Signal Perturbation Research Articles

Rapid SARS-CoV-2 Detection Using Electrochemical Immunosensor.

The outbreak of the coronavirus disease (COVID-19) pandemic caused by the novel coronavirus (SARS-CoV-2) has been declared an international public health crisis. It is essential to develop diagnostic tests that can quickly identify infected individuals to limit the spread of the virus and assign treatment options. Herein, we report a proof-of-concept label-free electrochemical immunoassay for the rapid detection of SARS-CoV-2 virus via the spike surface protein. The assay consists of a graphene working electrode functionalized with anti-spike antibodies. The concept of the immunosensor is to detect the signal perturbation obtained from ferri/ferrocyanide measurements after binding of the antigen during 45 min of incubation with a sample. The absolute change in the [Fe(CN)6]3−/4− current upon increasing antigen concentrations on the immunosensor surface was used to determine the detection range of the spike protein. The sensor was able to detect a specific signal above 260 nM (20 µg/mL) of subunit 1 of recombinant spike protein. Additionally, it was able to detect SARS-CoV-2 at a concentration of 5.5 × 105 PFU/mL, which is within the physiologically relevant concentration range. The novel immunosensor has a significantly faster analysis time than the standard qPCR and is operated by a portable device which can enable on-site diagnosis of infection.

Perinatal Epidermal Growth Factor Signal Perturbation Results in the Series of Abnormal Auditory Oscillations and Responses Relevant to Schizophrenia

Abstract Auditory neurophysiological responses, such as steady-state responses, event-related potential P300/P3, and phase-amplitude coupling, are promising translational biomarkers for schizophrenia, but their molecular underpinning is poorly understood. Focusing on ErbB receptor signals that are implicated in both schizophrenia and auditory processing/cognition, we explored the causal biological links between ErbB signals and these auditory traits with an experimental intervention into rats. We peripherally challenged rat pups with one of the amniotic ErbB ligands, epidermal growth factor (EGF), and characterized its consequence on the series of these auditory electrocorticographic measures. Auditory brainstem responses (ABRs) and cortical ON responses were also assessed under anesthesia to estimate the influence of higher brain regions. An auditory steady-state paradigm revealed attenuation of spectral power and phase synchrony to 40-Hz stimuli in EGF-challenged rats. We observed a reduction in duration mismatch negativity-like potentials and a delay of P3a responses, all of which are relevant to the reported auditory pathophysiological traits of patients with schizophrenia. Moreover, the perinatal EGF challenges resulted in enhanced theta-alpha/beta and theta-gamma coupling within the auditory cortex and changes in ABRs. However, the EGF challenges retained the normal ranges of cortical ON responses, potentially ruling out their fundamental auditory deficits. Perinatal exposure of an ErbB ligand to rats strikingly reproduced the whole series of aberrant auditory responses and oscillations previously reported in patients with schizophrenia. Accordingly, these findings suggest that developmental deficits in ErbB/EGF signaling might be involved in the auditory pathophysiology associated with schizophrenia.

Electrochemical noise analysis to obtain the Rsn value via FFT using Excel

Electrochemical noise (EN) measurements are based on the fluctuations of the electrochemical potential and the current that occur during, for example, a corrosion process without an external signal perturbation. EN analysis (ENA) allows assessment of the type of corrosion and rapid determination of the corrosion rate. Microsoft Excel®, an inexpensive and readily available software package, is an excellent tool for performing repetitive calculations, with automation that saves time for the users. It is a useful tool for the analysis of EN data using fast Fourier transform (FFT), a process that is often made repeatedly and, if not automated, is quite laborious. This work presents a step-by-step procedure using Excel to perform these calculations, automating the process of obtaining the spectral electrochemical noise resistance, . This routine was used to analyze experimental potential and current noise data recorded for chalcopyrite. The results were comparable to those obtained for the same set of experimental data using Origin® software.

Voice Quality Evaluation in Patients With COVID-19: An Acoustic Analysis

ObjectivesWith the COVID-19 outbreak around the globe and its potential effect on infected patients’ voice, this study set out to evaluate and compare the acoustic parameters of voice between healthy and infected people in an objective manner.MethodsVoice samples of 64 COVID-19 patients and 70 healthy Persian speakers who produced a sustained vowel /a/ were evaluated. Between-group comparisons of the data were performed using the two-way ANOVA and Wilcoxon's rank-sum test.ResultsThe results revealed significant differences in CPP, HNR, H1H2, F0SD, jitter, shimmer, and MPT values between COVID-19 patients and the healthy participants. There were also significant differences between the male and female participants in all the acoustic parameters, except jitter, shimmer and MPT. No interaction was observed between gender and health status in any of the acoustic parameters.ConclusionThe statistical analysis of the data revealed significant differences between the experimental and control groups in this study. Changes in the acoustic parameters of voice are caused by the insufficient airflow, and increased aperiodicity, irregularity, signal perturbation and level of noise, which are the consequences of pulmonary and laryngological involvements in patients with COVID-19.

Small Scale Non-Invasive Imaging Using Magnetic Induction Tomography - Hardware Desig

This study is conducted to preliminary image the conductivity profile through the development of small scale non-invasive Magnetic Induction Tomography (MIT) system. It is proved that the Magnetic Induction Tomography interested in mapping the passive electrical properties of materials; conductivity (σ), permittivity (e) and permeability (µ) in both process and medical tomography. The system is realized by designing the functional ferrite-core coil sensors, electronic measurements circuits for excitation and receiving coil, data acquisition system for transferring the data to the PC and suitable image reconstruction algorithm for providing the conductivity distributions measurement. The important characteristic for excitation coil is the one that can maintain the stability the optimum sine wave frequency ranging from 400 kHz up to 10 MHz. The sine waves are fed to the excitation coil through the application of high current amplifier component respectively. In the experiments, the copper phantom represent as high conductivity material were placed into the region of interest. The initial 16 channel MIT consists of 8 excitation coil and 8 receiving coil stacked alternately. On the receiving circuit, the major problem is the weak secondary signal perturbation sensed by the receiving coil has been improved by placing the variable amplifier on each receiver. The enhancement of conductivity profile imaging has been made by using a common Linear Back Projection (LBP) algorithm. The measurement was done on single and dual arrangement of copper phantom aligns in random coordinate so that the sensitivity of the excitation and receiving coil sensor can be experimentally observed. The imaging’s results show that the hardware’s and algorithm used was capable to process the data captured at the receiver. The results obtained can be useful for further improvement and research towards magnetic induction tomography.

A homologous series of internal standards for near universal application in the discovery LC-MS/MS bioanalytical laboratory

When using Liquid Chromatography-Tandem Mass Spectrometry (LC–MS/MS) to quantify In Vivo samples, an internal standard (ISTD) is key in correcting for variability within the sample extraction process and injection volume. Just as important is the ability of the internal standard to identify any matrix effects, which can artificially suppress or enhance the signal of the compound of interest. To properly do this, the internal standard should co-elute with the compound. A common source of potential matrix effects with In Vivo studies is from the excipient(s) used to formulate the compound for dosing. In the world of high-throughput discovery bioanalysis, a lab can quantitate over a hundred compounds each week, many of which are evaluated once, and rarely is a stable-isotope labeled (SIL) internal standard available (the industry gold standard). Finding a suitable and easy-to-use alternative LC–MS/MS method is important to providing high quality data. To overcome this challenge, a homologous series of compounds was synthesized to improve the chromatographic range for co-eluting ISTD’s. This novel mix of internal standards was shown to have key characteristics making it ideal for use as a near universal internal standard mix including but not limited to: they ionize in both positive and negative modes, they are susceptible to signal perturbation from common formulation excipients, and they cover a wide range of retention times.

WIDEBAND SATCOM MODEL: EVALUATION OF NUMERICAL ACCURACY AND EFFICIENCY

Abstract. The spectral method is typically applied as a simple and efficient method to solve the parabolic wave equation in phase screen scintillation models. The critical factors that can greatly affect the spectral method accuracy is the uniformity and smoothness of the input function. This paper observes these effects on the accuracy of the finite difference and the spectral methods applied to a wideband SATCOM signal propagation model simulated in the ultra-high frequency (UHF) band. The finite difference method uses local pointwise approximations to calculate a derivative. The spectral method uses global trigonometric interpolants that achieve remarkable accuracy for continuously differentiable functions. The differences in accuracy are presented for a Gaussian lens and Kolmogorov phase screen. The results demonstrate loss of accuracy in each method when a phase screen is applied, despite the spectral method's computational efficiency over the finite difference method. These results provide meaningful insights when discretizing an interior domain and solving the parabolic wave equation to obtain amplitude and phase of a signal perturbation.

Induction of the nicotinamide riboside kinase NAD+ salvage pathway in a model of sarcoplasmic reticulum dysfunction

BackgroundHexose-6-Phosphate Dehydrogenase (H6PD) is a generator of NADPH in the Endoplasmic/Sarcoplasmic Reticulum (ER/SR). Interaction of H6PD with 11β-hydroxysteroid dehydrogenase type 1 provides NADPH to support oxo-reduction of inactive to active glucocorticoids, but the wider understanding of H6PD in ER/SR NAD(P)(H) homeostasis is incomplete. Lack of H6PD results in a deteriorating skeletal myopathy, altered glucose homeostasis, ER stress and activation of the unfolded protein response. Here we further assess muscle responses to H6PD deficiency to delineate pathways that may underpin myopathy and link SR redox status to muscle wide metabolic adaptation.MethodsWe analysed skeletal muscle from H6PD knockout (H6PDKO), H6PD and NRK2 double knockout (DKO) and wild-type (WT) mice. H6PDKO mice were supplemented with the NAD+ precursor nicotinamide riboside. Skeletal muscle samples were subjected to biochemical analysis including NAD(H) measurement, LC-MS based metabolomics, Western blotting, and high resolution mitochondrial respirometry. Genetic and supplement models were assessed for degree of myopathy compared to H6PDKO.ResultsH6PDKO skeletal muscle showed adaptations in the routes regulating nicotinamide and NAD+ biosynthesis, with significant activation of the Nicotinamide Riboside Kinase 2 (NRK2) pathway. Associated with changes in NAD+ biosynthesis, H6PDKO muscle had impaired mitochondrial respiratory capacity with altered mitochondrial acylcarnitine and acetyl-CoA metabolism. Boosting NAD+ levels through the NRK2 pathway using the precursor nicotinamide riboside elevated NAD+/NADH but had no effect to mitigate ER stress and dysfunctional mitochondrial respiratory capacity or acetyl-CoA metabolism. Similarly, H6PDKO/NRK2 double KO mice did not display an exaggerated timing or severity of myopathy or overt change in mitochondrial metabolism despite depression of NAD+ availability.ConclusionsThese findings suggest a complex metabolic response to changes in muscle SR NADP(H) redox status that result in impaired mitochondrial energy metabolism and activation of cellular NAD+ salvage pathways. It is possible that SR can sense and signal perturbation in NAD(P)(H) that cannot be rectified in the absence of H6PD. Whether NRK2 pathway activation is a direct response to changes in SR NAD(P)(H) availability or adaptation to deficits in metabolic energy availability remains to be resolved.

BEM: Mining Coregulation Patterns in Transcriptomics via Boolean Matrix Factorization.

The matrix factorization is an important way to analyze coregulation patterns in transcriptomic data, which can reveal the tumor signal perturbation status and subtype classification. However, current matrix factorization methods do not provide clear bicluster structure. Furthermore, these algorithms are based on the assumption of linear combination, which may not be sufficient to capture the coregulation patterns. We presented a new algorithm for Boolean matrix factorization (BMF) via expectation maximization (BEM). BEM is more aligned with the molecular mechanism of transcriptomic coregulation and can scale to matrix with over 100 million data points. Synthetic experiments showed that BEM outperformed other BMF methods in terms of reconstruction error. Real-world application demonstrated that BEM is applicable to all kinds of transcriptomic data, including bulk RNA-seq, single-cell RNA-seq and spatial transcriptomic datasets. Given appropriate binarization, BEM was able to extract coregulation patterns consistent with disease subtypes, cell types or spatial anatomy. Python source code of BEM is available on https://github.com/LifanLiang/EM_BMF. Supplementary data are available at Bioinformatics online.

Dynamometer Test Rig Drive Train Control with a High Dynamic Performance: Measurements and Experiences

This paper presents the control design and dynamic performance evaluation for a 10MW dynamometer test rig for wind turbine nacelles. The purpose is to control the applied torque by the drive train, required for an accurate emulation of rotor characteristics in the laboratory. This is implemented in a hardware-in-the-loop simulation framework for electrical certification test procedures, introducing high dynamic requirements. Therefore, a feedback-feedforward as well as a H-infinity controller is implemented to benefit from high dynamic and robustness capabilities, respectively. Furthermore, due to the lack of a suitable torque measurement in the meganewton-meter range, model-based algorithms are incorporated and the implemented time-varying Kalman filter provides the unmeasured variables. In addition, for performance analysis independent of any specimen, experiments using small signal perturbation as test functions are executed under load conditions. The results are analysed here elaborately and the obtained control bandwidth is distinguished under realistic conditions. Overall, the measurements demonstrate an effective control with a bandwidth of up to 30Hz.

Intelligent fault diagnosis of rotating machinery using a new ensemble deep auto-encoder method

In traditional intelligent fault diagnosis methods of rotating machinery, features are designed manually by experts, which makes these methods less automatic. Deep auto-encoder (DA) provides an effective way to learn discriminative features. However, individual DA is of low generalization and not robust. This work develops an ensemble DA(EDA) method for intelligent fault diagnosis. EDA is constructed by combining sparse DA, denoising DA and contractive DA. Thus, EDA can effectively handle redundant information, noisy corruption and signal perturbation. To ensure the feature learning performance of each DA model, a self-adaptive fine-tuning is designed to obtain stable convergence. To enhance the discriminative features, a dynamic weighted average method is designed to aggregate these learned features. EDA is verified on three public datasets, and achieves the testing accuracies of 100%, 99.69% and 99.92%. Comparisons with other methods, including both traditional methods and individual DA methods, demonstrate that EDA obtains higher diagnosis accuracy.

Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry.

The increase in drone misuse by civilian apart from military applications is alarming and need to be addressed. This drone is characterized as a low altitude, slow speed, and small radar cross-section (RCS) (LSS) target and is considered difficult to be detected and classified among other biological targets, such as insects and birds existing in the same surveillance volume. Although several attempts reported the successful drone detection on radio frequency-based (RF), thermal, acoustic, video imaging, and other non-technical methods, however, there are also many limitations. Thus, this paper investigated a micro-Doppler analysis from drone rotating blades for detection in a special Forward Scattering Radar (FSR) geometry. The paper leveraged the identified benefits of FSR mode over conventional radars, such as improved radar cross-section (RCS) value irrespective of radar absorbing material (RAM), direct signal perturbation, and high resolutions. To prove the concept, a received signal model for micro-Doppler analysis, a simulation work, and experimental validation are elaborated and explained in the paper. Two rotating blades aspect angle scenarios were considered, which are (i) when drone makes a turn, the blade cross-sectional area faces the receiver and (ii) when drone maneuvers normally, the cross-sectional blade faces up. The FSR system successfully detected a commercial drone and extracted the micro features of a rotating blade. It further verified the feasibility of using a parabolic dish antenna as a receiver in FSR geometry; this marked an appreciable achievement towards the FSR system performance, which in future could be implemented as either active or passive FSR system.

Reconsideration of Loop Gain and Its Measurement in DC–DC Converters

Two measurement schemes, namely, the modulation signal perturbation scheme and the pulse perturbation scheme, have been used for evaluating the loop gain of dc–dc converters. However, the two measured loop gains do not give consistent results due to the use of different forms of the injected small perturbation signal, and the difference in the two schemes cannot be distinguished by the usual averaged model. In this paper, the two loop gain measurement schemes are analyzed based on an extended-frequency-range small-signal model. Expressions of the loop gain are derived and their use in stability assessment and derivation of closed loop transfer functions is demonstrated. A sample-and-hold scheme is proposed as a simple alternative implementation of the pulse perturbation scheme. Finally, experimental prototypes of buck, boost, and buck–boost converters are tested for verification of the analytical results and the effectiveness of the sample-and-hold scheme.

A neural network model predicts community-level signaling states in a diverse microbial community.

Signal crosstalk within biological communication networks is common, and such crosstalk can have unexpected consequences for decision making in heterogeneous communities of cells. Here we examined crosstalk within a bacterial community composed of five strains of Bacillus subtilis, with each strain producing a variant of the quorum sensing peptide ComX. In isolation, each strain produced one variant of the ComX signal to induce expression of genes associated with bacterial competence. When strains were combined, a mixture of ComX variants was produced resulting in variable levels of gene expression. To examine gene regulation in mixed communities, we implemented a neural network model. Experimental quantification of asymmetric crosstalk between pairs of strains parametrized the model, enabling the accurate prediction of activity within the full five-strain network. Unlike the single strain system in which quorum sensing activated upon exceeding a threshold concentration of the signal, crosstalk within the five-strain community resulted in multiple community-level quorum sensing states, each with a unique combination of quorum sensing activation among the five strains. Quorum sensing activity of the strains within the community was influenced by the combination and ratio of strains as well as community dynamics. The community-level signaling state was altered through an external signal perturbation, and the output state depended on the timing of the perturbation. Given the ubiquity of signal crosstalk in diverse microbial communities, the application of such neural network models will increase accuracy of predicting activity within microbial consortia and enable new strategies for control and design of bacterial signaling networks.

Analysis of Semi-Blind Channel Estimation in Multiuser Massive MIMO Systems With Perturbations

In the massive multiple-input multiple-output (MIMO) systems, pilot contamination and signal perturbation are two important issues in the semi-blind channel estimation methods. To evaluate the effects of pilot contamination and signal perturbation, the covariance matrix of the received signal should be obtained. In specific, the eigenvectors associated with the K largest eigenvalues of the ideal covariance matrix, contain the subspace information of the desired signals, in which the interference and partial noise are eliminated because of asymptotic orthogonality of the fading matrix. Since it is quite difficult to acquire the ideal covariance matrix, the sample covariance matrix calculated by the finite data samples is adopted to approximate the ideal covariance matrix in practice. However, the gap between the ideal covariance matrix and the sample covariance matrix leads to signal perturbation. In this paper, the perturbation analysis of a semi-blind channel estimation in the massive MIMO systems is presented. Simulation results verify the validity of our perturbation analysis. Furthermore, it is demonstrated by simulations that signal perturbation affects system performance by reshaping the eigenvectors and eigenvalue distributions of the target cell and interfering cells.

Development of a Fast Numerical Simulator for Infrared Thermography Testing Signals of Delamination Defect in a Multilayered Plate

In this paper, a very fast numerical solver for simulating signal perturbation of infrared thermography testing (IRT) due to delamination defects was developed by using the database of unflawed IRT information. First, the IRT signal simulation method of the frequency-domain summation scheme proposed by authors is briefly introduced as the bases of the present fast-forward solver. Second, a database-type fast numerical scheme for rapid simulation of single-frequency IRT harmonic signals was proposed to enhance the efficiency of the IRT simulation without worsening the numerical precision. In addition, in order to efficiently implement the proposed fast solver for simulation of delamination defects in a multilayered plate, a two-dimensional (2-D) shifting symmetry strategy was applied to reduce the computational burden for the construction of the unflawed database. Based on the proposed scheme, a fast-forward numerical code was developed for simulation of IRT signal perturbation due to the delamination defect. The validity of the proposed scheme and the corresponding numerical code was verified by comparing its results with those of a full FEM code and experiments. It was demonstrated that the database-type fast scheme can significantly reduce the simulation time for the IRT signal perturbation due to a delamination defect but keep the same simulation accuracy with that of the full FEM code.

Coulomb scattering mechanism transition in 2D layered MoTe2: effect of high-κ passivation and Schottky barrier height

Clean interface and low contact resistance are crucial requirements in two-dimensional (2D) materials to preserve their intrinsic carrier mobility. However, atomically thin 2D materials are sensitive to undesired Coulomb scatterers such as surface/interface adsorbates, metal-to-semiconductor Schottky barrier (SB), and ionic charges in the gate oxides, which often limits the understanding of the charge scattering mechanism in 2D electronic systems. Here, we present the effects of hafnium dioxide (HfO2) high-κ passivation and SB height on the low-frequency (LF) noise characteristics of multilayer molybdenum ditelluride (MoTe2) transistors. The passivated HfO2 passivation layer significantly suppresses the surface reaction and enhances dielectric screening effect, resulting in an excess electron n-doping, zero hysteresis, and substantial improvement in carrier mobility. After the high-κ HfO2 passivation, the obtained LF noise data appropriately demonstrates the transition of the Coulomb scattering mechanism from the SB contact to the channel, revealing the significant SB noise contribution to the 1/f noise. The substantial excess LF noise in the subthreshold regime is mainly attributed to the excess metal-to-MoTe2 SB noise and is fully eliminated at the high drain bias regime. This study provides a clear insight into the origin of electronic signal perturbation in 2D electronic systems.

Modeling D-region ionospheric response of the Great American TSE of August 21, 2017 from VLF signal perturbation

Solar eclipse is a unique opportunity to study the lower ionospheric variabilities under a controlled perturbation when the solar ultraviolet and X-ray are temporally occulted by the lunar disk. Sub-ionospheric Very Low Frequency (VLF) radio signal displays the ionospheric response of solar eclipse by modulating its amplitude and phase. During the Total Solar Eclipse (TSE) on August 21, 2017 in North America, data was recorded by a number of receivers as presented in public archive. Out of these, two receiving stations YADA in McBaine and K5TD in Tulsa could procure a reasonable quality of noise free data where the signal amplitude was clearly modulated due to the eclipse. During the lunar occultation, a C3.0 solar flare occurred and the signal received from Tulsa manifested the effect of sudden ionization due to the flare. The VLF amplitude in Tulsa shows the effect which is generally understood by superimposing effects of both the solar eclipse and flare. However, the signal by YADA did not perturb by the solar flare, as the flaring region was totally behind the lunar disk for the entire period. We numerically reproduced the observed signal amplitude variation at both the receiving locations by using Wait’s two component D-region ionospheric model and the well-known Long Wavelength Propagation Capability (LWPC) code. The perturbed electron density for both the cases is computed which matches satisfactorily with the true ionospheric conditions.

Interleaved susceptibility-weighted and FLAIR MRI for imaging lesion-penetrating veins in multiple sclerosis.

PurposeTo simultaneously image brain lesions and veins in multiple sclerosis.MethodsAn interleaved sequence was developed to simultaneously acquire 3‐dimensional ‐weighted (or susceptibility‐weighted (SW)) and fluid‐attenuated inversion recovery (FLAIR) images on a 3T MRI system. The pulse sequence parameters were calculated to minimize signal perturbation from steady state while maintaining acceptable image contrast and scan time. Fifteen multiple sclerosis patients were enrolled in this prospective study and underwent a standard multiple sclerosis imaging protocol. In addition, SW and FLAIR images were acquired separately and also in an interleaved manner. The SW and FLAIR images were combined into one image to visualize lesions and penetrating veins. The contrast ratios between white matter lesions and penetrating veins were compared between the interleaved sequence and the individual noninterleaved acquisitions.ResultsInterleaved scanning of the FLAIR and the SW pulse sequences was achieved, producing aligned images, and with similar image contrast as in the noninterleaved images. A total of 1076 lesions were identified in all patients on the combined SW‐FLAIR image, of which 968 lesions (90%) had visible penetrating veins. Lesion‐to‐vein contrast ratio was 32.7 ± 17.9 (mean ± standard deviation) for the interleaved sequence compared with 28.1 ± 13.7 using the separate acquisitions (P < 0.001).ConclusionThe feasibility of interleaved acquisition of SW and FLAIR images was demonstrated. This sequence provides self‐registered images and facilitates the visualization of veins in brain lesions. Magn Reson Med 80:1132–1137, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Effects of a Co-Reactant Redox Behavior on the AC Impedance Response of the ORR

Electrochemical impedance spectroscopy (EIS) is a useful, in-situ, minimally invasive tool to diagnose reactions. A small sinusoidal AC signal perturbation in current or voltage is applied to the electrochemical charging or discharging (DC current) processes and the response signal is collected for impedance/phase gain analysis. Reaction kinetics and reactant transport have different characteristic time constants, and are evaluated by separating impedance spectra into frequency ranges representative of electrochemical processes that are simulated by electrical circuit elements such as capacitors and resistors (1). The co-adsorption of other electrochemically active species present in reactant streams affect the impedance responses of the main electrochemical reaction. The coverage resistance, the change in reaction rate induced by the modification in other species coverage, is either positive or negative and depends on the co-reactant reaction. In this contribution, impedance responses of a H2/air fuel cell with propene (as a model co-reactant) in the cathode are investigated to evaluate the effect of co-adsorbates redox behavior. The EIS is simulated by an equivalent circuit model (ECM) that takes into account the co-adsorbing intermediate. Cells were operated under 80 °C, 2 stoichiometry, and 50/100 % relative humidity and 48.3/48.3 kPag for the cathode/anode. The current density was varied to ensure that propene undergoes an oxidation or a reduction at the steady state (fixed cathode potential). AC impedance data from 0.1 Hz to 10 kHz (10 points per decade) were obtained using a Solartron SI1260 Impedance/Gain-Phase Analyzer and Stanford Research SR560 Low Noise Preamplifiers with ZPlot® (Scribner Associates) software. An AC current perturbation of 0.75 A, resulting in a voltage change of approximately 5-10 mV, was applied to the single cell for different current densities. The load bank cables on the positive and negative sides were equal in length and twisted to reduce system inductance and improve accuracy. Figure 1 shows EIS examples for the impedance responses of fuel cell reactions without or with a trace of propene in the cathode stream. EIS spectra include the impacts of propene oxidation at a low current density (i.e. 0.2 A cm- 2) and reduction at a high current density (1.6 A cm- 2) on the oxygen reduction reactions (ORR). The adsorption of propene decreases the number of active Pt surface sites and competes with the ORR, resulting in a significant increase in charge transfer (~10 Hz to ~1 kHz) and mass transfer (<10 Hz) resistances. At low current densities and correspondingly high cathode potentials, the adsorbed propene is oxidized and desorbed. Furthermore, propene adsorption and reactions show an increase in both capacitive loops and the appearance of a new capacitive loop at 1.2 A cm- 2. For a high current density and correspondingly low cathode potential, the adsorbed propene is reduced and desorbed. Also, propene adsorption and reactions display an additional inductive loop at low frequencies. It is emphasized that the co-reactant effect is inexistent or masked (0.2 A cm- 2), leads to a differentiated behavior with the appearance of a new capacitive loop (1.2 A cm- 2) or overlaps other processes but is discernible with the extension of the capacitive loop into an inductive loop (1.6 A cm- 2). The present work is applicable to the contamination of proton exchange membrane fuel cells by species contained in the oxidant and fuel streams that adsorb on the catalyst surface and are oxidized or reduced at operating cell voltages (2). The work is also relevant to other electrochemical systems. For a main reaction that is a reduction, a co-reactant reduction leads to an inductive response whereas for a co-reactant oxidation, a capacitive response occurs. The co-reactant impact is reversed for a main reaction that is an oxidation. Acknowledgments The authors are indebted to the United States Department of Energy (award DE-EE0000467) and the Office of Naval Research (award N00014-12-1-0496) for financial support of this project. The authors are also grateful to the Hawaiian Electric Company for their ongoing support of the operations of the Hawaii Sustainable Energy Research Facility. References Y. Zhai, K. Bethune, G. Bender, R. Rocheleau, J. Electrochem. Soc., 159 (2012) B524.J. St-Pierre, Y. Zhai, M. S. Angelo, J. Electrochem. Soc., 161 (2014) F280. Figure 1. The EIS of a PEMFC under different current densities with or without 50 ppm propene in cathode. Figure 1