Real-time simulation of large open quantum spin systems driven by dissipation

We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

A Parallel Solver for the Time-Periodic Navier–Stokes Equations

We investigate parallel algorithms for the solution of the Navier–Stokes equations in space-time. For periodic solutions, the discretized problem can be written as a large non-linear system of equations. This system of equations is solved by a Newton iteration. The Newton correction is computed using a preconditioned GMRES solver. The parallel performance of the algorithm is illustrated.

Optimizing human in vivo dosing and delivery of β-alanine supplements for muscle carnosine synthesis

Interest into the effects of carnosine on cellular metabolism is rapidly expanding. The first study to demonstrate in humans that chronic β-alanine (BA) supplementation (~3-6 g BA/day for ~4 weeks) can result in significantly augmented muscle carnosine concentrations (>50%) was only recently published. BA supplementation is potentially poised for application beyond the niche exercise and performance-enhancement field and into other more clinical populations. When examining all BA supplementation studies that directly measure muscle carnosine (n=8), there is a significant linear correlation between total grams of BA consumed (of daily intake ranges of 1.6-6.4 g BA/day) versus both the relative and absolute increases in muscle carnosine. Supporting this, a recent dose-response study demonstrated a large linear dependency (R2=0.921) based on the total grams of BA consumed over 8 weeks. The pre-supplementation baseline carnosine or individual subjects' body weight (from 65 to 90 kg) does not appear to impact on subsequent carnosine synthesis from BA consumption. Once muscle carnosine is augmented, the washout is very slow (~2%/week). Recently, a slow-release BA tablet supplement has been developed showing a smaller peak plasma BA concentration and delayed time to peak, with no difference in the area under the curve compared to pure BA in solution. Further, this slow-release profile resulted in a reduced urinary BA loss and improved retention, while at the same time, eliciting minimal paraesthesia symptoms. However, our complete understanding of optimizing in vivo delivery and dosing of BA is still in its infancy. Thus, this review will clarify our current knowledge of BA supplementation to augment muscle carnosine as well as highlight future research questions on the regulatory points of control for muscle carnosine synthesis.

Exploiting Runtime Information in the IDE

Developers rely on the mechanisms provided by their IDE to browse and navigate a large software system. These mechanisms are usually based purely on a system's static source code. The static perspective, however, is not enough to understand an object-oriented program's behavior, in particular if implemented in a dynamic language. We propose to enhance IDEs with a program's runtime information (eg. message sends and type information) to support program comprehension through precise navigation and informative browsing. To precisely specify the type and amount of runtime data to gather about a system under development, dynamically and on demand, we adopt a technique known as partial behavioral reflection. We implemented navigation and browsing enhancements to an IDE that exploit this runtime information in a prototype called Hermion. We present preliminary validation of our experimental enhanced IDE by asking developers to assess its usefulness to understand an unfamiliar software system.

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.

Detection of urinary stones at reduced radiation exposure: a phantom study comparing computed radiography and a low-dose digital radiography linear slit scanning system

OBJECTIVE: In this experimental study we assessed the diagnostic performance of digital linear slit scanning radiography compared with computed radiography (CR) for the detection of urinary calculi in an anthropomorphic phantom imitating patients weighing approximately 58-88 kg. CONCLUSION: Compared with CR, linear slit scanning radiography is superior for the detection of urinary stones and may be used for pretreatment localization and follow-up at a lower patient exposure.