Influences of preschool policies and practices on children's physical activity

The objective of this study was to determine if moderate to vigorous physical activity (MVPA) of 3-5 year old preschool children varied with differences in policies/practices, and overall quality of preschools. A total of 266 children (47% males, 60% African American) from 9 preschools were observed for 1 hour on 3 different days. PA of children was observed twice per minute and scored as 1-5, with 1 for stationary/motionless and 5 for fast movement. Summary MVPA was calculated over the 3 days as percent of times observed at levels of 4 or 5, and percent of time at levels I or 2 as sedentary activity. A structured interview about PA policies was conducted with an administrator at each preschool and overall quality of the preschool was assessed using Early Childhood Environment Rating Scale-Revised Edition (ECERS-R). Preschools were divided into groups according to whether a specific policy/practice that would be logically hypothesized to promote PA was in place at the school. MVPA differences between groups of children was assessed using mixed ANOVA controlling for preschool. When preschools offered more field trips, and more college educated teachers, the children participated in more MVPA. Children who attended preschools with lower quality spent more time in sedentary activity. In conclusion, children in preschools which may have more resources and better quality appear to show both more sedentary behavior and more MVPA.

Criminal profiling : behavioural consistency, the homology assumption and case linkage

Criminal profiling is an investigative tool used around the world to infer the personality and behavioural characteristics of an offender based on their crime. Case linkage, the process of determining discreet connections between crimes of the same offender, is a practice that falls under the general banner of criminal profiling and has been widely criticized. Two theories, behavioural consistency and the homology assumption, are examined and their impact on profiling in general and case linkage specifically is discussed...

Modeling and control of a 3500 tonne mining robot

Draglines are extremely large machines that are widely used in open-cut coal mines for overburden stripping. Since 1994 we have been working toward the development of a computer control system capable of automatically driving a dragline for a large portion of its operating cycle. This has necessitated the development and experimental evaluation of sensor systems, machines models, closed-loop control controllers, and an operator interface. This paper describes our steps toward the goal through scale-model and full-scale field experimentation.

Identification of common variants associated with human hippocampal and intracranial volumes

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10 -16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10 -12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10 -7).

The ENIGMA Consortium: Large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Postglacial Early Permian (late Sakmarian-early Artinskian) shallow-marine carbonate deposition along a 2000 km transect from Timor to west Australia

Late Sakmarian to early Artinskian (Early Permian) carbonate deposition was widespread in the marine intracratonic rift basins that extended into the interior of Eastern Gondwana from Timor in the north to the northern Perth Basin in the south. These basins spanned about 20° of paleolatitude (approximately 35°S to 55°S). This study describes the type section of the Maubisse Limestone in Timor-Leste, and compares this unit with carbonate sections in the Canning Basin (Nura Nura Member of the Poole Sandstone), the Southern Carnarvon Basin (Callytharra Formation) and the northern Perth Basin (Fossil Cliff Member of the Holmwood Shale). The carbonate units have no glacial influence and formed part of a major depositional cycle that, in the southern basins, overlies glacially influenced strata and lies a short distance below mudstone containing marine fossils and scattered dropstones (perhaps indicative of sea ice). In the south marine conditions became more restricted and were replaced by coal measures at the top of the depositional sequence. In the north, the carbonate deposits are possibly bryozoan–crinoidal mounds; whereas in the southern basins they form laterally continuous relatively thin beds, deposited on a very low-gradient seafloor, at the tops of shale–limestone parasequences that thicken upward in parasequence sets. All marine deposition within the sequence took place under very shallow (inner neritic) conditions, and the limestones have similar grain composition. Bryozoan and crinoidal debris dominate the grain assemblages and brachiopod shell fragments, foraminifera and ostracod valves are usually common. Tubiphytes ranged as far south as the Southern Carnarvon Basin, albeit rarely, but is more common to the north. Gastropod and bivalve shell debris, echinoid spines, solitary rugose corals and trilobite carapace elements are rare. The uniformity of the grain assemblage and the lack of tropical elements such as larger fusulinid foraminifera, colonial corals or dasycladacean algae indicate temperate marine conditions with only a small increase in temperature to the north. The depositional cycle containing the studied carbonate deposits represents a warmer phase than the preceding glacially influenced Asselian to early Sakmarian interval and the subsequent cool phase of the “mid” Artinskian that is followed by significant warming during the late Artinskian–early Kungurian. The timing of cooler and warmer intervals in the west Australian basins seems out-of-phase with the eastern Australian succession, but this may be a problem of chronostratigraphic miscorrelation due to endemic faunas and palynofloras.

Classifying genotype by environment interactions for targeted germplasm deployment with a focus on Eucalyptus

A novel methodology for describing genotype by environment interactions estimated from multi-environment field trials is described and an empirical example using an extensive trial network of eucalypts is presented. The network of experiments containing 65 eucalypts was established in 38 replicated field trials across the tropics and subtropics of eastern Australia, with a selection of well-tested species used to provide a more detailed examination of productivity differentials across environmental gradients. By focusing on changes in species’ productivity across environmental gradients, the results are applicable for all species established across the range of environments evaluated in the trial network and simultaneously classify species and environments so that results may be applied across the landscape. The methodology developed was able to explain most (93 %) of the variation in the selected species relative changes in productivity across the various environmental variables examined. Responses were primarily regulated by changes in variables related to water availability and secondarily by temperature related variables. Clustering and ordination can identify groups of species with similar physiological responses to environment and may also guide the parameterisation and calibration of process based models of plant growth. Ordination was particularly useful in the identification of species with distinct environmental response patterns that would be useful as probes for extracting more information from future trials.

Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.

Evaluating the effects of international exposure from networks ties and mimetic pressure on clustered SMEs in Brazil

Research on the internationalisation of small and medium-sized enterprises (SMEs) has received increasing attention in recent years due to the important role they play in today’s economic environment. Internationalisation prompting, or awareness, is an already recognised phase of the innovation-related stages model (I-model). This phase of awareness is closely related to the international exposure that a firm may experience during the occasion when it realises its competitors are already internationalising. Although the literature has discussed the various forms in which international exposure may happen, there has been limited attention given to the extent of its effect on the internationalisation of clustered SMEs that behave according to the I-Model. This study will assess the applicability of the I-Model in a dynamic, competitive and co-operative setting of an industrial cluster. It also evaluates the impact (if any) of international exposure derived from networks and the mimetic pressure that these firms may experience due to their embeddedness in an industrial cluster. Results from this study will indicate the effectiveness of the improved adapted model that will provide a richer insight for both academic researchers and policy makers.

The mixed black hole partition function for the STU model

We evaluate the mixed partition function for dyonic BPS black holes using the recently proposed degeneracy formula for the STU model. The result factorizes into the OSV mixed partition function times a proportionality factor. The latter is in agreement with the measure factor that was recently conjectured for a class of N = 2 black holes that contains the STU model.

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.

Evidence for low temperature glassy behavior in La0.5Sr0.5CoO3

We report the observed low temperature spin glass like feature in the optimally doped La0.5Sr0.5CoO3 ferromagnetic system. The characteristic of glassy behavior has been identified by noting (i) the frequency-dependent shift of the low temperature hump position in the out of phase ac susceptibility component; (ii) evolution of freezing temperature with dc biasing field that adheres to de Almeida-Thouless relation; (iii) memory effect; and (iv) sluggish magnetic relaxation. The results of magnetic measurements demonstrate that neither the inter-cluster interaction nor the spin disorder at the interface between ferromagnetic clusters is responsible for the manifestation of such collective glassy behavior. Rather, it is believed to arise from a distinct cluster glass like phase that possibly coexists with the dominant ferromagnetic phase. (C) 2012 American Institute of Physics. [doi:10.1063/1.3684610]