Monograph No. 3: Estimating the prevalence of problematic heroin use in Melbourne

This monograph (No. 3) reports on work that tested new methods for estimating the prevalence of problematic heroin use in Melbourne. Using the non-fatal heroin overdose data, three different capture-recapture methods were employed. Estimates were derived for the year 2000 and the year 2003/2004. The lack of plausibility of some estimates coupled with the poor ‘goodness-of-fit’ of some models points to the need to continue to develop new methods for estimating problematic heroin use

Bulletin No. 5: Estimating the number of heroin users in Australia

Estimating the prevalence of drug use is one of the key focal areas of alcohol and drug epidemiology. Estimation of the extent of alcohol and drug use in the Australian community has primarily been undertaken using surveys of the general population. Nevertheless, it is widely understood that prevalence estimates derived from general population surveys underestimate the true extent of drug use in the community for drugs of low use prevalence (e.g. heroin) because of issues around sampling (e.g. response rates and the extent to which crucial samples such as the homeless are missed in household surveys) and the truthfulness of responses to questions concerning illegal or hidden behaviours. In response, epidemiologists have applied specialised statistical techniques to the analysis of data sources on the extent of drug-related harm (e.g. Opioid overdose deaths) to produce estimates of the extent of problematic drug use in the Australian community. Prevalence estimation using secondary data sources has generally been undertaken only in relation to heroin use in Australia. This work has used a variety of techniques (e.g. capture-recapture, back-projection, multiplier) in accordance with a general consensus that has emerged around the application of such techniques to the estimation of problematic drug use. In applying these methods Australian work has developed multiple estimates using available statistical estimation tools with convergence among estimates used as the source of the most parsimonious estimate (e.g. the median of the estimates derived). While this approach is appealing, the resultant ‘best’ estimates are derived primarily from the application of simple mortality multipliers (e.g. 1% annual mortality rate for heroin users) to the number of opioid overdose deaths occurring in specific Australian jurisdictions (generally NSW). The problem of this multiplier approach is highlighted by the effect of the heroin shortage in Australia. The aim of this component of the DPMP was to develop plausible estimates of the prevalence of heroin use in Melbourne with a view to informing various elements of DPMP projects. The work was also designed to provide a method for estimating the extent of injecting drug use more widely (specifically through application to amphetamines). It was funded by a Travelling Scholarship from the Victorian Premier’s Drug Prevention Council awarded to Paul Dietze

Bulletin No. 12: System dynamics modelling using a stocks and flows approach

One of the key components of the first phase of the DPMP project has been to develop a quantitative dynamic model of drug use in Australia. Using a stocks and flows approach, derived from similar work undertaken in the US on cocaine prevalence by Caulkins and collaborators, the key aim of this component of the DPMP has been to examine whether methods can be applied to the Australian context using available data. If a plausible model could be developed, then the subsequent aims were to use the model to describe: 1.The prevalence of drug use in Australia over time; and 2. the effects of changes in model parameters upon the prevalence of injecting drug use and the associated social costs

Atom-molecule Rabi oscillations in a Mott insulator

We observe large-amplitude Rabi oscillations between an atomic and a molecular state near a Feshbach resonance. The experiment uses 87Rb in an optical lattice and a Feshbach resonance near 414 G. The frequency and amplitude of the oscillations depend on magnetic field in a way that is well described by a two-level model. The observed density dependence of the oscillation frequency agrees with the theoretical expectation. We confirmed that the state produced after a half-cycle contains exactly one molecule at each lattice site. In addition, we show that for energies in a gap of the lattice band structure, the molecules cannot dissociate

CEP-stable Tunable THz-Emission Originating from Laser-Waveform-Controlled Sub-Cycle Plasma-Electron Bursts

We study THz-emission from a plasma driven by an incommensurate-frequency two-colour laser field. A semi-classical transient electron current model is derived from a fully quantum-mechanical description of the emission process in terms of sub-cycle field-ionization followed by continuum-continuum electron transitions. For the experiment, a CEP-locked laser and a near-degenerate optical parametric amplifier are used to produce two-colour pulses that consist of the fundamental and its near-half frequency. By choosing two incommensurate frequencies, the frequency of the CEP-stable THz-emission can be continuously tuned into the mid-IR range. This measured frequency dependence of the THz-emission is found to be consistent with the semi-classical transient electron current model, similar to the Brunel mechanism of harmonic generation

Charaterizing RDF graphs through graph-based measures - Framework and assessment

The topological structure of RDF graphs inherently differs from other types of graphs, like social graphs, due to the pervasive existence of hierarchical relations (TBox), which complement transversal relations (ABox). Graph measures capture such particularities through descriptive statistics. Besides the classical set of measures established in the field of network analysis, such as size and volume of the graph or the type of degree distribution of its vertices, there has been some effort to define measures that capture some of the aforementioned particularities RDF graphs adhere to. However, some of them are redundant, computationally expensive, and not meaningful enough to describe RDF graphs. In particular, it is not clear which of them are efficient metrics to capture specific distinguishing characteristics of datasets in different knowledge domains (e.g., Cross Domain vs. Linguistics). In this work, we address the problem of identifying a minimal set of measures that is efficient, essential (non-redundant), and meaningful. Based on 54 measures and a sample of 280 graphs of nine knowledge domains from the Linked Open Data Cloud, we identify an essential set of 13 measures, having the capacity to describe graphs concisely. These measures have the capacity to present the topological structures and differences of datasets in established knowledge domains