Model Probability in Self-organising Maps

Growing models have been widely used for clustering or topology learning. Traditionally these models work on stationary environments, grow incrementally and adapt their nodes to a given distribution based on global parameters. In this paper, we present an enhanced unsupervised self-organising network for the modelling of visual objects. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product.

Probability and Common-Sense: Tandem Towards Robust Robotic Object Recognition in Ambient Assisted Living

The suitable operation of mobile robots when providing Ambient Assisted Living (AAL) services calls for robust object recognition capabilities. Probabilistic Graphical Models (PGMs) have become the de-facto choice in recognition systems aiming to e ciently exploit contextual relations among objects, also dealing with the uncertainty inherent to the robot workspace. However, these models can perform in an inco herent way when operating in a long-term fashion out of the laboratory, e.g. while recognizing objects in peculiar con gurations or belonging to new types. In this work we propose a recognition system that resorts to PGMs and common-sense knowledge, represented in the form of an ontology, to detect those inconsistencies and learn from them. The utilization of the ontology carries additional advantages, e.g. the possibility to verbalize the robot's knowledge. A primary demonstration of the system capabilities has been carried out with very promising results.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

Maleku: A Culture in Danger of Extinction

This paper is about the Maleku, one of the indigenous languages that is still alive in the country; though the linguistic community that uses it, composed of less than 400 people, tends to reduce rapidly. There is a high risk that in the near future this language will disappear. This paper is the result of a research project that proposes the construction and implementation of learning strategies that would help to include the customs, traditions and the native language of the Malekus in the schools, to strengthen the identity and culture of this Costa Rican indigenous population.The research project includes a brief overview of the history and problems of the indigenous Maleku population, and an analysis on the importance of the language and oral expression. It also makes a review of how the indigenous languages in Costa Rican schools are currently taught. It later includes a diagnosis of the current situation of language from the perspective of different members of the Maleku community. This diagnosis is based on the research conducted and it will facilitate focusing on the integration of the Maleku and rural curriculums. Finally, there are some reflections about the bilingual intercultural education.

Relevant Aspects on Teaching Probability and Statistics in Basic General Education

Probability and Statistics were included in the Basic General Education curricula by the Ministry of Public Education (Costa Rica), since 1995. To analyze the teaching reality in these fields, a research was conducted in two educational regions of the country: Heredia and Pérez Zeledón. The survey included university training and updating processes of teachers teaching Statistics and Probability in the schools. The research demonstrated the limited university training in these fields, the dissatisfaction of teachers about it, and the poor support of training institutions to their professional exercise.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Spacecraft Collision Probability Calculation from Conjunction Data Message and High Precision Orbit Propagator

The increasing number of Resident Space Objects (RSOs) is a threat to spaceflight operations. Conjunction Data Messages (CDMs) are sent to satellite operators to warn for possible future collision and their probabilities. The research project described herein pushed forward an algorithm that is able to update the collision probability directly on-board starting from CDMs and the state vector of the hosting satellite which is constantly updated thanks to an onboard GNSS receiver. A large set of methods for computing the collision probability was analyzed in order to find the best ones for this application. The selected algorithm was then tested to assess and improve its performance. Finally, parts of the algorithm and external software were implemented on a Raspberry Pi 3B+ board to demonstrate the compatibility of this approach with computational resources similar to those typically available onboard modern spacecraft.

The Inadequacy Of The Y-axis Of Growth (sngn) For The Vertical Pattern Assessment In Patients With Sagittal Discrepancies.

The aim of this cephalometric study was to evaluate the influence of the sagittal skeletal pattern on the 'Y-axis of growth' measurement in patients with different malocclusions. Lateral head films from 59 patients (mean age 16y 7m, ranging from 11 to 25 years) were selected after a subjective analysis of 1630 cases. Sample was grouped as follows: Group 1 - class I facial pattern; group 2 - class II facial pattern; and Group 3 - class III facial pattern. Two angular measurements, SNGoGn and SNGn, were taken in order to determine skeletal vertical facial pattern. A logistic regression with errors distributed according to a binomial distribution was used to test the influence of the sagittal relationship (Class I, II, III facial patterns) on vertical diagnostic measurement congruence (SNGoGn and SNGn). RESULTS show that the probability of congruence between the patterns SNGn and SNGoGn was relatively high (70%) for group 1, but for groups II (46%) and III (37%) this congruence was relatively low. The use of SNGn appears to be inappropriate to determine the vertical facial skeletal pattern of patients, due to Gn point shifting throughout sagittal discrepancies. Clinical Significance: Facial pattern determined by SNGn must be considered carefully, especially when severe sagittal discrepancies are present.

Rapidly Switching Multidirectional Defibrillation: Reversal Of Ventricular Fibrillation With Lower Energy Shocks.

Cardiac arrest after open surgery has an incidence of approximately 3%, of which more than 50% of the cases are due to ventricular fibrillation. Electrical defibrillation is the most effective therapy for terminating cardiac arrhythmias associated with unstable hemodynamics. The excitation threshold of myocardial microstructures is lower when external electrical fields are applied in the longitudinal direction with respect to the major axis of cells. However, in the heart, cell bundles are disposed in several directions. Improved myocardial excitation and defibrillation have been achieved by applying shocks in multiple directions via intracardiac leads, but the results are controversial when the electrodes are not located within the cardiac chambers. This study was designed to test whether rapidly switching shock delivery in 3 directions could increase the efficiency of direct defibrillation. A multidirectional defibrillator and paddles bearing 3 electrodes each were developed and used in vivo for the reversal of electrically induced ventricular fibrillation in an anesthetized open-chest swine model. Direct defibrillation was performed by unidirectional and multidirectional shocks applied in an alternating fashion. Survival analysis was used to estimate the relationship between the probability of defibrillation and the shock energy. Compared with shock delivery in a single direction in the same animal population, the shock energy required for multidirectional defibrillation was 20% to 30% lower (P < .05) within a wide range of success probabilities. Rapidly switching multidirectional shock delivery required lower shock energy for ventricular fibrillation termination and may be a safer alternative for restoring cardiac sinus rhythm.

Fauna In Decline: Meek Shall Inherit.

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Experiences From The Brazilian Atlantic Forest: Ecological Findings And Conservation Initiatives.

The Brazilian Atlantic Forest hosts one of the world's most diverse and threatened tropical forest biota. In many ways, its history of degradation describes the fate experienced by tropical forests around the world. After five centuries of human expansion, most Atlantic Forest landscapes are archipelagos of small forest fragments surrounded by open-habitat matrices. This 'natural laboratory' has contributed to a better understanding of the evolutionary history and ecology of tropical forests and to determining the extent to which this irreplaceable biota is susceptible to major human disturbances. We share some of the major findings with respect to the responses of tropical forests to human disturbances across multiple biological levels and spatial scales and discuss some of the conservation initiatives adopted in the past decade. First, we provide a short description of the Atlantic Forest biota and its historical degradation. Secondly, we offer conceptual models describing major shifts experienced by tree assemblages at local scales and discuss landscape ecological processes that can help to maintain this biota at larger scales. We also examine potential plant responses to climate change. Finally, we propose a research agenda to improve the conservation value of human-modified landscapes and safeguard the biological heritage of tropical forests.

Dietary Supplement Usage And Motivation In Brazilian Road Runners.

The consumption of dietary supplements is highest among athletes and it can represent potential a health risk for consumers. The aim of this study was to determine the prevalence of consumption of dietary supplements by road runners. We interviewed 817 volunteers from four road races in the Brazilian running calendar. The sample consisted of 671 male and 146 female runners with a mean age of 37.9 ± 12.4 years. Of the sample, 28.33% reported having used some type of dietary supplement. The main motivation for this consumption is to increase in stamina and improve performance. The probability of consuming dietary supplements increased 4.67 times when the runners were guided by coaches. The consumption of supplements was strongly correlated (r = 0.97) with weekly running distance, and also highly correlated (r = 0.86) with the number of years the sport had been practiced. The longer the runner had practiced the sport, the higher the training volume and the greater the intake of supplements. The five most frequently cited reasons for consumption were: energy enhancement (29.5%), performance improvement (17.1%), increased level of endurance (10.3%), nutrient replacement (11.1%), and avoidance of fatigue (10.3%). About 30% of the consumers declared more than one reason for taking dietary supplements. The most consumed supplements were: carbohydrates (52.17%), vitamins (28.70%), and proteins (13.48%). Supplement consumption by road runners in Brazil appeared to be guided by the energy boosting properties of the supplement, the influence of coaches, and the experience of the user. The amount of supplement intake seemed to be lower among road runners than for athletes of other sports. We recommend that coaches and nutritionists emphasise that a balanced diet can meet the needs of physically active people.

Changes In Motor Behavior During Pregnancy In Rats: The Basis For A Possible Animal Model Of Restless Legs Syndrome.

Pregnant women have a 2-3 fold higher probability of developing restless legs syndrome (RLS - sleep-related movement disorders) than general population. This study aims to evaluate the behavior and locomotion of rats during pregnancy in order to verify if part of these animals exhibit some RLS-like features. We used 14 female 80-day-old Wistar rats that weighed between 200 and 250 g. The rats were distributed into control (CTRL) and pregnant (PN) groups. After a baseline evaluation of their behavior and locomotor activity in an open-field environment, the PN group was inducted into pregnancy, and their behavior and locomotor activity were evaluated on days 3, 10 and 19 of pregnancy and in the post-lactation period in parallel with the CTRL group. The serum iron and transferrin levels in the CTRL and PN groups were analyzed in blood collected after euthanasia by decapitation. There were no significant differences in the total ambulation, grooming events, fecal boli or urine pools between the CTRL and PN groups. However, the PN group exhibited fewer rearing events, increased grooming time and reduced immobilization time than the CTRL group (ANOVA, p<0.05). These results suggest that pregnant rats show behavioral and locomotor alterations similar to those observed in animal models of RLS, demonstrating to be a possible animal model of this sleep disorder.

In Vivo Determination Of The Volatile Metabolites Of Saprotroph Fungi By Comprehensive Two-dimensional Gas Chromatography.

In this work, we discuss the use of multi-way principal component analysis combined with comprehensive two-dimensional gas chromatography to study the volatile metabolites of the saprophytic fungus Memnoniella sp. isolated in vivo by headspace solid-phase microextraction. This fungus has been identified as having the ability to induce plant resistance against pathogens, possibly through its volatile metabolites. Adequate culture media was inoculated, and its headspace was then sampled with a solid-phase microextraction fiber and chromatographed every 24 h over seven days. The raw chromatogram processing using multi-way principal component analysis allowed the determination of the inoculation period, during which the concentration of volatile metabolites was maximized, as well as the discrimination of the appropriate peaks from the complex culture media background. Several volatile metabolites not previously described in the literature on biocontrol fungi were observed, as well as sesquiterpenes and aliphatic alcohols. These results stress that, due to the complexity of multidimensional chromatographic data, multivariate tools might be mandatory even for apparently trivial tasks, such as the determination of the temporal profile of metabolite production and extinction. However, when compared with conventional gas chromatography, the complex data processing yields a considerable improvement in the information obtained from the samples. This article is protected by copyright. All rights reserved.

Neurological evaluation of neonates with intraventricular and periventricular hemorrhage

We studied the clinical aspects of 100 consecutive premature newborns with and without intraventricular and periventricular hemorrhage (IPVH).The diagnosis of IPVH was obtained by ultrasonic scans of the skull during the first week of life and at the age of one month. Forty eight percent of newborns with IPVH had abnormal results, and there was a significant correlation with the neurological evaluation in 85% of the infants. The probability of normality for a child with no associated brain abnormalities was 72%, whereas for a child of the same gestational age with associated brain abnormalities was 48.7%.