A Causal Ordering Prior for Unsupervised Representation Learning

Unsupervised representation learning with variational inference relies heavily on independence assumptions over latent variables. Causal representation learning (CRL), however, argues that factors of variation in a dataset are, in fact, causally related. Allowing latent variables to be correlated, as a consequence of causal relationships, is more realistic and generalisable. So far, provably identifiable methods rely on: auxiliary information, weak labels, and interventional or even counterfactual data. Inspired by causal discovery with functional causal models, we propose a fully unsupervised representation learning method that considers a data generation process with a latent additive noise model (ANM). We encourage the latent space to follow a causal ordering via loss function based on the Hessian of the latent distribution

Flexible pressure sensing system for tongue-based control of prosthetic hands

A novel system to control robotic/prosthetic limbs with a tongue-based scheme is presented in this paper. In the proposed system six off-the-self pressure sensors soldered on a flexible PCB and placed in the inner part of cuspides, central and lateral incisors of the lower arch, are interfaced with electronics and wireless transmitters to form the complete system. The control system sends the appropriate commands to the prosthesis when users apply force to one of the pressure sensors with their tongue. Each pressure sensor represents one gesture for the prosthesis. The touch with the tongue results in an increase of the read pressure by the sensor. If the pressure exceeds a predetermined threshold the prosthesis is activated via wireless transmission of data. To package the system in the mouth a protective encapsulation was made using PDMS. Different thicknesses and concentrations of PDMS were tested to determine the optimum trade-off between the minimum exerted force by the user that activates the prosthesis and the threshold below which the prosthesis is not active

ZnO nanowires-based flexible UV photodetector system for wearable dosimetry

This paper presents a flexible ultraviolet (UV) photodetector (PD) system based on zinc oxide (ZnO) nanowires (NWs) for wearable UV dosimetry. High-crystal quality ZnO NWs have been synthesized by chemical vapour transport (CVT) technique on c-plane sapphire substrates, and thereafter, transferred and aligned at pre-defined locations on a flexible substrate using dielectrophoresis (DEP). The accurate control over DEP parameters permitted the fabrication of large-area (wafer scale) arrays of ZnO NWs based UV PDs. Resulting PDs showed photocurrent-to-dark current ratios above 103%, fast response times (<1 s), high sensitivity to different UV light intensities, and good stability under several UV/dark irradiation cycles. In addition, above PDs presented a robust response under extreme bending conditions, which is critical for their application in high-performance wearable UV dosimeters

Voltammetric determination of neotame by using chitosan/nickelnanoparticles/multi walled carbon nanotubes biocomposite as a modifier

A selective and simple biosensor was preparedby immobilizing chitosan/nickelnanoparticles/multi-walledcarbon nanotubes biocomposite on the glassy carbonelectrode surface for voltammetric quantification of neo-tame. The properties and morphology of the modifiedelectrode surfaces were characterized by scanning elec-tron microscope (SEM), energy dispersive X-ray analysis(EDX). Electro oxidation of neotame on this modifiedsurface was examined through cyclic voltammetry (CV)and square wave voltammetry (SWV) techniques. Thebiocomposite modified surface (Chi/NiNPs/MWCNTs/GCE) proposed in this study showed good electrocatalyticactivity for neotame with an improved voltammetric peakcurrent at 1.004 V, unlike the bare glassy carbon electrode(GCE) surface and several other modified surfaces.Under optimum conditions, Chi/NiNPs/MWCNTs/GCEgave linear SWV responses at the range of 2 M ~ 50 Mfor neotame with 0.84 M determination limit. Thisvoltammetric sensor was successfully employed for thequantification of neotame on food samples and showedlong-term stability, advanced voltammetric behavior, andgood repeatability. Selective, accurate, and precise deter-mination of neotame highlight the importance of thiselectrode in monitoring the control of food additives andensures attract a great deal of attention

Modelling of nanowire FETs based neural network for tactile pattern recognition in E-skin

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