Letters which passed between Count Gyllenborg, the Barons Gortz, Sparre, & others; relating to the design of raising a rebellion in His Majesty's dominions, to be supported by a force from Sweden.

French & English text in parallel columns.

Ultrafine particles in indoor air of a school : possible role of secondary organic aerosols

The aim of this work was to investigate ultrafine particles (< 0.1 μm) in primary school classrooms, in relation to the classrooms activities. The investigations were conducted in three classrooms during two measuring campaigns, which together encompassed a period of 60 days. Initial investigations showed that under the normal operating conditions of the school there were many occasions in all three classrooms where indoor particle concentrations increased significantly compared to outdoor levels. By far the highest increases in the classroom resulted from art activities (painting, gluing and drawing), at times reaching over 1.4 x 105 particle cm-3. The indoor particle concentrations exceeded outdoor concentrations by approximately one order of magnitude, with a count median diameter ranging from 20-50 nm. Significant increases also occurred during cleaning activities, when detergents were used. GC-MS analysis conducted on 4 samples randomly selected from about 30 different paints and glues, as well as the detergent used in the school, showed that d-limonene was one of the main organic compounds of the detergent, however, it was not detected in the samples of the paints and the glue. Controlled experiments showed that this monoterpene, emitted from the detergent, reacted with O3 (at outdoor ambient concentrations ranging from 0.06-0.08ppm) and formed secondary organic aerosols. Further investigations to identify other liquids which may be potential sources of the precursors of secondary organic aerosols, were outside the scope of this project, however, it is expected that the problem identified by this study could be more widely spread, since most primary schools use liquid materials for art classes, and all schools use detergents for cleaning. Further studies are therefore recommended to better understand this phenomenon and also to minimize school children exposure to ultrafine particles from these indoor sources.

Differences in the performance of safety performance functions estimated for total crash count and for crash count by crash type

In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as safety performance functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach for applying intersection SPFs is to assume that crash types occur in fixed proportions (e.g., rear-end crashes make up 20% of crashes, angle crashes 35%, and so forth) and then apply these fixed proportions to crash totals to estimate crash frequencies by type. As demonstrated in this paper, such a practice makes questionable assumptions and results in considerable error in estimating crash proportions. Through the use of rudimentary SPFs based solely on the annual average daily traffic (AADT) of major and minor roads, the homogeneity-in-proportions assumption is shown not to hold across AADT, because crash proportions vary as a function of both major and minor road AADT. For example, with minor road AADT of 400 vehicles per day, the proportion of intersecting-direction crashes decreases from about 50% with 2,000 major road AADT to about 15% with 82,000 AADT. Same-direction crashes increase from about 15% to 55% for the same comparison. The homogeneity-in-proportions assumption should be abandoned, and crash type models should be used to predict crash frequency by crash type. SPFs that use additional geometric variables would only exacerbate the problem quantified here. Comparison of models for different crash types using additional geometric variables remains the subject of future research.

Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

When the right to be counted doesn’t count : the politics and challenges of researching the health of asylum seekers

A fundamental prerequisite of population health research is the ability to establish an accurate denominator. This in turn requires that every individual in the study population is counted. However, this seemingly simple principle has become a point of conflict between researchers whose aim is to produce evidence of disparities in population health outcomes and governments whose policies promote(intentionally or not) inequalities that are the underlying causes of health disparities. Research into the health of asylum seekers is a case in point. There is a growing body of evidence documenting the adverse affects of recent changes in asylum-seeking legislation, including mandatory detention. However, much of this evidence has been dismissed by some governments as being unsound, biased and unscientific because, it is argued, evidence is derived from small samples or from case studies. Yet, it is the policies of governments that are the key barrier to the conduct of rigorous population health research on asylum seekers. In this paper, the authors discuss the challenges of counting asylum seekers and the limitations of data reported in some industrialized countries. They argue that the lack of accurate statistical data on asylum seekers has been an effective neo-conservative strategy for erasing the health inequalities in this vulnerable population, indeed a strategy that renders invisible this population. They describe some alternative strategies that may be used by researchers to obtain denominator data on hard-to-reach populations such as asylum seekers.

Does 'habitus' count in Chinese Australians' mathematics achievement?

Large-scale international comparative studies and cross-ethnic studies have revealed that Chinese students, whether living in China or overseas, consistently outperform their counterparts in mathematics achievement. These studies tended to explain this result from psychological, educational, or cultural perspectives. However, there is scant sociological investigation addressing Chinese students’ better mathematics achievement. Drawing on Bourdieu’s sociological theory, this study conceptualises Chinese Australians’ “Chineseness” by the notion of ‘habitus’ and considers this “Chineseness” generating but not determinating mechanism that underpins Chinese Australians’ mathematics learning. Two hundred and thirty complete responses from Chinese Australian participants were collected by an online questionnaire. Simple regression model statistically significantly well predicted mathematics achievement by “Chineseness” (F = 141.90, R = .62, t = 11.91, p < .001). Taking account of “Chineseness” as a sociological mechanism for Chinese Australians’ mathematics learning, this study complements psychological and educational impacts on better mathematics achievement of Chinese students revealed by previous studies. This study also challenges the cultural superiority discourse that attributes better mathematics achievement of Chinese students to cultural factors.

Exact and approximate Bayesian inference for low count time series models with intractable likelihoods

In this paper we present a new simulation methodology in order to obtain exact or approximate Bayesian inference for models for low-valued count time series data that have computationally demanding likelihood functions. The algorithm fits within the framework of particle Markov chain Monte Carlo (PMCMC) methods. The particle filter requires only model simulations and, in this regard, our approach has connections with approximate Bayesian computation (ABC). However, an advantage of using the PMCMC approach in this setting is that simulated data can be matched with data observed one-at-a-time, rather than attempting to match on the full dataset simultaneously or on a low-dimensional non-sufficient summary statistic, which is common practice in ABC. For low-valued count time series data we find that it is often computationally feasible to match simulated data with observed data exactly. Our particle filter maintains $N$ particles by repeating the simulation until $N+1$ exact matches are obtained. Our algorithm creates an unbiased estimate of the likelihood, resulting in exact posterior inferences when included in an MCMC algorithm. In cases where exact matching is computationally prohibitive, a tolerance is introduced as per ABC. A novel aspect of our approach is that we introduce auxiliary variables into our particle filter so that partially observed and/or non-Markovian models can be accommodated. We demonstrate that Bayesian model choice problems can be easily handled in this framework.

Count-min sketches for estimating password frequency within Hamming distance two

The count-min sketch is a useful data structure for recording and estimating the frequency of string occurrences, such as passwords, in sub-linear space with high accuracy. However, it cannot be used to draw conclusions on groups of strings that are similar, for example close in Hamming distance. This paper introduces a variant of the count-min sketch which allows for estimating counts within a specified Hamming distance of the queried string. This variant can be used to prevent users from choosing popular passwords, like the original sketch, but it also allows for a more efficient method of analysing password statistics.

Mining universities : can we count on the integrity of research coming out of today's mining-funded tertiary sector?

Australia's economic growth and national identity have been widely celebrated as being founded on the nation's natural resources. With the golden era of pastoralism fading into the distance, a renewed love affair with primary industries has been much lauded, particularly by purveyors of neoliberal ideology. The considerable wealth generated by resource extraction has, despite its environmental and social record, proved seductive to the university sector. The mining industry is one of a number of industries and sectors (alongside pharmaceutical, chemical and biotechnological) that is increasingly courting Australian universities. These new public-private alliances are often viewed as the much-needed cash cow to bridge the public funding shortfall in the tertiary sector. However, this trend also raises profound questions about the capacity of public good institutions, as universities were once assumed to be, to maintain institutional independence and academic freedoms.

Does counting still count? Revisiting the security of counting based user authentication protocols against statistical attacks

At NDSS 2012, Yan et al. analyzed the security of several challenge-response type user authentication protocols against passive observers, and proposed a generic counting based statistical attack to recover the secret of some counting based protocols given a number of observed authentication sessions. Roughly speaking, the attack is based on the fact that secret (pass) objects appear in challenges with a different probability from non-secret (decoy) objects when the responses are taken into account. Although they mentioned that a protocol susceptible to this attack should minimize this difference, they did not give details as to how this can be achieved barring a few suggestions. In this paper, we attempt to fill this gap by generalizing the attack with a much more comprehensive theoretical analysis. Our treatment is more quantitative which enables us to describe a method to theoretically estimate a lower bound on the number of sessions a protocol can be safely used against the attack. Our results include 1) two proposed fixes to make counting protocols practically safe against the attack at the cost of usability, 2) the observation that the attack can be used on non-counting based protocols too as long as challenge generation is contrived, 3) and two main design principles for user authentication protocols which can be considered as extensions of the principles from Yan et al. This detailed theoretical treatment can be used as a guideline during the design of counting based protocols to determine their susceptibility to this attack. The Foxtail protocol, one of the protocols analyzed by Yan et al., is used as a representative to illustrate our theoretical and experimental results.