A PROCESS FOR ACHIEVING COMPARABLE DATA FROM HETEROGENEOUS DATABASES

The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, collected for different purposes and represented differently, that are presently impossible to share or analyze in toto. The greatest challenge for large-scale and meaningful analyses of health-related data is to achieve a uniform data representation for data extracted from heterogeneous source representations. Based upon an analysis and categorization of heterogeneities, a process for achieving comparable data content by using a uniform terminological representation is developed. This process addresses the types of representational heterogeneities that commonly arise in healthcare data integration problems. Specifically, this process uses a reference terminology, and associated "maps" to transform heterogeneous data to a standard representation for comparability and secondary use. The capture of quality and precision of the “maps” between local terms and reference terminology concepts enhances the meaning of the aggregated data, empowering end users with better-informed queries for subsequent analyses. A data integration case study in the domain of pediatric asthma illustrates the development and use of a reference terminology for creating comparable data from heterogeneous source representations. The contribution of this research is a generalized process for the integration of data from heterogeneous source representations, and this process can be applied and extended to other problems where heterogeneous data needs to be merged.

A current literature review of the social and economic ramifications of pharmacogenomic research

Objective. To explore issues in current literature concerning possible social and economic ramifications of pharmacogenomic research. Design. Review of the literature. Data sources: Academic Search Premier, Blackwell Synergy, PUBMED and Social Sciences Citation Index. Review methods. Articles dealing with the social and economic ramifications of pharmacogenomic research were selected. The articles discussed at least one of 5 areas (race, privacy/confidentiality, ethics, insurance, and research and development). Some restrictions were placed on the articles chosen to narrow down the number of articles to a relevant, manageable amount. Results. Approximately 219 articles were selected for review; 159 were fully reviewed and found to be relevant to the issues; and 33 were cited. Conclusion. Insurance and research and development decisions are led by the free-market system with limited intervention from government. Race/ethnicity, privacy/confidentiality, and ethics continue to be debated with no clear answer. However, some compromise is regulated by government based upon current laws involving these issues. ^

Treatment modalities of female Operation Iraqi Freedom/Operation Enduring Freedom Veterans with posttraumatic stress disorder: A systematic review of the literature

Objective. To review professional literature regarding treatment modalities of post-traumatic stress disorder (PTSD) amongst female Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) veterans, to assess the efficacy of these treatment options, and to summarize implications of the findings from this literature. Design. Systematic review of published literature. Data sources. Medline, Pubmed, Psycinfo. Review Methods. Articles selected for the literature review pertain to the treatment options of female OIF or OEF veterans who have a diagnosis of PTSD. In addition, other relevant articles, such as articles that discuss the prevalence of the problem, access to care, and similar treatment modalities for PTSD in other war settings, were selected for background information for the review. Results. The search strategy identified 1,305 potential journal articles, taken from thorough searches in Medline, Pubmed, and Psycinfo. These articles were then imported into Refworks. Following final screening, there were 18 articles included in the systematic review and 28 articles used as background information. The remaining articles were excluded following screening of abstract and/or full text of articles. Treatment modalities presented in these trials include: Exposure Therapy (average of 68% reduction in PTSD symptoms), Imagery Rehearsal Therapy (23% reduction), Body-Oriented Therapy (57% reduction), Electroconvulsive Therapy (35% reduction), Holographic Reprocessing (47% reduction), a self-defense training program (13% reduction), Cognitive Behavioral Therapy (65% reduction) and a variety of pharmacotherapies (antipsychotics at 81% reduction, sympatholytic drug at 100% reduction). Outcomes of the studies included in this systematic review were measured by using personal assessment of whether there was a reduction in symptoms of PTSD, based on the results in each study. Conclusion. Overall, all of the treatment modalities investigated in the systematic review proved to be somewhat effective in relieving the burden of symptoms of PTSD amongst female veterans of OIF/OEF. In addition to pharmacotherapy, which had the highest reduction in PTSD symptoms, both the Exposure Therapy and the Cognitive Behavioral Therapy techniques proved to have the most positive results. As all of the therapies had a positive effect on this population, to some degree, a study needs to be done in the future to compare and contrast the efficacy of each therapy intervention when applied to a standardized population.^

Automatic physical activity pattern recognition and meal intake modelling in type 1 diabetes for their inclusion in artificial pancreas systems

La diabetes comprende un conjunto de enfermedades metabólicas que se caracterizan por concentraciones de glucosa en sangre anormalmente altas. En el caso de la diabetes tipo 1 (T1D, por sus siglas en inglés), esta situación es debida a una ausencia total de secreción endógena de insulina, lo que impide a la mayoría de tejidos usar la glucosa. En tales circunstancias, se hace necesario el suministro exógeno de insulina para preservar la vida del paciente; no obstante, siempre con la precaución de evitar caídas agudas de la glucemia por debajo de los niveles recomendados de seguridad. Además de la administración de insulina, las ingestas y la actividad física son factores fundamentales que influyen en la homeostasis de la glucosa. En consecuencia, una gestión apropiada de la T1D debería incorporar estos dos fenómenos fisiológicos, en base a una identificación y un modelado apropiado de los mismos y de sus sorrespondientes efectos en el balance glucosa-insulina. En particular, los sistemas de páncreas artificial –ideados para llevar a cabo un control automático de los niveles de glucemia del paciente– podrían beneficiarse de la integración de esta clase de información. La primera parte de esta tesis doctoral cubre la caracterización del efecto agudo de la actividad física en los perfiles de glucosa. Con este objetivo se ha llevado a cabo una revisión sistemática de la literatura y meta-análisis que determinen las respuestas ante varias modalidades de ejercicio para pacientes con T1D, abordando esta caracterización mediante unas magnitudes que cuantifican las tasas de cambio en la glucemia a lo largo del tiempo. Por otro lado, una identificación fiable de los periodos con actividad física es un requisito imprescindible para poder proveer de esa información a los sistemas de páncreas artificial en condiciones libres y ambulatorias. Por esta razón, la segunda parte de esta tesis está enfocada a la propuesta y evaluación de un sistema automático diseñado para reconocer periodos de actividad física, clasificando su nivel de intensidad (ligera, moderada o vigorosa); así como, en el caso de periodos vigorosos, identificando también la modalidad de ejercicio (aeróbica, mixta o de fuerza). En este sentido, ambos aspectos tienen una influencia específica en el mecanismo metabólico que suministra la energía para llevar a cabo el ejercicio y, por tanto, en las respuestas glucémicas en T1D. En este trabajo se aplican varias combinaciones de técnicas de aprendizaje máquina y reconocimiento de patrones sobre la fusión multimodal de señales de acelerometría y ritmo cardíaco, las cuales describen tanto aspectos mecánicos del movimiento como la respuesta fisiológica del sistema cardiovascular ante el ejercicio. Después del reconocimiento de patrones se incorpora también un módulo de filtrado temporal para sacar partido a la considerable coherencia temporal presente en los datos, una redundancia que se origina en el hecho de que en la práctica, las tendencias en cuanto a actividad física suelen mantenerse estables a lo largo de cierto tiempo, sin fluctuaciones rápidas y repetitivas. El tercer bloque de esta tesis doctoral aborda el tema de las ingestas en el ámbito de la T1D. En concreto, se propone una serie de modelos compartimentales y se evalúan éstos en función de su capacidad para describir matemáticamente el efecto remoto de las concetraciones plasmáticas de insulina exógena sobre las tasas de eleiminación de la glucosa atribuible a la ingesta; un aspecto hasta ahora no incorporado en los principales modelos de paciente para T1D existentes en la literatura. Los datos aquí utilizados se obtuvieron gracias a un experimento realizado por el Institute of Metabolic Science (Universidad de Cambridge, Reino Unido) con 16 pacientes jóvenes. En el experimento, de tipo ‘clamp’ con objetivo variable, se replicaron los perfiles individuales de glucosa, según lo observado durante una visita preliminar tras la ingesta de una cena con o bien alta carga glucémica, o bien baja. Los seis modelos mecanísticos evaluados constaban de: a) submodelos de doble compartimento para las masas de trazadores de glucosa, b) un submodelo de único compartimento para reflejar el efecto remoto de la insulina, c) dos tipos de activación de este mismo efecto remoto (bien lineal, bien con un punto de corte), y d) diversas condiciones iniciales. ABSTRACT Diabetes encompasses a series of metabolic diseases characterized by abnormally high blood glucose concentrations. In the case of type 1 diabetes (T1D), this situation is caused by a total absence of endogenous insulin secretion, which impedes the use of glucose by most tissues. In these circumstances, exogenous insulin supplies are necessary to maintain patient’s life; although caution is always needed to avoid acute decays in glycaemia below safe levels. In addition to insulin administrations, meal intakes and physical activity are fundamental factors influencing glucose homoeostasis. Consequently, a successful management of T1D should incorporate these two physiological phenomena, based on an appropriate identification and modelling of these events and their corresponding effect on the glucose-insulin balance. In particular, artificial pancreas systems –designed to perform an automated control of patient’s glycaemia levels– may benefit from the integration of this type of information. The first part of this PhD thesis covers the characterization of the acute effect of physical activity on glucose profiles. With this aim, a systematic review of literature and metaanalyses are conduced to determine responses to various exercise modalities in patients with T1D, assessed via rates-of-change magnitudes to quantify temporal variations in glycaemia. On the other hand, a reliable identification of physical activity periods is an essential prerequisite to feed artificial pancreas systems with information concerning exercise in ambulatory, free-living conditions. For this reason, the second part of this thesis focuses on the proposal and evaluation of an automatic system devised to recognize physical activity, classifying its intensity level (light, moderate or vigorous) and for vigorous periods, identifying also its exercise modality (aerobic, mixed or resistance); since both aspects have a distinctive influence on the predominant metabolic pathway involved in fuelling exercise, and therefore, in the glycaemic responses in T1D. Various combinations of machine learning and pattern recognition techniques are applied on the fusion of multi-modal signal sources, namely: accelerometry and heart rate measurements, which describe both mechanical aspects of movement and the physiological response of the cardiovascular system to exercise. An additional temporal filtering module is incorporated after recognition in order to exploit the considerable temporal coherence (i.e. redundancy) present in data, which stems from the fact that in practice, physical activity trends are often maintained stable along time, instead of fluctuating rapid and repeatedly. The third block of this PhD thesis addresses meal intakes in the context of T1D. In particular, a number of compartmental models are proposed and compared in terms of their ability to describe mathematically the remote effect of exogenous plasma insulin concentrations on the disposal rates of meal-attributable glucose, an aspect which had not yet been incorporated to the prevailing T1D patient models in literature. Data were acquired in an experiment conduced at the Institute of Metabolic Science (University of Cambridge, UK) on 16 young patients. A variable-target glucose clamp replicated their individual glucose profiles, observed during a preliminary visit after ingesting either a high glycaemic-load or a low glycaemic-load evening meal. The six mechanistic models under evaluation here comprised: a) two-compartmental submodels for glucose tracer masses, b) a single-compartmental submodel for insulin’s remote effect, c) two types of activations for this remote effect (either linear or with a ‘cut-off’ point), and d) diverse forms of initial conditions.

Investigation on Heart Rate Variability (HRV) and psycho-social-affective adjustment in Italian women with ovarian cancer

INTRODUZIONE: L’integrazione mente-corpo applicata ad un ambito patologico predominante in questi tempi, come il cancro, è il nucleo di questa tesi. Il background teorico entro cui è inserita, è quello della Psiconeuroendocrinoimmunologia (Bottaccioli, 1995) e Psico-Oncologia. Sono state identificate, nella letteratura scientifica, le connessioni tra stati psicologici (mente) e condizioni fisiologiche (corpo). Le variabili emerse come potenzialmente protettive in pazienti che si trovano ad affrontare il cancro sono: il supporto sociale, l’immagine corporea, il coping e la Qualità della Vita, insieme all’indice fisiologico Heart Rate Variability (HRV; Shaffer & Venner, 2013). Il potenziale meccanismo della connessione tra queste variabili potrebbe essere spiegato dall’azione del Nervo Vago, come esposto nella Teoria Polivagale di Stephen Porges (2007; 2009). OBIETTIVI: Gli obiettivi principali di questo studio sono: 1. Valutare l’adattamento psicologico alla patologia in termini di supporto sociale percepito, immagine corporea, coping prevalente e qualità della vita in donne con cancro ovarico; 2. Valutare i valori di base HRV in queste donne; 3. Osservare se livelli più elevati di HRV sono associati ad un migliore adattamento psicologico alla patologia; 4. Osservare se una peggiore percezione dell’immagine corporea e l’utilizzo di strategie di coping disadattive sono associate ad una Qualità della Vita più scarsa. METODO: 38 donne affette da cancro ovarico, al momento della valutazione libere da patologia, sono state reclutate presso la clinica oncologica del reparto di Ginecologia dell’Azienda Ospedaliero-Universitaria di Parma, Italia. Ad ogni partecipante è stato chiesto di compilare una batteria di test composta da: MSPSS, per la valutazione del supporto sociale percepito; DAS-59, per la valutazione dell’immagine corporea; MAC, per la valutazione delle strategie di coping prevalenti utilizzate verso il cancro; EORTC-QLQ30, per la valutazione della Qualità della Vita. Per ogni partecipante è stato registrato HRV di base utilizzando lo strumento emWave (HeartMath). RISULTATI PRINCIPALI: Rispondendo agli obiettivi 1 e 2, in queste donne si è rilevato una alto tasso di supporto sociale percepito, in particolare ricevuto dalla persona di riferimento. L’area rivelatasi più critica nel supporto sociale è quella degli amici. Per quanto riguarda l’immagine corporea, la porzione di campione dai 30 ai 61 anni, ha delle preoccupazioni globali legate all’immagine corporea paragonabili ai dati provenienti dalla popolazione generale con preoccupazioni riguardo l’aspetto corporeo. Invece, nella porzione di campione dai 61 anni in su, il pattern di disagio verso l’aspetto fisico sembra decisamente peggiorare. Inoltre, in questo campione, si è rilevato un disagio globale verso l’immagine corporea significativamente più alto rispetto ai valori normativi presenti in letteratura riferiti a donne con cancro al seno con o senza mastectomia (rispettivamente t(94)= -4.78; p<0.000001; t(110)= -6.81;p<0.000001). La strategia di coping più utilizzata da queste donne è lo spirito combattivo, seguito dal fatalismo. Questo campione riporta, inoltre, una Qualità della Vita complessivamente soddisfacente, con un buon livello di funzionamento sociale. L’area di funzionalità più critica risulta essere il funzionamento emotivo. Considerando i sintomi prevalenti, i più riferiti sono affaticamento, disturbi del sonno e dolore. Per definire, invece, il pattern HRV, sono stati confrontati i dati del campione con quelli presenti in letteratura, riguardanti donne con cancro ovarico. Il campione valutato in questo studio, ha un HRV SDNN (Me=28.2ms) significativamente più alto dell’altro gruppo. Tuttavia, confrontando il valore medio di questo campione con i dati normativi sulla popolazione sana (Me=50ms), i nostri valori risultano drasticamente più bassi. In ultimo, donne che hanno ricevuto diagnosi di cancro ovarico in età fertile, sembrano avere maggiore HRV, migliore funzionamento emotivo e minore sintomatologia rispetto alle donne che hanno ricevuto diagnosi non in età fertile. Focalizzando l’attenzione sulla ricerca di relazioni significative tra le variabili in esame (obiettivo 3 e 4) sono state trovate numerose correlazioni significative tra: l’età e HRV, supporto percepito , Qualità della Vita; Qualità della Vita e immagine corporea, supporto sociale, strategie di coping; strategie di coping e immagine corporea, supporto sociale; immagine corporea e supporto sociale; HRV e supporto sociale, Qualità della Vita. Per verificare la possibile connessione causale tra le variabili considerate, sono state applicate regressioni lineari semplici e multiple per verificare la bontà del modello teorico. Si è rilevato che HRV è significativamente positivamente influenzata dal supporto percepito dalla figura di riferimento, dal funzionamento di ruolo, dall’immagine corporea totale. Invece risulta negativamente influenzata dal supporto percepito dagli amici e dall’uso di strategie di coping evitanti . La qualità della vita è positivamente influenzata da: l’immagine corporea globale e l’utilizzo del fatalismo come strategia di coping prevalente. Il funzionamento emotivo è influenzato dal supporto percepito dalla figura di riferimento e dal fatalismo. DISCUSSIONI E CONCLUSIONI: Il campione Italiano valutato, sembra essere a metà strada nell’adattamento dello stato psicologico e dell’equilibrio neurovegetativo al cancro. Sicuramente queste donne vivono una vita accettabile, in quanto sopravvissute al cancro, ma sembra anche che portino con sé preoccupazioni e difficoltà, in particolare legate all’accettazione della loro condizione di sopravvissute. Infatti, il migliore adattamento si riscontra nelle donne che hanno avuto peggiori condizioni in partenza: stadio del cancro avanzato, più giovani, con diagnosi ricevuta in età fertile. Pertanto, è possibile suggerire che queste condizioni critiche forzino queste donne ad affrontare apertamente il cancro e la loro situazione di sopravvissute al cancro, portandole ad “andare avanti” piuttosto che “tornare indietro”. Facendo riferimento alle connessioni tra variabili psicologiche e fisiologiche in queste donne, si è evidenziato che HRV è influenzata dalla presenza di figure significative ma, in particolare, è presumibile che sia influenzata da un’appropriata condivisione emotiva con queste figure. Si è anche evidenziato che poter continuare ad essere efficaci nel proprio contesto personale si riflette in un maggiore HRV, probabilmente in quanto permette di preservare il senso di sé, riducendo in questo modo lo stress derivante dall’esperienza cancro. Pertanto, HRV in queste donne risulta associato con un migliore adattamento psicologico. Inoltre, si è evidenziato che in queste donne la Qualità della Vita è profondamente influenzata dalla percezione dell’immagine corporea. Si tratta di un aspetto innovativo che è stato rilevato in questo campione e che, invece, nei precedenti studi non è stato indagato. In ultimo, la strategia di coping fatalismo sembra essere protettiva e sembra facilitare il processo di accettazione del cancro. Si spera sinceramente che le ricerche future possano superare i limiti del presente studio, come la scarsa numerosità e l’uso di strumenti di valutazione che, per alcuni aspetti come la scala Evitamento nel MAC, non centrano totalmente il target di indagine. Le traiettorie future di questo studio sono: aumentare il numero di osservazioni, reclutando donne in diversi centri specialistici in diverse zone d’Italia; utilizzare strumenti più specifici per valutare i costrutti in esame; valutare se un intervento di supporto centrato sul miglioramento di HRV (come HRV Biofeedback) può avere una ricaduta positiva sull’adattamento emotivo e la Qualità della Vita.

Studio Integrato Geomorfologico-Geofisico dell'Area Epicentrale del Terremoto del 20 Maggio 2012 (Mw 5.9) in Emilia-Romagna

La Sequenza Sismica Emiliana del 2012 ha colpito la zona compresa tra Mirandola e Ferrara con notevoli manifestazioni cosismiche e post-sismiche secondarie, soprattutto legate al fenomeno della liquefazione delle sabbie e alla formazione di fratturazioni superficiali del terreno. A fronte del fatto che la deformazione principale, osservata tramite tecniche di remote-sensing, ha permesso di individuare la posizione della struttura generatrice, ci si è interrogati sul rapporto tra strutture profonde e manifestazioni secondarie superficiali. In questa tesi è stato svolto un lavoro di integrazione di dati a varia scala, dalla superficie al sottosuolo, fino profondità di alcuni chilometri, per analizzare il legame tra le strutture geologiche che hanno generato il sisma e gli effetti superficiali percepiti dagli osservatori. Questo, non solo in riferimento allo specifico del sisma emiliano del 2012, ma al fine di trarre utili informazioni in una prospettiva storica e geologica sugli effetti di un terremoto “tipico”, in una regione dove le strutture generatrici non affiorano in superficie. Gli elementi analizzati comprendono nuove acquisizioni e rielaborazioni di dati pregressi, e includono cartografie geomorfologiche, telerilevamenti, profili sismici a riflessione superficiale e profonda, stratigrafie e informazioni sulla caratterizzazione dell’area rispetto al rischio sismico. Parte dei dati di nuova acquisizione è il risultato dello sviluppo e la sperimentazione di metodologie innovative di prospezione sismica in corsi e specchi d’acqua continentali, che sono state utilizzate con successo lungo il Cavo Napoleonico, un canale artificiale che taglia ortogonalmente la zona di massima deformazione del sisma del 20 Maggio. Lo sviluppo della nuova metodologia di indagine geofisica, applicata ad un caso concreto, ha permesso di migliorare le tecniche di imaging del sottosuolo, oltre a segnalare nuove evidenze co-sismiche che rimanevano nascoste sotto le acque del canale, e a fornire elementi utili alla stratigrafia del terreno. Il confronto tra dati geofisici e dati geomorfologici ha permesso di cartografare con maggiore dettaglio i corpi e le forme sedimentarie superficiali legati alla divagazione fluviale dall’VIII sec a.C.. I dati geofisici, superficiali e profondi, hanno evidenziato il legame tra le strutture sismogeniche e le manifestazioni superficiali seguite al sisma emiliano. L’integrazione dei dati disponibili, sia nuovi che da letteratura, ha evidenziato il rapporto tra strutture profonde e sedimentazione, e ha permesso di calcolare i tassi geologici di sollevamento della struttura generatrice del sisma del 20 Maggio. I risultati di questo lavoro hanno implicazioni in vari ambiti, tra i quali la valutazione del rischio sismico e la microzonazione sismica, basata su una caratterizzazione geomorfologico-geologico-geofisica dettagliata dei primi 20 metri al di sotto della superficie topografica. Il sisma emiliano del 2012 ha infatti permesso di riconoscere l’importanza del substrato per lo sviluppo di fenomeni co- e post-sismici secondari, in un territorio fortemente eterogeneo come la Pianura Padana.

Grid Approach to Satellite Monitoring Systems Integration

This paper highlights the challenges of satellite monitoring systems integration, in particular based on Grid platform, and reviews possible solutions for these problems. We describe integration issues on different levels: data integration level and task management level (job submission in terms of Grid). We show example of described technologies for integration of monitoring systems of Ukraine (National Space Agency of Ukraine, NASU) and Russia (Space Research Institute RAS, IKI RAN). Another example refers to the development of InterGrid infrastructure that integrates several regional and national Grid systems: Ukrainian Academician Grid (with Satellite data processing Grid segment) and RSGS Grid (Chinese Academy of Sciences).

Discovering biomarkers for antidepressant response:protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Heterogeneous data source access for mobile devices

The mediator software architecture design has been developed to provide data integration and retrieval in distributed, heterogeneous environments. Since the initial conceptualization of this architecture, many new technologies have emerged that can facilitate the implementation of this design. The purpose of this thesis was to show that a mediator framework supporting users of mobile devices could be implemented using common software technologies available today. In addition, the prototype was developed with a view to providing a better understanding of what a mediator is and to expose issues that will have to be addressed in full, more robust designs. The prototype developed for this thesis was implemented using various technologies including: Java, XML, and Simple Object Access Protocol (SOAP) among others. SOAP was used to accomplish inter-process communication. In the end, it is expected that more data intensive software applications will be possible in a world with ever-increasing demands for information.

Integrating structured data using property precedence

Data integration systems offer uniform access to a set of autonomous and heterogeneous data sources. One of the main challenges in data integration is reconciling semantic differences among data sources. Approaches that been used to solve this problem can be categorized as schema-based and attribute-based. Schema-based approaches use schema information to identify the semantic similarity in data; furthermore, they focus on reconciling types before reconciling attributes. In contrast, attribute-based approaches use statistical and structural information of attributes to identify the semantic similarity of data in different sources. This research examines an approach to semantic reconciliation based on integrating properties expressed at different levels of abstraction or granularity using the concept of property precedence. Property precedence reconciles the meaning of attributes by identifying similarities between attributes based on what these attributes represent in the real world. In order to use property precedence for semantic integration, we need to identify the precedence of attributes within and across data sources. The goal of this research is to develop and evaluate a method and algorithms that will identify precedence relations among attributes and build property precedence graph (PPG) that can be used to support integration.

Using individual tracking data to validate the predictions of species distribution models

The authors would like to thank the College of Life Sciences of Aberdeen University and Marine Scotland Science which funded CP's PhD project. Skate tagging experiments were undertaken as part of Scottish Government project SP004. We thank Ian Burrett for help in catching the fish and the other fishermen and anglers who returned tags. We thank José Manuel Gonzalez-Irusta for extracting and making available the environmental layers used as environmental covariates in the environmental suitability modelling procedure. We also thank Jason Matthiopoulos for insightful suggestions on habitat utilization metrics as well as Stephen C.F. Palmer, and three anonymous reviewers for useful suggestions to improve the clarity and quality of the manuscript.

Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line

Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.

Decisions, decisions everywhere (in the open data era).

Abstract: Decision support systems have been widely used for years in companies to gain insights from internal data, thus making successful decisions. Lately, thanks to the increasing availability of open data, these systems are also integrating open data to enrich decision making process with external data. On the other hand, within an open-data scenario, decision support systems can be also useful to decide which data should be opened, not only by considering technical or legal constraints, but other requirements, such as "reusing potential" of data. In this talk, we focus on both issues: (i) open data for decision making, and (ii) decision making for opening data. We will first briefly comment some research problems regarding using open data for decision making. Then, we will give an outline of a novel decision-making approach (based on how open data is being actually used in open-source projects hosted in Github) for supporting open data publication. Bio of the speaker: Jose-Norberto Mazón holds a PhD from the University of Alicante (Spain). He is head of the "Cátedra Telefónica" on Big Data and coordinator of the Computing degree at the University of Alicante. He is also member of the WaKe research group at the University of Alicante. His research work focuses on open data management, data integration and business intelligence within "big data" scenarios, and their application to the tourism domain (smart tourism destinations). He has published his research in international journals, such as Decision Support Systems, Information Sciences, Data & Knowledge Engineering or ACM Transaction on the Web. Finally, he is involved in the open data project in the University of Alicante, including its open data portal at http://datos.ua.es