Full Signal Research Articles

3D-MSNet: a point cloud-based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data.

Liquid chromatography coupled with high-resolution mass spectrometry is widely used in composition profiling in untargeted metabolomics research. While retaining complete sample information, mass spectrometry (MS) data naturally have the characteristics of high dimensionality, high complexity, and huge data volume. In mainstream quantification methods, none of the existing methods can perform direct 3D analysis on lossless profile MS signals. All software simplify calculations by dimensionality reduction or lossy grid transformation, ignoring the full 3D signal distribution of MS data and resulting in inaccurate feature detection and quantification. On the basis that the neural network is effective for high-dimensional data analysis and can discover implicit features from large amounts of complex data, in this work, we propose 3D-MSNet, a novel deep learning-based model for untargeted feature extraction. 3D-MSNet performs direct feature detection on 3D MS point clouds as an instance segmentation task. After training on a self-annotated 3D feature dataset, we compared our model with nine popular software (MS-DIAL, MZmine 2, XCMS Online, MarkerView, Compound Discoverer, MaxQuant, Dinosaur, DeepIso, PointIso) on two metabolomics and one proteomics public benchmark datasets. Our 3D-MSNet model outperformed other software with significant improvement in feature detection and quantification accuracy on all evaluation datasets. Furthermore, 3D-MSNet has high feature extraction robustness and can be widely applied to profile MS data acquired with various high-resolution mass spectrometers with various resolutions. 3D-MSNet is an open-source model and is freely available at https://github.com/CSi-Studio/3D-MSNet under a permissive license. Benchmark datasets, training dataset, evaluation methods, and results are available at https://doi.org/10.5281/zenodo.6582912.

Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm.

Frequent cortical arousal is associated with cardiovascular dysfunction among people with sleep-disordered breathing. Changes in heart rate variability (HRV) can represent pathological conditions associated with autonomic nervous system dysfunction. Previous studies showed changes in cardiac activity due to cortical arousals. However, few studies have examined the instantaneous association between cortical arousal and HRV in an ethnically diverse population. In this study, we included 1,069 subjects' full night ECG signals from unattended polysomnography in the Multi-Ethnic Study of Atherosclerosis dataset. An automated deep learning tool was employed to annotate arousal events from ECG signals. The etiology (e.g., respiratory, or spontaneous) of each arousal event was classified through a temporal analysis. Time domain HRVs and mean heart rate were calculated on pre-, intra-, and post-arousal segments of a 25-s period for each arousal event. We observed that heart rate and HRVs increased during the arousal onsets in the intra-arousal segments, regardless of arousal etiology. Furthermore, HRVs response to cortical arousal occurrence differed according to gender and the sleep stages in which arousal occurred. The more intense HRVs variation due to arousal in females can contribute to a potentially stronger association between arousal burden and long-term mortality. The excessive abrupt sympathetic tone elevation in REM caused by arousal may provide insights on the association between sleep and sudden cardiac death.

Ultrasonic imaging of damage in plates in spectral ripple frequency domain

The ultrasonic C-scan method is a well-known non-destructive inspection method which typically analyzes ultrasound echoes in time domain. Although demonstrated for a variety of defects and materials, it has certain challenges in correctly assessing complex and distributed defects in multi-layer heterogeneous materials, e.g. barely visible impact damage in composite laminates.This paper proposes a C-scan imaging technique in the spectral ripple frequency domain by exploiting interference phenomena between multiple ultrasonic echoes in the response signal. The spectral ripple frequency domain imaging method processes the full A-scan signal without having to define an evaluation time gate. As such, it is highly suited for inspection of curved or tilted parts, or parts having different thickness sections. The method is demonstrated on several 5.5 mm thick carbon fiber reinforced polymer laminates with barely visible impact damage, revealing its capability to resolve neighboring delaminations and small defect fragments over the entire depth of the sample. The spectral ripple frequency domain imaging method shows good performance on datasets with high noise levels and/or low sampling rates, and is computationally very efficient, allowing real-time defect imaging.

UAV-Based Bistatic SAR-Imaging Using a Stationary Repeater

Synthetic aperture radar (SAR) is an established technique for high-resolution radar imaging relying on the ego-motion of the radar. The long coherent integration time of the radar in conjunction with a linear or circular trajectory enables the illumination of targets under different observation angles leading to robustness against short-time interference signals. The use of a bistatic setup to simultaneously acquire multiple observation angles further increases the aforementioned benefits. In this work, a bistatic SAR system using an active repeater is proposed, in the following called Bistatic Repeater-SAR (BR-SAR). In BR-SAR the repeater acts as a second observer providing a bistatic path with low system cost and hardware effort. This article discusses the BR-SAR approach with all signal processing and hardware considerations necessary to build the bistatic radar system. This includes a description of the full system and signal chain with a focus on the signal separation and evaluation of both monostatic and bistatic signals and the subsequent SAR processing. The approach is verified via simulations and measurements, in which conventional SAR is compared to the proposed BR-SAR system. Hardware effects leading to a deteriorated system performance of the bistatic system are analyzed and countermeasures are discussed and implemented. Finally, the benefits of the bistatic system are demonstrated based on a realistic measurement scenario.

A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates

Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis.

Asynchronous FIFO Design Based on Verilog

With the rapid development of integrated circuits, asynchronous First Input First Output (FIFO) is often used to solve the problem of data transmission across the clock domain. This paper mainly studies the key problem of asynchronous FIFO design - the generation of empty - full signal. To solve this problem, it is necessary to realize the synchronization of signal across the clock domain and convert binary code into gray code to reduce the probability of metastable state. The null and full signals generated by the asynchronous FIFO designed in this paper are false null and false full, but this does not affect the function of the asynchronous FIFO, and will only lose part of the performance. Through Modelsim simulation verification, the designed asynchronous FIFO can realize first-in, first-out of data and correctly generate empty and full signal, which meets the design requirements. The research of this paper is helpful for further application of asynchronous FIFO in data transmission across clock domains.

Acoustic emission characteristics and fracture mechanism of cemented tailings backfill under uniaxial compression: experimental and numerical study

Cemented tailings backfill (CTB) is the most cost-effective and environmentally friendly method to recycle tailings for filling mining. It is of great significance to study the fracture mechanism of CTB for safe mining. In this study, three cylindrical CTB samples with a cement-tailings ratio of 1:4 and a mass fraction of 72% were prepared. An acoustic emission (AE) test under uniaxial compression (UC) with WAW-300 microcomputer electro-hydraulic servo universal testing machine and DS2 series full information AE signal analyzer was carried out to discuss the AE characteristics of CTB, such as hits, energy, peak frequency, and AF-RA. Combined with particle flow and moment tensor theory, a meso AE model of CTB was constructed to reveal the fracture mechanism of CTB. The results show that (1) the AE law of CTB under UC has periodic characteristics, which can be divided into the rising stage, stable stage, booming stage, and active stage. (2) The peak frequency of the AE signal is mainly focused on three frequency bands. The ultra-high frequency AE signal may be the precursor information for CTB failure. (3) The low frequency band AE signals represent shear crack, while the medium and high frequency band AE signals represent tension crack. The shear crack initially decreases and then increases, and the tension crack is the opposite. (4) The fracture types of the AE source are divided into tension crack, mixed crack, and shear crack. The tension crack is dominant, while a larger magnitude AE source is frequently shear crack. The results can provide a basis for the stability monitoring and fracture prediction of CTB.

Illumination of a progressive allosteric mechanism mediating the glycine receptor activation

Pentameric ligand-gated ion channel mediate signal transduction at chemical synapses by transiting between resting and open states upon neurotransmitter binding. Here, we investigate the gating mechanism of the glycine receptor fluorescently labeled at the extracellular-transmembrane interface by voltage-clamp fluorometry (VCF). Fluorescence reports a glycine-elicited conformational change that precedes pore opening. Low concentrations of glycine, partial agonists or specific mixtures of glycine and strychnine trigger the full fluorescence signal while weakly activating the channel. Molecular dynamic simulations of a partial agonist bound-closed Cryo-EM structure show a highly dynamic nature: a marked structural flexibility at both the extracellular-transmembrane interface and the orthosteric site, generating docking properties that recapitulate VCF data. This work illuminates a progressive propagating transition towards channel opening, highlighting structural plasticity within the mechanism of action of allosteric effectors.

In situ characterization of nanoparticle protein corona using real-time 3D single-particle tracking.

Nanoparticles (NPs) adsorb proteins when they are exposed to biological fluids, forming a dynamic protein corona that consists of tightly bound “hard” corona and rapidly exchanged “soft” corona. This protein layer alters the NPs’ surface identity and affects their fate in vivo. However, current methods fail to directly investigate single NP-protein interactions in the solution phase due to the fast NP diffusion and protein exchange dynamics. To address this gap, we introduce a real-time lock-on protein corona spectroscopy based on previously developed 3D single molecule active real-time tracking (3D-SMART), primarily using polystyrene NP (PSNP) and bovine serum albumin (BSA) as a model system. 3D-SMART uses real-time photon arrival information to estimate the PSNP's position within a rapid 3D laser scanning pattern. The position estimate is then used to move a piezoelectric stage to counteract the PSNP's diffusion, keeping the NP-protein complex locked in the center of detection volume for spectral interrogation. Consequently, the 3D trajectory of the NP-protein complex and the fluorescence traces of the associated proteins can be synchronously measured for size measurement and hard corona quantification. Moreover, we applied a lock-in filtering-based algorithm to the protein intensity trace to extract the full protein corona signal in situ at signal-to-background ratios of 1%. It was discovered that the full corona consists of a sub-monolayer of BSA on PSNP, which contains twice the quantity of proteins compared to hard corona measurements, indicating that half of the full protein corona can be classified as soft corona. To expand this method to smaller NP-protein systems, we have further implemented a Galvo mirror as control actuator with response time five times faster than the piezoelectric stage, opening the possibility of studying a wider range of transient NP-protein interaction in vivo.

The TRISTAN 166-pixel detector: Preliminary results with a planar setup

We present the first experimental results achieved with a monolithic array of 166 Silicon Drift Detectors (SDD). This detector was developed for the TRISTAN experiment, targeting the search for a sterile neutrino in the keV mass range by means of accurate Beta spectroscopy of the Tritium decay. We briefly report on the design and characterization with X-rays of the full signal chain: from the SDD array, operated in a planar configuration with all the components of the final system, to the acquisition platform simultaneously acquiring all 166 channels. The average energy resolution is better than 250eV FWHM at 5.9keV at a temperature of 0 °C, a 6 μs shaping time, and an average count rate of 1kcps per channel, 100 times smaller than the final experiment one.

N-glycosylation on Asn-57 is required for the correct HAI-2 protein folding and protease inhibitory activity.

Hepatocyte growth factor activator inhibitor (HAI)-2 is an integral membrane Kunitz-type serine protease inhibitor that regulates the proteolysis of matriptase and prostasin in a cell-type selective manner. The cell-type selective nature of HAI-2 function depends largely on whether the inhibitor and potential target enzymes are targeted to locations in close proximity. The N-glycan moiety of HAI-2 can function as a subcellular targeting signal. HAI-2 is synthesized with 1 of 2 different N-glycan modifications: one of oligomannose-type, which largely remains in the endoplasmic reticulum/GA, and another of complex-type, which is targeted toward the apical surface in vesicle-like structures, and could function as an inhibitor of matriptase and prostasin. HAI-2 contains 2 putative N-glycosylation sites, Asn-57 and Asn-94, point mutations of which were generated and characterized in this study. The protein expression profile of the HAI-2 mutants indicates that Asn-57, and not Asn-94, is responsible for the N-glycosylation of both HAI-2 species, suggesting that the form with oligomannose-type N-glycan is the precursor of the form with complex-type N-glycan. Unexpectedly, the vast majority of non-glycosylated HAI-2 is synthesized into multiple disulfide-linked oligomers, which lack protease inhibitory function, likely due to distorted conformations caused by the disarrayed disulfide linkages. Although forced expression of HAI-2 in HAI-2 knockout cells artificially enhances HAI-2 oligomerization, disulfide-linked HAI-2 oligomers can also be observed in unmodified cells. These results suggest that N-glycosylation on Asn-57 is required for folding into a functional HAI-2 with full protease suppressive activity and correct subcellular targeting signal.

First characterization results of ARCADIA FD-MAPS after X-ray irradiation

The ARCADIA collaboration is developing fully-depleted (FD) Monolithic Active Pixel Sensors (MAPS) in a 110 nm CMOS process in collaboration with LFoundry. The sensor design incorporates an n+ collection node within a n-type epi-layer on top of a high-resistivity n-type substrate and p+ backside. Thus, the pn-junction sits on the backside and through an applied backside bias, the full substrate gets depleted. The targeted applications of this technology range from future high energy physics experiments to space applications, and medical and industrial scanners. Together, these applications set the minimum requirements on the detector: data collection at hit rates of (10–100) MHz/cm2, full signal processing within (1–10) μs, maximum power consumption (5–20) mW/cm2 and radiation tolerances of up to 3.4 Mrad or 6.2 × 1012 1 MeV neutron equivalent fluence. In order to proof the performance of the technology, a demonstrator chip of 512 × 512 pixels with 25 μm pitch was designed and fabricated in a first engineering run in 2021, together with additional test structures of pixel and strip arrays with different pitches and sensor geometries. The production run has produced functional passive and active pixel matrices. Earlier studies have shown that positive oxide charges and traps at the Si-SiO2 interface, introduced by ionising radiation, affect the depletion region around the collection electrode, increasing the pixel capacitance. By varying the gap size between collection node and pwells, the geometry can be optimised to keep the capacitance low also after irradiation. To study the performance after irradiation, of the optimised diode designs, the passive pixel matrices were irradiated with doses up to 10 Mrad (SiO2) using a X-ray tube with a Tungsten anode. The measurements are complemented by TCAD simulations. The maximum capacitance increase after irradiation was found to reach 6 and 12 fF/pixel for pixel pitches of 25 and 50 μm, respectively. The relative capacitance increase after irradiation has hereby been found to reach up to 250% after a dose of 10 Mrad.

Biased tracers as a probe of beyond-ΛCDM cosmologies

Cosmological models beyond ΛCDM, such as those featuring massive neutrinos or modifications of gravity, often display a characteristic change (scale-dependent suppression or enhancement) in the matter power spectrum when compared to a six-parameter ΛCDM baseline. It is therefore a widely held view that constraints on those models can be obtained by searching for such features in the clustering statistics of large-scale structure. However, when using biased tracers of matter in the analysis, the situation is complicated by the fact that the bias also depends on cosmology. Here we investigate how the selection of tracers affects the observed signatures for two examples of beyond-ΛCDM cosmologies: massive neutrinos and clustering dark energy (k-essence). We study the signatures in the monopole, quadrupole, and hexadecapole of the redshift-space power spectra for halo catalogues from large N-body simulations and argue that a fixed selection criterion based on local attributes, such as tracer mass, leads to a near loss of signal in most cases. Instead, the full signal is recovered only if the selection of tracers is done at fixed bias. This emphasises the need to model or measure the bias parameters accurately in order to get meaningful constraints on the cosmological model.

A bubble size distribution model for the Epoch of Reionization

Aims. The bubble size distribution is a summary statistics that can be computed from the observed 21-cm signal from the Epoch of Reionization. As it depends only on the ionization field and is not limited to Gaussian information, it is an interesting probe that is complementary to the power spectrum of the full 21-cm signal. Devising a flexible and reliable theoretical model for the bubble size distribution paves the way for its use in astrophysical parameter inference. Methods. The proposed model was built from the excursion set theory and a functional relation between the bubble volume and the collapsed mass in the bubble. Unlike previous models, it can accommodate any functional relation or distribution. The use of parameterized relations allows us to test the predictive power of the model by performing a minimization best-fit to the bubble size distribution obtained from a high-resolution, fully coupled radiative hydrodynamics simulation known as HIRRAH-21. Results. Our model is able to provide a better fit to the numerical bubble size distribution at an ionization fraction of xH II ∼ 1% and 3%, as compared to other existing models. Moreover, we compare the relation between the bubble volume and the collapsed mass corresponding to the best-fit parameters, which is not an observable, to the numerical simulation data. A good match is obtained, confirming the possibility of inferring this relation from an observed bubble size distribution using our model. Finally, we present a simple algorithm that empirically implements the process of percolation. We show that it extends the usability of our bubble size distribution model up to xH II ∼ 30%.

Phase information in cosmological collider signals

Massive particles produced during the cosmic inflation can imprint in the primordial non-Gaussianities as characteristic oscillating functions of various momentum ratios, known as cosmological collider signals. We initiate a study of the phase of the oscillating signals which can be unambiguously defined and measured. The phase can provide useful new information about the spin and the couplings of the intermediate heavy particles that cannot be obtained from the signal frequency and angular dependences alone. We also present new analytical results for full nonlocal signals from two typical 1-loop processes, enabling precise determination of the signal phase away from the squeezed limit.

PROTOTYPE OF A DESKTOP-BASED COMMUNICATION APPLICATION USING A DELAY TOLERANT NETWORK ARCHITECTURE

Currently, the process of exchanging information or data is carried out quickly, precisely, effectively and efficiently using the internet network. However, in reality, there are still some problems in areas that are difficult to get a signal, such as connection loss or unstable connection. One of the proposed solutions to anticipate this problem is the implementation of a network using the Delay Tolerant Network architecture. This architecture was chosen because of its basic capability, namely being able to send files even in a high delay state or used in areas with intermittent properties. The implementation carried out is making a chat application prototype that is able to function in intermittent areas and can be used for communication between sender and receiver in difficult signal conditions. The hardware used is a raspberry pi and supporting software using ION-DTN and traffic management designed using the python programming language. The application is tested by applying the concept of functionality testing, namely with full signal condition scenarios and limited signal conditions as a representation of the intermittent area. The test results show that the application is able to function based on the initial design with a delay with test variations of 1-10 minutes of signal dropout time. Further development can be done by adding a chat feature so that it is able to send more varied data.

Analysis of Hydrogen Feeding to the Anode of a PEMFC By a Transport Impedance Technique

Hydrogen feeding to the catalyst layer of the anode of a proton-exchange membrane fuel cell (PEMFC) must be fast enough to allow for high power response and avoid starvation events. However, there are limitations to the flow rate posed by the anode architecture (manifold, inlet port, flow field), and the gas diffusion layer (GDL). Within the GDL, hydrogen transport conditions may change in-operando as a result of water generation and saturation of pores. Delays in hydrogen feeding will give rise to a decrease in power response, and transitory sub-stoichiometric conditions, that may damage the electrode and decrease fuel cell durability. Therefore, it is of high interest to probe hydrogen feeding conditions when designing new anode architectures, and during operation of the fuel cell.Mass transport conditions in the fuel cell and electrochemical systems can be probed by techniques based on the impedance concept [1,2,3]. Among them, one recently applied in our group is the current modulated H2 flow-rate spectroscopy (CH2S), which provides the transfer function H [4,5]:H(j w) = nF QH2 / I (Eq. 1)Where QH2 is the modulated hydrogen inlet flow, I the modulated cell current, n(=2) the electron exchanges per H2 molecule, and F(=96485 C mol-1) the Faraday constant. A typical response in a PEMFC with dead-end anode is shown in Fig. 1.The H function normally presents two or more semicircles in Nyquist plots, extending in the real axis from H'=0 to H'=1 (stoichiometric modulation). The high frequency semicircle is normally ascribed to the set-up time response limitation, mostly the flow meter. At higher frequencies, the H function shows characteristics of the time response of hydrogen flow up to the anodic catalyst layer.In this communication, the CH2S technique is applied in conventional single cells and in passive portable feeding PEMFCs. Some properties of H2 transport path towards the anodic catalyst layer are analyzed, like conduits length, inlet port type, anode flow field, liquid water contents, hydrogen stoichiometry, and anode hydrophobicity.Acknowledgement: The work is partially financed by the ELHYPORT project (PID2019−110896RB-I00), Spanish Ministry of Science and Innovation.[1] C. Deslouis, I. Epelboin, C. Gabrielli, P.S.-R. Fanchine, B. Tribollet, Relationship between the electrochemical impedance and the electrohydrodynamical impedances measured using a rotating disc electrode, J. Electroanal. Chem. Interfacial Electrochem. 107 (1980) 193–195.[2] A. Sorrentino, T. Vidakovic-Koch, R. Hanke-Rauschenbach, K. Sundmacher, Concentration-alternating frequency response: A new method for studying polymer electrolyte membrane fuel cell dynamics, Electrochim. Acta. 243 (2017) 53–64.[3] D. Grübl, J. Janek, W.G. Bessler, Electrochemical Pressure Impedance Spectroscopy (EPIS) as Diagnostic Method for Electrochemical Cells with Gaseous Reactants: A Model-Based Analysis, J. Electrochem. Soc. 163 (2016) A599–A610.[4] M.A. Folgado, H. Moreno, A. Molinero, J.C. Oller, J.M. Barcala, A.M. Chaparro Hydrogen Transport Impedance for the Study of Anodes in PEMFCs, European Fuel Cell Forum 2021, A0704 (Extended ). Lucerne (Switzerland).[5] A. Molinero, J.C. Oller, J.M. Barcala, H. Moreno, M.A. Folgado, A.M. Chaparro, Experimental Set-Up for Transport Studies of Anodes in PEMFCs. European Fuel Cell Forum 2021, B0207 (Extended ). Lucerne (Switzerland).Fig. 1. Nyquist plot of the H function according to Eq. 1, for a PEMFC cell with commercial electrodes (Pt/C 0.3mg·cm-2) and Nafion 212NR membrane, working with hydrogen feeding in dead-end mode, and air feeding in cathode. a) Full signal; b) Low frequency detail. Numbers are modulation frequencies. Figure 1

(Digital Presentation) Liquid-Metal-Printed Ultra-Thin ITO-Thin-Film Transistor

Indium oxide is one of the promising materials for the n-channel layer for high-mobility oxide-TFT because of its high electron mobility characteristics due to the nature of spatially spread-In 5s orbital. However, excess carrier electrons in In-based channels cancel field-effect gate modulation and causes the formation of a short depletion layer. Moreover, it is challenging to reduce the electron density without the degradation of electron transport. Therefore, developing fully-depletion operated TFT using an ultra-thin channel is a straightforward strategy to demonstrate the high potential of In-based materials for TFT applications.In this work, we developed an ultra-thin tin-doped Indium oxide (ITO) channel (~ 1.9 nm-thick.) and demonstrated a fully-depleted ITO-TFT exhibiting high mobility of 27 cm2/Vs. The ITO channel was grown by a cost-effective vacuum-free liquid-metal-printing route at the maximum process temperature of ~ 200 oC in an ambient atmosphere. Post-thermal annealing in air made significant improvement of device characteristics originating from the reduction of shallow acceptor-like in-gap defects in the ITO channels, and high-performance n-channel ITO-TFT with a large on/off-current ratio of 109 and a sharp threshold slope was achieved. By controlling air-annealing temperature, we also successfully fabricated both enhancement and depletion-mode devices and developed a full signal swinged-oxide-NMOS inverter composed of a depletion-load structure.

Dynamic Load Angle Estimation Through an Angular Domain GDFT Filter for Optimal Energetic BLDC Control

Nowadays, Brushless dc (BLDC) motors are increasingly used to drive speed-controlled applications (e.g., drones, air compressors, etc.) thanks to their high power density, good torque inertia ratio, and their simple square wave commutation principle. However, with growing attention toward energy usage, a more efficient sinusoidal current wave is favored over the classical square wave profile. Nevertheless, changing the waveform to absent the silence phase implicates that simple control principles (e.g., hall-sensors or back electromotive force tracing) are no longer functional, and a more advanced sensorless solution is required. Earlier, an innovative sensorless load angle based controller was suggested with the potential to overcome all restrictions concerning state-of-the-art sensorless control. One of the proposed estimator’s fundamental building blocks is a sliding discrete Fourier filter, requiring both a signal with a fixed base frequency and a full signal period of samples before updating completely. Both requirements severely limit the application field. This article presents an enhanced load angle estimator that can estimate the load angle 66% faster on average and without quality deterioration, regardless of the rotor speed. Both speed and accuracy of the estimated load angle are validated based on BLDC measurements, confirming the potential and revealing possible further estimation lag decreases if a limited estimation quality regression is allowed.

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

This study is a review of recent applications to seismic imaging of optimal transport based numerical tools. Modern seismic imaging methods used in the industry rely on the interpretation of the full signal. The characterization of the subsurface mechanical properties is formulated as a PDE-constrained optimization problem, solved through local optimization strategies. The choice of the misfit function used to measure the distance between actual seismic recordings and those synthetized by the solution of wave propagation PDE is crucial. Indeed, the conventional least-squares distance function leads to a non-convex optimization problem whose solution through local optimization then strongly depends on the initial guess. Using an optimal transport distance is an interesting alternative from its convexity properties with respect to translation and dilation. Specific strategies need however to be implemented as seismic data are oscillatory, while the optimal transport theory has been developed for the comparison of positive measures. In this study we review two optimal transport based misfit functions, from their mathematical formulation to their application to field data through their numerical implementation. Advantages and drawbacks of both strategies are discussed. Numerical experiments show that they represent two interesting and complementary alternative to the classical least-squares misfit function, mitigating the dependency to the choice of the initial guess.