Scaling in Nonstationary Voltammetry Representations

Despite the widespread use of voltammetry for a range of chemical, biological, environmental, and industrial applications, there is still a lack of understanding regarding the functionality between the applied voltage and the resulting patterns in the current response. This is due to the highly nonlinear relation between the applied voltage and the nonstationary current response, which casts a direct association nonintuitive. In this Article, we focus on large-amplitude/high-frequency ac voltammetry, a technique that has shown to offer increased voltammetric detail compared to alternative methods, to study heterogeneous electrochemical reaction-diffusion cases using a nonstationary time-series analysis, the Hilbert transform, and symmetry considerations. We show that application of this signal processing technique minimizes the significant capacitance contribution associated with rapid voltammetric measurements. From a series of numerical simulations conducted for different voltage excitation parameters as well as kinetic, thermodynamic, and mass transport parameters, a number of scaling laws arise that are related to the underlying parameters/dynamics of the process. Under certain conditions, these observations allow the determination of all underlying parameters very rapidly, experiment duration typically ≤1 s, using standard electrode geometries and without any a priori assumptions regarding their value. The theoretical results derived from this analysis are compared to experiments with an outer-sphere electron-transfer species, Ru(NH3)62+/3+, on different electrode materials, and the determined parameters are in excellent agreement with published values

Suplemental Material (PDF file) from Evaluation of a portable retinal imaging device: towards a comparative quantitative analysis for morphological measurements of retinal blood vessels

A figure with a zoomed version of the USAF test chart. / Graphs of the rest of the tested metrics. / Figures of other segmentation algorithms tested

Matlab Code (ZIP file) from Evaluation of a portable retinal imaging device: towards a comparative quantitative analysis for morphological measurements of retinal blood vessels

Retinal blood vessel segmentation cod

Subsecond Voltammetric Separation between Dopamine and Serotonin in the Presence of Ascorbate

Although voltammetry has proved an important tool for unraveling the dynamics of specific neurotransmitter molecules during the past decade, it has been very difficult to monitor more than one neurotransmitter simultaneously. In this work, we present a voltammetric methodology that allows discrimination between dopamine and serotonin, two important neurotransmitter molecules with very similar electrochemical properties, in the presence of high concentrations of ascorbate. We combined the application of a novel large-amplitude/high-frequency voltage excitation with signal processing techniques valid for the analysis of nonstationary and nonlinear phenomena. This allows us to minimize the contribution from capacitance and preserve the faradaic features of the voltammetric response providing us with excellent voltammetric detail. Using appropriate voltage excitation parameters and defining specific regions in the voltage space, so-called voltage windows, we can measure the concentrations of dopamine and serotonin separately or independently in mixed solutions even in the presence of high concentrations of ascorbate. Because of the enhanced voltammetric detail of this new technique, it is also possible to explore effects attributed to interfacial phenomena such as adsorption/desorption and electrode fouling

Correlations between magnitude and timings of various indices of wave reflection.

<p>AIx, augmentation index; P_b backward pressure, P_b/P_f, the ratio of forward to backward pressure; T_s, the time of the shoulder of the waveform; WRI, wave reflection index. Data are Pearson’s correlation coefficients.</p

Scatterplots of the relationship between age and various indices.

<p>A) Age vs. AIx B) Age vs, Log wave reflection index (WRI) and C) Age vs. peak backward/peak forward pressure (P_b/P_f). Regression lines are derived from data pooled by gender but data points for men (○) and women (•) are indicated separately.</p

Wave intensity analysis and pressure separation of the 3 different types of pressure waveform.

<p>The three types of pressure waveform (A, B, C) and their respective augmentation indices (AIx) are shown. The magnitude of the pressure and wave intensity traces have been scaled equally to allow comparison of morphology. Three principal wave S, c⁻₁ and D, forward pressure (P_f) backward pressure (P_b) and the shoulder point (P_s) are indicated.</p

Characteristics of the individuals studied.

<p>Data for men and women are also shown separately.</p><p>Data are mean (SD); p values were calculated using a Student’s t-test comparing women and men. AIx, augmentation index; BMI, body mass index; cSBP, central systolic pressure; DBP, diastolic blood pressure; HR, heart rate, Pb/Pf, the ratio of forward to backward pressure; SBP, systolic pressure; T₁, the time difference between the foot and the shoulder of the waveform; WRI, wave reflection index.</p

Automated speckle tracking algorithm to aid on-axis imaging in echocardiography

Obtaining a “correct” view in echocardiography is a subjective process in which an operator attempts to obtain images conforming to consensus standard views. Real-time objective quantification of image alignment may assist less experienced operators, but no reliable index yet exists. We present a fully automated algorithm for detecting incorrect medial/lateral translation of an ultrasound probe by image analysis. The ability of the algorithm to distinguish optimal from sub-optimal four-chamber images was compared to that of specialists—the current “gold-standard.” The orientation assessments produced by the automated algorithm correlated well with consensus visual assessments of the specialists (r=0.87r=0.87) and compared favourably with the correlation between individual specialists and the consensus, 0.82±0.09. Each individual specialist’s assessments were within the consensus of other specialists, 75±14% of the time, and the algorithm’s assessments were within the consensus of specialists 85% of the time. The mean discrepancy in probe translation values between individual specialists and their consensus was 0.97±0.87??cm, and between the automated algorithm and specialists’ consensus was 0.92±0.70??cm. This technology could be incorporated into hardware to provide real-time guidance for image optimisation—a potentially valuable tool both for training and quality control.</p

Correlations between magnitude and timings of various indices of wave reflection and height.

<p>AIx, augmentation index; P_b backward pressure; P_b/P_f, the ratio of forward to backward pressure; T_s, the time of the shoulder of the waveform; WRI, wave reflection index. Data are Pearson’s correlation coefficients. Data are Pearson’s correlation coefficients.</p