A verification technique for multiple soft fault diagnosis of linear analog circuits

The paper deals with multiple soft fault diagnosis of linear analog circuits. A fault verification method is developed that allows estimating the values of a set of the parameters considered as potentially faulty. The method exploits the transmittance of the circuit and is based on a diagnostic test leading to output signal in discrete form. Applying Z-transform a diagnostic equation is written which is next reproduced. The obtained system of equations consisting of larger number of equations than the number of the parameters is solved using appropriate numerical approach. The method is adapted to real circumstances taking into account scattering of the fault–free parameters within their tolerance ranges and some errors produced by the method. In consequence, the results provided by the method have the form of ranges including the values of the tested parameters. To illustrate the method two examples of real electronic circuits are given

Fault simulation for structural testing of analogue integrated circuits

In this thesis the ANTICS analogue fault simulation software is described which provides a statistical approach to fault simulation for accurate analogue IC test evaluation. The traditional figure of fault coverage is replaced by the average probability of fault detection. This is later refined by considering the probability of fault occurrence to generate a more realistic, weighted test metric. Two techniques to reduce the fault simulation time are described, both of which show large reductions in simulation time with little loss of accuracy. The final section of the thesis presents an accurate comparison of three test techniques and an evaluation of dynamic supply current monitoring. An increase in fault detection for dynamic supply current monitoring is obtained by removing the DC component of the supply current prior to measurement

Heart rate responses to autonomic challenges in obstructive sleep apnea.

Obstructive sleep apnea (OSA) is accompanied by structural alterations and dysfunction in central autonomic regulatory regions, which may impair dynamic and static cardiovascular regulation, and contribute to other syndrome pathologies. Characterizing cardiovascular responses to autonomic challenges may provide insights into central nervous system impairments, including contributions by sex, since structural alterations are enhanced in OSA females over males. The objective was to assess heart rate responses in OSA versus healthy control subjects to autonomic challenges, and, separately, characterize female and male patterns. We studied 94 subjects, including 37 newly-diagnosed, untreated OSA patients (6 female, age mean ± std: 52.1 ± 8.1 years; 31 male aged 54.3 ± 8.4 years), and 57 healthy control subjects (20 female, 50.5 ± 8.1 years; 37 male, 45.6 ± 9.2 years). We measured instantaneous heart rate with pulse oximetry during cold pressor, hand grip, and Valsalva maneuver challenges. All challenges elicited significant heart rate differences between OSA and control groups during and after challenges (repeated measures ANOVA, p<0.05). In post-hoc analyses, OSA females showed greater impairments than OSA males, which included: for cold pressor, lower initial increase (OSA vs. control: 9.5 vs. 7.3 bpm in females, 7.6 vs. 3.7 bpm in males), OSA delay to initial peak (2.5 s females/0.9 s males), slower mid-challenge rate-of-increase (OSA vs. control: -0.11 vs. 0.09 bpm/s in females, 0.03 vs. 0.06 bpm/s in males); for hand grip, lower initial peak (OSA vs. control: 2.6 vs. 4.6 bpm in females, 5.3 vs. 6.0 bpm in males); for Valsalva maneuver, lower Valsalva ratio (OSA vs. control: 1.14 vs. 1.30 in females, 1.29 vs. 1.34 in males), and OSA delay during phase II (0.68 s females/1.31 s males). Heart rate responses showed lower amplitude, delayed onset, and slower rate changes in OSA patients over healthy controls, and impairments may be more pronounced in females. The dysfunctions may reflect central injury in the syndrome, and suggest autonomic deficiencies that may contribute to further tissue and functional pathologies

Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach.

Functional magnetic resonance imaging (fMRI) is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a general linear model (GLM) approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power, and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making

Machine Learning based Surrogate Modeling of Electronic Devices and Circuits

L'abstract è presente nell'allegato / the abstract is in the attachmen

Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke.

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation

New Aspects of Fault Diagnosis of Nonlinear Analog Circuits

The paper is focused on nonlinear analog circuits, with the special attention paid to circuits comprising bipolar and MOS transistors manufactured in micrometer and submicrometer technology. The problem of fault diagnosis of this class of circuits is discussed, including locating faulty elements and evaluating their parameters. The paper deals with multiple parametric fault diagnosis using the simulation after test approach as well as detection and location of single catastrophic faults, using the simulation before test approach. The discussed methods are based on diagnostic test, leading to a system of nonlinear algebraic type equations, which are not given in explicit analytical form. An important and new aspect of the fault diagnosis is finding multiple solutions of the test equation, i.e. several sets of the parameters values that meet the test. Another new problems in this area are global fault diagnosis of technological parameters in CMOS circuits fabricated in submicrometer technology and testing the circuits  having multiple DC operating points. To solve these problems several methods have been recently developed, which employ  different concepts and mathematical tools of nonlinear analysis. In this paper they are sketched and illustrated.  All the discussed methods are based on the homotopy (continuation) idea. It is shown that various versions of homotopy and combinations  of the homotopy with some other mathematical algorithms lead to very powerful tools for fault diagnosis of nonlinear analog circuits.  To trace the homotopy path which allows finding multiple solutions, the simplicial method, the restart method, the theory of linear complementarity problem and Lemke's algorithm are employed. For illustration four numerical examples are given

Measurements, Models, Systems and Design

531 s.

A collaborator's reputation can bias decisions and anxiety under uncertainty

Informational social influence theory posits that under conditions of uncertainty, we are inclined to look to others for advice. This leaves us remarkably vulnerable to being influenced by other's opinions or advice. Rational agents, however, do not blindly seek and act on arbitrary information, but often consider the quality of its source before committing to a course of action. Here, we ask the question of whether a collaborator's reputation can increase their social influence and, in turn bias perception and anxiety under changing levels of uncertainty. Human male and female participants were asked to provide estimations of dot direction using the random dot motion (RDM) perceptual discrimination task and paired with transient collaborators of high or low reputation whom provided their own estimations. The RDM varied in degrees of uncertainty and joint performance accuracy was linked to risk of an electric shock. Despite providing identical information, we show that collaborating with a high reputation compared to a low reputation partner, led to significantly more conformity during the RDM task for uncertain perceptual decisions. Consequently, high reputation partners decreased the subjects' anxiety during the anticipatory shock periods. fMRI data showed that parametric changes in conformity resulted in increased activity in the ventromedial PFC, while dissent was associated with increased in activity the dorsal anterior cingulate cortex (dACC). Furthermore, the dACC and insula, regions involved in anticipatory pain were significantly more active when collaborating with a low reputation partner. These results suggest that information about reputation can influence both cognitive and affective processes and in turn alter the neural circuits that underlie decision-making and emotion