Long-term patterns in interpersonal behaviour amongst psychopathic patients in secure inpatient treatment: A follow-up study.

Psychopathy is a disorder that is partly defined by with maladaptive interpersonal behaviour and has significant effects on treatment outcomes. A previous study (Draycott et al., ) found that higher levels of psychopathy led to a specific interpersonal 'trajectory' amongst patients in a secure psychiatric treatment programme during the first 9 months of their admission. In that programme, more psychopathic patients became increasingly dominant over time, and less psychopathic patients became increasingly hostile. This study is a longer-term follow-up and extension of that study, extending the window of observation to 33 months of treatment. It was found that the more psychopathic patients' increased dominance returned to baseline levels by 33 months, as did the less psychopathic patients' increased hostility. This suggests that treatment for this group is not idiopathic but leaves unanswered the question as to what these divergent trajectories represent

Instrument Bias Correction With Machine Learning Algorithms: Application to Field-Portable Mass Spectrometry

In situ sensors for environmental chemistry promise more thorough observations, which are necessary for high confidence predictions in earth systems science. However, these can be a challenge to interpret because the sensors are strongly influenced by temperature, humidity, pressure, or other secondary environmental conditions that are not of direct interest. We present a comparison of two statistical learning methods—a generalized additive model and a long short-term memory neural network model for bias correction of in situ sensor data. We discuss their performance and tradeoffs when the two bias correction methods are applied to data from submersible and shipboard mass spectrometers. Both instruments measure the most abundant gases dissolved in water and can be used to reconstruct biochemical metabolisms, including those that regulate atmospheric carbon dioxide. Both models demonstrate a high degree of skill at correcting for instrument bias using correlated environmental measurements; the difference in their respective performance is less than 1% in terms of root mean squared error. Overall, the long short-term memory bias correction produced an error of 5% for O2 and 8.5% for CO2 when compared against independent membrane DO and laser spectrometer instruments. This represents a predictive accuracy of 92–95% for both gases. It is apparent that the most important factor in a skillful bias correction is the measurement of the secondary environmental conditions that are likely to correlate with the instrument bias. These statistical learning methods are extremely flexible and permit the inclusion of nearly an infinite number of correlates in finding the best bias correction solution

Membrance interface evaluations for underwater mass spectrometers.

A component that has enabled the development of underwater mass spectrometry is a mechanically supported membrane interface probe. Our two research groups have used metallic porous frits that support polydimethyl siloxane (PDMS) membranes embedded in a heated membrane probe assembly, allowing the deployment of the underwater membrane introduction mass spectrometer (MIMS) instruments to ocean depths of 2000 meters. The fabrication of such frits has consisted of shaping larger Hastalloy C porous frits to the size required to support a PDMS capillary of 0.64 mm ID and 1.19 mm OD using a diamond‐coated wheel and Dremel tool. This procedure is time‐consuming and cumbersome, and the porosity of the final frits is likely not reproducible. To facilitate the fabrication of the membrane assembly, we report on the use of new porous metallic structures. Frits with diameters of approximately 3.0 mm (1/8”) and known porosities (48.3 % and 32.5%) were produced by the Fraunhofer Institute in Dresden, Germany, using powder metallurgical processes. We used these frits to fabricate new membrane interface assemblies. Using a new custom‐heated membrane probe with the new porous frits, we performed calibrations relating dissolved methane concentrations to mass spectrometer response (m/z 15) using linear least‐squares fitting procedures. Both the limit of detection (methane concentration in the tens of nanomolars) and the sensitivity (on the order of 10‐1 pico‐amps/nanomole of methane) were found to be comparable with those obtained with the previously fabricated Hastelloy C frits. The calibration parameters for the new assembly were also found to be a function of the flow rate, temperature, and sample hydrostatic pressure

Economies of space and the school geography curriculum

This paper is about the images of economic space that are found in school curricula. It suggests the importance for educators of evaluating these representations in terms of the messages they contain about how social processes operate. The paper uses school geography texts in Britain since the 1970s to illustrate the different ways in which economic space has been represented to students, before exploring some alternative resources that could be used to provide a wider range of representations of economic space. The paper highlights the continued importance of understanding the politics of school knowledge

Can dark matter be a Bose-Einstein condensate?

We consider the possibility that the dark matter, which is required to explain the dynamics of the neutral hydrogen clouds at large distances from the galactic center, could be in the form of a Bose-Einstein condensate. To study the condensate we use the non-relativistic Gross-Pitaevskii equation. By introducing the Madelung representation of the wave function, we formulate the dynamics of the system in terms of the continuity equation and of the hydrodynamic Euler equations. Hence dark matter can be described as a non-relativistic, Newtonian Bose-Einstein gravitational condensate gas, whose density and pressure are related by a barotropic equation of state. In the case of a condensate with quartic non-linearity, the equation of state is polytropic with index $n=1$. To test the validity of the model we fit the Newtonian tangential velocity equation of the model with a sample of rotation curves of low surface brightness and dwarf galaxies, respectively. We find a very good agreement between the theoretical rotation curves and the observational data for the low surface brightness galaxies. The deflection of photons passing through the dark matter halos is also analyzed, and the bending angle of light is computed. The bending angle obtained for the Bose-Einstein condensate is larger than that predicted by standard general relativistic and dark matter models. Therefore the study of the light deflection by galaxies and the gravitational lensing could discriminate between the Bose-Einstein condensate dark matter model and other dark matter models.Comment: 20 pages, 7 figures, accepted for publication in JCAP, references adde

Filling some black holes: modeling the connection between urbanization, infrastructure, and global service intensity

This empirical article combines insights from previous research on the level of knowledge-intensive service in metropolitan areas with the aim to develop an understanding of the spatial structure of the global service economy. We use a stepwise regression model with the Globalization and World Cities research network's measure of globalized service provisioning as the dependent variable and a range of variables focusing on population, infrastructure, urban primacy, and national regulation as independent variables. The discussion of the results focuses on model parameters as well as the meaning of outliers and is used to explore some avenues for future research

University of Texas bulletin

Report published in a scientific bulletin, describing the Lytton Springs oil fields

Status, Trends, and Conservation of Eelgrass in Atlantic Canada and the Northeastern United States: Workshop Report

Eelgrass (Zostera marina L) is the dominant seagrass occurring in eastern Canada and the northeastern United States, where it often forms extensive meadows in coastal and estuarine areas. Eelgrass beds are extremely productive and provide many valuable ecological functions and ecosystem services. They serve as critical feeding and nursery habitat for a wide variety of commercially and recreationally important fish and shellfish and as feeding areas for waterfowl and other waterbirds. Eelgrass detritus is also transported considerable distances to fuel offshore food webs. In addition, eelgrass beds stabilize bottom sediments, dampen wave energy, absorb nutrients from surrounding waters, and retain carbon through burial