On the integration of self-tracking data amongst quantified self members

Self-tracking, the process of recording one's own behaviours, thoughts and feelings, is a popular approach to enhance one's self-knowledge. While dedicated self-tracking apps and devices support data collection, previous research highlights that the integration of data constitutes a barrier for users. In this study we investigated how members of the Quantified Self movement---early adopters of self-tracking tools---overcome these barriers. We conducted a qualitative analysis of 51 videos of Quantified Self presentations to explore intentions for collecting data, methods for integrating and representing data, and how intentions and methods shaped reflection. The findings highlight two different intentions---striving for self-improvement and curiosity in personal data---which shaped how these users integrated data, i.e. the effort required. Furthermore, we identified three methods for representing data---binary, structured and abstract---which influenced reflection. Binary representations supported reflection-in-action, whereas structured and abstract representations supported iterative processes of data collection, integration and reflection. For people tracking out of curiosity, this iterative engagement with personal data often became an end in itself, rather than a means to achieve a goal. We discuss how these findings contribute to our current understanding of self-tracking amongst Quantified Self members and beyond, and we conclude with directions for future work to support self-trackers with their aspirations.

Context-dependent mate choice in the sand goby, Pomatoschistus minutus

The results presented in this thesis show that all females of a given population do not necessarily choose similar mating partners. Specifically, partner preferences of a fish, the sand goby (Pomatoschistus minutus), varied among individual females and depended on the social context at the time of choice. I also show that females assess multiple mate choice cues simultaneously; partner preferences were based more strongly on an interaction effect between different choice cues than on any individual cue. Furthermore, I found that preferred matings involved fitness benefits in the form of increased offspring success, but these benefits were not significantly affected by mate compatibility. Hence, mate choice for partner compatibility does not appear to be an important determinant of the observed variation in female mate preferences in this species. The context-dependency of female mating preferences revealed is relevant to how genetic variation in sexually selected traits might be maintained: as the mating success of a certain male type varies according to the choice context, directional sexual selection on male traits is shown to be less intense than generally thought making for a slower loss of genetic variation in these traits. Mating preferences of sand gobies were assessed by giving females a binary choice between males that differed in body size and/or other focus traits. These association preferences were found to be sexually motivated, repeatable and to correspond to actual mating decisions.

Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

On the expressive power of behavioral profiles

Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

Cochannel Interference in Partially Coherent Communication

Effects of cochannel interference and synchronization error of the carrier phase on the probability of error in binary communications are considered. Several bounds on the probability of error are proposed. The bounds are easy to compute and do not require complete statistical characterization of the errors. They turn out to be simple linear combinations of error probabilities with no cochannel interferences and no phase errors. Several illustrative examples are given which show that the bounds can be tight.

Liquid-liquid critical phenomena. The coexistence curve of n-heptane-acetic anhydride

The coexistence curve of the binary liquid mixture n-heptane-acetic anhydride has been determined by the observation of the transition temperatures of 76 samples over the range of compositions. The functional form of the difference in order parameter, in terms of either the mole fraction or the volume fraction, is consistent with theoretical predictions invoking the concept of universality at critical points. The average value of the order parameter, the diameter of the coexistence curve, shows an anomaly which can be described by either an exponent 1 - a, as predicted by various theories (where a is the critical exponent of the specific heat), or by an exponent 20 (where P is the coexistence curve exponent), as expected when the order parameter used is not the one the diameter of which diverges asymptotically as 1 - a.

Power Minimization for CDMA under Colored Noise

Rate-constrained power minimization (PMIN) over a code division multiple-access (CDMA) channel with correlated noise is studied. PMIN is. shown to be an instance of a separable convex optimization problem subject to linear ascending constraints. PMIN is further reduced to a dual problem of sum-rate maximization (RMAX). The results highlight the underlying unity between PMIN, RMAX, and a problem closely related to PMIN but with linear receiver constraints. Subsequently, conceptually simple sequence design algorithms are proposed to explicitly identify an assignment of sequences and powers that solve PMIN. The algorithms yield an upper bound of 2N - 1 on the number of distinct sequences where N is the processing gain. The sequences generated using the proposed algorithms are in general real-valued. If a rate-splitting and multi-dimensional CDMA approach is allowed, the upper bound reduces to N distinct sequences, in which case the sequences can form an orthogonal set and be binary +/- 1-valued.

Can an Ecdysiast Fag speak the voice of transgender? Phoenix (un)rising and the assumptions in Re Kevin revisited

"Each night the men look so surprised I change my sex before their eyes Tell me if you can What makes a man a man" - Charles Aznavour, ‘What makes a man a man (Comme ils disent)’. In (the few) Western jurisdictions in which marriage remains a forensic artefact constructed on the basis of a man|woman binary, the anatomical and heteronormative assumptions which underlie the construction of marriage remain as artificial constructs which do not map well (if indeed at all) to current social, or even medical, approaches to gender. In Re Kevin (Validity of Marriage of Transsexual) [2001] FamCA 1074, Justice Chisolm sought to recast the forensic ascription of sex against a broader set of criteria, expanding the range of sexually dimorphic anatomy used to determine sex for the purposes of marriage in Australia and incorporating observations of psycho-social gender-differentiation as factors relevant to the ultimate question for the Court — ‘What makes a man a man?’ Yet neither expansion is unproblematic. This article explores this fundamental forensic question against the background of Aznavour’s ‘Comme ils dissent’, in which the persona of un(e) stripteaseuse travesti struggles to answer precisely the same question. It concludes that Re Kevin might offer no more sophisticated an analysis of the lived reality of trans than Aznavour’s ecdysiast fag — not trans, but un travesti: "I shop and cook and sew a bit Though mum does too, I must admit I do it better."

Magnesium ion conducting, room temperature molten electrolytes

Room temperature, magnesium ion conducting binary molten electrolyte consisting of acetamide and magnesium perchlorate has been prepared and characterized. The molten liquid is very stable and shows high ionic conductivity, of the order of several mS cm(-1) at 25 degrees C with other favourable physicochemical properties. Vibrational spectroscopic studies reveal that the free ion concentration is higher than that of ion pairs and aggregates in the melt. The electrochemical reversibility of magnesium deposition and dissolution is demonstrated using voltammetry and impedance studies. Preliminary studies on rechargeable batteries assembled using gamma-MnO2 and Mg metal as the electrodes together with the molten electrolyte show high discharge capacity.

Direct physical evidence for the back-transformation of stress-induced martensite in the vicinity of cracks in pseudoelastic NiTi shape memory alloys

Crack loading and crack extension in pseudoelastic binary NiTi shape memory alloy (SMA) miniature compact tension (CT) specimens with 50.7 at.% Ni (austenitic, pseudoelastic) was investigated using infrared (IR) thermography during in situ loading and unloading. IR thermographic measurements allow for the observation of heat effects associated with the stress-induced transformation of martensite from B2 to BIT during loading and the reverse transformation during unloading. The results are compared with optical images and discussed in terms of the crack growth mechanisms in pseudoelastic NiTi SMAs. Direct experimental evidence is presented which shows that crack growth occurs into a stress-induced martensitic microstructure, which immediately retransforms to austenite in the wake of the crack.

Molecular mechanisms of bacteriophage phi6 RNA-dependent RNA polymerase and its utilization in biotechnology

Double-stranded RNA (dsRNA) viruses encode only a single protein species that contains RNA-dependent RNA polymerase (RdRP) motifs. This protein is a central component in the life cycle of a dsRNA virus, carrying out both RNA transcription and replication. The architecture of viral RdRPs resembles that of a 'cupped right hand' with fingers, palm and thumb domains. Those applying de novo initiation have additional structural features, including a flexible C-terminal domain that constitutes the priming platform. Moreover, viral RdRPs must be able to interact with the incoming 3'-terminus of the template and position it so that a productive binary complex is formed. Bacteriophage phi6 of the Cystoviridae family is to date one of the best studied dsRNA viruses. The purified recombinant phi6 RdRP is highly active in vitro and possesses both RNA replication and transcription activities. The extensive biochemical observations and the atomic level crystal structure of the phi6 RdRP provides an excellent platform for in-depth studies of RNA replication in vitro. In this thesis, targeted structure-based mutagenesis, enzymatic assays and molecular mapping of phi6 RdRP and its RNA were used to elucidate the formation of productive RNA-polymerase binary complexes. The positively charged rim of the template tunnel was shown to have a significant role in the engagement of highly structured ssRNA molecules, whereas specific interactions further down in the template tunnel promote ssRNA entry to the catalytic site. This work demonstrated that by aiding the formation of a stable binary complex with optimized RNA templates, the overall polymerization activity of the phi6 RdRP can be greatly enhanced. Furthermore, proteolyzed phi6 RdRPs that possess a nick in the polypeptide chain at the hinge region, which is part of the extended loop, were better suited for catalysis at higher temperatures whilst favouring back-primed initiation. The clipped C-terminus remains associated with the main body of the polymerase and the hinge region, although structurally disordered, is involved in the control of C-terminal domain displacement. The accumulated knowhow on bacteriophage phi6 was utilized in the development of two technologies for the production of dsRNA: (i) an in vitro system that combines the T7 RNA polymerase and the phi6 RdRP to generate dsRNA molecules of practically unlimited length, and (ii) an in vivo RNA replication system based on restricted infection with phi6 polymerase complexes in bacterial cells to produce virtually unlimited amounts of dsRNA. The pools of small interfering RNAs derived from dsRNA produced by these systems were validated and shown to efficiently decrease the expression of both exogenous and endogenous targets.

Visual detection of occluded crop: For automated harvesting

This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.

Temperature independent mixing rules to correlate the solubilities of antibiotics and anti-inflammatory drugs in SCCO2

The accurate experimental determination of the solubilities of antibiotics and anti-inflammatory drugs in supercritical fluids (SCFs) and correlations are essential for the development of supercritical technologies for the pharmaceuticals industry. In this work, the solubilities of penicillinG, penicillinV, flurbiprofen, ketoprofen, naproxen, ibuprofen, aspirin and diflunisal in supercritical carbon dioxide (SCCO2) were correlated using Peng-Robinson equation of state (PR EOS) with the modified Kwak and Mansoori mixing rules (mKM) and with Bartle model. The ability of mKM rules was compared against the conventional mixing rules of van der Waals in correlating the solubilities. In the present model, vapor pressure was considered as an adjustable parameter along with binary interactions parameters. In the proposed model, the constants used in the mixing rule, and vapor pressure expression coefficients are temperature independent. The optimization of these constants with experimental data gives binary interaction parameters along with vapor pressure correlations. Sublimation enthalpies were estimated with both the models compared with literature reported experimental values.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Surfactant-Mediated Synthesis of Functional Metal Oxide Nanostructures Via Microwave Irradiation-Assisted Chemical Synthesis

In the present work we report a rapid microwave irradiation-assisted chemical synthesis technique for the growth of nanoparticles, nanorods, and nanotubes of a variety of metal oxides in the presence of an appropriate surfactant (cationic, anionic, non ionic and polymeric), without the use of any templates. The method is simple, inexpensive, and helps one to prepare nanostructures in quick time, measured in seconds and minutes. This method has been applied successfully to synthesize nanostructures of a variety of binary and ternary metal oxides such as ZnO, CdO, Fe2O3, CuO, Ga2O3, Gd2O3, ZnFe2O4, etc. There is an observed variation in the morphology of the nanostructures with changes in different process parameters, such as microwave power, irradiation time, identity of solvent, type of surfactant, and its concentration.