Moving forward with combinatorial interaction testing

Combinatorial interaction testing (CIT) is an efficient and effective method of detecting failures that are caused by the interactions of various system input parameters. In this paper, we discuss CIT, point out some of the difficulties of applying it in practice, and highlight some recent advances that have improved CIT’s applicability to modern systems. We also provide a roadmap for future research and directions; one that we hope will lead to new CIT research and to higher quality testing of industrial systems

VRCC-3D+: Qualitative spatial and temporal reasoning in 3 dimensions

Qualitative Spatial Reasoning (QSR) has varying applications in Geographic Information Systems (GIS), visual programming language semantics, and digital image analysis. Systems for spatial reasoning over a set of objects have evolved in both expressive power and complexity, but implementations or usages of these systems are not common. This is partially due to the computational complexity of the operations required by the reasoner to make informed decisions about its surroundings. These theoretical systems are designed to focus on certain criteria, including efficiency of computation, ease of human comprehension, and expressive power. Sadly, the implementation of these systems is frequently left as an exercise for the reader. Herein, a new QSR system, VRCC-3D+, is proposed that strives to maximize expressive power while minimizing the complexity of reasoning and computational cost of using the system. This system is an evolution of RCC-3D; the system and implementation are constantly being refined to handle the complexities of the reasoning being performed. The refinements contribute to the accuracy, correctness, and speed of the implementation. To improve the accuracy and correctness of the implementation, a way to dynamically change error tolerance in the system to more accurately reflect what the user sees is designed. A method that improves the speed of determining spatial relationships between objects by using composition tables and decision trees is introduced, and improvements to the system itself are recommended; by streamlining the relation set and enforcing strict rules for the precision of the predicates that determine the relationships between objects. A potential use case and prototype implementation is introduced to further motivate the need for implementations of QSR systems, and show that their use is not precluded by computational complexity. --Abstract, page iv

Study of lipid bilayer behaviour modified by substrate interactions

Biological membranes rarely exist as free-floating structures but are often confined and supported by various cellular assemblies such as the cytoskeleton and the extracellular matrix. It has already been shown that biological and polymeric substrates can modulate the morphology and response to various stimuli of supported lipid bilayers significantly. The interaction between such structures and the membrane are obviously important yet remain poorly understood even in minimal or synthetic systems. The work of this thesis utilises a variety of fluorescence microscopy and atomic force microscopy (AFM) techniques to investigate the behaviour and structure of supported lipid bilayers, in particular how interfacial features of their support substrate influence and modulate their morphology and biophysical properties. First, surface modification of polydimethylsiloxane is systematically explored, in particular how the interfacial properties of such a polymer substrate can be modified to create fully and partially plasma-treated interfaces that stably support lipid bilayers. Lipid patch formation on such substrates is then investigated, revealing that the membrane undergoes significant morphological reorganisation after vesicle fusion has completed forming a lipid patch. The underlying mechanisms can be altered by substrate interactions following different pathways for fully and partially plasma-treated PDMS substrates. Furthermore, partially plasma-treated substrates are demonstrated to be capable of specifically depleting cholesterol from supported lipid membranes, while stably supporting the other remaining phospholipid species. Studies of cholesterol depletion of lipid patches possessing liquid-ordered and disordered domains reveal a disruption in domains structure, with the partitioning of fluorescent dyes into regions from which they were previously excluded. This structure perturbation was found to be reversible upon the reinsertion of cholesterol into the bilayer. Many of the discussed mechanisms are only observed in the presence of a substrate, emphasising the importance of substrate interactions in both functional biomembranes and the development of supported membrane technologie

Frequent itemset mining on multiprocessor systems

Frequent itemset mining is an important building block in many data mining applications like market basket analysis, recommendation, web-mining, fraud detection, and gene expression analysis. In many of them, the datasets being mined can easily grow up to hundreds of gigabytes or even terabytes of data. Hence, efficient algorithms are required to process such large amounts of data. In recent years, there have been many frequent-itemset mining algorithms proposed, which however (1) often have high memory requirements and (2) do not exploit the large degrees of parallelism provided by modern multiprocessor systems. The high memory requirements arise mainly from inefficient data structures that have only been shown to be sufficient for small datasets. For large datasets, however, the use of these data structures force the algorithms to go out-of-core, i.e., they have to access secondary memory, which leads to serious performance degradations. Exploiting available parallelism is further required to mine large datasets because the serial performance of processors almost stopped increasing. Algorithms should therefore exploit the large number of available threads and also the other kinds of parallelism (e.g., vector instruction sets) besides thread-level parallelism. In this work, we tackle the high memory requirements of frequent itemset mining twofold: we (1) compress the datasets being mined because they must be kept in main memory during several mining invocations and (2) improve existing mining algorithms with memory-efficient data structures. For compressing the datasets, we employ efficient encodings that show a good compression performance on a wide variety of realistic datasets, i.e., the size of the datasets is reduced by up to 6.4x. The encodings can further be applied directly while loading the dataset from disk or network. Since encoding and decoding is repeatedly required for loading and mining the datasets, we reduce its costs by providing parallel encodings that achieve high throughputs for both tasks. For a memory-efficient representation of the mining algorithms’ intermediate data, we propose compact data structures and even employ explicit compression. Both methods together reduce the intermediate data’s size by up to 25x. The smaller memory requirements avoid or delay expensive out-of-core computation when large datasets are mined. For coping with the high parallelism provided by current multiprocessor systems, we identify the performance hot spots and scalability issues of existing frequent-itemset mining algorithms. The hot spots, which form basic building blocks of these algorithms, cover (1) counting the frequency of fixed-length strings, (2) building prefix trees, (3) compressing integer values, and (4) intersecting lists of sorted integer values or bitmaps. For all of them, we discuss how to exploit available parallelism and provide scalable solutions. Furthermore, almost all components of the mining algorithms must be parallelized to keep the sequential fraction of the algorithms as small as possible. We integrate the parallelized building blocks and components into three well-known mining algorithms and further analyze the impact of certain existing optimizations. Our algorithms are already single-threaded often up an order of magnitude faster than existing highly optimized algorithms and further scale almost linear on a large 32-core multiprocessor system. Although our optimizations are intended for frequent-itemset mining algorithms, they can be applied with only minor changes to algorithms that are used for mining of other types of itemsets

Interleaflet and Substrate Coupling in Phospholipid Bilayers

Since the existence of lateral organisation in the cell membrane was first proposed by Erwin London in 1997, much has been discovered about the complex behaviour of lipid bilayers. Whilst some membrane proteins involved in signalling are almost as mobile as lipid molecules, such as the photoreceptor protein rhodopsin, others such as the peripheral glycoprotein fibronectin are virtually static. This has been linked to the existence of phase separated micro-domains, sometimes known as lipid rafts, in model systems. However, there are still many open questions, including the effect of asymmetry and curvature on bilayers. Domains in the two leaflets of a model bilayer always align, or register. Conversely, the plasma membrane is asymmetric in composition, which implies that different phases can exist across the bilayer midplane, known as anti-registration. Hydrophobic mismatch at phase boundaries should favour a fully anti-registered bilayer in model systems, implying an interleaflet coupling force drives registration. In this thesis, hydrophobic mismatch between phases is controlled, with anti-registered domains forming at a mismatch of 8 carbons per leaflet. A coupling free energy of 0.021 kBT/nm2 was determined, in close agreement with the only other experimental study using a different methodology, and refining the values found via simulation. Methods are explored to induce anti-registration with lower mismatch, and to characterise the orientation of the anti-registered states. Arising from this work is a greater understanding of how substrate choice for supported bilayers greatly affects phase behaviour. Glass, used in fluorescence microscopy experiments, and PDMS (Polydimethylsiloxane), used to create flexible and curved bilayer substrates, result in nanoscale domain formation compared to micro-scale domains on atomically flat mica. This difference is investigated and it is found that the hydrodynamic motion of domains is hindered by rougher substrates, having great implications for the study and understanding of supported lipid bilayers