perot and interferometric techniques. Two applications using these techniques are described: hull loads monitoring on an all-composite fast patrol boat and bolt pre-load loss monitoring in a composite beam in conjunction with a state-space modelling data analysis technique.