Speeded detection of spectrotemporal modulations of sound

We tested whether joint spectrotemporal sensitivity follows from spectrotemporal separability for normal-hearing conditions and for impaired-hearing simulations. In a manual reaction-time task, normal-hearing listeners had to detect the onset of a ripple (with density between 0-8 cycles/octave and a fixed modulation depth of 50%), that moved up or down the log-frequency axis at constant velocity (between 0-64 Hz), in an otherwise-unmodulated broadband white-noise. Spectral and temporal modulations elicited band-pass filtered sensitivity characteristics, with fastest detection rates around 1 cycle/oct and 32 Hz for normal-hearing conditions. These results closely resemble data from other studies that typically used the modulation-depth threshold as a sensitivity measure for spectral-temporal modulations. To simulate hearing-impairment, stimuli were processed with a 6-channel cochlear-implant vocoder, and a hearing-aid simulation that introduced spectral smearing and low-pass filtering. Reaction times were always much slower compared to normal hearing, especially for the highest spectral densities. Binaural performance was predicted well by the benchmark race model of statistical facilitation of independent monaural channels. For the impaired-hearing simulations this implied a "best-of-both-worlds" principle in which the listeners relied on the hearing-aid ear to detect spectral modulations, and on the cochlear-implant ear for temporal-modulation detection. Although singular-value decomposition indicated that the joint spectrotemporal sensitivity matrix could be largely reconstructed from independent temporal and spectral sensitivity functions, in line with time-spectrum separability, a significant inseparable spectral-temporal interaction was present in all hearing conditions. These results imply that the reaction-time task yields a solid and effective objective measure of acoustic spectrotemporal modulation sensitivity, which may also be applicable to hearing-impaired individuals.

Type B Uncertainty Analysis of Gravity-Based Determinations of Triaxial-Accelerometer Properties by Simulation of Measurement Errors

We simulated the effects of gimbal-alignment errors and rotational step-size errors on measurements of the sensitivity matrix and intrinsic properties of a triaxial accelerometer. We restricted the study to measurements carried out on a two-axis calibration system using a previously described measurement and analysis protocol. As well as imperfections in the calibration system, we simulated imperfect orthogonality of the accelerometer axes and non-identical sensitivity of the individual accelerometers in an otherwise perfect triaxial accelerometer, but we left characterization of other accelerometer imperfections such as non-linearity for future study. Within this framework, sensitivity-matrix errors are caused by imperfections in the construction and installation of the accelerometer calibration system, but not by the accelerometer imperfections included in the simulations. We use the results of this study to assign type B uncertainties to the components of the sensitivity matrix and related intrinsic properties due to imperfections in the measurement system. For calibrations using a reasonably well manufactured and installed multi-axis rotation stage such as that studied in this paper, we estimated upper bounds to the standard uncertainties of the order of 1 ×10−5 , 2 ×10−5 , 2 ×10−4 , and 5 ×10−5 for the intrinsic sensitivities, diagonal elements of the sensitivity matrix, off-diagonal elements of the sensitivity matrix, and zero-acceleration offsets, relative to a sensitivity-matrix element of 1, respectively, and 5 ×10−3 degrees for the intrinsic angles

Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations

A sensitivity-based identifiability analysis of mathematical model for partial differential equations is carried out using an orthogonal method and an eigenvalue method. These methods are used to study the properties of the sensitivity matrix and the effects of changes in the model coefficients on the simulation results. Practical identifiability is investigated to determine whether the coefficients can be reconstructed with noisy experimental data. The analysis is performed using correlation matrix method with allowance for Gaussian noise in the measurements. The results of numerical calculations to obtain identifiable sets of parameters for the mathematical model arising in social networks are presented and discussed.

Prior Assumptions for Leak Localisation in Water Distribution Networks with Uncertainties

Hydraulic model-based leak (burst) localisation in water distribution networks is a challenging problem due to a limited number of hydraulic measurements, a wide range of leak properties, and model and data uncertainties. In this study, prior assumptions are investigated to improve the leak localisation in the presence of uncertainties. For example, $$\ell _2$$ ℓ 2 -regularisation relies on the assumption that the Euclidean norm of the leak coefficient vector should be minimised. This approach is compared with a method based on the sensitivity matrix, which assumes the existence of only a single leak. The results show that while the sensitivity matrix method often yields a better leak location estimate in single leak scenarios, the $$\ell _2$$ ℓ 2 -regularisation successfully identifies a search area for pinpointing the accurate leak location. Furthermore, it is shown that the additional error introduced by a quadratic approximation of the Hazen-Williams formula for the solution of the localisation problem is negligible given the uncertainties in Hazen-Williams resistance coefficients in operational water network models.

A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

The occurrence of voltage violations is a major deterrent for absorbing more rooftop solar power into smart Low-Voltage Distribution Grids (LVDGs). Recent studies have focused on decentralized control methods to solve this problem due to the high computational time in performing load flows in centralized control techniques. To address this issue, a novel sensitivity matrix was developed to estimate the voltages of the network by replacing load flow simulations. In this paper, a Centralized Active, Reactive Power Management System (CARPMS) is proposed to optimally utilize the reactive power capability of smart Photovoltaic (PV) inverters with minimal active power curtailment to mitigate the voltage violation problem. The developed sensitivity matrix is able to reduce the time consumed by 55.1% compared to load flow simulations, enabling near-real-time control optimization. Given the large solution space of power systems, a novel two-stage optimization is proposed, where the solution space is narrowed down by a Feasible Region Search (FRS) step, followed by Particle Swarm Optimization (PSO). The failure of standalone PSO to converge to a feasible solution for 34% of the scenarios evaluated further validates the necessity of the two-stage optimization using FRS. The performance of the proposed methodology was analysed in comparison to the load flow method to demonstrate the accuracy and the capability of the optimization algorithm to mitigate voltage violations in near-real time. The deviations of the mean voltages of the proposed methodology from the load flow method were: 6.5×10−3 p.u for reactive power control using Q-injection, 1.02×10−2 p.u for reactive power control using Q-absorption, and 0 p.u for active power curtailment case.

Fully Graph Sensitivity Solution of the Switched Circuits by Two-graph

The most general parameter of the electronic circuit is its sensitivity. Sensitivity analysis helps circuit designers to determine boundaries to predict the variations that a particular design variable will generate in a target specifications, if it differs from what is previously assumed. There are two basic methods for calculating the sensitivity: matrix methods and graph methods. The method described in this article is based on a graph, that contains separate input ad output nodes for each phase. This makes it possible to determine the transmission sensitivity even between partial switching phases. The described fully-graph method is suitable for switched current circuits and switched capacitors circuits, too

Sensitive and quantitative detection of cardiac troponin I with upconverting nanoparticle lateral flow test with minimized interference

Measurement of cardiac troponin I (cTnI) should be feasible for point-of-care testing (POCT) to diagnose acute myocardial infarction (AMI). Lateral flow immunoassays (LFIAs) have been long implemented in POCT and clinical settings. However, sensitivity, matrix effect and quantitation in lateral flow immunoassays (LFIAs) have been major limiting factors. The performance of LFIAs can be improved with upconverting nanoparticle (UCNP) reporters. Here we report a new methodological approach to quantify cTnI using UCNP-LFIA technology with minimized plasma interference. The performance of the developed UCNP-LFIA was evaluated using clinical plasma samples (n = 262). The developed UCNP-LFIA was compared to two reference assays, the Siemens Advia Centaur assay and an in-house well-based cTnI assay. By introducing an anti-IgM scrub line and dried EDTA in the LFIA strip, the detection of cTnI in plasma samples was fully recovered. The UCNP-LFIA was able to quantify cTnI concentrations in patient samples within the range of 30–10,000 ng/L. The LoB and LoD of the UCNP-LFIA were 8.4 ng/L and 30 ng/L. The method comparisons showed good correlation (Spearman’s correlation 0.956 and 0.949, p < 0.0001). The developed UCNP-LFIA had LoD suitable for ruling in AMI in patients with elevated cTnI levels and was able to quantify cTnI concentrations in patient samples. The technology has potential to provide simple and rapid assay for POCT in ED setting