Modulus and Poincaré Inequalities on Non-Self-Similar Sierpiński Carpets

A carpet is a metric space homeomorphic to the Sierpiński carpet. We characterize, within a certain class of examples, non-self-similar carpets supporting curve families of nontrivial modulus and supporting Poincaré inequalities. Our results yield new examples of compact doubling metric measure spaces supporting Poincaré inequalities: these examples have no manifold points, yet embed isometrically as subsets of Euclidean space.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Influence of microphysical schemes on atmospheric water in the Weather Research and Forecasting model

This study examines how different microphysical parameterization schemes influence orographically induced precipitation and the distributions of hydrometeors and water vapour for midlatitude summer conditions in the Weather Research and Forecasting (WRF) model. A high-resolution two-dimensional idealized simulation is used to assess the differences between the schemes in which a moist air flow is interacting with a bell-shaped 2 km high mountain. Periodic lateral boundary conditions are chosen to recirculate atmospheric water in the domain. It is found that the 13 selected microphysical schemes conserve the water in the model domain. The gain or loss of water is less than 0.81% over a simulation time interval of 61 days. The differences of the microphysical schemes in terms of the distributions of water vapour, hydrometeors and accumulated precipitation are presented and discussed. The Kessler scheme, the only scheme without ice-phase processes, shows final values of cloud liquid water 14 times greater than the other schemes. The differences among the other schemes are not as extreme, but still they differ up to 79% in water vapour, up to 10 times in hydrometeors and up to 64% in accumulated precipitation at the end of the simulation. The microphysical schemes also differ in the surface evaporation rate. The WRF single-moment 3-class scheme has the highest surface evaporation rate compensated by the highest precipitation rate. The different distributions of hydrometeors and water vapour of the microphysical schemes induce differences up to 49 W m−2 in the downwelling shortwave radiation and up to 33 W m−2 in the downwelling longwave radiation.

A generalisation of the fractional Brownian field based on non-Euclidean norms

We explore a generalisation of the L´evy fractional Brownian field on the Euclidean space based on replacing the Euclidean norm with another norm. A characterisation result for admissible norms yields a complete description of all self-similar Gaussian random fields with stationary increments. Several integral representations of the introduced random fields are derived. In a similar vein, several non-Euclidean variants of the fractional Poisson field are introduced and it is shown that they share the covariance structure with the fractional Brownian field and converge to it. The shape parameters of the Poisson and Brownian variants are related by convex geometry transforms, namely the radial pth mean body and the polar projection transforms.

The consequences of social intolerance on non-violent protest behavior

This paper scrutinizes the impact of intolerance toward diverse ethnic, religious, and cultural groups on an individuals willingness to actively engage in non-violent protest. Following new insights, we examine the individual as well as the ecological effect of social intolerance on protest behavior. Drawing from insights of social psychology and communication science, we expect that the prevalence of intolerance reinforces the positive effect of individual-level intolerance on protest participation. From a rational choice perspective, however, a negative moderating effect is expected, as the expression of opinions becomes redundant for intolerant individuals in an intolerant society. We base our multilevel analyses on data from the World Values Surveys covering 32 established democracies. Our results reveal that intolerance leads to more non-violent protest participation. This relationship, however, is strongly influenced by the prevalence of intolerance in a country.

Regulation of peripheral classical and non-classical monocytes on infliximab treatment in patients with rheumatoid arthritis and ankylosing spondylitis.

OBJECTIVE To investigate the regulatory effect of tumour necrosis factor (TNF) blockade with infliximab on the distribution of peripheral blood monocyte subpopulations in patients with rheumatoid arthritis (RA) and ankylosing spondylitis (AS). METHODS Purified CD11b+CD14+ monocytes from 5 patients with RA and 5 AS were analysed ex vivo before and after infliximab treatment by flow cytometry for CD16, CD163, CD11b, C-C chemokine receptor type 2 (CCR2) and CXC chemokine receptor 4 (CXCR4) at baseline and at days 2, 14, 84 and 168 after the first infliximab administration. Serum levels of the stromal cell-derived factor (SDF)-1 and monocyte chemotactic peptide (MCP)-1 at different time points were measured in either patient group before and on infliximab treatment. RESULTS Anti-TNF treatment with infliximab led to a significant increase of circulating CD11b+ non-classical and a concomitantly decrease of CD11b+ classical monocytes, to a decline in SDF-1 levels and reduced expression of CCR2 and CXCR4 on non-classical monocyte subpopulation. CONCLUSIONS Our study shows, that TNFα blockade by infliximab resulted in a dichotomy of the regulation of classical and non-classical monocytes that might have substantial impact on inhibition of osteoclastogenesis and of subsequent juxta-articular bone destruction and systemic bone loss in RA and AS.

Effects of {beta}-blocker selectivity on blood pressure variability and stroke: A systematic review

β-Blockers increase variability in systolic blood pressure (SBP), which probably explains their lesser effectiveness in preventing stroke vs myocardial infarction compared with other agents. This increase in variability in blood pressure (BP) may be particularly marked on non-cardioselective agents, potentially calling into question the widespread first-line use of propranolol in migraine with aura, elderly patients with essential tremor or anxiety, and other groups at risk of stroke.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.