Perception of Time-Discrete Haptic Feedback on the Waist is Invariant with Gait Events

The effectiveness of haptic feedback devices highly depends on the perception of tactile stimuli, which differs across body parts and can be affected by movement. In this study, a novel wearable sensory feedback apparatus made of a pair of pressure-sensitive insoles and a belt equipped with vibrotactile units is presented; the device provides time-discrete vibrations around the waist, synchronized with biomechanically-relevant gait events during walking. Experiments with fifteen healthy volunteers were carried out to investigate users' tactile perception on the waist. Stimuli of different intensities were provided at twelve locations, each time synchronously with one pre-defined gait event (i.e. heel strike, flat foot or toe off), following a pseudo-random stimulation sequence. Reaction time, detection rate and localization accuracy were analyzed as functions of the stimulation level and site and the effect of gait events on perception was investigated. Results revealed that above-threshold stimuli (i.e. vibrations characterized by acceleration amplitudes of 1.92g and 2.13g and frequencies of 100 Hz and 150 Hz, respectively) can be effectively perceived in all the sites and successfully localized when the intertactor spacing is set to 10 cm. Moreover, it was found that perception of time-discrete vibrations was not affected by phase-related gating mechanisms, suggesting that the waist could be considered as a preferred body region for delivering haptic feedback during walking

Assessment of intuitiveness and comfort of wearable haptic feedback strategies for assisting level and stair walking

Nowadays, lower-limb prostheses are reaching real-world usability especially on ground-level walking. However, some key tasks such as stair walking are still quite demanding. Providing haptic feedback about the foot placement on the steps might reduce the cognitive load of the task, compensating for increased dependency on vision and lessen the risk of falling. Experiments on intact subjects can be useful to define the feedback strategies prior to clinical trials, but effective methods to assess the efficacy of the strategies are few and usually rely on the emulation of the disability condition. The present study reports on the design and testing of a wearable haptic feedback system in a protocol involving intact subjects to assess candidate strategies to be adopted in clinical trials. The system integrated a sensorized insole wirelessly connected to a textile waist belt equipped with three vibrating motors. Three stimulation strategies for mapping the insole pressure data to vibrotactile feedback were implemented and compared in terms of intuitiveness and comfort perceived during level and stair walking. The strategies were ranked using a relative rating approach, which highlighted the differences between them and suggested guidelines for their improvement. The feedback evaluation procedure proposed could facilitate the selection and improvement of haptic feedback strategies prior to clinical testing

Comparing dynamics: deep neural networks versus glassy systems

We analyze numerically the training dynamics of deep neural networks (DNN) by using methods developed in statistical physics of glassy systems. The two main issues we address are (1) the complexity of the loss landscape and of the dynamics within it, and (2) to what extent DNNs share similarities with glassy systems. Our findings, obtained for different architectures and datasets, suggest that during the training process the dynamics slows down because of an increasingly large number of flat directions. At large times, when the loss is approaching zero, the system diffuses at the bottom of the landscape. Despite some similarities with the dynamics of mean-field glassy systems, in particular, the absence of barrier crossing, we find distinctive dynamical behaviors in the two cases, showing that the statistical properties of the corresponding loss and energy landscapes are different. In contrast, when the network is under-parametrized we observe a typical glassy behavior, thus suggesting the existence of different phases depending on whether the network is under-parametrized or over-parametrized

Self-explaining AI as an alternative to interpretable AI

The ability to explain decisions made by AI systems is highly sought after, especially in domains where human lives are at stake such as medicine or autonomous vehicles. While it is often possible to approximate the input-output relations of deep neural networks with a few human-understandable rules, the discovery of the double descent phenomena suggests that such approximations do not accurately capture the mechanism by which deep neural networks work. Double descent indicates that deep neural networks typically operate by smoothly interpolating between data points rather than by extracting a few high level rules. As a result, neural networks trained on complex real world data are inherently hard to interpret and prone to failure if asked to extrapolate. To show how we might be able to trust AI despite these problems we introduce the concept of self-explaining AI. Self-explaining AIs are capable of providing a human-understandable explanation of each decision along with confidence levels for both the decision and explanation. For this approach to work, it is important that the explanation actually be related to the decision, ideally capturing the mechanism used to arrive at the explanation. Finally, we argue it is important that deep learning based systems include a "warning light" based on techniques from applicability domain analysis to warn the user if a model is asked to extrapolate outside its training distribution. For a video presentation of this talk see https://www.youtube.com/watch?v=Py7PVdcu7WY& .Comment: 10pgs, 2 column forma

Molecular cytogenetics (FISH, GISH) of Coccinia grandis: A ca. 3 myr-old species of Cucurbitaceae with the largest Y/autosome divergence in flowering plants

The independent evolution of heteromorphic sex chromosomes in 19 species from 4 families of flowering plants permits studying X/Y divergence after the initial recombination suppression. Here, we document autosome/Y divergence in the tropical Cucurbitaceae Coccinia grandis, which is ca. 3 myr old. Karyotyping and C-value measurements show that the C. grandis Y chromosome has twice the size of any of the other chromosomes, with a male/female C-value difference of 0.094 pg or 10% of the total genome. FISH staining revealed 5S and 45S rDNA sites on autosomes but not on the Y chromosome, making it unlikely that rDNA contributed to the elongation of the Y chromosome; recent end-to-end fusion also seems unlikely given the lack of interstitial telomeric signals. GISH with different concentrations of female blocking DNA detected a possible pseudo-autosomal region on the Y chromosome, and C-banding suggests that the entire Y chromosome in C. grandis is heterochromatic. During meiosis, there is an end-to-end connection between the X and the Y chromosome, but the X does not otherwise differ from the remaining chromosomes. These findings and a review of plants with heteromorphic sex chromosomes reveal no relationship between species age and degree of sex chromosome dimorphism. Its relatively small genome size (0.943 pg/2C in males), large Y chromosome, and phylogenetic proximity to the fully sequenced Cucumis sativus make C. grandis a promising model to study sex chromosome evolution. Copyright © 2012 S. Karger AG, Base

A specific insertion of a solo-LTR characterizes the Y-chromosome of Bryonia dioica (Cucurbitaceae)

Background: Relatively few species of flowering plants are dioecious and even fewer are known to have sex chromosomes. Current theory posits that homomorphic sex chromosomes, such as found in Bryonia dioica (Cucurbitaceae), offer insight into the early stages in the evolution of sex chromosomes from autosomes. Little is known about these early steps, but an accumulation of transposable element sequences has been observed on the Ychromosomes of some species with heteromorphic sex chromosomes. Recombination, by which transposable elements are removed, is suppressed on at least part of the emerging Y-chromosome, and this may explain the correlation between the emergence of sex chromosomes and transposable element enrichment. Findings: We sequenced 2321 bp of the Y-chromosome in Bryonia dioica that flank a male-linked marker, BdY1, reported previously. Within this region, which should be suppressed for recombination, we observed a solo-LTR nested in a Copia-like transposable element. We also found other, presumably paralogous, solo-LTRs in a consensus sequence of the underlying Copia-like transposable element. Conclusions: Given that solo-LTRs arise via recombination events, it is noteworthy that we find one in a genomic region where recombination should be suppressed. Although the solo-LTR could have arisen before recombination was suppressed, creating the male-linked marker BdY1, our previous study on B. dioica suggested that BdY1 may not lie in the recombination-suppressed region of the Y-chromosome in all populations. Presence of a solo-LTR near BdY1 therefore fits with the observed correlation between retrotransposon accumulation and the suppression of recombination early in the evolution of sex chromosomes. These findings further suggest that the homomorphic sex chromosomes of B. dioica, the first organism for which genetic XY sex-determination was inferred, are evolutionarily young and offer reference information for comparative studies of other plant sex chromosomes

The spatial scale of density-dependent growth and implications for dispersal from nests in juvenile Atlantic salmon

By dispersing from localized aggregations of recruits, individuals may obtain energetic benefits due to reduced experienced density. However, this will depend on the spatial scale over which individuals compete. Here, we quantify this scale for juvenile Atlantic salmon (Salmo salar) following emergence and dispersal from nests. A single nest was placed in each of ten replicate streams during winter, and information on the individual positions (±1 m) and the body sizes of the resulting young-of-the-year (YOY) juveniles was obtained by sampling during the summer. In six of the ten streams, model comparisons suggested that individual body size was most closely related to the density within a mean distance of 11 m (range 2–26 m). A link between body size and density on such a restricted spatial scale suggests that dispersal from nests confers energetic benefits that can counterbalance any survival costs. For the four remaining streams, which had a high abundance of trout and older salmon cohorts, no single spatial scale could best describe the relation between YOY density and body size. Energetic benefits of dispersal associated with reduced local density therefore appear to depend on the abundance of competing cohorts or species, which have spatial distributions that are less predictable in terms of distance from nests. Thus, given a trade-off between costs and benefits associated with dispersal, and variation in benefits among environments, we predict an evolving and/or phenotypically plastic growth rate threshold which determines when an individual decides to disperse from areas of high local density

How to make a sex chromosome

Sex chromosomes can evolve once recombination is halted between a homologous pair of chromosomes. Owing to detailed studies using key model systems, we have a nuanced understanding and a rich review literature of what happens to sex chromosomes once recombination is arrested. However, three broad questions remain unanswered. First, why do sex chromosomes stop recombining in the first place? Second, how is recombination halted? Finally, why does the spread of recombination suppression, and therefore the rate of sex chromosome divergence, vary so substantially across clades? In this review, we consider each of these three questions in turn to address fundamental questions in the field, summarize our current understanding, and highlight important areas for future work

Familiarization: A theory of repetition suppression predicts interference between overlapping cortical representations

Repetition suppression refers to a reduction in the cortical response to a novel stimulus that results from repeated presentation of the stimulus. We demonstrate repetition suppression in a well established computational model of cortical plasticity, according to which the relative strengths of lateral inhibitory interactions are modified by Hebbian learning. We present the model as an extension to the traditional account of repetition suppression offered by sharpening theory, which emphasises the contribution of afferent plasticity, by instead attributing the effect primarily to plasticity of intra-cortical circuitry. In support, repetition suppression is shown to emerge in simulations with plasticity enabled only in intra-cortical connections. We show in simulation how an extended ‘inhibitory sharpening theory’ can explain the disruption of repetition suppression reported in studies that include an intermediate phase of exposure to additional novel stimuli composed of features similar to those of the original stimulus. The model suggests a re-interpretation of repetition suppression as a manifestation of the process by which an initially distributed representation of a novel object becomes a more localist representation. Thus, inhibitory sharpening may constitute a more general process by which representation emerges from cortical re-organisation

Quantitative estimates of unique continuation for parabolic equations, determination of unknown time-varying boundaries and optimal stability estimates

In this paper we will review the main results concerning the issue of stability for the determination unknown boundary portion of a thermic conducting body from Cauchy data for parabolic equations. We give detailed and selfcontained proofs. We prove that such problems are severely ill-posed in the sense that under a priori regularity assumptions on the unknown boundaries, up to any finite order of differentiability, the continuous dependence of unknown boundary from the measured data is, at best, of logarithmic type