Design automation in synthetic biology : a dual evolutionary strategy

PhD ThesisSynthetic biology o ers a new horizon in designing complex systems. However, unprecedented complexity hinders the development of biological systems to its full potential. Mitigating complexity via adopting design principles from engineering and computer science elds has resulted in some success. For example, modularisation to foster reuse of design elements, and using computer assisted design tools have helped contain complexity to an extent. Nevertheless, these design practices are still limited, due to their heavy dependence on rational decision making by human designers. The issue with rational design approaches here arises from the challenging nature of dealing with highly complex biological systems of which we currently do not have complete understanding. Systematic processes that can algorithmically nd design solutions would be better able to cope with uncertainties posed by high levels of design complexity. A new framework for enabling design automation in synthetic biology was investigated. The framework works by projecting design problems into search problems, and by searching for design solutions based on the dual-evolutionary approach to combine the respective power of design domains in vivo and in silico. Proof-of-concept ideas, software, and hardware were developed to exemplify key technologies necessary in realising the dual evolutionary approach. Some of the areas investigated as part of this research included single-cell-level micro uidics, programmatic data collection, processing and analysis, molecular devices supporting solution search in vivo, and mathematical modelling. These somewhat eclectic collection of research themes were shown to work together to provide necessary means with which to design and characterise biological systems in a systematic fashion

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

Indirect impact of landslide hazards on transportation infrastructure

This thesis examines the indirect impact of natural hazards on infrastructure networks. It addresses several key themes and issues for hazard assessment, network modelling and risk assessment using the case study of landslides impacting the national road network in Scotland, United Kingdom. The research follows four distinct stages. First, a landslide susceptibility model is developed using a database of landslide occurrences, spatial data sets and logistic regression. The model outputs indicate the terrain characteristics that are associated with increased landslide potential, including critical slope angles and south westerly aspects associated with increased rates of solar irradiance and precipitation. The results identify the hillslopes and road segments that are most prone to disruption by landslides and these indicate that 40 % (1,700 / 4,300 km) of Scotland s motorways and arterial roads (i.e. strategic road network) are susceptible to landslides and this is above previous assessments. Second, a novel user-equilibrium traffic model is developed using UK Census origin-destination tables. The traffic model calculates the additional travel time and cost (i.e. indirect impacts) caused by network disruptions due to landslide events. The model is applied to calculate the impact of historic scenarios and for sets of plausible landslide events generated using the landslide susceptibility model. Impact assessments for historic scenarios are 29 to 83 % greater than previous, including £1.2 million of indirect impacts over 15 days of disruption at the A83 Rest and Be Thankful landslide October 2007. The model results indicate that the average impact of landslides is £64 k per day of disruption, and up to £130 k per day on the most critical road segments in Scotland. In addition to identifying critical road segments with both high impact and high susceptibility to landslides, the study indicates that the impact of landslides is concentrated away from urban centres to the central and north-west regions of Scotland that are heavily reliant on road and haulage-based industries such as seasonal tourism, agriculture and craft distilling. The third research element is the development of landslide initiation thresholds using weather radar data. The thresholds classify the rainfall conditions that are most commonly associated with landslide occurrence in Scotland, improving knowledge of the physical initiation processes and their likelihood. The thresholds are developed using a novel optimal-point threshold selection technique, high resolution radar and new rain variables that provide spatio-temporally normalised thresholds. The thresholds highlight the role of the 12-day antecedent hydrological condition of soils as a precursory factor in controlling the rain conditions that trigger landslides. The new results also support the observation that landslides occur more frequently in the UK during the early autumn and winter seasons when sequences or clustering of multiple cyclonic-storm systems is common in periods lasting 5 to 15 days. Fourth, the three previous elements are combined to evaluate the landslide hazard of the strategic road segments and a prototype risk assessment model is produced - a catastrophe model. The catastrophe model calculates the annual average loss and aggregated exceedance probability of losses due to the indirect impact of landslides in Scotland. Beyond application to cost-benefit analyses for landslide mitigation efforts, the catastrophe model framework is applicable to the study of other natural hazards (e.g. flooding), combinations of hazards, and other infrastructure networks