Deploying and processing neural representations of signals

Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.

Medidas de audição de pais de indivíduos com deficiência auditiva de herança autossômica recessiva

TEMA: avaliação audiológica de pais de indivíduos com perda auditiva de herança autossômica recessiva. OBJETIVO: estudar o perfil audiológico de pais de indivíduos com perda auditiva, de herança autossômica recessiva, inferida pela história familial ou por testes moleculares que detectaram mutação no gene GJB2, responsável por codificar a Conexina 26. MÉTODO: 36 indivíduos entre 30 e 60 anos foram avaliados e divididos em dois grupos: grupo controle, sem queixas auditivas e sem história familiar de deficiência auditiva, e grupo de estudos composto por pais heterozigotos em relação a genes de surdez de herança autossômica recessiva inespecífica ou portadores heterozigotos de mutação no gene da Conexina 26. Todos foram submetidos à audiometria tonal liminar (0,25kHz a 8), audiometria de altas freqüências (9kHz a 20) e emissões otoacústicas produtos de distorção (EOAPD). RESULTADOS: houve diferenças significativas na amplitude das EOAPD nas freqüências 1001 e 1501Hz entre os grupos, sendo maior a amplitude no grupo controle. Não houve diferença significativa entre os grupos para os limiares tonais de 0,25 a 20KHz. CONCLUSÃO: as EOAPD foram mais eficazes, em comparação com a audiometria tonal liminar, para detectar diferenças auditivas entre os grupos. Mais pesquisas são necessárias para verificar a confiabilidade destes dados.

Fatores relacionados à autopercepção da audição entre idosos do município de São Paulo - Projeto SABE

Este artigo relata a influência de fatores sociodemográficos e de saúde na autopercepção da audição entre os idosos do projeto " Saúde, Bem-Estar e Envelhecimento" (Projeto SABE) no município de São Paulo. O estudo incluiu 2.143 indivíduos de 60 anos e mais. Um modelo de regressão logística ordinal, considerando o desenho da amostra, foi usado na análise multivariável. O aumento da idade; o sexo masculino; morar acompanhado; relatar tontura; memória regular/ ruim e saúde regular ou ruim aumentaram a chance de autopercepção ruim da audição. O conhecimento da autopercepção da audição e dos seus fatores relacionados é importante para avaliar a qualidade de vida dos idosos e a necessidade de reabilitação auditiva

Chaotic Patterns in Aeroelastic Signals

This work presents the analysis of nonlinear aeroelastic time series from wing vibrations due to airflow separation during wind tunnel experiments. Surrogate data method is used to justify the application of nonlinear time series analysis to the aeroelastic system, after rejecting the chance for nonstationarity. The singular value decomposition (SVD) approach is used to reconstruct the state space, reducing noise from the aeroelastic time series. Direct analysis of reconstructed trajectories in the state space and the determination of Poincare sections have been employed to investigate complex dynamics and chaotic patterns. With the reconstructed state spaces, qualitative analyses may be done, and the attractors evolutions with parametric variation are presented. Overall results reveal complex system dynamics associated with highly separated flow effects together with nonlinear coupling between aeroelastic modes. Bifurcations to the nonlinear aeroelastic system are observed for two investigations, that is, considering oscillations-induced aeroelastic evolutions with varying freestream speed, and aeroelastic evolutions at constant freestream speed and varying oscillations. Finally, Lyapunov exponent calculation is proceeded in order to infer on chaotic behavior. Poincare mappings also suggest bifurcations and chaos, reinforced by the attainment of maximum positive Lyapunov exponents. Copyright (C) 2009 F. D. Marques and R. M. G. Vasconcellos.

Time-frequency and time-scale analysis of Barkhausen noise signals

Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.

Sudan Black B treatment reduces autofluorescence and improves resolution of in situ hybridization specific fluorescent signals of brain sections

Interference by autofluorescence is one of the major concerns of immunofluorescence analysis of in situ hybridization-based diagnostic assays. We present a useful technique that reduces autofluorescent background without affecting the tissue integrity or direct immunofluorescence signals in brain sections. Using six different protocols, such as ammonia/ethanol, Sudan Black B (SBB) in 70% ethanol, photobleaching with UV light and different combinations of them in both formalin-fixed paraffin-embedded and frozen human brain tissue sections, we have found that tissue treatment of SBB in a concentration of 0.1% in 70% ethanol is the best approach to reduce/eliminate tissue autofluorescence and background, while preserving the specific fluorescence hybridization signals. This strategy is a feasible, non-time consuming method that provides a reasonable compromise between total reduction of the tissue autofluorescence and maintenance of specific fluorescent labels.

Signals for new spin-1 resonances in electroweak gauge boson pair production at the LHC

The mechanism of electroweak symmetry breaking ( EWSB) will be directly scrutinized soon at the CERN Large Hadron Collider. We analyze the LHC potential to look for new vector bosons associated with the EWSB sector, presenting a possible model independent approach to search for these new spin-1 resonances. We show that the analyses of the processes pp -> l(+)l(1-)E(T), l +/- jjE(T), l(1 +/-)l(+)l(-)E(T), l(+/-)jjE(T), and l(+)l(-) jj (with l, l' = e or mu and j = jet) have a large reach at the LHC and can lead to the discovery or exclusion of many EWSB scenarios such as Higgsless models.

Quirky collider signals of folded supersymmetry

We investigate the collider signals associated with scalar quirks (squirks) in folded supersymmetric models. As opposed to regular superpartners in supersymmetric models these particles are uncolored, but are instead charged under a new confining group, leading to radically different collider signals. Because of the new strong dynamics, squirks that are pair produced do not hadronize separately, but rather form a highly excited bound state. The excited squirkonium loses energy to radiation before annihilating back into standard model particles. We calculate the branching fractions into various channels for this process, which is prompt on collider time scales. The most promising annihilation channel for discovery is W+photon which dominates for squirkonium near its ground state. We demonstrate the feasibility of the LHC search, showing that the mass peak is visible above the SM continuum background and estimate the discovery reach.

CERN LHC signals for a neutrino mass model with bilinear R-parity violating minimal anomaly mediated supersymmetry

We investigate a neutrino mass model in which the neutrino data is accounted for by bilinear R-parity violating supersymmetry with anomaly mediated supersymmetry breaking. We focus on the CERN Large Hadron Collider (LHC) phenomenology, studying the reach of generic supersymmetry search channels with leptons, missing energy and jets. A special feature of this model is the existence of long-lived neutralinos and charginos which decay inside the detector leading to detached vertices. We demonstrate that the largest reach is obtained in the displaced vertices channel and that practically all of the reasonable parameter space will be covered with an integrated luminosity of 10 fb(-1). We also compare the displaced vertex reaches of the LHC and Tevatron.

The influence of peripheral afferent signals on the rating of perceived exertion and time to exhaustion during exercise at different intensities

This study determined which peripheral variables would better predict the rating of perceived exertion (RPE) and time to exhaustion (TE) during exercise at different intensities. Ten men performed exercises at first lactate threshold (LT1), second lactate threshold (LT2), 50% of the distance from LT1 to LT2 (TT(50%)), and 25% of the distance from LT2 to maximal power output (TW(25%)). Lactate, catecholamines, potassium, pH, glucose, (V) over dotO(2), VE, HR, respiratory rate (RR) and RPE were measured and plotted against the exercise duration for the slope calculation. Glucose, dopamine, and noradrenaline predicted RPE in TT(50%) (88%), LT2 (64%), and TW(25%) (77%), but no variable predicted RPE in LT1. RPE (55%), RPE+HR (86%), and RPE+RR (92% and 55%) predicted TE in LT1, TT(50%), LT2, and TW(25%), respectively. At intensities from TT(50%) to TW(25%), variables associated with brain activity seem to explain most of the RPE slope, and RPE (+HR and+RR) seems to predict the TE.

Predictability Analysis of Voice Signals Analyzing Healthy and Pathologic Samples

Research Foundation of the State of Sao Paulo (FAPESP)

Normal Versus Pathological Voice Signals Using Wavelet Analysis and Least Squares Support-Vector Machines

State of Sao Paulo Research Foundation (FAPESP)

Falling sheet envelope method for non-destructive testing time-dependent signals

In this work, an algorithm to compute the envelope of non-destructive testing (NDT) signals is proposed. This method allows increasing the speed and reducing the memory in extensive data processing. Also, this procedure presents advantage of preserving the data information for physical modeling applications of time-dependent measurements. The algorithm is conceived to be applied for analyze data from non-destructive testing. The comparison between different envelope methods and the proposed method, applied to Magnetic Bark Signal (MBN), is studied. (C) 2010 Elsevier Ltd. All rights reserved.

Computational Method to Determine Reflected Ultrasonic Signals From Arbitrary-Geometry Targets

A computational method based on the impulse response and on the discrete representation computational concept is proposed for the determination of the echo responses from arbitrary-geometry targets. It is supposed that each point of the transducer aperture can be considered as a source radiating hemispherical waves to the reflector. The local interaction with each of the hemispherical waves at the reflector surface can be modeled as a plane wave impinging on a planar surface, using the respective reflection coefficient. The method is valid for all field regions and can be performed for any excitation waveform radiated from an arbitrary acoustic aperture. The effects of target geometry, position, and material on both the amplitude and the shape of the echo response are studied. The model is compared with experimental results obtained using broadband transducers together with plane and cylindrical concave rectangular reflectors (aluminum, brass, and acrylic), as well as a circular cavity placed on a plane surface, in a water medium. The method can predict the measured echoes accurately. This paper shows an improved approach of the method, considering the reflection coefficient for all incident hemispherical waves arriving at each point of the target surface.

Signals in Communication Engineering History

This paper is a study of various electric signals, which have been employed throughout the history of communication engineering in its two main landmarks: the telegraph and the telephone. The signals are presented in their time and frequency domain representations. The historical order has been followed in the presentation: wired systems, spark gap wireless, continuous wave (CW) and amplitude modulation (AM), detection by rectification, and frequency modulation (FM). The analysis of these signals is meant to lead into a better understanding of the evolution of communication technology. The material presented in this work could be used to illustrate ""Signals and Systems"" and ""Communication Systems"" courses by taking advantage of its technical as well as historical contents.