Time Constraints in the School Environment: What Does a Sleepy Student Tell Us?

In this article, we discuss school schedules and their implications in the context of chronobiological contemporary knowledge, arguing for the need to reconsider time planning in the school setting. We present anecdotal observations regarding chronobiological challenges imposed by the school system throughout different ages and discuss the effects of these schedules in terms of sleepiness and its deleterious consequences on learning, memory, and attention. Different settings (including urban vs. rural habitats) influence timing, which also depends on self-selected sleep schedules. Finally, we criticize the traditional view of a necessary strict stability of sleep-wake habits.

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)

Voice Feature Characteristic in Morbid Obese Population

Morbid obesity is highly prevalent in the Western World, and its consequences present a real public health challenge. Voice alterations can represent one of these consequences and represent an opportunity for interference with therapeutic methods. This particularly features of the individual`s voice was the goal of the present study. A group of 45 adult volunteers of both sexes with a BMI greater than 35 Kg/m(2) was selected among patients of the Obesity Ambulatory of the Digestive Surgery Division. The control group consisted of volunteers matched by sex, age (+/- 1 year), and smoking habits, but with a BMI bellow 30 Kg/m(2). All subjects were submitted to laryngoscopic examination, audio perceptive analysis, and voice acoustics determination. Examinations were always performed by the same doctor, and diagnoses were provided by two different physician specialists in laryngology and voice. Obese individuals exhibit the following modifications in voice feature: hoarseness, murmuring, vocal instability, altered jitter and shimmer, and reduced maximum phonation times as well the presence of voice strangulation at the end of emission. The voices of individuals with morbid obesity are different of the voice of nonobese people and demonstrate significant changes in vocal characteristics.

Metallic Voice: Physiological and Acoustic Features

The metallic voice is usually confused with ring or nasality by singers and nontrained listeners. who are not used to perceptual vocal analysis. They believe a metallic voice results from a rise in fundamental frequency. A diagnostic error in this aspect may lead to lowering pitch, an incorrect procedure that Could Cause vocal overload and fatigue. The purpose of this article is to Study the quality of metallic voice considering the correlation between information of the physiological and acoustic plans, based on a perceptive consensual assumption. Fiberscopic video pharyngolaryngoscopy was performed on 21 professional singers while speaking vowel [e]-in normal and metallic modes to observe muscular movements and structural changes of the velopharynx, pharynx, and larynx. Vocal samples captured simultaneously to the fiberscopic examination were acoustically analyzed. Frequency and amplitude of the first four formants (F(1), F(2), F(3), and F(4)) were extracted by means of linear predictor coefficients (LPC) Spectrum and were statistically analyzed. Vocal tract adjustments such as velar lowering, pharyngeal wall narrowing, laryngeal rise, aryepiglottic, and lateral laryngeal constrictions were frequently found: there were no significant changes in frequency and amplitude of F(1) in the metallic voiced there were significant increases in amplitudes of F(2), F(3), and F(4) and in frequency for F, metallic Voice perceived as louder was correlated to an increase ill amplitude of F(3) and F(4). Physiological adjustments of velopharynx, pharynx, and larynx are combined in characterizing the metallic voice and can be acoustically related to changes in formant pattern.

Use of Music and Voice Stimulus on Patients With Disorders of Consciousness

The objectives of this study were to check music and voice message influence on vital signs and facial expressions of patients with disorders of consciousness and to connect the existence of patient`s responses with the Glasgow Coma Scale or with the Ramsay Sedation Scale. The method was a single-blinded randomized controlled clinical trial with 30 patients, from two intensive care units, being divided into two groups (control and experimental). Their relatives recorded a voice message and chose a song according to the patient`s preference. The patients were submitted to three sessions for three consecutive days. Significant statistical alterations of the vital signs were noted during the message playback (oxygen saturation-Day 1 and Day 3; respiratory frequency-Day 3) and with facial expression, on Day 1, during both music and message. The conclusion was that the voice message was a stronger stimulus than the music.

Influence of Orthognathic Surgery on Voice Fundamental Frequency

Considering that orthognathic surgery promotes changes in orofacial structures constituting the resonating system, functional changes secondary to surgery are expected to affect speech, leading to the need for further speech and voice adjustments. Thus, understanding the possible relationships of these structures with voice production is important. Therefore, this Study aimed to describe the changes in voice fundamental frequency of a patient submitted to orthognathic surgery and observe if there is a relationship with hyoid bone positioning at the different treatment periods. The results revealed that voice fundamental frequency increased after surgery, returning to values close to the preoperative condition, which corresponded to vertical movement of the hyoid bone.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

Relative entropy measures applied to healthy and pathological voice characterization

Nowadays, noninvasive methods of diagnosis have increased due to demands of the population that requires fast, simple and painless exams. These methods have become possible because of the growth of technology that provides the necessary means of collecting and processing signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this paper is to characterize healthy and pathological voice signals with the aid of relative entropy measures. Phase space reconstruction technique is also used as a way to select interesting regions of the signals. Three groups of samples were used, one from healthy individuals and the other two from people with nodule in the vocal fold and Reinke`s edema. All of them are recordings of sustained vowel /a/ from Brazilian Portuguese. The paper shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Relative entropy is well suited due to its sensibility to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. The results showed that the pathological groups had higher entropy values in accordance with other vocal acoustic parameters presented. This suggests that these techniques may improve and complement the recent voice analysis methods available for clinicians. (C) 2008 Elsevier Inc. All rights reserved.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.