Prevalence and determinants of spectacle nonwear among rural Chinese secondary schoolchildren: the Xichang Pediatric Refractive Error Study Report 3.

OBJECTIVE: To study spectacle wear among rural Chinese children. METHODS: Visual acuity, refraction, spectacle wear, and visual function were measured. RESULTS: Among 1892 subjects (84.7% of the sample), the mean (SD) age was 14.7 (0.8) years. Among 948 children (50.1%) potentially benefiting from spectacle wear, 368 (38.8%) did not own them. Among 580 children owning spectacles, 17.9% did not wear them at school. Among 476 children wearing spectacles, 25.0% had prescriptions that could not improve their visual acuity to better than 6/12. Therefore, 62.3% (591 of 948) of children needing spectacles did not benefit from appropriate correction. Children not owning and not wearing spectacles had better self-reported visual function but worse visual acuity at initial examination than children wearing spectacles and had a mean (SD) refractive error of -2.06 (1.15) diopter (D) and -2.78 (1.32) D, respectively. Girls (P < .001) and older children (P = .03) were more likely to be wearing their spectacles. A common reason for nonwear (17.0%) was the belief that spectacles weaken the eyes. Among children without spectacles, 79.3% said their families would pay for them (mean, US $15). CONCLUSIONS: Although half of the children could benefit from spectacle wear, 62.3% were not wearing appropriate correction. These children have significant uncorrected refractive errors. There is potential to support programs through spectacle sales.

Validating the accuracy of a model to predict the onset of myopia in children.

PURPOSE: To assess the sensitivity and specificity of models predicting myopia onset among ethnically Chinese children. METHODS: Visual acuity, height, weight, biometry (A-scan, keratometry), and refractive error were assessed at baseline and 3 years later using the same equipment and protocol in primary schools in Xiamen (China) and Singapore. A regression model predicting the onset of myopia < -0.75 diopters (D) after 3 years in either eye among Xiamen children was validated with Singapore data. RESULTS: Baseline data were collected from 236 Xiamen children (mean age, 7.82 ± 0.63 years) and from 1979 predominantly Chinese children in Singapore (7.83 ± 0.84 years). Singapore children were significantly taller and heavier, and had more myopia (31.4% vs. 6.36% < -0.75 D in either eye, P < 0.001) and longer mean axial length. Three-year follow-up was available for 80.0% of Xiamen children and 83.1% in Singapore. For Xiamen, the area under the receiver-operator curve (AUC) in a model including ocular biometry, height, weight, and presenting visual acuity was 0.974 (95% confidence interval [CI], 0.945-0.997). In Singapore, the same model achieved sensitivity, specificity, and positive predictive value of 0.844, 0.650, and 0.669, with an AUC of 0.815 (95% CI, 0.791-0.839). CONCLUSIONS: Accuracy in predicting myopia onset based on simple measurements may be sufficient to make targeted early intervention practical in settings such as Singapore with high myopia prevalence. Models based on cohorts with a greater prevalence of high myopia than that in Xiamen could be used to assess accuracy of models predicting more severe forms of myopia.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

A Spiking Neural Network Model of the Medial Superior Olive using Spike Timing Dependent Plasticity for Sound Localisation

Sound localization can be defined as the ability to identify the position of an input sound source and is considered a powerful aspect of mammalian perception. For low frequency sounds, i.e., in the range 270 Hz-1.5 KHz, the mammalian auditory pathway achieves this by extracting the Interaural Time Difference between sound signals being received by the left and right ear. This processing is performed in a region of the brain known as the Medial Superior Olive (MSO). This paper presents a Spiking Neural Network (SNN) based model of the MSO. The network model is trained using the Spike Timing Dependent Plasticity learning rule using experimentally observed Head Related Transfer Function data in an adult domestic cat. The results presented demonstrate how the proposed SNN model is able to perform sound localization with an accuracy of 91.82% when an error tolerance of +/-10 degrees is used. For angular resolutions down to 2.5 degrees , it will be demonstrated how software based simulations of the model incur significant computation times. The paper thus also addresses preliminary implementation on a Field Programmable Gate Array based hardware platform to accelerate system performance.

Partial volume correction using bimodal contrast agents in PET-MRI

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2014

Essays on Applications of the Factor Model

Thesis (Ph.D.)--University of Washington, 2013

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical and physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration time of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5–Yonsei University–Noah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limitations of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical configuration for the region of interest together with the use of high resolution terrain data, if available.

Top-down and Bottom-up influences on ACC activation: Evaluation of a proposed model of the feedback-related negativity

The Feedback-Related Negativity (FRN) is thought to reflect the dopaminergic prediction error signal from the subcortical areas to the ACC (i.e., a bottom-up signal). Two studies were conducted in order to test a new model of FRN generation, which includes direct modulating influences of medial PFC (i.e., top-down signals) on the ACC at the time of the FRN. Study 1 examined the effects of one’s sense of control (top-down) and of informative cues (bottom-up) on the FRN measures. In Study 2, sense of control and instruction-based (top-down) and probability-based expectations (bottom-up) were manipulated to test the proposed model. The results suggest that any influences of medial PFC on the activity of the ACC that occur in the context of incentive tasks are not direct. The FRN was shown to be sensitive to salient stimulus characteristics. The results of this dissertation partially support the reinforcement learning theory, in that the FRN is a marker for prediction error signal from subcortical areas. However, the pattern of results outlined here suggests that prediction errors are based on salient stimulus characteristics and are not reward specific. A second goal of this dissertation was to examine whether ACC activity, measured through the FRN, is altered in individuals at-risk for problem-gambling behaviour (PG). Individuals in this group were more sensitive to the valence of the outcome in a gambling task compared to not at-risk individuals, suggesting that gambling contexts increase the sensitivity of the reward system to valence of the outcome in individuals at risk for PG. Furthermore, at-risk participants showed an increased sensitivity to reward characteristics and a decreased response to loss outcomes. This contrasts with those not at risk whose FRNs were sensitive to losses. As the results did not replicate previous research showing attenuated FRNs in pathological gamblers, it is likely that the size and time of the FRN does not change gradually with increasing risk of maladaptive behaviour. Instead, changes in ACC activity reflected by the FRN in general can be observed only after behaviour becomes clinically maladaptive or through comparison between different types of gain/loss outcomes.

The effects of manipulated augmented sensory feedback on error detection when using a touch screen

The purpose of the present study was to determine which augmented sensory modality would best develop subjective error-detection capabilities of learners performing a spatial-temporal task when using a touch screen monitor. Participants were required to learn a 5-digit key-pressing task in a goal time of 2550 ms over 100 acquisition trials on a touch screen. Participants were randomized into 1 of 4 groups: 1) visual-feedback (colour change of button when selected), 2) auditory-feedback (click sound when button was selected), 3) visual-auditory feedback (both colour change and click sound when button was selected), and 4) no-feedback (no colour change or click sound when button was selected). Following each trial, participants were required to provide a subjective estimate regarding their performance time in relation to the actual time it took for them complete the 5-digit sequence. A no-KR retention test was conducted approximately 24-hours after the last completed acquisition trial. Results showed that practicing a timing task on a touch screen augmented with both visual and auditory information may have differentially impacted motor skill acquisition such that removal of one or both sources of augmented feedback did not result in a severe detriment to timing performance or error detection capabilities of the learner. The present study reflects the importance of multimodal augmented feedback conditions to maximize cognitive abilities for developing a stronger motor memory for subjective error-detection and correction capabilities.

Inférence topologique

Les données provenant de l'échantillonnage fin d'un processus continu (champ aléatoire) peuvent être représentées sous forme d'images. Un test statistique permettant de détecter une différence entre deux images peut être vu comme un ensemble de tests où chaque pixel est comparé au pixel correspondant de l'autre image. On utilise alors une méthode de contrôle de l'erreur de type I au niveau de l'ensemble de tests, comme la correction de Bonferroni ou le contrôle du taux de faux-positifs (FDR). Des méthodes d'analyse de données ont été développées en imagerie médicale, principalement par Keith Worsley, utilisant la géométrie des champs aléatoires afin de construire un test statistique global sur une image entière. Il s'agit d'utiliser l'espérance de la caractéristique d'Euler de l'ensemble d'excursion du champ aléatoire sous-jacent à l'échantillon au-delà d'un seuil donné, pour déterminer la probabilité que le champ aléatoire dépasse ce même seuil sous l'hypothèse nulle (inférence topologique). Nous exposons quelques notions portant sur les champs aléatoires, en particulier l'isotropie (la fonction de covariance entre deux points du champ dépend seulement de la distance qui les sépare). Nous discutons de deux méthodes pour l'analyse des champs anisotropes. La première consiste à déformer le champ puis à utiliser les volumes intrinsèques et les compacités de la caractéristique d'Euler. La seconde utilise plutôt les courbures de Lipschitz-Killing. Nous faisons ensuite une étude de niveau et de puissance de l'inférence topologique en comparaison avec la correction de Bonferroni. Finalement, nous utilisons l'inférence topologique pour décrire l'évolution du changement climatique sur le territoire du Québec entre 1991 et 2100, en utilisant des données de température simulées et publiées par l'Équipe Simulations climatiques d'Ouranos selon le modèle régional canadien du climat.

Les appareils myofonctionnels de correction de la Classe II : l’EMG.

Introduction: La correction de la Classe II avec un appareil myofonctionnel est un traitement commun chez les patients en croissance. Le Twin Block et le correcteur de Classe II fixe (CCF) sont des appareils populaires et plusieurs publications scientifiques ont décrit leurs effets sur les tissus orofaciaux. Plusieurs articles rapportent les changements de l’électromyographie des muscles de la mastication durant le traitement avec un Twin Block, mais peu d’articles ont étudié ces changements avec un CCF. Comme le Twin Block et le CCF ont des biomécaniques différentes, leur influence sur les muscles est possiblement différente. Objectifs: Évaluer les adaptations musculaires suite à un traitement par appareil myofonctionnel : Twin Block et CCF. Matériels et méthodes: Dans une étude cohorte prospective, 24 patients en pic de croissance ont été assignés aléatoirement à un traitement (13 Twin Block; 11 CCF) et l’EMG des muscles masséters et temporaux a été mesurée à 1, 5, 13, 21, 29, 37 semaines. Les muscles ont été mesurés sous trois états: au repos, en occlusion centré (OC) et en contraction volontaire maximal (CVM) Résultats: Les données ont été analysées à l’aide d’un modèle mixte linéaire à mesures répétées et ont été documentées pour chaque muscle selon quatre conditions: i- avec Twin Block en bouche, ii- sans Twin Block en bouche iii- avec CCF en bouche et iv- sans Twin Block comparé au groupe avec CCF. Dans la condition i, des résultats significatifs ont été observés au repos pour le masséter droit et gauche, ainsi que le temporal gauche avec une valeur-p≤0.005. En CVM, la condition i montre aussi des résultats significatifs pour le masséter droit et le temporal gauche avec une valeur-p≤0.05. Les conditions ii et iii ont obtenu des résultats non-significatifs en tout temps. Par contre, lorsque ces deux conditions sont comparées l’une à l’autre (condition iv), des résultats significatifs ont été obtenus en OC pour les temporaux gauche et droit avec une valeur-p=0.005. Conclusions: Avec le Twin Block en bouche, l’EMG augmente au cours du temps en CVM, mais diminue en OC. Par contre, sans le Twin Block en bouche et avec le CCF en bouche, l’EMG ne varie pas. Cependant, le Twin Block et le CCF sont différents au niveau des mesures de l’EMG au cours des neuf mois de traitement. Ceci peut être expliqué par le nivellement graduel de l’occlusion postérieure durant le traitement avec le CCF qui ne se produit pas avec le Twin Block.

3D registration of MR and X-ray spine images using an articulated model.

Présentation: Cet article a été publié dans le journal : Computerised medical imaging and graphics (CMIG). Le but de cet article est de recaler les vertèbres extraites à partir d’images RM avec des vertèbres extraites à partir d’images RX pour des patients scoliotiques, en tenant compte des déformations non-rigides due au changement de posture entre ces deux modalités. À ces fins, une méthode de recalage à l’aide d’un modèle articulé est proposée. Cette méthode a été comparée avec un recalage rigide en calculant l’erreur sur des points de repère, ainsi qu’en calculant la différence entre l’angle de Cobb avant et après recalage. Une validation additionelle de la méthode de recalage présentée ici se trouve dans l’annexe A. Ce travail servira de première étape dans la fusion des images RM, RX et TP du tronc complet. Donc, cet article vérifie l’hypothèse 1 décrite dans la section 3.2.1.

Articulated Model Registration of MRI/X-Ray Spine Data

This paper presents a method based on articulated models for the registration of spine data extracted from multimodal medical images of patients with scoliosis. With the ultimate aim being the development of a complete geometrical model of the torso of a scoliotic patient, this work presents a method for the registration of vertebral column data using 3D magnetic resonance images (MRI) acquired in prone position and X-ray data acquired in standing position for five patients with scoliosis. The 3D shape of the vertebrae is estimated from both image modalities for each patient, and an articulated model is used in order to calculate intervertebral transformations required in order to align the vertebrae between both postures. Euclidean distances between anatomical landmarks are calculated in order to assess multimodal registration error. Results show a decrease in the Euclidean distance using the proposed method compared to rigid registration and more physically realistic vertebrae deformations compared to thin-plate-spline (TPS) registration thus improving alignment.

A Coupled 2 × 2D Babcock–Leighton Solar Dynamo Model. I. Surface Magnetic Flux Evolution

The need for reliable predictions of the solar activity cycle motivates the development of dynamo models incorporating a representation of surface processes sufficiently detailed to allow assimilation of magnetographic data. In this series of papers we present one such dynamo model, and document its behavior and properties. This first paper focuses on one of the model's key components, namely surface magnetic flux evolution. Using a genetic algorithm, we obtain best-fit parameters of the transport model by least-squares minimization of the differences between the associated synthetic synoptic magnetogram and real magnetographic data for activity cycle 21. Our fitting procedure also returns Monte Carlo-like error estimates. We show that the range of acceptable surface meridional flow profiles is in good agreement with Doppler measurements, even though the latter are not used in the fitting process. Using a synthetic database of bipolar magnetic region (BMR) emergences reproducing the statistical properties of observed emergences, we also ascertain the sensitivity of global cycle properties, such as the strength of the dipole moment and timing of polarity reversal, to distinct realizations of BMR emergence, and on this basis argue that this stochasticity represents a primary source of uncertainty for predicting solar cycle characteristics.