Speech-language therapy for treatment of dysphagia and dysphonia in systemic granulomatous diseases: granulomatous diseases: dysphagia and dysphonia treatments

The granulomatous lesions are frequently founded in infectious diseases and can involve the larynx and pharynx and can cause varying degrees of dysphonia and dysphagia. There is still no systematic review that analyzes effectiveness of speech therapy in systemic granulomatous diseases. Research strategy: A systematic review was performed according to Cochrane guideline considering the inclusion of RCTs and quasi-RCTs about the effectiveness of speech-language therapy to treat dysphagia and dysphonia symptoms in systemic granulomatous diseases of the larynx and pharynx. Selection criteria: The outcome planned to be measured in this review were: swallowing impairment, frequency of chest infections and voice and swallowing symptoms. Data analysis: We identified 1,140 citations from all electronic databases. After an initial shift we only selected 9 titles to be retrieved in full-text. After full reading, there was no RCT found in this review and therefore, we only described the existing 2 case series studies. Results: There were no randomized controlled trials found in the literature. Therefore, two studies were selected to be included only for narratively analysis as they were case series. Conclusion: There is no evidence from high quality studies about the effectiveness of speech-language therapy in patients with granulomatous diseases of the larynx and pharynx. The investigators could rely in the outcomes suggested in this review to design their own clinical trials.

Protecting the √SWAP operation from general and residual errors by continuous dynamical decoupling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Protecting the √SWAP operation from general and residual errors by continuous dynamical decoupling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The dynamic behavior of a parametrically excited time-periodic MEMS taking into account parametric errors

Micro-electromechanical systems (MEMS) are micro scale devices that are able to convert electrical energy into mechanical energy or vice versa. In this paper, the mathematical model of an electronic circuit of a resonant MEMS mass sensor, with time-periodic parametric excitation, was analyzed and controlled by Chebyshev polynomial expansion of the Picard interaction and Lyapunov-Floquet transformation, and by Optimal Linear Feedback Control (OLFC). Both controls consider the union of feedback and feedforward controls. The feedback control obtained by Picard interaction and Lyapunov-Floquet transformation is the first strategy and the optimal control theory the second strategy. Numerical simulations show the efficiency of the two control methods, as well as the sensitivity of each control strategy to parametric errors. Without parametric errors, both control strategies were effective in maintaining the system in the desired orbit. On the other hand, in the presence of parametric errors, the OLFC technique was more robust.

An Investigation into Careless Errors Made by 7th Grade Mathematics Students

In this action research study, I investigated the careless errors made by my seventh-grade mathematics students on their homework and tests. Beyond analyzing the types of careless errors and the frequency at which they were made, I also analyzed my students’ attitudes toward reviewing their work before they turn it in and self-reflection about the quality of work that they were producing. I found that many students did not know how to review their test before turning it in; no one had ever taught them how to do so. However, when students were given tools to help them with this task, they were able to make strides towards reducing the number of careless errors that they made and began to turn in high quality work that demonstrated their understanding of the content that had been taught. As a result of this research, I plan to teach my students how to go back over their homework and tests before turning them in. I also intend to continue to use the tools that I have produced to encourage students to self-reflect on the work that they have done. Assessment is such an important piece of educating my students and the careless errors made on these assessments needed to be addressed.

ABN Noon Speech (Short version)

Folks, because we find ourselves in a time crunch, I'm going to forego the terrific speech I planned to give today and quickly make five key points. Please know I will be happy to provide additional information on any of them at any time.

Public Speaking in Social Phobia: A Pilot Study of Self-Ratings and Observers' Ratings of Social Skills

Objectives: The aim of this pilot study was to investigate whether patients with social anxiety disorder (SAD) differ from controls in the quality of skill-related behaviors displayed during a speech and in overall behavioral adequacy as perceived by observers and by the patients themselves. Design: A total of 18 SAD patients and 18 controls were screened by a diagnostic interview and took part in a 3-minute speech of their own choosing. For each videotaped speech, observers rated the adequacy of the skill-related behaviors and overall performance adequacy. After the experiment, participants were asked to rate their own overall performance adequacy. Results: The results showed that SAD patients exhibited significantly worse voice intonation and fluency of the speech, however no differences were found in global self-ratings. Moreover, the performance evaluations of the SAD group were consistent with the observers, while the controls evaluated their performance lower than the observers. Conclusions: The results are inconsistent with the cognitive model, because patients with SAD did not underestimate their performance. Compared with spontaneous interactions, the clear rules established for such social situations as speeches may result in less cognitive distortion for SAD patients. (C) 2012 Wiley Periodicals, Inc. J. Clin. Psychol. 68:397-402, 2012.

Inconsistent-tolerant base revision through Argument Theory Change

Reasoning and change over inconsistent knowledge bases (KBs) is of utmost relevance in areas like medicine and law. Argumentation may bring the possibility to cope with both problems. Firstly, by constructing an argumentation framework (AF) from the inconsistent KB, we can decide whether to accept or reject a certain claim through the interplay among arguments and counterarguments. Secondly, by handling dynamics of arguments of the AF, we might deal with the dynamics of knowledge of the underlying inconsistent KB. Dynamics of arguments has recently attracted attention and although some approaches have been proposed, a full axiomatization within the theory of belief revision was still missing. A revision arises when we want the argumentation semantics to accept an argument. Argument Theory Change (ATC) encloses the revision operators that modify the AF by analyzing dialectical trees-arguments as nodes and attacks as edges-as the adopted argumentation semantics. In this article, we present a simple approach to ATC based on propositional KBs. This allows to manage change of inconsistent KBs by relying upon classical belief revision, although contrary to it, consistency restoration of the KB is avoided. Subsequently, a set of rationality postulates adapted to argumentation is given, and finally, the proposed model of change is related to the postulates through the corresponding representation theorem. Though we focus on propositional logic, the results can be easily extended to more expressive formalisms such as first-order logic and description logics, to handle evolution of ontologies.

Prediction with measurement errors in finite populations

We address the problem of selecting the best linear unbiased predictor (BLUP) of the latent value (e.g., serum glucose fasting level) of sample subjects with heteroskedastic measurement errors. Using a simple example, we compare the usual mixed model BLUP to a similar predictor based on a mixed model framed in a finite population (FPMM) setup with two sources of variability, the first of which corresponds to simple random sampling and the second, to heteroskedastic measurement errors. Under this last approach, we show that when measurement errors are subject-specific, the BLUP shrinkage constants are based on a pooled measurement error variance as opposed to the individual ones generally considered for the usual mixed model BLUP. In contrast, when the heteroskedastic measurement errors are measurement condition-specific, the FPMM BLUP involves different shrinkage constants. We also show that in this setup, when measurement errors are subject-specific, the usual mixed model predictor is biased but has a smaller mean squared error than the FPMM BLUP which points to some difficulties in the interpretation of such predictors. (C) 2011 Elsevier By. All rights reserved.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Homology and errors

A recent review of the homology concept in cladistics is critiqued in light of the historical literature. Homology as a notion relevant to the recognition of clades remains equivalent to synapomorphy. Some symplesiomorphies are homologies inasmuch as they represent synapomorphies of more inclusive taxa; others are complementary character states that do not imply any shared evolutionary history among the taxa that exhibit the state. Undirected character-state change (as characters optimized on an unrooted tree) is a necessary but not sufficient test of homology, because the addition of a root may alter parsimonious reconstructions. Primary and secondary homology are defended as realistic representations of discovery procedures in comparative biology, recognizable even in Direct Optimization. The epistemological relationship between homology as evidence and common ancestry as explanation is again emphasized. An alternative definition of homology is proposed. (c) The Willi Hennig Society 2012.

Result on speech perception after conversion from Spectra (R) to Freedom (R)

New technology in the Freedom (R) speech processor for cochlear implants was developed to improve how incoming acoustic sound is processed; this applies not only for new users, but also for previous generations of cochlear implants. Aim: To identify the contribution of this technology - the Nucleus 22 (R) - on speech perception tests in silence and in noise, and on audiometric thresholds. Methods: A cross-sectional cohort study was undertaken. Seventeen patients were selected. The last map based on the Spectra (R) was revised and optimized before starting the tests. Troubleshooting was used to identify malfunction. To identify the contribution of the Freedom (R) technology for the Nucleus22 (R), auditory thresholds and speech perception tests were performed in free field in soundproof booths. Recorded monosyllables and sentences in silence and in noise (SNR = 0dB) were presented at 60 dBSPL. The nonparametric Wilcoxon test for paired data was used to compare groups. Results: Freedom (R) applied for the Nucleus22 (R) showed a statistically significant difference in all speech perception tests and audiometric thresholds. Conclusion: The reedom (R) technology improved the performance of speech perception and audiometric thresholds of patients with Nucleus 22 (R).

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.