The focus of this thesis is to investigate resilience at an organisational level. The research aims to identify and establish the features of resilience within the response of an organisation to disruptive and crisis events. Natural disasters, pandemic disease, terrorist attacks, economic recession, equipment failure and human error can all pose both a potentially unpredictable and severe threat to the continuity of an organisation's operations. As a result, disruptive events highlight the need to develop robust and resilient organisational and infrastructural systems capable of adapting and overcoming complex disruptive events.

Electrophysiological recordings are a valuable tool for neuroscience in order to monitor the activity of multiple or even single neurons. Significant insights into the nervous system have been gained by analyses of resulting data; in particular, many findings were gained from spike trains whose correlations can give valuable indications about neural interplay. But detecting, specifying, and representing neural interactions is mathematically challenging. Further, recent advances of recording techniques led to an increase in volume of collected data, which often poses additional computational problems. These developments call for new, improved methods in order to extract crucial information. The matter of this thesis is twofold: It presents a novel method for the analysis of neural spike train data, as well as a generic framework in order to assess the new and related techniques. The new computational method, the Snap Shot Score, can be used to inspect spike trains with respect to temporal dependencies, which are visualised as an information flow network. These networks can specify the relationships in the data, indicate changes in dependencies, and point to causal interactions. The Snap Shot Score is demonstrated to reveal plausible networks both in a variety of simulations and for real data, which indicate its value for understanding neural dynamics. Additional to the Snap Shot Score, a neural simulation framework is suggested, which facilitates the assessment of neural network inference techniques in a highly automated fashion. Due to a new formal concept to rate learned networks, the framework can be used to test techniques under partial observability conditions. In the presence of hidden units quantification of results has been a tedious task that had to be done by hand, but which can now be automated. Thereby high throughput assessments become possible, which facilitate a comprehensive simulation-based characterisation of new methods.

Orientador: Fernando Sebastián Baldi Rey / Resumo: A compreensão de processos regulatórios e organização molecular dos organismos vivos progrediram consideravelmente na última década. As metodologias também evoluíram com o sequenciamento de DNA e RNA e de ferramentas genômicas permitindo a análise de centenas ou milhares de genes, proteínas ou metabólitos. O uso simultâneo dessas informações auxilia na obteção de informações relevantes sobre as variáveis que envolvem as variações fenotípicas de características de interesse. O objetivo do presente estudo foi integrar dados fenotípicos, genotípicos e transcriptômicos em busca de aprimoramento sobre os mecanismos genéticos e metabólicos que determinam o perfil de ácidos graxos na carne de bovinos Nelore, a fim de contribuir para o melhoramento da composição de ácidos graxos da carne. Foram utilizados machos da raça Nelore terminados em confinamento, abatidos com média de idade 24 meses. Amostras do músculo L. thoracis, entre a 12ª a 13ª costela foram coletadas para as análises de perfil de ácidos graxos, extração de RNA e de DNA. Os resultados foram apresentados nos capítulos 2 e 3. No capítulo 2, o objetivo foi identificar genes diferencialmente expressos pelo método RNA-seq e perfil de ácidos graxos no músculo L. thoracis com uso de componentes principais (principal components: PC). Foram selecionados dois grupos de 10 animais, os quais possuíam valores de PC1 e PC2 extremos (Alto x Baixo) para os grupos somatórios de ácidos graxos (AG): ácidos graxos saturados (AGS), ácidos g... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The understanding of regulatory processes and molecular organization of organisms has progressed considerably in the last 10 years.The methodologies also evolved with the sequencing of DNA, RNA and genomic tools allowing the analysis a lot of genes, proteins or metabolites. The simultaneous use of this information should help to obtain relevant information about the variables that result the phenotypic variations of traits of interest. The objective of the present study was to integrate phenotypic, genotypic and transcriptomic studies in order to clarify the genetic and metabolic mechanisms that determine the fatty acid profile in Nelore beef, in order to contribute to the improvement of the fatty acid composition of the meat. Nelore males were used in feedlot, coming from farms that integrate three breeding programs and slaughtered with an average of 24 months. Samples of the L. thoracis muscle between the 12th to 13th rib were collected for analysis of fatty acid profile, RNA and DNA extraction. The results were presented in chapters 2 and 3. In chapter 2, the objective was to identify genes differentially expressed by RNA-seq method and fatty acid profile in the L. thoracis muscle with the use of Principal Components (PC). Two groups of 10 animals were selected, which had PC1 and PC2 extreme values (High x Low) for the fatty acids (FA) groups: saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), omega 3 (n-3) and omega 6 (n-6... (Complete abstract click electronic access below) / Doutor