Challenge stressors: longitudinal effects on self attitudes, work attitudes, and health.

Recent research suggests that some stressors (i.e. hindrance stressors) have mainly negative consequences, whereas others (i.e. challenge stressors) can simultaneously have positive and negative consequences (e.g., LePine et al., 2005). Although a number of studies have dealt with potential outcomes of challenge stressors, some criteria have received only limited attention (e.g., positive self-attitudes; cf. Widmer et al., 2012), and some have been neglected altogether (i.e., physical health outcomes). Furthermore, while sophisticated methods – such as meta-analyses (e.g., LePine et al., 2005), diary studies (Ohly & Fritz, 2010), and multi-source analyses (Wallace et al., 2009) – have been applied to the framework, there are no longitudinal studies. We report results from a longitudinal study containing three waves, with two time-lags of one month each (N = 393). We analyzed relationships between challenge stressors and work attitudes (e.g. job satisfaction), self attitudes (e.g. self-esteem), and health indicators (e.g. sleep quality) using cross-lagged SEM. We expected positive effects of challenge stressors to appear only when their negative variance is controlled (e.g. by including hindrance stressors as a suppressor variable; cf. Cavanaugh et al., 2000). As the positive aspects of challenge stressors relate to self-affirming experiences, we also expected positive effects to be especially strong for self attitudes. Regarding work attitudes, the only significant paths found were from work attitudes to challenge stressors over both time lags. Regarding health, there was a significant cross-sectional association at time 1, which was negative, as expected. Longitudinally, a positive path from challenge stressors to health for both time lags was found only when hindrances stressors were controlled, confirming the expected suppressor effect. Hindrance stressors had a negative effect on health. For self-attitudes, there was a positive cross-sectional association at time one. In addition, a positive effect on self attitudes was found longitudinally for both time lags, but only when hindrance stressors were controlled. Additional analyses showed that the positive longitudinal effect on health was mediated by self attitudes. Although the lack of associations with work attitudes was surprising, our results indicate that challenge stressors contain aspects that provide an opportunity to develop self-esteem through demanding work situations, thereby contributing to personal growth and thriving at the workplace. They also confirm the ambiguous nature of challenge stressors, as, with one exception, positive effects were found only when hindrance stressors were controlled (cf. Widmer et al., 2012). Finally, our results confirm the importance of self-related attitudes in the stress process.

Improving residency training with the help of multisource feedback: Generation of a model of influencing factors

Background: Feedback is considered to be one of the most important drivers of learning. One form of structured feedback used in medical settings is multisource feedback (MSF). This feedback technique provides the opportunity to gain a differentiated view on a doctor’s performance from several perspectives using a questionnaire and a facilitating conversation, in which learning goals are formulated. While many studies have been conducted on the validity, reliability and feasibility of the instrument, little is known about the impact of factors that might influence the effects of MSF on clinical performance. Summary of Work: To study under which circumstances MSF is most effective, we performed a literature review on Google Scholar with focus on MSF and feedback in general. Main key-words were: MSF, multi-source-feedback, multi source feedback, and feedback each combined with influencing/ hindering/ facilitating factors, effective, effectiveness, doctors-intraining, and surgery. Summary of Results: Based on the literature, we developed a preliminary model of facilitating factors. This model includes five main factors influencing MSF: questionnaire, doctor-in-training, group of raters, facilitating supervisor, and facilitating conversation. Discussion and Conclusions: Especially the following points that might influence MSF have not yet been sufficiently studied: facilitating conversation with the supervisor, individual aspects of doctors-in-training, and the causal relations between influencing factors. Overall there are only very few studies focusing on the impact of MSF on actual and long-term performance. We developed a preliminary model of hindering and facilitating factors on MSF. Further studies are needed to better understand under which circumstances MSF is most effective. Take-home messages: The preliminary model might help to guide further studies on how to implement MSF to use it at its full potential.

LiDAR remote sensing applied to forest resources assessment

Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el número de pies, el volumen de madera, la altura dominante, el diámetro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicación de los denominados métodos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y características de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (información proveniente de vuelo nacionales e información capturada de forma específica). Como consecuencia de lo anterior, se profundiza en la generación de inventarios forestales continuos con LiDAR en grandes áreas. Los métodos de masa se basan en la búsqueda de relaciones estadísticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartografía continua de inventario forestal. El rápido desarrollo de esta tecnología en los últimos años ha llevado a muchos países a implantar programas nacionales de captura de información LiDAR aerotransportada. Estos vuelos nacionales no están pensados ni diseñados para fines forestales por lo que es necesaria la evaluación de la validez de esta información LiDAR para la descripción de la estructura del bosque y la medición de variables forestales. Esta información podría suponer una drástica reducción de costes en la generación de información continua de alta resolución de inventario forestal. En el capítulo 2 se evalúa la estimación de variables forestales a partir de la información LiDAR capturada en el marco del Plan Nacional de Ortofotografía Aérea (PNOA-LiDAR) en España. Para ello se compara un vuelo específico diseñado para inventario forestal con la información de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra cómo el ángulo de escaneo, la pendiente y orientación del terreno afectan de forma estadísticamente significativa, aunque con pequeñas diferencias, a la estimación de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas resultó más afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimación de la biomasa con ambas bases de datos no presentó diferencias estadísticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimación de biomasa entre un vuelo específico y el vuelo nacional podrán superar el 4% en áreas abruptas, con ángulos de escaneo altos y cuando la pendiente de la ladera no esté orientada hacia la línea de escaneo. En el capítulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la información disponible (vuelos LiDAR nacionales de baja densidad de puntos, imágenes satelitales Landsat y parcelas permanentes del inventario forestal nacional español). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resolución en grandes superficies. Los errores obtenidos en la fase de ajuste y de validación de los modelos de área basimétrica y volumen son similares a los registrados por otros autores (usando un vuelo específico y parcelas de campo específicas). Se observan errores mayores en la variable número de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodología de parcelas de radio variable en esta variable. En los capítulos 4 y 5 se evalúan los métodos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volcán Poás (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del área de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es técnica o económicamente posible y se combina una cobertura incompleta de LiDAR con imágenes Landsat e información auxiliar para la estimación de biomasa y carbono (capitulo 5). En el capítulo 4 se valida un modelo LiDAR general de estimación de biomasa aérea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma específica para el área de estudio. Ambos modelos están basados en la variable altura media de copas (TCH por sus siglas en inglés) derivada del modelo digital LiDAR de altura de la vegetación. Los resultados en el área de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos específicos y que la biomasa aérea puede ser estimada en una nueva zona midiendo en campo únicamente la variable área basimétrica (BA). Para mejorar la aplicación de esta metodología es necesario definir en futuros trabajos procedimientos adecuados de medición de la variable área basimétrica en campo (localización, tamaño y forma de las parcelas de campo). La relación entre la altura media de copas del LiDAR y el área basimétrica (Coeficiente de Stock) obtenida en el área de estudio varía localmente. Por tanto es necesario contar con más información de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificación pueden reducir los errores en la estimación de biomasa y carbono en bosques tropicales. En el capítulo 5 se concluye que la combinación de una muestra sistemática de información LiDAR con una cobertura completa de imagen satelital de moderada resolución (e información auxiliar) es una alternativa efectiva para la realización de inventarios continuos en bosques tropicales. Esta metodología permite estimar altura de la vegetación, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realización de un gran volumen de trabajo de campo es económica o/y técnicamente inviable. Las alternativas examinadas para la predicción de biomasa a partir de imágenes Landsat muestran una ligera disminución del coeficiente de determinación y un pequeño aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetación, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del área de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15º. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.

Grain size distribution analysis of prominent beds on Southern Central Chilean seamounts

Gravity cores obtained from isolated seamounts located within, and rising up to 300 m from the sediment-filled Peru-Chile Trench off Southern Central Chile (36°S-39°S) contain numerous turbidite layers which are much coarser than the hemipelagic background sedimentation. The mineralogical composition of some of the beds indicates a mixed origin from various source terrains while the faunal assemblage of benthic foraminifera in one of the turbidite layers shows a mixed origin from upper shelfal to middle-lower bathyal depths which could indicate a multi-source origin and therefore indicate an earthquake triggering of the causing turbidity currents. The bathymetric setting and the grain size distribution of the sampled layers, together with swath echosounder and sediment echosounder data which monitor the distribution of turbidites on the elevated Nazca Plate allow some estimates on the flow direction, flow velocity and height of the causing turbidity currents. We discuss two alternative models of deposition, both of which imply high (175-450 m) turbidity currents and we suggest a channelized transport process as the general mode of turbidite deposition. Whether these turbidites are suspension fallout products of thick turbiditic flows or bedload deposits from sheet-like turbidity currents overwhelming elevated structures cannot be decided upon using our sedimentological data, but the specific morphology of the seamounts rather argues for the first option. Oxygen isotope stratigraphy of one of the cores indicates that the turbiditic sequences were deposited during the last Glacial period and during the following transition period and turbiditic deposition stopped during the Holocene. This climatic coupling seems to be dominant, while the occurrence of megathrust earthquakes provides a trigger mechanism. This seismic triggering takes effect only during times of very high sediment supply to the shelf and slope.

Sviluppo e Applicazione di Metodologie per l'Ottimizzazione di Sistemi Energetici

La riduzione dei consumi di combustibili fossili e lo sviluppo di tecnologie per il risparmio energetico sono una questione di centrale importanza sia per l’industria che per la ricerca, a causa dei drastici effetti che le emissioni di inquinanti antropogenici stanno avendo sull’ambiente. Mentre un crescente numero di normative e regolamenti vengono emessi per far fronte a questi problemi, la necessità di sviluppare tecnologie a basse emissioni sta guidando la ricerca in numerosi settori industriali. Nonostante la realizzazione di fonti energetiche rinnovabili sia vista come la soluzione più promettente nel lungo periodo, un’efficace e completa integrazione di tali tecnologie risulta ad oggi impraticabile, a causa sia di vincoli tecnici che della vastità della quota di energia prodotta, attualmente soddisfatta da fonti fossili, che le tecnologie alternative dovrebbero andare a coprire. L’ottimizzazione della produzione e della gestione energetica d’altra parte, associata allo sviluppo di tecnologie per la riduzione dei consumi energetici, rappresenta una soluzione adeguata al problema, che può al contempo essere integrata all’interno di orizzonti temporali più brevi. L’obiettivo della presente tesi è quello di investigare, sviluppare ed applicare un insieme di strumenti numerici per ottimizzare la progettazione e la gestione di processi energetici che possa essere usato per ottenere una riduzione dei consumi di combustibile ed un’ottimizzazione dell’efficienza energetica. La metodologia sviluppata si appoggia su un approccio basato sulla modellazione numerica dei sistemi, che sfrutta le capacità predittive, derivanti da una rappresentazione matematica dei processi, per sviluppare delle strategie di ottimizzazione degli stessi, a fronte di condizioni di impiego realistiche. Nello sviluppo di queste procedure, particolare enfasi viene data alla necessità di derivare delle corrette strategie di gestione, che tengano conto delle dinamiche degli impianti analizzati, per poter ottenere le migliori prestazioni durante l’effettiva fase operativa. Durante lo sviluppo della tesi il problema dell’ottimizzazione energetica è stato affrontato in riferimento a tre diverse applicazioni tecnologiche. Nella prima di queste è stato considerato un impianto multi-fonte per la soddisfazione della domanda energetica di un edificio ad uso commerciale. Poiché tale sistema utilizza una serie di molteplici tecnologie per la produzione dell’energia termica ed elettrica richiesta dalle utenze, è necessario identificare la corretta strategia di ripartizione dei carichi, in grado di garantire la massima efficienza energetica dell’impianto. Basandosi su un modello semplificato dell’impianto, il problema è stato risolto applicando un algoritmo di Programmazione Dinamica deterministico, e i risultati ottenuti sono stati comparati con quelli derivanti dall’adozione di una più semplice strategia a regole, provando in tal modo i vantaggi connessi all’adozione di una strategia di controllo ottimale. Nella seconda applicazione è stata investigata la progettazione di una soluzione ibrida per il recupero energetico da uno scavatore idraulico. Poiché diversi layout tecnologici per implementare questa soluzione possono essere concepiti e l’introduzione di componenti aggiuntivi necessita di un corretto dimensionamento, è necessario lo sviluppo di una metodologia che permetta di valutare le massime prestazioni ottenibili da ognuna di tali soluzioni alternative. Il confronto fra i diversi layout è stato perciò condotto sulla base delle prestazioni energetiche del macchinario durante un ciclo di scavo standardizzato, stimate grazie all’ausilio di un dettagliato modello dell’impianto. Poiché l’aggiunta di dispositivi per il recupero energetico introduce gradi di libertà addizionali nel sistema, è stato inoltre necessario determinare la strategia di controllo ottimale dei medesimi, al fine di poter valutare le massime prestazioni ottenibili da ciascun layout. Tale problema è stato di nuovo risolto grazie all’ausilio di un algoritmo di Programmazione Dinamica, che sfrutta un modello semplificato del sistema, ideato per lo scopo. Una volta che le prestazioni ottimali per ogni soluzione progettuale sono state determinate, è stato possibile effettuare un equo confronto fra le diverse alternative. Nella terza ed ultima applicazione è stato analizzato un impianto a ciclo Rankine organico (ORC) per il recupero di cascami termici dai gas di scarico di autovetture. Nonostante gli impianti ORC siano potenzialmente in grado di produrre rilevanti incrementi nel risparmio di combustibile di un veicolo, è necessario per il loro corretto funzionamento lo sviluppo di complesse strategie di controllo, che siano in grado di far fronte alla variabilità della fonte di calore per il processo; inoltre, contemporaneamente alla massimizzazione dei risparmi di combustibile, il sistema deve essere mantenuto in condizioni di funzionamento sicure. Per far fronte al problema, un robusto ed efficace modello dell’impianto è stato realizzato, basandosi sulla Moving Boundary Methodology, per la simulazione delle dinamiche di cambio di fase del fluido organico e la stima delle prestazioni dell’impianto. Tale modello è stato in seguito utilizzato per progettare un controllore predittivo (MPC) in grado di stimare i parametri di controllo ottimali per la gestione del sistema durante il funzionamento transitorio. Per la soluzione del corrispondente problema di ottimizzazione dinamica non lineare, un algoritmo basato sulla Particle Swarm Optimization è stato sviluppato. I risultati ottenuti con l’adozione di tale controllore sono stati confrontati con quelli ottenibili da un classico controllore proporzionale integrale (PI), mostrando nuovamente i vantaggi, da un punto di vista energetico, derivanti dall’adozione di una strategia di controllo ottima.

The role of self-regulation as a meta-competency in developing leaders: a longitudinal field experimental study

The question of how to develop leaders so that they are more effective in a variety of situations, roles and levels has inspired a voluminous amount of research. While leader development programs such as executive coaching and 360-degree feedback have been widely practiced to meet this demand within organisations, the research in this area has only scratched the surface. Drawing from the past literature and leadership practices, the current research conceptualised self-regulation, as a metacompetency that would assist leaders to further develop the specific competencies needed to perform effectively in their leadership role, leading to an increased rating of leader effectiveness and to enhanced group performance. To test this conceptualisation, a longitudinal field experimental study was conducted across ten months with a pre- and two post-test intervention designs with a matched control group. This longitudinal field experimental compared the difference in leader and team performance after receiving self-regulation intervention that was delivered by an executive coach. Leaders in experimental group also received feedback reports from 360-degree feedback at each stage. Participants were 40 leaders, 155 followers and 8 supervisors. Leaders’ performance was measured using a multi-source perceptual measure of leader performance and objective measures of team financial and assessment performance. Analyses using repeated measure of ANCOVA on pre-test and two post-tests responses showed a significant difference between leader and team performance between experimental and control group. Furthermore, leader competencies mediated the relationship between self-regulation and performance. The implications of these findings for the theory and practice of leadership development training programs and the impact on organisational performance are discussed.

Identification of industrial sources of airborne heavy metal pollution in urban areas

The research examines the deposition of airborne particles which contain heavy metals and investigates the methods that can be used to identify their sources. The research focuses on lead and cadmium because these two metals are of growing public and scientific concern on environmental health grounds. The research consists of three distinct parts. The first is the development and evaluation of a new deposition measurement instrument - the deposit cannister - designed specifically for large-scale surveys in urban areas. The deposit cannister is specifically designed to be cheap, robust, and versatile and therefore to permit comprehensive high-density urban surveys. The siting policy reduces contamination from locally resuspended surface-dust. The second part of the research has involved detailed surveys of heavy metal deposition in Walsall, West Midlands, using the new high-density measurement method. The main survey, conducted over a six-week period in November - December 1982, provided 30-day samples of deposition at 250 different sites. The results have been used to examine the magnitude and spatial variability of deposition rates in the case-study area, and to evaluate the performance of the measurement method. The third part of the research has been to conduct a 'source-identification' exercise. The methods used have been Receptor Models - Factor Analysis and Cluster Analysis - and a predictive source-based deposition model. The results indicate that there are six main source processes contributing to deposition of metals in the Walsall area: coal combustion, vehicle emissions, ironfounding, copper refining and two general industrial/urban processes. |A source-based deposition model has been calibrated using facctorscores for one source factor as the dependent variable, rather than metal deposition rates, thus avoiding problems traditionally encountered in calibrating models in complex multi-source areas. Empirical evidence supports the hypothesised associatlon of this factor with emissions of metals from the ironfoundry industry.

The role of self-regulation in developing leaders:a longitudinal field experiment

A longitudinal field experiment examined a leader self-regulation intervention in teams engaged in a Business Strategy Module (BSM) of a University course. The BSM, which is an integral part of the degree programme, involved teams of four or five individuals, under the direction of a leader, working on a (simulated) car manufacturing task over a period of 24. weeks. Various aspects of team performance contributed towards module assessment. All leaders received multi-source feedback of leader task-relevant capabilities (from the leader, followers and module tutor). Leaders were randomly allocated into a self-regulation intervention (15 leaders, 46 followers) or control (25 leaders, 109 followers) conditions. The intervention, which was run by an independent coach, was designed to improve leaders' use of self-regulatory processes to aid the development of task-relevant leadership competencies. Survey data was collected from the leaders and followers (on three occasions: pre- and two post-test intervention), team financial performance (three occasions: post-test) and a final team report (post-test). The leader self-regulation intervention led to increased followers' ratings of leader's effectiveness, higher team financial performance and higher final team grade compared to the control (non-intervention) condition. Furthermore, the benefits of the self-regulation intervention were mediated by leaders' attaining task-relevant competencies. © 2013.

Knowledge discovery using multiple sources of biological data

The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^

Apports de la texture multibande dans la classification orientée-objets d'images multisources (optique et radar).

Résumé : La texture dispose d’un bon potentiel discriminant qui complète celui des paramètres radiométriques dans le processus de classification d’image. L’indice Compact Texture Unit (CTU) multibande, récemment mis au point par Safia et He (2014), permet d’extraire la texture sur plusieurs bandes à la fois, donc de tirer parti d’un surcroît d’informations ignorées jusqu’ici dans les analyses texturales traditionnelles : l’interdépendance entre les bandes. Toutefois, ce nouvel outil n’a pas encore été testé sur des images multisources, usage qui peut se révéler d’un grand intérêt quand on considère par exemple toute la richesse texturale que le radar peut apporter en supplément à l’optique, par combinaison de données. Cette étude permet donc de compléter la validation initiée par Safia (2014) en appliquant le CTU sur un couple d’images optique-radar. L’analyse texturale de ce jeu de données a permis de générer une image en « texture couleur ». Ces bandes texturales créées sont à nouveau combinées avec les bandes initiales de l’optique, avant d’être intégrées dans un processus de classification de l’occupation du sol sous eCognition. Le même procédé de classification (mais sans CTU) est appliqué respectivement sur : la donnée Optique, puis le Radar, et enfin la combinaison Optique-Radar. Par ailleurs le CTU généré sur l’Optique uniquement (monosource) est comparé à celui dérivant du couple Optique-Radar (multisources). L’analyse du pouvoir séparateur de ces différentes bandes à partir d’histogrammes, ainsi que l’outil matrice de confusion, permet de confronter la performance de ces différents cas de figure et paramètres utilisés. Ces éléments de comparaison présentent le CTU, et notamment le CTU multisources, comme le critère le plus discriminant ; sa présence rajoute de la variabilité dans l’image permettant ainsi une segmentation plus nette, une classification à la fois plus détaillée et plus performante. En effet, la précision passe de 0.5 avec l’image Optique à 0.74 pour l’image CTU, alors que la confusion diminue en passant de 0.30 (dans l’Optique) à 0.02 (dans le CTU).

Multi-elemental analysis of ready-to-eat “baby leaf” vegetables using microwave digestion and high-resolution continuum source atomic absorption spectrometry

The mineral content (phosphorous (P), potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu)) of eight ready-to-eat baby leaf vegetables was determined. The samples were subjected to microwave-assisted digestion and the minerals were quantified by High-Resolution Continuum Source Atomic Absorption Spectrometry (HR-CS-AAS) with flame and electrothermal atomisation. The methods were optimised and validated producing low LOQs, good repeatability and linearity, and recoveries, ranging from 91% to 110% for the minerals analysed. Phosphorous was determined by a standard colorimetric method. The accuracy of the method was checked by analysing a certified reference material; results were in agreement with the quantified value. The samples had a high content of potassium and calcium, but the principal mineral was iron. The mineral content was stable during storage and baby leaf vegetables could represent a good source of minerals in a balanced diet. A linear discriminant analysis was performed to compare the mineral profile obtained and showed, as expected, that the mineral content was similar between samples from the same family. The Linear Discriminant Analysis was able to discriminate different samples based on their mineral profile.

Creació automàtica de gràfics estadístics a partir de dades de soroll d’Europa amb tecnologies Open Source en el visor Noise Map Viewer de l’ETC-LUSI

El projecte ha consistit en la creació de gràfics estadístics de soroll d’Europa de forma automàtica amb tecnologies Open Source dins el visor Noise Map Viewer per Europa de l’ETC-LUSI. La llibreria utilitzada per fer aquest procés ha estat JFreeChart i el llenguatge de programació utilitzat ha estat Java (programació orientada a objectes) dins l’entorn de desenvolupament integrat Eclipse. La base de dades utilitzada ha estat PostgreSQL. Com a servidors s’han fet servir Apache (servidor HTTP) i Tomcat (servidor contenidor d’aplicacions). Un cop acabat el procés s’ha integrat dins de MapFish canviant el codi JavaScript corresponent de la web original.

The Coordinated Radio and Infrared Survey for High-mass Star Formation. II. Source Catalog

The CORNISH project is the highest resolution radio continuum survey of the Galactic plane to date. It is the 5 GHz radio continuum part of a series of multi-wavelength surveys that focus on the northern GLIMPSE region (10° < l < 65°), observed by the Spitzer satellite in the mid-infrared. Observations with the Very Large Array in B and BnA configurations have yielded a 1.''5 resolution Stokes I map with a root mean square noise level better than 0.4 mJy beam 1. Here we describe the data-processing methods and data characteristics, and present a new, uniform catalog of compact radio emission. This includes an implementation of automatic deconvolution that provides much more reliable imaging than standard CLEANing. A rigorous investigation of the noise characteristics and reliability of source detection has been carried out. We show that the survey is optimized to detect emission on size scales up to 14'' and for unresolved sources the catalog is more than 90% complete at a flux density of 3.9 mJy. We have detected 3062 sources above a 7σ detection limit and present their ensemble properties. The catalog is highly reliable away from regions containing poorly sampled extended emission, which comprise less than 2% of the survey area. Imaging problems have been mitigated by down-weighting the shortest spacings and potential artifacts flagged via a rigorous manual inspection with reference to the Spitzer infrared data. We present images of the most common source types found: H II regions, planetary nebulae, and radio galaxies. The CORNISH data and catalog are available online at http://cornish.leeds.ac.uk.

Movies as a source of non-occupational noise exposure

This paper examines the noise levels of movies and whether or not movie theater sound levels may be hazardous to audience members.

A solid-state noise source for millimetre wave spectrometry

A novel wide-band noise source for millimetre-wave spectrometry is described. It uses power combined Schottky diodes, reverse biased to avalanche breakdown, mounted in a wide-band tapered slot antenna. Power has been produced from 15 to 200 GHz with an equivalent temperature of 28200 K at 40 GHz.