Clustering of variables with a three-way approach for health sciences

© 2014 Cises This work is distributed with License Creative Commons Attribution-Non commercial-No derivatives 4.0 International (CC BY-BC-ND 4.0)

Mission and Scenario Planning for Unmanned Aerial Vehicles (Path Planning and Collision Avoidance Systems)

As unmanned autonomous vehicles (UAVs) are being widely utilized in military and civil applications, concerns are growing about mission safety and how to integrate dierent phases of mission design. One important barrier to a coste ective and timely safety certication process for UAVs is the lack of a systematic approach for bridging the gap between understanding high-level commander/pilot intent and implementation of intent through low-level UAV behaviors. In this thesis we demonstrate an entire systems design process for a representative UAV mission, beginning from an operational concept and requirements and ending with a simulation framework for segments of the mission design, such as path planning and decision making in collision avoidance. In this thesis, we divided this complex system into sub-systems; path planning, collision detection and collision avoidance. We then developed software modules for each sub-system

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

Mathematical models for cellular aggregation: the chemotactic instability and clustering formation

In this thesis we present a mathematical formulation of the interaction between microorganisms such as bacteria or amoebae and chemicals, often produced by the organisms themselves. This interaction is called chemotaxis and leads to cellular aggregation. We derive some models to describe chemotaxis. The first is the pioneristic Keller-Segel parabolic-parabolic model and it is derived by two different frameworks: a macroscopic perspective and a microscopic perspective, in which we start with a stochastic differential equation and we perform a mean-field approximation. This parabolic model may be generalized by the introduction of a degenerate diffusion parameter, which depends on the density itself via a power law. Then we derive a model for chemotaxis based on Cattaneo's law of heat propagation with finite speed, which is a hyperbolic model. The last model proposed here is a hydrodynamic model, which takes into account the inertia of the system by a friction force. In the limit of strong friction, the model reduces to the parabolic model, whereas in the limit of weak friction, we recover a hyperbolic model. Finally, we analyze the instability condition, which is the condition that leads to aggregation, and we describe the different kinds of aggregates we may obtain: the parabolic models lead to clusters or peaks whereas the hyperbolic models lead to the formation of network patterns or filaments. Moreover, we discuss the analogy between bacterial colonies and self gravitating systems by comparing the chemotactic collapse and the gravitational collapse (Jeans instability).

Clustering of tau-immunoreactive pathology in chronic traumatic encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disorder which may result from repetitive brain injury. A variety of tau-immunoreactive pathologies are present, including neurofibrillary tangles (NFT), neuropil threads (NT), dot-like grains (DLG), astrocytic tangles (AT), and occasional neuritic plaques (NP). In tauopathies, cellular inclusions in the cortex are clustered within specific laminae, the clusters being regularly distributed parallel to the pia mater. To determine whether a similar spatial pattern is present in CTE, clustering of the tau-immunoreactive pathology was studied in the cortex, hippocampus, and dentate gyrus in 11 cases of CTE and 7 cases of Alzheimer’s disease neuropathologic change (ADNC) without CTE. In CTE: (1) all aspects of tau-immunoreactive pathology were clustered and the clusters were frequently regularly distributed parallel to the tissue boundary, (2) clustering was similar in two CTE cases with minimal co-pathology compared with cases with associated ADNC or TDP-43 proteinopathy, (3) in a proportion of cortical gyri, estimated cluster size was similar to that of cell columns of the cortico-cortical pathways, and (4) clusters of the tau-immunoreactive pathology were infrequently spatially correlated with blood vessels. The NFT and NP in ADNC without CTE were less frequently randomly or uniformly distributed and more frequently in defined clusters than in CTE. Hence, the spatial pattern of the tau-immunoreactive pathology observed in CTE is typical of the tauopathies but with some distinct differences compared to ADNC alone. The spread of pathogenic tau along anatomical pathways could be a factor in the pathogenesis of the disease.

What to do when K-means clustering fails:a simple yet principled alternative algorithm

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.

Scenario-based preparedness plan for floods

The increasing trend of disaster victims globally is posing a complex challenge for disaster management authorities. Moreover, to accomplish successful transition between preparedness and response, it is important to consider the different features inherent to each type of disaster. Floods are portrayed as one of the most frequent and harmful disasters, hence introducing the necessity to develop a tool for disaster preparedness to perform efficient and effective flood management. The purpose of the article is to introduce a method to simultaneously define the proper location of shelters and distribution centers, along with the allocation of prepositioned goods and distribution decisions required to satisfy flood victims. The tool combines the use of a raster geographical information system (GIS) and an optimization model. The GIS determines the flood hazard of the city areas aiming to assess the flood situation and to discard floodable facilities. Then, the multi-commodity multimodal optimization model is solved to obtain the Pareto frontier of two criteria: distance and cost. The methodology was applied to a case study in the flood of Villahermosa, Mexico, in 2007, and the results were compared to an optimized scenario of the guidelines followed by Mexican authorities, concluding that the value of the performance measures was improved using the developed method. Furthermore, the results exhibited the possibility to provide adequate care for people affected with less facilities than the current approach and the advantages of considering more than one distribution center for relief prepositioning.

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

Clustering of Rab11 vesicles in influenza A virus infected cells creates hotspots containing the 8 viral ribonucleoproteins

Influenza A virus is an important human pathogen causative of yearly epidemics and occasional pandemics. The ability to replicate within the host cell is a determinant of virulence, amplifying viral numbers for host-to-host transmission. This process requires multiple rounds of entering permissive cells, replication, and virion assembly at the plasma membrane, the site of viral budding and release. The assembly of influenza A virus involves packaging of several viral (and host) proteins and of a segmented genome, composed of 8 distinct RNAs in the form of viral ribonucleoproteins (vRNPs). The selective assembly of the 8-segment core remains one of the most interesting unresolved problems in virology. The recycling endosome regulatory GTPase Rab11 was shown to contribute to the process, by transporting vRNPs to the periphery, giving rise to enlarged cytosolic puncta rich in Rab11 and the 8 vRNPs. We recently reported that vRNP hotspots were formed of clustered vesicles harbouring protruding electron-dense structures that resembled vRNPs. Mechanistically, vRNP hotspots were formed as vRNPs outcompeted the cognate effectors of Rab11, the Rab11-Family-Interacting-Proteins (FIPs) for binding, and as a consequence impair recycling sorting at an unknown step. Here, we speculate on the impact that such impairment might have in host immunity, membrane architecture and viral assembly.

European lobster (Homarus gammarus) larvae under an acidification scenario: addressing biochemical, development and behaviour responses

A acidificação dos oceanos constitui uma problemática global e a realidade de que está, efetivamente, a acontecer não é uma consideração subjetiva. A Acidificação dos oceanos provocada por emissões de dióxido de carbono de origem antropogénica tem vindo a reduzir o pH das águas superficiais do Oceano e projeções preveem a continuidade deste processo. Embora muita investigação tenha sido desenvolvida no âmbito dos invertebrados que calcificam, tais como moluscos e crustáceos, poucos consideraram o estudo de efeitos ao nível sub-celular para avaliar stress oxidativo ou respostas funcionais do metabolismo energético em tais condições, interligando vários níveis de organização biológica. O objetivo do presente estudo foi o de avaliar os efeitos da exposição a diferentes níveis-alvo de pCO2 (controlo: 370 μatm; aumentado: 710 μatm) e de pH (controlo: 8.15; reduzido: 7.85) em parâmetros de crescimento bem como avaliar respostas comportamentais e bioquímicas relacionadas com stress oxidativo e metabolismo energético durante o desenvolvimento larvar de um crustáceo decápode. Este cenário de acidificação está de acordo com os RCPs previstos pelo Painel Intergovernamental para as Alterações Climáticas (IPCC, 2014) para o ano 2100. Para o presente estudo, foi utilizado o crustáceo Homarus gammarus (L.) – sendo uma espécie com elevado valor comercial, que tem vindo a sofrer elevada pressão de pesca em águas Europeias. Fêmeas adultas provenientes da costa Atlântica Oeste Portuguesa foram obtidas de um retalhista local. Após a eclosão em ambiente laboratorial controlado, larvas provenientes da mesma progenitora foram expostas às condições acima descritas desde o momento da eclosão até à chegada ao Estádio III. A sobrevivência individual e ocorrência de ecdise foram avaliados individualmente de 12h em 12h. Réplicas de cada tratamento foram recolhidas em momentos específicos durante o Estádio I (primeiro estádio larvar) e Estádio III (último estádio larvar) para análise morfométrica e de crescimento (peso fresco e comprimento carapaça) e respostas bioquímicas. Os biomarcadores analisados incluíram parâmetros relacionados com stress oxidativo e danos (atividade da enzima superóxido dismutase (SOD), peroxidação lipídica (LPO) e danos no DNA) e metabolismo energético (atividade da cadeia transportadora de eletrões (ETS) e da enzima lactato desidrogenase (LDH) e quantificação de Hidratos de Carbono). Os resultados obtidos sugerem que a sobrevivência diminui e que o período inter-muda é afetado durante a exposição a cenários de acidificação. No que respeita aos parâmetros de crescimento/morfométricos, larvas do cenário de acidificação apresentam uma tendência para crescimento diminuído, menor peso e comprimento de carapaça. As análises bioquímicas realizadas indicam a ocorrência de stress oxidativo sob condições de acidificação. Respostas ao nível do metabolismo energético não variaram significativamente entre tratamentos. Os resultados apontam também para que fases larvares possam possuir um sistema antioxidante ainda em desenvolvimento, tornando-as mais suscetíveis ao stress oxidativo. As fases larvares são uma fase vulnerável e crucial no ciclo de vida das espécies, influenciando o recrutamento e a renovação de stocks. Este estudo contribui para um melhor entendimento sobre a vulnerabilidade desta espécie num cenário de alterações climáticas – Acidificação dos oceanos – ao endereçar os mecanismos envolvidos nas respostas deste crustáceo a este agente causador de stress.

Travelers’ use of social media: A clustering approach

Research regarding the use of social media among travelers has mainly focused on its impact on travelers’ travel planning process and there is consensus that travel decisions are highly influenced by social media. Yet, little attention has been paid to the differences among travelers regarding their use of social media for travel purposes. Based on the use of travel social media, cluster analysis was employed to identify different segments among travelers. Furthermore, the study profiles the clusters based on demographic and other travel related characteristics. The findings of this study are important to online marketers to better understand traveler’s use of social media and their characteristics, in order to adapt online marketing strategies according to the profile of each segment.

Travelers’ use of social media: A clustering approach

Research regarding the use of social media among travelers has mainly focused on its impact on travelers’ travel planning process and there is consensus that travel decisions are highly influenced by social media. Yet, little attention has been paid to the differences among travelers regarding their use of social media for travel purposes. Based on the use of travel social media, cluster analysis was employed to identify different segments among travelers. Furthermore, the study profiles the clusters based on demographic and other travel related characteristics. The findings of this study are important to online marketers to better understand traveler’s use of social media and their characteristics, in order to adapt online marketing strategies according to the profile of each segment.

Clustering von deutschen Ortsnamen

Diese Studie untersucht Gruppen von Ortsnamen in Deutschland (in den Postleitregionen) nach vorhandenen Ähnlichkeiten. Als Messgröße wird ein Häufigkeitsvektor von Trigrammen in jeder Gruppe herangezogen. Mit der Anwendung des Average Linkage-Algorithmus auf die Messgröße werden Cluster aus räumlich zusammenhängenden Gebieten gebildet, obwohl das Verfahren keine Kenntnis über die Lage der Cluster zueinander besitzt. In den Clustern werden die zehn häufigsten n-Gramme ermittelt, um charakteristische Wortpartikel darzustellen. Die von den Clustern umschriebenen Gebiete lassen sich zwanglos durch historische oder linguistische Entwicklungen erklären. Das hier verwendete Verfahren setzt jedoch kein linguistisches, geographisches oder historisches Wissen voraus, ermöglicht aber die Gruppierung von Namen in eindeutiger Weise unter Berücksichtigung einer Vielzahl von Wortpartikeln in einem Schritt. Die Vorgehensweise ohne Vorwissen unterscheidet diese Studie von den meisten bisher angewendeten Untersuchungen.

Small states and the promotion of their foreign policy agenda in the international scenario: Trinidad and Tobago and the Kyoto Protocol

Este estudio de caso busca identificar los elementos del portafolio de política exterior de Trinidad y Tobago que le permitieron promover exitosamente sus intereses en el Protocolo de Kioto. Al hacer esto, este texto analizará las limitaciones de Trinidad y Tobago en términos de vulnerabilidades de localización, burocracia y recursos. Posteriormente, una revisión del portafolio de política exterior de este Estado ilustrará el uso de estrategias de creación de capacidades y de organización como lo son el contacto con actores institucionales y no gubernamentales, la formación de coaliciones y estrategias argumentativas, entre otras. Finalmente, este artículo concluirá que dichas acciones permitieron la promoción de la agenda de política exterior de Trinidad y Tobago a través de la creación de hojas de ruta y la coordinación de la incertidumbre con el Protocolo de Kioto. Para hacer esto, este trabajo se concentrará en examinar conceptos como vulnerabilidad y priorización, asimismo contrastando diferentes artículos académicos en la materia junto con documentos oficiales de Trinidad y Tobago.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.