The Parallelism Motifs of Genomic Data Analysis

Genomic data sets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share this data with the research community, but some of these genomic data analysis problems require large scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high end parallel systems today and place different requirements on programming support, software libraries, and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high performance genomics analysis, including alignment, profiling, clustering, and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or motifs that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing

Mini is beautiful:Playing serious mini-games to facilitate collective learning on complex urban processes

Spatial planning projects can be conceived as processes of collective learning. Planners have been looking at games and playful approaches to support these processes. Considering that planning projects are long and complex, we propose to not reason for single, full-fledged and all-encompassing games, but instead work with strings of, so-called, serious mini-games that each addresses a specific learning goal, guided by a collective learning model. This paper conceptualizes a toolbox to support the development and contextualization of such strings of serious mini-games

Simple networks on complex cellular automata: From de Bruijn diagrams to jump-graphs

We overview networks which characterise dynamics in cellular automata. These networks are derived from one-dimensional cellular automaton rules and global states of the automaton evolution: de Bruijn diagrams, subsystem diagrams, basins of attraction, and jump-graphs. These networks are used to understand properties of spatially-extended dynamical systems: emergence of non-trivial patterns, self-organisation, reversibility and chaos. Particular attention is paid to networks determined by travelling self-localisations, or gliders.Comment: 25 pages, 14 figure

Capturing interpersonal coordination processes in association football : from dyads to collectives

Doutoramento em Motricidade Humana, na especialidade de Ciências do DesportoThe purpose of this thesis was to investigate how football performers coordinate their behaviours in different levels of social organisation. We began with a position paper proposing the re-conceptualisation of sport teams as functional integrated superorganisms to frame a deeper understanding of the interpersonal coordination processes emerging between team players. Time-motion analysis procedures and innovative tools were developed and presented in order to capture the superorganismic properties of sports teams and the interpersonal coordination tendencies developed by players. These tendencies were captured and analysed in representative 1vs1 and 3vs3 sub-phases, as well as in the 11-a-side game format. Data showed higher levels of variability at the individual level compared to the team level. This finding suggested that micro-variability may contribute to stabilise the behavioural dynamics at the collective level. Moreover, the specificities of the interpersonal coordination tendencies displayed within attacking-defending dyads demonstrated to have influenced the performance outcome. Attacking players tend to succeed when they were more synchronised in space and time with the defenders, and their interaction were more unpredictable/irregular. Besides, the time-evolving dynamics of the collective behaviours (i.e., at 11-a-side level) during competitive football performance indicated a tendency for an increase in the predictability (i.e., more regularity). These data were interpreted as evidencing co-adaptation processes between opponent players, which suggest that team players may shift from prevalent explorative and irregular behaviours to more predictable behaviours emerging due changes in their functional movement possibilities. However, some game events such as goals scored, halftime and stoppages in play seemed to break this continuum and acted as relevant performance constraints.FCT - Fundação para Ciência e a Tecnologi

A meta-analysis of randomness in human behavioral research

This work analyzes the concept of randomness in binary sequences from three different perspectives: mathematically, statistically, and psychologically and examines the research on human perception of randomness and the question of whether or not humans can simulate random behavior. Generally, research shows that human subjects have great difficulty producing random sequences, even when they are instructed and motivated. We survey some of the literature and present some leading theoretical proposals. Finally, we present some basic statistical tests that can be used to evaluate randomness in a given binary sequence