Observable Effects of Scalar Fields and Varying Constants

We show by using the method of matched asymptotic expansions that a sufficient condition can be derived which determines when a local experiment will detect the cosmological variation of a scalar field which is driving the spacetime variation of a supposed constant of Nature. We extend our earlier analyses of this problem by including the possibility that the local region is undergoing collapse inside a virialised structure, like a galaxy or galaxy cluster. We show by direct calculation that the sufficient condition is met to high precision in our own local region and we can therefore legitimately use local observations to place constraints upon the variation of "constants" of Nature on cosmological scales.Comment: Invited Festscrift Articl

The development of a fuzzy controller for tractive effort of a resistor technology locomotive

The application of a rule based fuzzy controller, implementing human skill and experience to control tractive effort of a resistor technology locomotive, is presented. The fuzzy controller aims to smoothly and safely accelerate the train from standstill. The controller provides the operational consistency and feedback functions required for improved protection of the traction motors, locomotives, rails and load. A simulation model for the locomotive and load is included

The Value of the Cosmological Constant

We make the cosmological constant, {\Lambda}, into a field and restrict the variations of the action with respect to it by causality. This creates an additional Einstein constraint equation. It restricts the solutions of the standard Einstein equations and is the requirement that the cosmological wave function possess a classical limit. When applied to the Friedmann metric it requires that the cosmological constant measured today, t_{U}, be {\Lambda} ~ t_{U}^(-2) ~ 10^(-122), as observed. This is the classical value of {\Lambda} that dominates the wave function of the universe. Our new field equation determines {\Lambda} in terms of other astronomically measurable quantities. Specifically, it predicts that the spatial curvature parameter of the universe is {\Omega}_{k0} \equiv -k/a_(0)^(2)H^2= -0.0055, which will be tested by Planck Satellite data. Our theory also creates a new picture of self-consistent quantum cosmological history.Comment: 6 pages. This article received Third Prize in the 2011 Gravity Research Foundation Awards for Essays on Gravitatio

A Fast and Accurate Diagnostic Test for Severe Sepsis Using Kernel Classifiers

Severe sepsis occurs frequently in the intensive care unit (ICU) and is a leading cause of admission, mortality, and cost. Treatment guidelines recommend early intervention, however gold standard blood culture test results may return in up to 48 hours. Insulin sensitivity (SI) is known to decrease with worsening condition and inflammatory response, and could thus be used to aid clinical treatment decisions. Some glycemic control protocols are able to accurately identify SI in real-time. A biomarker for severe sepsis was developed from retrospective SI and concurrent temperature, heart rate, respiratory rate, blood pressure, and SIRS score from 36 adult patients with sepsis. Patients were identified as having sepsis based on a clinically validated sepsis score (ss) of 2 or higher (ss = 0–4 for increasing severity). Kernel density estimates were used for the development of joint probability density profiles for ss = 2 and ss < 2 data hours (213 and 5858 respectively of 6071 total hours) and for classification. From the receiver operator characteristic (ROC) curve, the optimal probability cutoff values for classification were determined for in-sample and out-of-sample estimates. A biomarker including concurrent insulin sensitivity and clinical data for the diagnosis of severe sepsis (ss = 2) achieves 69–94% sensitivity, 75–94% specificity, 0.78–0.99 AUC, 3–17 LHR+, 0.06–0.4 LHR-, 9–38% PPV, 99–100% NPV, and a diagnostic odds ratio of 7–260 for optimal probability cutoff values of 0.32 and 0.27 for in-sample and out-of-sample data, respectively. The overall result lies between these minimum and maximum error bounds. Thus, the clinical biomarker shows good to high accuracy and may provide useful information as a real-time diagnostic test for severe sepsis

Impact of glucocorticoids on insulin resistance in the critically ill

Glucocorticoids (GCs) have been shown to reduce insulin sensitivity in healthy individuals. Widely used in critical care to treat a variety of inflammatory and allergic disorders, they may inadvertently exacerbate stress-hyperglycaemia. This research uses model-based methods to quantify the reduction of insulin sensitivity from GCs in critically ill patients, and thus their impact on glycaemic control. A clinically validated model-based measure of insulin sensitivity (SI) was used to quantify changes between two matched cohorts of 40 intensive care unit (ICU) patients who received GCs and a control cohort who did not. All patients were admitted to the Christchurch hospital ICU between 2005 and 2007 and spent at least 24 hours on the SPRINT glycaemic control protocol. A 31% reduction in whole-cohort median insulin sensitivity was seen between the control cohort and patients receiving glucocorticoids with a median dose equivalent to 200mg/day of hydrocortisone per patient. Comparing percentile-patients as a surrogate for matched patients, reductions in median insulin sensitivity of 20, 25, and 21% were observed for the 25th, 50th and 75th-percentile patients. All these cohort and per-patient reductions are less than or equivalent to the 30-62% reductions reported in healthy subjects especially when considering the fact that the GC doses in this study are 1.3-4 times larger than those in studies of healthy subjects. This reduced suppression of insulin sensitivity in critically ill patients could be a result of saturation due to already increased levels of catecholamines and cortisol common in critically illness. Virtual trial simulation showed that reductions in insulin sensitivity of 20-30% associated with glucocorticoid treatment in the ICU have limited impact on glycaemic control levels within the context of the SPRINT protocol

Further support for thermal ecosystem engineering by wandering albatross

On sub-Antarctic Marion Island, wandering albatross (Diomedea exulans) nests support high abundances of tineid moth, Pringleophaga marioni, caterpillars. Previous work proposed that the birds serve as thermal ecosystem engineers by elevating nest temperatures relative to ambient, thereby promoting growth and survival of the caterpillars. However, only 17 days of temperature data were presented previously, despite year-long nest occupation by birds. Previous sampling was also restricted to old and recently failed nests, though nests from which chicks have recently fledged are key to understanding how the engineering effect is realized. Here we build on previous work by providing nest temperature data for a full year and by sampling all three nest types. For the full duration of nest occupancy, temperatures within occupied nests are significantly higher, consistently by c. 7°C, than those in surrounding soils and abandoned nests, declining noticeably when chicks fledge. Caterpillar abundance is significantly higher in new nests compared to nests from which chicks have fledged, which in turn have higher caterpillar abundances than old nests. Combined with recent information on the life history of P. marioni, our data suggest that caterpillars are incidentally added to the nests during nest construction, and subsequently benefit from an engineering effect

Consistent Anisotropic Repulsions for Simple Molecules

We extract atom-atom potentials from the effective spherical potentials that suc cessfully model Hugoniot experiments on molecular fluids, e.g., $O_2$ and $N_2$. In the case of $O_2$ the resulting potentials compare very well with the atom-atom potentials used in studies of solid-state propertie s, while for $N_2$ they are considerably softer at short distances. Ground state (T=0K) and room temperatu re calculations performed with the new $N-N$ potential resolve the previous discrepancy between experimental and theoretical results.Comment: RevTeX, 5 figure

Tensile Forces and Shape Entropy Explain Observed Crista Structure in Mitochondria

A model is presented from which the observed morphology of the inner mitochondrial membrane can be inferred as minimizing the system's free energy. Besides the usual energetic terms for bending, surface area, and pressure difference, our free energy includes terms for tension that we believe to be exerted by proteins and for an entropic contribution due to many dimensions worth of shapes available at a given energy. In order to test the model, we measured the structural features of mitochondria in HeLa cells and mouse embryonic fibroblasts using 3D electron tomography. Such tomograms reveal that the inner membrane self-assembles into a complex structure that contains both tubular and flat lamellar crista components. This structure, which contains one matrix compartment, is believed to be essential to the proper functioning of mitochondria as the powerhouse of the cell. We find that tensile forces of the order of 10 pN are required to stabilize a stress-induced coexistence of tubular and flat lamellar cristae phases. The model also predicts \Deltap = -0.036 \pm 0.004 atm and \sigma=0.09 \pm 0.04 pN/nm

Towards Subject and Diagnostic Identifiability in the Alzheimer’s Disease Spectrum Based on Functional Connectomes

Alzheimer’s disease (AD) is the only major cause of mortality in the world without an effective disease modifying treatment. Evidence supporting the so called “disconnection hypothesis” suggests that functional connectivity biomarkers may have clinical potential for early detection of AD. However, known issues with low test-retest reliability and signal to noise in functional connectivity may prevent accuracy and subsequent predictive capacity. We validate the utility of a novel principal component based diagnostic identifiability framework to increase separation in functional connectivity across the Alzheimer’s spectrum by identifying and reconstructing FC using only AD sensitive components or connectivity modes. We show that this framework (1) increases test-retest correspondence and (2) allows for better separation, in functional connectivity, of diagnostic groups both at the whole brain and individual resting state network level. Finally, we evaluate a posteriori the association between connectivity mode weights with longitudinal neurocognitive outcomes

Flux-noise spectra around the Kosterlitz-Thouless transition for two-dimensional superconductors

The flux-noise spectra around the Kosterlitz-Thouless transition are obtained from simulations of the two-dimensional resistively shunted junction model. In particular the dependence on the distance $d$ between the pick-up coil and the sample is investigated. The typical experimental situation corresponds to the large-$d$ limit and a simple relation valid in this limit between the complex impedance and the noise spectra is clarified. Features, which distinguish between the large- and small-$d$ limit, are identified and the possibility of observing these features in experiments is discussed.Comment: 12 pages including 8 figures, submitted to Phys. Rev.