A combinatorial approach to knot recognition

This is a report on our ongoing research on a combinatorial approach to knot recognition, using coloring of knots by certain algebraic objects called quandles. The aim of the paper is to summarize the mathematical theory of knot coloring in a compact, accessible manner, and to show how to use it for computational purposes. In particular, we address how to determine colorability of a knot, and propose to use SAT solving to search for colorings. The computational complexity of the problem, both in theory and in our implementation, is discussed. In the last part, we explain how coloring can be utilized in knot recognition

Sea-level constraints on the amplitude and source distribution of Meltwater Pulse 1A.

During the last deglaciation, sea levels rose as ice sheets retreated. This climate transition was punctuated by periods of more intense melting; the largest and most rapid of these—Meltwater Pulse 1A—occurred about 14,500 years ago, with rates of sea-level rise reaching approximately 4 m per century1, 2, 3. Such rates of rise suggest ice-sheet instability, but the meltwater sources are poorly constrained, thus limiting our understanding of the causes and impacts of the event4, 5, 6, 7. In particular, geophysical modelling studies constrained by tropical sea-level records1, 8, 9 suggest an Antarctic contribution of more than seven metres, whereas most reconstructions10 from Antarctica indicate no substantial change in ice-sheet volume around the time of Meltwater Pulse 1A. Here we use a glacial isostatic adjustment model to reinterpret tropical sea-level reconstructions from Barbados2, the Sunda Shelf3 and Tahiti1. According to our results, global mean sea-level rise during Meltwater Pulse 1A was between 8.6 and 14.6 m (95% probability). As for the melt partitioning, we find an allowable contribution from Antarctica of either 4.1 to 10.0 m or 0 to 6.9 m (95% probability), using two recent estimates11, 12 of the contribution from the North American ice sheets. We conclude that with current geologic constraints, the method applied here is unable to support or refute the possibility of a significant Antarctic contribution to Meltwater Pulse 1A

Inhalation characteristics of asthma patients, COPD patients and healthy volunteers with the Spiromax® and Turbuhaler® devices: a randomised, cross-over study.

BACKGROUND: Spiromax® is a novel dry-powder inhaler containing formulations of budesonide plus formoterol (BF). The device is intended to provide dose equivalence with enhanced user-friendliness compared to BF Turbuhaler® in asthma and chronic obstructive pulmonary disease (COPD). The present study was performed to compare inhalation parameters with empty versions of the two devices, and to investigate the effects of enhanced training designed to encourage faster inhalation. METHODS: This randomised, open-label, cross-over study included children with asthma (n = 23), adolescents with asthma (n = 27), adults with asthma (n = 50), adults with COPD (n = 50) and healthy adult volunteers (n = 50). Inhalation manoeuvres were recorded with each device after training with the patient information leaflet (PIL) and after enhanced training using an In-Check Dial device. RESULTS: After PIL training, peak inspiratory flow (PIF), maximum change in pressure (∆P) and the inhalation volume (IV) were significantly higher with Spiromax than with the Turbuhaler device (p values were at least <0.05 in all patient groups). After enhanced training, numerically or significantly higher values for PIF, ∆P, IV and acceleration remained with Spiromax versus Turbuhaler, except for ∆P in COPD patients. After PIL training, one adult asthma patient and one COPD patient inhaled <30 L/min through the Spiromax compared to one adult asthma patient and five COPD patients with the Turbuhaler. All patients achieved PIF values of at least 30 L/min after enhanced training. CONCLUSIONS: The two inhalers have similar resistance so inhalation flows and pressure changes would be expected to be similar. The higher flow-related values noted for Spiromax versus Turbuhaler after PIL training suggest that Spiromax might have human factor advantages in real-world use. After enhanced training, the flow-related differences between devices persisted; increased flow rates were achieved with both devices, and all patients achieved the minimal flow required for adequate drug delivery. Enhanced training could be useful, especially in COPD patients

Amino Acid Requirements in Critically Ill Patients with Acute Kidney Injury Treated with Continuous Renal Replacement Therapy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90284/1/phco.28.5.600.pd

Mutations in thyroid hormone receptor α1 cause premature neurogenesis and progenitor cell depletion in human cortical development

Mutations in the thyroid hormone receptor α 1 gene (THRA) have recently been identified as a cause of intellectual deficit in humans. Patients present with structural abnormalities including microencephaly, reduced cerebellar volume and decreased axonal density. Here, we show that directed differentiation of THRA mutant patient-derived induced pluripotent stem cells to forebrain neural progenitors is markedly reduced, but mutant progenitor cells can generate deep and upper cortical layer neurons and form functional neuronal networks. Quantitative lineage tracing shows that THRA mutation-containing progenitor cells exit the cell cycle prematurely, resulting in reduced clonal output. Using a micropatterned chip assay, we find that spatial self-organization of mutation-containing progenitor cells in vitro is impaired, consistent with down-regulated expression of cell–cell adhesion genes. These results reveal that thyroid hormone receptor α1 is required for normal neural progenitor cell proliferation in human cerebral cortical development. They also exemplify quantitative approaches for studying neurodevelopmental disorders using patient-derived cells in vitro

Modeling and Measurement of Field and Flux of MPI

Magnetic particle inspection (MPI) is one of the oldest NDT techniques and it is the most common method used to detect surface defects in ferromagnetic materials. But since the beginning MPI has been based on experiments, experience and on subjective judgements. This contribution shows for the first time how MPI of complex shaped parts can be designed objectively by applying Maxwell equations and finite element calculations. The comparison between modelling and measurement shows substantial agreement. Results are given and discussed especially for automotive components like crankshaft and hub under DC- as well as AC-magnetization using coils and yokes

Human arachnoid granulations Part I: a technique for quantifying area and distribution on the superior surface of the cerebral cortex

<p>Abstract</p> <p>Background</p> <p>The arachnoid granulations (AGs) are herniations of the arachnoid membrane into the dural venous sinuses on the surface of the brain. Previous morphological studies of AGs have been limited in scope and only one has mentioned surface area measurements. The purpose of this study was to investigate the topographic distribution of AGs on the superior surface of the cerebral cortex.</p> <p>Methods</p> <p><it>En face </it>images were taken of the superior surface of 35 formalin-fixed human brains. AGs were manually identified using Adobe Photoshop, with a pixel location containing an AG defined as 'positive'. A set of 25 standard fiducial points was marked on each hemisphere for a total of 50 points on each image. The points were connected on each hemisphere to create a segmented image. A standard template was created for each hemisphere by calculating the average position of the 25 fiducial points from all brains. Each segmented image was mapped to the standard template using a linear transformation. A topographic distribution map was produced by calculating the proportion of AG positive images at each pixel in the standard template. The AG surface area was calculated for each hemisphere and for the total brain superior surface. To adjust for different brain sizes, the proportional involvement of AGs was calculated by dividing the AG area by the total area.</p> <p>Results</p> <p>The total brain average surface area of AGs was 78.53 ± 13.13 mm²(n = 35) and average AG proportional involvement was 57.71 × 10^-4± 7.65 × 10^-4. Regression analysis confirmed the reproducibility of AG identification between independent researchers with r²= 0.97. The surface AGs were localized in the parasagittal planes that coincide with the region of the lateral lacunae.</p> <p>Conclusion</p> <p>The data obtained on the spatial distribution and <it>en face </it>surface area of AGs will be used in an <it>in vitro </it>model of CSF outflow. With an increase in the number of samples, this analysis technique can be used to study the relationship between AG surface area and variables such as age, race and gender.</p

Measuring and Modeling Risk Using High-Frequency Data

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns. In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures of systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorporation and of the DJIA index

Quantifying the effects of climate change and water abstraction on a population of barramundi (Lates calcarifer), a diadromous estuarine finfish

Many aquatic species are linked to environmental drivers such as temperature and salinity through processes such as spawning, recruitment and growth. Information is needed on how fished species may respond to altered environmental drivers under climate change so that adaptive management strategies can be developed. Barramundi (Lates calcarifer) is a highly prized species of the Indo-West Pacific, whose recruitment and growth is driven by river discharge. We developed a monthly age- and length-structured population model for barramundi. Monte Carlo Markov Chain simulations were used to explore the population's response to altered river discharges under modelled total licenced water abstraction and projected climate change, derived and downscaled from Global Climate Model A1FI. Mean values of exploitable biomass, annual catch, maximum sustainable yield and spawning stock size were significantly reduced under scenarios where river discharge was reduced; despite including uncertainty. These results suggest that the upstream use of water resources and climate change have potential to significantly reduce downstream barramundi stock sizes and harvests and may undermine the inherent resilience of estuarine-dependent fisheries. © 2012 CSIRO