A fixed-links modeling approach to assess individual differences in the attentional blink: Analysis of behavioral and psychophysiological data

The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.

Psychological therapies for panic disorder with or without agoraphobia in adults: a network meta-analysis.

BACKGROUND Panic disorder is characterised by the presence of recurrent unexpected panic attacks, discrete periods of fear or anxiety that have a rapid onset and include symptoms such as racing heart, chest pain, sweating and shaking. Panic disorder is common in the general population, with a lifetime prevalence of 1% to 4%. A previous Cochrane meta-analysis suggested that psychological therapy (either alone or combined with pharmacotherapy) can be chosen as a first-line treatment for panic disorder with or without agoraphobia. However, it is not yet clear whether certain psychological therapies can be considered superior to others. In order to answer this question, in this review we performed a network meta-analysis (NMA), in which we compared eight different forms of psychological therapy and three forms of a control condition. OBJECTIVES To assess the comparative efficacy and acceptability of different psychological therapies and different control conditions for panic disorder, with or without agoraphobia, in adults. SEARCH METHODS We conducted the main searches in the CCDANCTR electronic databases (studies and references registers), all years to 16 March 2015. We conducted complementary searches in PubMed and trials registries. Supplementary searches included reference lists of included studies, citation indexes, personal communication to the authors of all included studies and grey literature searches in OpenSIGLE. We applied no restrictions on date, language or publication status. SELECTION CRITERIA We included all relevant randomised controlled trials (RCTs) focusing on adults with a formal diagnosis of panic disorder with or without agoraphobia. We considered the following psychological therapies: psychoeducation (PE), supportive psychotherapy (SP), physiological therapies (PT), behaviour therapy (BT), cognitive therapy (CT), cognitive behaviour therapy (CBT), third-wave CBT (3W) and psychodynamic therapies (PD). We included both individual and group formats. Therapies had to be administered face-to-face. The comparator interventions considered for this review were: no treatment (NT), wait list (WL) and attention/psychological placebo (APP). For this review we considered four short-term (ST) outcomes (ST-remission, ST-response, ST-dropouts, ST-improvement on a continuous scale) and one long-term (LT) outcome (LT-remission/response). DATA COLLECTION AND ANALYSIS As a first step, we conducted a systematic search of all relevant papers according to the inclusion criteria. For each outcome, we then constructed a treatment network in order to clarify the extent to which each type of therapy and each comparison had been investigated in the available literature. Then, for each available comparison, we conducted a random-effects meta-analysis. Subsequently, we performed a network meta-analysis in order to synthesise the available direct evidence with indirect evidence, and to obtain an overall effect size estimate for each possible pair of therapies in the network. Finally, we calculated a probabilistic ranking of the different psychological therapies and control conditions for each outcome. MAIN RESULTS We identified 1432 references; after screening, we included 60 studies in the final qualitative analyses. Among these, 54 (including 3021 patients) were also included in the quantitative analyses. With respect to the analyses for the first of our primary outcomes, (short-term remission), the most studied of the included psychological therapies was CBT (32 studies), followed by BT (12 studies), PT (10 studies), CT (three studies), SP (three studies) and PD (two studies).The quality of the evidence for the entire network was found to be low for all outcomes. The quality of the evidence for CBT vs NT, CBT vs SP and CBT vs PD was low to very low, depending on the outcome. The majority of the included studies were at unclear risk of bias with regard to the randomisation process. We found almost half of the included studies to be at high risk of attrition bias and detection bias. We also found selective outcome reporting bias to be present and we strongly suspected publication bias. Finally, we found almost half of the included studies to be at high risk of researcher allegiance bias.Overall the networks appeared to be well connected, but were generally underpowered to detect any important disagreement between direct and indirect evidence. The results showed the superiority of psychological therapies over the WL condition, although this finding was amplified by evident small study effects (SSE). The NMAs for ST-remission, ST-response and ST-improvement on a continuous scale showed well-replicated evidence in favour of CBT, as well as some sparse but relevant evidence in favour of PD and SP, over other therapies. In terms of ST-dropouts, PD and 3W showed better tolerability over other psychological therapies in the short term. In the long term, CBT and PD showed the highest level of remission/response, suggesting that the effects of these two treatments may be more stable with respect to other psychological therapies. However, all the mentioned differences among active treatments must be interpreted while taking into account that in most cases the effect sizes were small and/or results were imprecise. AUTHORS' CONCLUSIONS There is no high-quality, unequivocal evidence to support one psychological therapy over the others for the treatment of panic disorder with or without agoraphobia in adults. However, the results show that CBT - the most extensively studied among the included psychological therapies - was often superior to other therapies, although the effect size was small and the level of precision was often insufficient or clinically irrelevant. In the only two studies available that explored PD, this treatment showed promising results, although further research is needed in order to better explore the relative efficacy of PD with respect to CBT. Furthermore, PD appeared to be the best tolerated (in terms of ST-dropouts) among psychological treatments. Unexpectedly, we found some evidence in support of the possible viability of non-specific supportive psychotherapy for the treatment of panic disorder; however, the results concerning SP should be interpreted cautiously because of the sparsity of evidence regarding this treatment and, as in the case of PD, further research is needed to explore this issue. Behaviour therapy did not appear to be a valid alternative to CBT as a first-line treatment for patients with panic disorder with or without agoraphobia.

Revealing Assembly of a Pore-Forming Complex Using Single-Cell Kinetic Analysis and Modeling

Many biological processes depend on the sequential assembly of protein complexes. However, studying the kinetics of such processes by direct methods is often not feasible. As an important class of such protein complexes, pore-forming toxins start their journey as soluble monomeric proteins, and oligomerize into transmembrane complexes to eventually form pores in the target cell membrane. Here, we monitored pore formation kinetics for the well-characterized bacterial pore-forming toxin aerolysin in single cells in real time to determine the lag times leading to the formation of the first functional pores per cell. Probabilistic modeling of these lag times revealed that one slow and seven equally fast rate-limiting reactions best explain the overall pore formation kinetics. The model predicted that monomer activation is the rate-limiting step for the entire pore formation process. We hypothesized that this could be through release of a propeptide and indeed found that peptide removal abolished these steps. This study illustrates how stochasticity in the kinetics of a complex process can be exploited to identify rate-limiting mechanisms underlying multistep biomolecular assembly pathways.

Analysis of the Phosphorylated Forms of Protein Kinase R

Protein Kinase R (PKR) is induced by interferon and activated by dsRNA. Subsequent autophosphorylation and phosphorylation of eIF2alpha inhibits viral replication. In the latent state PKR exists as an unphosphorylated monomer. Work in the Cole laboratory has shown two additional states, a phosphorylated monomeric state (pPKRm) and a phosphorylated dimeric state (pPKRd). RNA serves as a scaffold bringing two PKRs together allowing dimerization and autophosphorylation to occur. The contribution of each state to the function of PKR remains unclear. Western blots were performed to examine the phosphorylation states of the essential residues, T446 and T451. Activity assays have shown activation of pPKRm at a level comparable to pPKRd in its ability to phosphorylate eIF2alpha. Phosphorylation of eIF2alpha by both pPKRm and pPKRd was shown to be RNA independent. Despite reaching similar terminal levels of eIF2alpha phosphorylation, kinetic measurements revealed a faster reaction from pPKRd. Therefore, pPKRm and pPKRd may both contribute to the activity of PKR.

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD

Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment. This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research. On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text. This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

La apoteosis en las Metamorfosis de Ovidio : Función estructural y valor semántico

El objeto de este trabajo ha sido estudiar el motivo de la apoteosis con el fin de descubrir de qué manera se integra positivamente en la representación de las Metamorfosis. Se intenta trascender interpretaciones denigratorias o irónicas del motivo. El estudio consta de dos partes. En el primer capítulo de la primera parte, "La apoteosis en la estructura de las Metamorfosis", se demuestra con un análisis intratextual la importancia que tiene el relato de la creación del hombre como sanctius animal, considerada paradigmática, en el estudio del motivo de la apoteosis. El segundo capítulo insiste en la dimensión intertextual, recordando la influencia estructural de dos modelos poéticos de las Metamorfosis de Ovidio, Hesíodo y la Égloga 6 de Virgilio, para una representación que comienza en la creación del hombre y termina en la apoteosis del poeta. La introducción a la segunda parte, "Valor semántico de la apoteosis", pone el acento en tres aspectos esenciales para el estudio de la apoteosis. En primer lugar, la idea de "lectura", i.e., la trascendencia latente del motivo de la apoteosis y de la idea de estirpe a lo largo de la obra. Se propone, en segundo lugar, el concepto de "mitologización" como una forma de examinar la apropiación que hace el poeta del mito historizado y del mito con alusión augustea. Esa apropiación tendrá como fin destacar el aspecto literatio de las historias y ejercerá un papel fundamental en la construcción de una gfigura de poeta que, mediante la apoteosis por su obra, se eleva por sobre las figuras de filósofo y de político. Su tratamiento en este trabajo, pues, se debe al hecho de que está ligado, en último término, con el motivo de la apoteosis. Dado que el estudio tiene como punto de partida la relación entre el sanctius animal, paradigma de la creación del hombre, y la apoteosis, se ha elegido examinar detalladamente aquellas apoteosis en que aparece una alusión explícita a la parte mortal o a la parte inmortal, i.e., las de Ino y Melicertes, Hércules, Eneas, Glauco, Rómulo, Hersilia, César, Augusto y Ovidio. Se incluyen, de todas maneras, otras referencias y apoteosis relevantes. La alusión a la imagen de la pars, siguiendo una de las denominaciones con más trascendencia formal en la obra, remite a la creación del hombre divino semine y a partir de semina caeli, aspecto que se estudia en el primer capítulo de la primera parte y se retoma en el análisis de cada apoteosis. La conclusión del trabajo es que el motivo de la apoteosis sólo puede inteligirse a la luz del final, en el que se representa la apoteosis del poeta. Al margen de la mitologización que opera en las historias con valor histórico y augusteo, Ovidio se ha preocupado por mantener, aunque sólo sea en forma referencial, el sentido de las apoteosis con el fin de desplegar toda su significación en la apoteosis final. Inversamente, el valor completo del motivo en el cierre de la obra exige aceptar su significación a lo largo de la obra. En el final, el poeta, un poeta Romanus en la medida en que su obra será leída donde se extienda la Romana potentia, se revela como el auténtico sanctius animal referido en la creación.

La apoteosis en las Metamorfosis de Ovidio : Función estructural y valor semántico

El objeto de este trabajo ha sido estudiar el motivo de la apoteosis con el fin de descubrir de qué manera se integra positivamente en la representación de las Metamorfosis. Se intenta trascender interpretaciones denigratorias o irónicas del motivo. El estudio consta de dos partes. En el primer capítulo de la primera parte, "La apoteosis en la estructura de las Metamorfosis", se demuestra con un análisis intratextual la importancia que tiene el relato de la creación del hombre como sanctius animal, considerada paradigmática, en el estudio del motivo de la apoteosis. El segundo capítulo insiste en la dimensión intertextual, recordando la influencia estructural de dos modelos poéticos de las Metamorfosis de Ovidio, Hesíodo y la Égloga 6 de Virgilio, para una representación que comienza en la creación del hombre y termina en la apoteosis del poeta. La introducción a la segunda parte, "Valor semántico de la apoteosis", pone el acento en tres aspectos esenciales para el estudio de la apoteosis. En primer lugar, la idea de "lectura", i.e., la trascendencia latente del motivo de la apoteosis y de la idea de estirpe a lo largo de la obra. Se propone, en segundo lugar, el concepto de "mitologización" como una forma de examinar la apropiación que hace el poeta del mito historizado y del mito con alusión augustea. Esa apropiación tendrá como fin destacar el aspecto literatio de las historias y ejercerá un papel fundamental en la construcción de una gfigura de poeta que, mediante la apoteosis por su obra, se eleva por sobre las figuras de filósofo y de político. Su tratamiento en este trabajo, pues, se debe al hecho de que está ligado, en último término, con el motivo de la apoteosis. Dado que el estudio tiene como punto de partida la relación entre el sanctius animal, paradigma de la creación del hombre, y la apoteosis, se ha elegido examinar detalladamente aquellas apoteosis en que aparece una alusión explícita a la parte mortal o a la parte inmortal, i.e., las de Ino y Melicertes, Hércules, Eneas, Glauco, Rómulo, Hersilia, César, Augusto y Ovidio. Se incluyen, de todas maneras, otras referencias y apoteosis relevantes. La alusión a la imagen de la pars, siguiendo una de las denominaciones con más trascendencia formal en la obra, remite a la creación del hombre divino semine y a partir de semina caeli, aspecto que se estudia en el primer capítulo de la primera parte y se retoma en el análisis de cada apoteosis. La conclusión del trabajo es que el motivo de la apoteosis sólo puede inteligirse a la luz del final, en el que se representa la apoteosis del poeta. Al margen de la mitologización que opera en las historias con valor histórico y augusteo, Ovidio se ha preocupado por mantener, aunque sólo sea en forma referencial, el sentido de las apoteosis con el fin de desplegar toda su significación en la apoteosis final. Inversamente, el valor completo del motivo en el cierre de la obra exige aceptar su significación a lo largo de la obra. En el final, el poeta, un poeta Romanus en la medida en que su obra será leída donde se extienda la Romana potentia, se revela como el auténtico sanctius animal referido en la creación.

La apoteosis en las Metamorfosis de Ovidio : Función estructural y valor semántico

El objeto de este trabajo ha sido estudiar el motivo de la apoteosis con el fin de descubrir de qué manera se integra positivamente en la representación de las Metamorfosis. Se intenta trascender interpretaciones denigratorias o irónicas del motivo. El estudio consta de dos partes. En el primer capítulo de la primera parte, "La apoteosis en la estructura de las Metamorfosis", se demuestra con un análisis intratextual la importancia que tiene el relato de la creación del hombre como sanctius animal, considerada paradigmática, en el estudio del motivo de la apoteosis. El segundo capítulo insiste en la dimensión intertextual, recordando la influencia estructural de dos modelos poéticos de las Metamorfosis de Ovidio, Hesíodo y la Égloga 6 de Virgilio, para una representación que comienza en la creación del hombre y termina en la apoteosis del poeta. La introducción a la segunda parte, "Valor semántico de la apoteosis", pone el acento en tres aspectos esenciales para el estudio de la apoteosis. En primer lugar, la idea de "lectura", i.e., la trascendencia latente del motivo de la apoteosis y de la idea de estirpe a lo largo de la obra. Se propone, en segundo lugar, el concepto de "mitologización" como una forma de examinar la apropiación que hace el poeta del mito historizado y del mito con alusión augustea. Esa apropiación tendrá como fin destacar el aspecto literatio de las historias y ejercerá un papel fundamental en la construcción de una gfigura de poeta que, mediante la apoteosis por su obra, se eleva por sobre las figuras de filósofo y de político. Su tratamiento en este trabajo, pues, se debe al hecho de que está ligado, en último término, con el motivo de la apoteosis. Dado que el estudio tiene como punto de partida la relación entre el sanctius animal, paradigma de la creación del hombre, y la apoteosis, se ha elegido examinar detalladamente aquellas apoteosis en que aparece una alusión explícita a la parte mortal o a la parte inmortal, i.e., las de Ino y Melicertes, Hércules, Eneas, Glauco, Rómulo, Hersilia, César, Augusto y Ovidio. Se incluyen, de todas maneras, otras referencias y apoteosis relevantes. La alusión a la imagen de la pars, siguiendo una de las denominaciones con más trascendencia formal en la obra, remite a la creación del hombre divino semine y a partir de semina caeli, aspecto que se estudia en el primer capítulo de la primera parte y se retoma en el análisis de cada apoteosis. La conclusión del trabajo es que el motivo de la apoteosis sólo puede inteligirse a la luz del final, en el que se representa la apoteosis del poeta. Al margen de la mitologización que opera en las historias con valor histórico y augusteo, Ovidio se ha preocupado por mantener, aunque sólo sea en forma referencial, el sentido de las apoteosis con el fin de desplegar toda su significación en la apoteosis final. Inversamente, el valor completo del motivo en el cierre de la obra exige aceptar su significación a lo largo de la obra. En el final, el poeta, un poeta Romanus en la medida en que su obra será leída donde se extienda la Romana potentia, se revela como el auténtico sanctius animal referido en la creación.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Proposal for the Management of temporal and semantic components of Geographic Information

This poster raises the issue of a research work oriented to the storage, retrieval, representation and analysis of dynamic GI, taking into account The ultimate objective is the modelling and representation of the dynamic nature of geographic features, establishing mechanisms to store geometries enriched with a temporal structure (regardless of space) and a set of semantic descriptors detailing and clarifying the nature of the represented features and their temporality. the semantic, the temporal and the spatiotemporal components. We intend to define a set of methods, rules and restrictions for the adequate integration of these components into the primary elements of the GI: theme, location, time [1]. We intend to establish and incorporate three new structures (layers) into the core of data storage by using mark-up languages: a semantictemporal structure, a geosemantic structure, and an incremental spatiotemporal structure. Thus, data would be provided with the capability of pinpointing and expressing their own basic and temporal characteristics, enabling them to interact each other according to their context, and their time and meaning relationships that could be eventually established

The state of semantic technology today - overview of the first SEALS evaluation campaigns

This paper describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning tools, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions.

Two Novel Methods For The Determination Of The Number Of Components In Independent Components Analysis Models

Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance.