Geometric simplicial embeddings of arc-type graphs

In this paper, we investigate a family of graphs associated to collections of arcs on surfaces. These {\it multiarc graphs} naturally interpolate between arc graphs and flip graphs, both well studied objects in low dimensional geometry and topology. We show a number of rigidity results, namely showing that, under certain complexity conditions, that simplicial maps between them only arise in the "obvious way". We also observe that, again under necessary complexity conditions, subsurface strata are convex. Put together, these results imply that certain simplicial maps always give rise to convex images.Comment: 18 pages, 2 figure

Introduction to Vassiliev Knot Invariants

This book is a detailed introduction to the theory of finite type (Vassiliev) knot invariants, with a stress on its combinatorial aspects. It is intended to serve both as a textbook for readers with no or little background in this area, and as a guide to some of the more advanced material. Our aim is to lead the reader to understanding by means of pictures and calculations, and for this reason we often prefer to convey the idea of the proof on an instructive example rather than give a complete argument. While we have made an effort to make the text reasonably self-contained, an advanced reader is sometimes referred to the original papers for the technical details of the proofs. Version 3: some typos and inaccuracies are corrected.Comment: 512 pages, thousands picture

The analysis of organic ballistic materials

Both gas chromatography/mass chromatography (GC/MS) and solid phase microextraction (SPME) methodologies have been developed for the extraction and analysis of compounds encountered in relation to unburned propellant powders from firearm ammunitions. These methods allowed the detection of 27 compounds that may be present in organic gunshot residues (OGSR). The developed methodologies were applied to the analysis of unburned propellant and OGSR from spent ammunition cartridges and fabrics subjected to firearm discharges. Throughout the study a total of 16 ammunition types where investigated. Work carried out on the suitability of various SPME fibre types showed that 65μm PDMS/DVB was the most appropriate type for extracting the compounds of interest. Extractions carried out on unburned propellant powders showed that all of the ammunitions analysed produced different chromatographic results. All of the ammunitions in the analysed population could be differentiated from one another; it was determined to be highly unlikely that false matches could occur

Applications of topology in magnetic fields

This thesis concerns applications of topology in magnetic fields. First, we examine the influence of writhe in the stretch-twist-fold dynamo. We consider a thin flux tube distorted by simple stretch, twist, and fold motions and calculate the helicity and energy spectra. The writhe number assists in the calculations, as it tells us how much the internal twist changes as the tube is distorted. In addition it provides a valuable diagnostic for the degree of distortion. Non mirror-symmetric dynamos typically generate magnetic helicity of one sign on large-scales and of the opposite sign on small-scales. The calculations presented here confirm the hypothesis that the large-scale helicity corresponds to writhe and the small-scale corresponds to twist. In addition, the writhe helicity spectrum exhibits an interesting oscillatory behaviour. Second, we examine the effect of reconnection on the structure of a braided magnetic field. A prominent model for both heating of the solar corona and the source of small flares involves reconnection of braided magnetic flux elements. Much of this braiding is thought to occur at as yet unresolved scales, for example braiding of threads within an EUV or X-ray loop. However, some braiding may be still visible at scales accessible to Trace or the EIS imager on Hinode. We suggest that attempts to estimate the amount of braiding at these scales must take into account the degree of coherence of the braid structure. We demonstrate that simple models of braided magnetic fields which balance input of topological structure with reconnection evolve to a self-organized critical state. An initially random braid can become highly ordered, with coherence lengths obeying power law distributions. The energy released during reconnection also obeys a power law

Chaotic price dynamics of agricultural commodities

Traditionally, commodity prices have been analyzed and modeled in the context of linear generating processes. The purpose of this dissertation is to address the adequacy of this work through examination of the critical assumption of independence in the residual process of linearly specified models. As an alternative, a test procedure is developed and utilized to demonstrate the appropriateness of applying generalized conditional heteroscedastic time series models (GARCH) to agricultural commodity prices. In addition, a distinction is made between testing for independence and testing for chaos in commodity prices. The price series of interest derive from the major international agricultural commodity markets, sampled monthly over the period 1960--1994. The results of the present analysis suggest that for bananas, beef, coffee, soybeans, wool and wheat seasonally adjusted growth rates, ARCH-GARCH models account for some of the non-linear dependence in these commodity price series. As an alternative to the ARCH-GARCH models, several neural network models were estimated and in some cases outperformed the ARCH family of models in terms of forecast ability. This further demonstrated the nonlinearity present in these time series. Although, further examination is needed, all prices were found to be non-linearly dependent. It was determined by use of different statistical measures for testing for deterministic chaos that wheat prices may be an example of such behavior. Therefore, their may be something to be gained in terms of short-run forecast accuracy by using semi-parametric modeling approaches as applied to wheat prices

The Mechanical Properties of Carbon Fibre With Glass Fibre Hybrid Reinforced Plastics

Merged with duplicate record 10026.1/2475 on 15.03.2017 by CS (TIS)Fibre composite hybrid materials are generally plastics reinforced with two different fibre species. The combination of these three materials (in this thesis they are carbon fibres, glass fibres and polyester resin) allows a balance to be achieved between the properties of the two monofibre composites. Over the fifteen years since the introduction of continuous carbon fibre as a reinforcement, there has been considerable speculation about the "hybrid effect", a synergistic strengthening of reinforced plastics with two fibres when compared with the strength predicted from a weighted average from the component composites. A new equation is presented which predicts the extent of the hybrid effect. Experiments with a variety of carbon-glass hybrids were undertaken to examine the validity of the theory and the effect of the degree of inter-mixing of the fibres. The classification and quantification of the hybrid microstructures was examined with a view to crosscorrelation of the intimacy of mixing and the strength. Mechanical tests were monitored with acoustic emission counting and acoustic emission amplitude distribution equipment. Some specimens were subjected to one thermal cycle to liquid nitrogen temperature prior to testing. Fracture surfaces were examined in the scanning electron microscope. Numerical analysis by finite element methods was attempted. A constant strain triangular element was used initially, but in the later analyses the PAFEC anisotropic isoparametric quadrilateral elements were used. The system was adapted so that a \Ir singularity could be modelled, and post processor software was written to allow nodal averaging of the stresses and the presentation of this data graphically as stress contour maps

Sustainability in design: now! Challenges and opportunities for design research, education and practice in the XXI century

Copyright @ 2010 Greenleaf PublicationsLeNS project funded by the Asia Link Programme, EuropeAid, European Commission

THE SUM OF THE PARTS: HEURISTIC STRATEGIES IN SYSTEMS BIOLOGY

This thesis addresses philosophical issues regarding the young field of systems biology. Systems biologists commonly present their approach as a superior alternative to \u2018traditional\u2019 molecular biology that they describe as being overly \u2018reductionist.\u2019 However, the heterogeneity of systems approaches makes it difficult to understand what \u2018the\u2019 approach of systems biology exactly consists in. Here I propose a framework for the systematic comparison of different scientific approaches in biology. I argue that the relevant issues arise at the level of strategies of mechanistic discovery. These strategies are best understood as \u2018heuristic,\u2019 that is, as tools to reduce the complexity of a given research task. While having the virtue of making the search for mechanisms more efficient, heuristic strategies rely on particular assumptions about the system under study. This can introduce bias and lead biologists to underestimate the actual complexity of the system. Framing the analysis in terms of heuristic strategies pro- vides a precise way to distinguish between different approaches and to better understand the ongoing rhetoric battles. I discuss a number of case studies, both from molecular biology and from systems biology. I argue that the traditional approach of molecular biology relies on a relatively well-defined set of heuristics that corresponds to a particular idea of the organization and complexity of living systems. Approaches in systems biology relax some of the underlying assumptions of the traditional approach, notably by applying tools of mathematical modeling, but they have to make use of alternative heuristics in order to be efficient. As a result, they rely on different assumptions about organization and complexity. My detailed discussion of case studies reveals that there are a number of different systems approaches that can be distinguished by analyzing their heuristic character. The ambition of systems biologists to build formal models of biological mechanisms, however, has the virtue of making many of the underlying assumptions explicit which helps to recognize and reduce bias, and moreover facilitates the integration of different approaches. Some of the issues touched upon also have relevance for more general questions in the philosophy of biology. Assumptions about biological organization and complexity can heavily influence what we think of as a good scientific explanation. Since systems biology puts into question some of these assumptions, we might be forced to revise our ideas about mechanistic explanation. I argue that notably the concept of biological robustness has to be taken into account by philosophers who are thinking about mechanisms in biology

Modelling of Electrical Appliance Signatures for Energy Disaggregation

The rapid development of technology in the electrical sector within the last 20 years has led to growing electric power needs through the increased number of electrical appliances and automation of tasks. In contrary, reduction of the overall energy consumption as well as efficient energy management are needed, in order to reduce global warming and meet the global climate protection goals. These requirements have led to the recent adoption of smart-meters and smart-grids, as well as to the rise of Non-Intrusive Load Monitoring. Non-Intrusive Load Monitoring aims to extract the energy consumption of individual electrical appliances through disaggregation of the total power consumption as measured by a single smart meter at the inlet of a household. Therefore, Non-Intrusive Load Monitoring is a highly under-determined problem which aims to estimate multiple variables from a single observation, thus is impossible to be solved analytical. In order to find accurate estimates of the unknown variables three fundamentally different approaches, namely deep-learning, pattern matching and single-channel source separation, have been investigated in the literature in order to solve the Non-Intrusive Load Monitoring problem. While Non-Intrusive Load Monitoring has multiple areas of application, including energy reduction through consumer awareness, load scheduling for energy cost optimization or reduction of peak demands, the focus of this thesis is especially on the performance of the disaggregation algorithm, the key part of the Non-Intrusive Load Monitoring architecture. In detail, optimizations are proposed for all three architectures, while the focus lies on deep-learning based approaches. Furthermore, the transferability capability of the deep-learning based approach is investigated and a NILM specific transfer architecture is proposed. The main contribution of the thesis is threefold. First, with Non-Intrusive Load Monitoring being a time-series problem incorporation of temporal information is crucial for accurate modelling of the appliance signatures and the change of signatures over time. Therefore, previously published architectures based on deep-learning have focused on utilizing regression models which intrinsically incorporating temporal information. In this work, the idea of incorporating temporal information is extended especially through modelling temporal patterns of appliances not only in the regression stage, but also in the input feature vector, i.e. by using fractional calculus, feature concatenation or high-frequency double Fourier integral signatures. Additionally, multi variance matching is utilized for Non-Intrusive Load Monitoring in order to have additional degrees of freedom for a pattern matching based solution. Second, with Non-Intrusive Load Monitoring systems expected to operate in realtime as well as being low-cost applications, computational complexity as well as storage limitations must be considered. Therefore, in this thesis an approximation for frequency domain features is presented in order to account for a reduction in computational complexity. Furthermore, investigations of reduced sampling frequencies and their impact on disaggregation performance has been evaluated. Additionally, different elastic matching techniques have been compared in order to account for reduction of training times and utilization of models without trainable parameters. Third, in order to fully utilize Non-Intrusive Load Monitoring techniques accurate transfer models, i.e. models which are trained on one data domain and tested on a different data domain, are needed. In this context it is crucial to transfer time-variant and manufacturer dependent appliance signatures to manufacturer invariant signatures, in order to assure accurate transfer modelling. Therefore, a transfer learning architecture specifically adapted to the needs of Non-Intrusive Load Monitoring is presented. Overall, this thesis contributes to the topic of Non-Intrusive Load Monitoring improving the performance of the disaggregation stage while comparing three fundamentally different approaches for the disaggregation problem