Multivariate analysis of the temporal variability of sugarcane ripening in south-eastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Why is it so difficult to identify a single indicator of water stress in plants? A proposal for a multivariate analysis to assess emergent properties

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

Stabilometric parameters analysis in children with visual disorder

Background: Although postural changes were already reported in blind adults, no previous study has investigated postural stability in blind children. Moreover, there are few studies which used a stabilometric instrument to measure postural balance. In this study we evaluated stabilometric paramaters in blind children. Methods: We evaluated children between 7 to 12 years old, they were divided into two groups: Blind (n = 11) and age-matched control (n = 11) groups by using computerized stabilometry. The stabilometric examination was performed taking the gravity centers displacement of the individual projected into the platform. Thirthy seconds after the period in which this information was collected, the program defined a medium-pressure center, which was used to define x and y axes displacement and the distance between the pressure center and the platform center. Furthermore, the average sway rate and the body sway area were obtained by dividing the pressure center displacement and the time spent on the task; and by an ellipse function (95% percentille), respectively. Percentages of anterior, posterior, left and right feet weight also were calculated. Variables were compared by using the Student’s t test for unpaired data. Significance level was considered for p <0.05. Results: Displacement of the x axis (25.55 ± 9.851 vs. -3.545 ± 7.667; p <0.05) and average sway rate (19.18 ± 2.7 vs. -10.55 ± 1.003; p <0.001) were increased in the blind children group. Percentage of left foot weight was reduced (45.82 ± 2.017 vs. 52.36 ± 1.33; p <0.05) while percentage of right foot weight was increased (54.18 ± 2.17 vs. 47.64 ± 1.33; p <0.05) in blind children. Other variables did not show differences. Conclusions: Blind children present impaired stabilometric parameters.

ITScan: a web-based analysis tool for Internal Transcribed Spacer (ITS) sequences

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

On Modular Design of Field Robotic Systems

Robots are needed to perform important field tasks such as hazardous material clean-up, nuclear site inspection, and space exploration. Unfortunately their use is not widespread due to their long development times and high costs. To make them practical, a modular design approach is proposed. Prefabricated modules are rapidly assembled to give a low-cost system for a specific task. This paper described the modular design problem for field robots and the application of a hierarchical selection process to solve this problem. Theoretical analysis and an example case study are presented. The theoretical analysis of the modular design problem revealed the large size of the search space. It showed the advantages of approaching the design on various levels. The hierarchical selection process applies physical rules to reduce the search space to a computationally feasible size and a genetic algorithm performs the final search in a greatly reduced space. This process is based on the observation that simple physically based rules can eliminate large sections of the design space to greatly simplify the search. The design process is applied to a duct inspection task. Five candidate robots were developed. Two of these robots are evaluated using detailed physical simulation. It is shown that the more obvious solution is not able to complete the task, while the non-obvious asymmetric design develop by the process is successful.

DESIGN AND ANALYSIS OF MULTIFUNCTIONAL ROBOT FOR NOTES

The elimination of all external incisions is an important step in reducing the invasiveness of surgical procedures. Natural Orifice Translumenal Endoscopic Surgery (NOTES) is an incision-less surgery and provides explicit benefits such as reducing patient trauma and shortening recovery time. However, technological difficulties impede the widespread utilization of the NOTES method. A novel robotic tool has been developed, which makes NOTES procedures feasible by using multiple interchangeable tool tips. The robotic tool has the capability of entering the body cavity through an orifice or a single incision using a flexible articulated positioning mechanism and once inserted is not constrained by incisions, allowing for visualization and manipulations throughout the cavity. Multiple interchangeable tool tips of the robotic device initially consist of three end effectors: a grasper, scissors, and an atraumatic Babcock clamp. The tool changer is capable of selecting and switching between the three tools depending on the surgical task using a miniature mechanism driven by micro-motors. The robotic tool is remotely controlled through a joystick and computer interface. In this thesis, the following aspects of this robotic tool will be detailed. The first-generation robot is designed as a conceptual model for implementing a novel mechanism of switching, advancing, and controlling the tool tips using two micro-motors. It is believed that this mechanism achieves a reduction in cumbersome instrument exchanges and can reduce overall procedure time and the risk of inadvertent tissue trauma during exchanges with a natural orifice approach. Also, placing actuators directly at the surgical site enables the robot to generate sufficient force to operate effectively. Mounting the multifunctional robot on the distal end of an articulating tube provides freedom from restriction on the robot kinematics and helps solve some of the difficulties otherwise faced during surgery using NOTES or related approaches. The second-generation multifunctional robot is then introduced in which the overall size is reduced and two arms provide 2 additional degrees of freedom, resulting in feasibility of insertion through the esophagus and increased dexterity. Improvements are necessary in future iterations of the multifunctional robot; however, the work presented is a proof of concept for NOTES robots capable of abdominal surgical interventions.

Psychophysical analysis of contrast processing segregated into magnocellular and parvocellular systems in asymptomatic carriers of 11778 Leber`s hereditary optic neuropathy

We examined achromatic contrast discrimination in asymptomatic carriers of 11778 Leber`s hereditary optic neuropathy (LHON 18 controls) and 18 age-match were also tested. To evaluate magnocellular (MC) and Parvocellular (PC) contrast discrimination, we used a version of Pokorny and Smith`s (1997) Pulsed/steady-pedestal paradigms (PPP/SPP) thought to be detected via PC and MC pathways, respectively. A luminance pedestal (four 1 degrees x 1 degrees squares) was presented on a 12 cd/m(2) surround. The luminance of one of the squares (trial square, TS) was randomly incremented for either 17 or 133 ms. Observers had to detect the TS, in a forced-choice task, at each duration, for three pedestal levels: 7, 12, 19 cd/m(2). In the SPP, the pedestal was fixed, and the TS was modulated. For the PPP, all four pedestal squares pulsed for 17 or 133 ms, and the TS was simultaneously incremented or decremented. We found that contrast discrimination thresholds of LHON carriers were significantly higher than controls` in the condition with the highest luminance of both paradigms, implying impaired contrast processing with no evidence of differential sensitivity losses between the two systems. Carriers` thresholds manifested significantly longer temporal integration than controls in the SPP, consistent with slowed MC responses. The SPP and PPP paradigms can identify contrast and temporal processing deficits in asymptomatic LHON carriers, and thus provide an additional tool for early detection and characterization of the disease.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Detecting an abnormality in a recovery boiler using dynamic multivariate data analysis with parallel coordinate plots

Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

Use of Demonstrably Effective Therapies in the Treatment of Acute Coronary Syndromes: Comparison between Different Brazilian Regions. Analysis of the Brazilian Registry on Acute Coronary Syndromes (BRACE)

Background: Little is known in our country about regional differences in the treatment of acute coronary disease. Objective: To analyze the behavior regarding the use of demonstrably effective regional therapies in acute coronary disease. Methods: A total of 71 hospitals were randomly selected, respecting the proportionality of the country in relation to geographic location, among other criteria. In the overall population was regionally analyzed the use of aspirin, clopidogrel, ACE inhibitors / AT1 blocker, beta-blockers and statins, separately and grouped by individual score ranging from 0 (no drug used) to 100 (all drugs used). In myocardial infarction with ST elevation (STEMI) regional differences were analyzed regarding the use of therapeutic recanalization (fibrinolytics and primary angioplasty). Results: In the overall population, within the first 24 hours of hospitalization, the mean score in the North-Northeast (70.5 +/- 22.1) was lower (p < 0.05) than in the Southeast (77.7 +/- 29.5), Midwest (82 +/- 22.1) and South (82.4 +/- 21) regions. At hospital discharge, the score of the North-Northeast region (61.4 +/- 32.9) was lower (p < 0.05) than in the Southeast (69.2 +/- 31.6), Midwest (65.3 +/- 33.6) and South (73.7 +/- 28.1) regions; additionally, the score of the Midwest was lower (p < 0.05) than the South region. In STEMI, the use of recanalization therapies was highest in the Southeast (75.4%, p = 0.001 compared to the rest of the country), and lowest in the North-Northeast (52.5%, p < 0.001 compared to the rest of the country). Conclusion: The use of demonstrably effective therapies in the treatment of acute coronary disease is much to be desired in the country, with important regional differences.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Analysis of kinematic, kinetic and electromyographic patterns during root canal preparation with rotary and manual instruments

Objective: This study assessed the muscular activity during root canal preparation through kinematics, kinetics, and electromyography (EMG). Material and Methods: The operators prepared one canal with RaCe rotary instruments and another with Flexofiles. The kinematics of the major joints was reconstructed using an optoelectronic system and electromyographic responses of the flexor carpi radial's, extensor carpi radialis, brachioradialis, biceps brachii, triceps brachii, middle deltoid, and upper trapezius were recorded. The joint torques of the shoulder, elbow and wrist were calculated using inverse dynamics. In the kinematic analysis, angular movements of the wrist and elbow were classified as low risk factors for work-related musculoskeletal disorders. With respect to the shoulder, the classification was medium-risk. Results: There was no significant difference revealed by the kinetic reports. The EMG results showed that for the middle deltoid and upper trapezius the rotary instrumentation elicited higher values. The flexor carpi radialis and extensor carpi radialis, as well as the brachioradialis showed a higher value with the manual method. Conclusion: The muscular recruitment for accomplishment of articular movements for root canal preparation with either the rotary or manual techniques is distinct. Nevertheless, the rotary instrument presented less difficulty in the generation of the joint torque in each articulation, thus, presenting a greater uniformity of joint torques.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Functional coupling of sensorimotor and associative areas during a catching ball task: a qEEG coherence study

Abstract Background Catching an object is a complex movement that involves not only programming but also effective motor coordination. Such behavior is related to the activation and recruitment of cortical regions that participates in the sensorimotor integration process. This study aimed to elucidate the cortical mechanisms involved in anticipatory actions when performing a task of catching an object in free fall. Methods Quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 20 healthy right-handed participants performed the catching ball task. We used the EEG coherence analysis to investigate subdivisions of alpha (8-12 Hz) and beta (12-30 Hz) bands, which are related to cognitive processing and sensory-motor integration. Results Notwithstanding, we found the main effects for the factor block; for alpha-1, coherence decreased from the first to sixth block, and the opposite effect occurred for alpha-2 and beta-2, with coherence increasing along the blocks. Conclusion It was concluded that to perform successfully our task, which involved anticipatory processes (i.e. feedback mechanisms), subjects exhibited a great involvement of sensory-motor and associative areas, possibly due to organization of information to process visuospatial parameters and further catch the falling object.