6,032 research outputs found
Objective dysphonia quantification in vocal fold paralysis: comparing nonlinear with classical measures
Clinical acoustic voice recording analysis is usually performed using classical perturbation measures including jitter, shimmer and noise-to-harmonic ratios. However, restrictive mathematical limitations of these measures prevent analysis for severely dysphonic voices. Previous studies of alternative nonlinear random measures addressed wide varieties of vocal pathologies. Here, we analyze a single vocal pathology cohort, testing the performance of these alternative measures alongside classical measures.

We present voice analysis pre- and post-operatively in unilateral vocal fold paralysis (UVFP) patients and healthy controls, patients undergoing standard medialisation thyroplasty surgery, using jitter, shimmer and noise-to-harmonic ratio (NHR), and nonlinear recurrence period density entropy (RPDE), detrended fluctuation analysis (DFA) and correlation dimension. Systematizing the preparative editing of the recordings, we found that the novel measures were more stable and hence reliable, than the classical measures, on healthy controls.

RPDE and jitter are sensitive to improvements pre- to post-operation. Shimmer, NHR and DFA showed no significant change (p > 0.05). All measures detect statistically significant and clinically important differences between controls and patients, both treated and untreated (p < 0.001, AUC > 0.7). Pre- to post-operation, GRBAS ratings show statistically significant and clinically important improvement in overall dysphonia grade (G) (AUC = 0.946, p < 0.001).

Re-calculating AUCs from other study data, we compare these results in terms of clinical importance. We conclude that, when preparative editing is systematized, nonlinear random measures may be useful UVFP treatment effectiveness monitoring tools, and there may be applications for other forms of dysphonia.

Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection
Background: Voice disorders affect patients profoundly, and acoustic tools can potentially measure voice function objectively. Disordered sustained vowels exhibit wide-ranging phenomena, from nearly periodic to highly complex, aperiodic vibrations, and increased "breathiness". Modelling and surrogate data studies have shown significant nonlinear and non-Gaussian random properties in these sounds. Nonetheless, existing tools are limited to analysing voices displaying near periodicity, and do not account for this inherent biophysical nonlinearity and non-Gaussian randomness, often using linear signal processing methods insensitive to these properties. They do not directly measure the two main biophysical symptoms of disorder: complex nonlinear aperiodicity, and turbulent, aeroacoustic, non-Gaussian randomness. Often these tools cannot be applied to more severe disordered voices, limiting their clinical usefulness.

Methods: This paper introduces two new tools to speech analysis: recurrence and fractal scaling, which overcome the range limitations of existing tools by addressing directly these two symptoms of disorder, together reproducing a "hoarseness" diagram. A simple bootstrapped classifier then uses these two features to distinguish normal from disordered voices.

Results: On a large database of subjects with a wide variety of voice disorders, these new techniques can distinguish normal from disordered cases, using quadratic discriminant analysis, to overall correct classification performance of 91.8% plus or minus 2.0%. The true positive classification performance is 95.4% plus or minus 3.2%, and the true negative performance is 91.5% plus or minus 2.3% (95% confidence). This is shown to outperform all combinations of the most popular classical tools.

Conclusions: Given the very large number of arbitrary parameters and computational complexity of existing techniques, these new techniques are far simpler and yet achieve clinically useful classification performance using only a basic classification technique. They do so by exploiting the inherent nonlinearity and turbulent randomness in disordered voice signals. They are widely applicable to the whole range of disordered voice phenomena by design. These new measures could therefore be used for a variety of practical clinical purposes.

Functional Morphology and Fluid Interactions During Early Development of the Scyphomedusa Aurelia aurita
Scyphomedusae undergo a predictable ontogenetic transition from a conserved, universal larval form to a diverse array of adult morphologies. This transition entails a change in bell morphology from a highly discontinuous ephyral form, with deep clefts separating eight discrete lappets, to a continuous solid umbrella-like adult form. We used a combination of kinematic, modeling, and flow visualization techniques to examine the function of the medusan bell throughout the developmental changes of the scyphomedusa Aurelia aurita. We found that flow around swimming ephyrae and their lappets was relatively viscous (1 < Re < 10) and, as a result, ephyral lappets were surrounded by thick, overlapping boundary layers that occluded flow through the gaps between lappets. As medusae grew, their fluid environment became increasingly influenced by inertial forces (10 < Re < 10,000) and, simultaneously, clefts between the lappets were replaced by organic tissue. Hence, although the bell undergoes a structural transition from discontinuous (lappets with gaps) to continuous (solid bell) surfaces during development, all developmental stages maintain functionally continuous paddling surfaces. This developmental pattern enables ephyrae to efficiently allocate tissue to bell diameter increase via lappet growth, while minimizing tissue allocation to inter-lappet spaces that maintain paddle function due to boundary layer overlap
Evolving localizations in reaction-diffusion cellular automata
We consider hexagonal cellular automata with immediate cell neighbourhood and
three cell-states. Every cell calculates its next state depending on the
integral representation of states in its neighbourhood, i.e. how many
neighbours are in each one state. We employ evolutionary algorithms to breed
local transition functions that support mobile localizations (gliders), and
characterize sets of the functions selected in terms of quasi-chemical systems.
Analysis of the set of functions evolved allows to speculate that mobile
localizations are likely to emerge in the quasi-chemical systems with limited
diffusion of one reagent, a small number of molecules is required for
amplification of travelling localizations, and reactions leading to stationary
localizations involve relatively equal amount of quasi-chemical species.
Techniques developed can be applied in cascading signals in nature-inspired
spatially extended computing devices, and phenomenological studies and
classification of non-linear discrete systems.Comment: Accepted for publication in Int. J. Modern Physics
Stillbirth should be given greater priority on the global health agenda
Stillbirths are largely excluded from international measures of mortality and morbidity. Zeshan Qureshi and colleagues argue that stillbirth should be higher on the global health agenda
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GENOME WIDE DNA METHYLATION PROFILING IS PREDICTIVE OF OUTCOME IN JUVENILE MYELOMONOCYTIC LEUKEMIA
“I just want to be skinny.”: A content analysis of tweets expressing eating disorder symptoms
There is increasing concern about online communities that promote eating disorder (ED) behaviors through messages and/or images that encourage a “thin ideal” (i.e., promotion of thinness as attractive) and harmful weight loss/weight control practices. The purpose of this paper is to assess the content of body image and ED-related content on Twitter and provide a deeper understanding of EDs that may be used for future studies and online-based interventions. Tweets containing ED or body image-related keywords were collected from January 1-January 31, 2015 (N = 28,642). A random sample (n = 3000) was assessed for expressions of behaviors that align with subscales of the Eating Disorder Examination (EDE) 16.0. Demographic characteristics were inferred using a social media analytics company. The comprehensive research that we conducted indicated that 2,584 of the 3,000 tweets were ED-related; 65% expressed a preoccupation with body shape, 13% displayed issues related to food/eating/calories, and 4% expressed placing a high level of importance on body weight. Most tweets were sent by girls (90%) who were ≤19 years old (77%). Our findings stress a need to better understand if and how ED-related content on social media can be used for targeting prevention and intervention messages towards those who are in-need and could potentially benefit from these efforts.</div
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Exposure-Lag-Response in Longitudinal Studies: Application of Distributed-Lag Nonlinear Models in an Occupational Cohort.
Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Summary measures such as cumulative exposure or average intensity of exposure may not fully capture these relationships. We applied penalized and unpenalized distributed-lag nonlinear models (DLNMs) with flexible exposure-response and lag-response functions in order to examine the association between crystalline silica exposure and mortality from lung cancer and nonmalignant respiratory disease in a cohort study of 2,342 California diatomaceous earth workers followed during 1942-2011. We also assessed associations using simple measures of cumulative exposure assuming linear exposure-response and constant lag-response. Measures of association from DLNMs were generally higher than those from simpler models. Rate ratios from penalized DLNMs corresponding to average daily exposures of 0.4 mg/m3 during lag years 31-50 prior to the age of observed cases were 1.47 (95% confidence interval (CI): 0.92, 2.35) for lung cancer mortality and 1.80 (95% CI: 1.14, 2.85) for nonmalignant respiratory disease mortality. Rate ratios from the simpler models for the same exposure scenario were 1.15 (95% CI: 0.89, 1.48) and 1.23 (95% CI: 1.03, 1.46), respectively. Longitudinal cohort studies of prolonged exposures and chronic health outcomes should explore methods allowing for flexibility and nonlinearities in the exposure-lag-response
Equivalences between GIT quotients of Landau-Ginzburg B-models
We define the category of B-branes in a (not necessarily affine)
Landau-Ginzburg B-model, incorporating the notion of R-charge. Our definition
is a direct generalization of the category of perfect complexes. We then
consider pairs of Landau-Ginzburg B-models that arise as different GIT
quotients of a vector space by a one-dimensional torus, and show that for each
such pair the two categories of B-branes are quasi-equivalent. In fact we
produce a whole set of quasi-equivalences indexed by the integers, and show
that the resulting auto-equivalences are all spherical twists.Comment: v3: Added two references. Final version, to appear in Comm. Math.
Phy
Group And Individual Social Network Metrics Are Robust To Changes In Resource Distribution In Experimental Populations Of Forked Fungus Beetles
1. Social interactions drive many important ecological and evolutionary processes. It is therefore essential to understand the intrinsic and extrinsic factors that underlie social patterns. A central tenet of the field of behavioural ecology is the expectation that the distribution of resources shapes patterns of social interactions. 2. We combined experimental manipulations with social network analyses to ask how patterns of resource distribution influence complex social interactions. 3. We experimentally manipulated the distribution of an essential food and reproductive resource in semi-natural populations of forked fungus beetles Bolitotherus cornutus. We aggregated resources into discrete clumps in half of the populations and evenly dispersed resources in the other half. We then observed social interactions between individually marked beetles. Half-way through the experiment, we reversed the resource distribution in each population, allowing us to control any demographic or behavioural differences between our experimental populations. At the end of the experiment, we compared individual and group social network characteristics between the two resource distribution treatments. 4. We found a statistically significant but quantitatively small effect of resource distribution on individual social network position and detected no effect on group social network structure. Individual connectivity (individual strength) and individual cliquishness (local clustering coefficient) increased in environments with clumped resources, but this difference explained very little of the variance in individual social network position. Individual centrality (individual betweenness) and measures of overall social structure (network density, average shortest path length and global clustering coefficient) did not differ between environments with dramatically different distributions of resources. 5. Our results illustrate that the resource environment, despite being fundamental to our understanding of social systems, does not always play a central role in shaping social interactions. Instead, our results suggest that sex differences and temporally fluctuating environmental conditions may be more important in determining patterns of social interactions
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