Tuberculosis: the implications for anaesthesia

Tuberculosis is a common problem in South Africa, and provides a number of challenges for the anaesthetist. Patients may present in a variety of ways. Constitutional and pulmonary symptoms are the most common. These may impact on fitness for surgery and choice of anaesthesia. Tuberculosis treatment has the potential for a number of significant drug interactions. These are primarily mediated through induction of the cytochrome P450 enzyme system by rifampicin. Guidelines for the prevention of tuberculosis in the theatre environment need to be followed to avoid placing staff and other patients in danger.Keywords: tuberculosis, antitubercular agents, drug interactions, transmission, bacterial filte

Assortative Mixing Equilibria in Social Network Games

It is known that individuals in social networks tend to exhibit homophily (a.k.a. assortative mixing) in their social ties, which implies that they prefer bonding with others of their own kind. But what are the reasons for this phenomenon? Is it that such relations are more convenient and easier to maintain? Or are there also some more tangible benefits to be gained from this collective behaviour? The current work takes a game-theoretic perspective on this phenomenon, and studies the conditions under which different assortative mixing strategies lead to equilibrium in an evolving social network. We focus on a biased preferential attachment model where the strategy of each group (e.g., political or social minority) determines the level of bias of its members toward other group members and non-members. Our first result is that if the utility function that the group attempts to maximize is the degree centrality of the group, interpreted as the sum of degrees of the group members in the network, then the only strategy achieving Nash equilibrium is a perfect homophily, which implies that cooperation with other groups is harmful to this utility function. A second, and perhaps more surprising, result is that if a reward for inter-group cooperation is added to the utility function (e.g., externally enforced by an authority as a regulation), then there are only two possible equilibria, namely, perfect homophily or perfect heterophily, and it is possible to characterize their feasibility spaces. Interestingly, these results hold regardless of the minority-majority ratio in the population. We believe that these results, as well as the game-theoretic perspective presented herein, may contribute to a better understanding of the forces that shape the groups and communities of our society

The Millimeter Astronomy Legacy Team 90 GHz Survey (MALT90) and ALMA

ALMA will revolutionize our understanding of star formation within our galaxy, but before we can use ALMA we need to know where to look. The Millimeter Astronomy Legacy Team 90 GHz (MALT90) Survey is a large international project to map the molecular line emission of over 2,000 dense clumps in the Galactic plane. MALT90 serves as a pathfinder for ALMA, providing a large public database of dense molecular clumps associated with high-mass star formation. In this proceedings, we describe the survey parameters and share early science highlights from the survey, including (1) a comparison between galactic and extragalactic star formation relations, (2) chemical trends in MALT90 clumps, (3) the distribution of high-mass star formation in the Milky Way, and (4) a discussion of the Brick, the target of successful ALMA Cycle 0 and Cycle 1 proposals

Estimating δ15N fractionation and adjusting the lipid correction equation using Southern African freshwater fishes

Stable isotope analysis is an important tool for characterising food web structure; however, interpretation of isotope data can often be flawed. For instance, lipid normalisation and trophic fractionation values are often assumed to be constant, but can vary considerably between ecosystems, species and tissues. Here, previously determined lipid normalisation equations and trophic fractionation values were re-evaluated using freshwater fish species from three rivers in the Upper Zambezian floodplain ecoregion in southern Africa. The parameters commonly used in lipid normalisation equations were not correct for the 18 model species (new D and I parameters were estimated as D = 4.46‰ [95% CI: 2.62, 4.85] and constant I = 0 [95% CI: 0, 0.17]). We suggest that future isotopic analyses on freshwater fishes use our new values if the species under consideration do not have a high lipid content in their white muscle tissue. Nitrogen fractionation values varied between species and river basin; however, the average value closely matched that calculated in previous studies on other species (δ15N fractionation factor of 3.37 ± 1.30 ‰). Here we have highlighted the need to treat stable isotope data correctly in food web studies to avoid misinterpretation of the data

A survey for low mass spectroscopic binary stars in the young clusters around sigma Orionis and lambda Orionis

We have obtained multi-epoch, high-resolution spectroscopy of 218 candidate low-mass stars and brown dwarfs in the young clusters around sigma Ori and lambda Ori. We find that 196 targets are cluster members based on their radial velocity, the equivalent width of their NaI 8200 lines and the spectral type from their TiO band strength. We have identified 11 new binary stars among the cluster members based on their variable radial velocity and an additional binary from the variation in its line width and shape. The sample covers the magnitude range Ic=14-18.9 (mass =~ 0.55-0.03 Msun), but all of the binary stars are brighter than Ic=16.6 (mass =~ 0.12Msun) and 10 are brighter than Ic=15.5 (mass =~ 0.23Msun). There is a significant lack of spectroscopic binaries in our sample at faint magnitudes even when we account for the decrease in sensitivity with increasing magnitude. We can reject the hypothesis that the fraction of spectroscopic binaries is a uniform function of Ic magnitude with more than 99% confidence. The spectroscopic binary fraction for stars more massive than about 0.1Msun (Ic < 16.9) is f_bright=0.095(+0.012)(-0.028). The 90% confidence upper limit to the spectroscopic binary fraction for very low mass (VLM) stars (mass < 0.1Msun) and brown dwarfs (BDs) is f_faint < 7.5%. The hypothesis that f_bright and f_faint are equal can be rejected with 90% confidence. We conclude that we have found strong evidence for a change in the fraction of spectroscopic binaries among young VLM stars and brown dwarfs when compared to more massive stars in the same star-forming region. This implies a difference in the total binary fraction between VLM stars and BDs compared to more massive stars or a difference in the distribution of semi-major axes, or both. (Abridged

Z2SAL: a translation-based model checker for Z

Despite being widely known and accepted in industry, the Z formal specification language has not so far been well supported by automated verification tools, mostly because of the challenges in handling the abstraction of the language. In this paper we discuss a novel approach to building a model-checker for Z, which involves implementing a translation from Z into SAL, the input language for the Symbolic Analysis Laboratory, a toolset which includes a number of model-checkers and a simulator. The Z2SAL translation deals with a number of important issues, including: mapping unbounded, abstract specifications into bounded, finite models amenable to a BDD-based symbolic checker; converting a non-constructive and piecemeal style of functional specification into a deterministic, automaton-based style of specification; and supporting the rich set-based vocabulary of the Z mathematical toolkit. This paper discusses progress made towards implementing as complete and faithful a translation as possible, while highlighting certain assumptions, respecting certain limitations and making use of available optimisations. The translation is illustrated throughout with examples; and a complete working example is presented, together with performance data

Shear properties of MgO inferred using neural networks

Shear properties of mantle minerals are vital for interpreting seismic shear wave speeds and therefore inferring the composition and dynamics of a planetary interior. Shear wave speed and elastic tensor components, from which the shear modulus can be computed, are usually measured in the laboratory mimicking the Earth's (or a planet's) internal pressure and temperature conditions. A functional form that relates the shear modulus to pressure (and temperature) is fitted to the measurements and used to interpolate within and extrapolate beyond the range covered by the data. Assuming a functional form provides prior information, and the constraints on the predicted shear modulus and its uncertainties might depend largely on the assumed prior rather than the data. In the present study, we propose a data-driven approach in which we train a neural network to learn the relationship between the pressure, temperature and shear modulus from the experimental data without prescribing a functional form a priori. We present an application to MgO, but the same approach works for any other mineral if there are sufficient data to train a neural network. At low pressures, the shear modulus of MgO is well-constrained by the data. However, our results show that different experimental results are inconsistent even at room temperature, seen as multiple peaks and diverging trends in probability density functions predicted by the network. Furthermore, although an explicit finite-strain equation mostly agrees with the likelihood predicted by the neural network, there are regions where it diverges from the range given by the networks. In those regions, it is the prior assumption of the form of the equation that provides constraints on the shear modulus regardless of how the Earth behaves (or data behave). In situations where realistic uncertainties are not reported, one can become overconfident when interpreting seismic models based on those defined equations of state. In contrast, the trained neural network provides a reasonable approximation to experimental data and quantifies the uncertainty from experimental errors, interpolation uncertainty, data sparsity and inconsistencies from different experiments

The Janus-Faced Role of Gambling Flow in Addiction Issues

YesFlow experience has been widely investigated in experiential activities such as sports, the performing arts, gaming and Internet usage. Most studies focus on the positive aspects of flow experience and its effect on performance. In stark contrast, gambling research focusing on the negative side of addiction lacks an in-depth investigation of gamblers’ (positive) flow encounters. This separation of research lines seems out of place given that recent research indicates connections between flow and addiction. Joining both constructs in a causal effects model helps to gain a better understanding of their relationship and its contingencies. This paper empirically investigates whether and how it is possible to observe a “Janus face” of flow with its various sub-dimensions in online gambling. Empirical data was collected from 500 online gamblers by applying a structured questionnaire with established scales. The data was analyzed with a confirmatory factor analysis and a double-hurdle model to separate casual gamblers who are unsusceptible to any addiction issues from gamblers affected by initiatory addiction issues. The findings indicate that online gambling addiction is negatively influenced by two sub-dimensions of flow experience, namely a sense of control and concentration on the task at hand, while enhanced by a transformation of time and autotelic experience