Nodular Cutaneous Amyloidosis at the Temple

A 52-year-old woman presented with a large partially yellow and erythematous tumor on her right temple. She reported that it had grown over the last 4 years. Regional lymph nodes were impalpable. A punch biopsy showed eosinophilic material in the dermis and subcutis. Immunohistochemistry showed positive staining for kappa and lambda light chains. Electron microscopy showed the typical amyloid fibrils (7–10 nm in diameter). There was no evidence of systemic amyloidosis, paraproteinemia or underlying plasmacytoma. The tumor was completely removed via curettage. At follow-up, the patient presented in good health with no signs of relapse

Worst-Case Energy Consumption Analysis for Energy-Constrained Embedded Systems

Abstract—The fact that energy is a scarce resource in many embedded real-time systems creates the need for energy-aware task schedulers, which not only guarantee timing constraints but also consider energy consumption. Unfortunately, existing approaches to analyze the worst-case execution time (WCET) of a task usually cannot be directly applied to determine its worst-case energy consumption (WCEC) due to execution time and energy consumption not being closely correlated on many state-of-the-art processors. Instead, a WCEC analyzer must take into account the particular energy characteristics of a target platform. In this paper, we present 0g, a comprehensive approach to WCEC analysis that combines different techniques to speed up the analysis and to improve results. If detailed knowledge about the energy costs of instructions on the target platform is available, our tool is able to compute upper bounds for the WCEC by statically analyzing the program code. Otherwise, a novel ap-proach allows 0g to determine the WCEC by measurement after having identified a set of suitable program inputs based on an auxiliary energy model, which specifies the energy consumption of instructions in relation to each other. Our experiments for three target platforms show that 0g provides precise WCEC estimates. I

Stability of shortest paths in complex networks with random edge weights

We study shortest paths and spanning trees of complex networks with random edge weights. Edges which do not belong to the spanning tree are inactive in a transport process within the network. The introduction of quenched disorder modifies the spanning tree such that some edges are activated and the network diameter is increased. With analytic random-walk mappings and numerical analysis, we find that the spanning tree is unstable to the introduction of disorder and displays a phase-transition-like behavior at zero disorder strength $\epsilon=0$. In the infinite network-size limit ($N\to \infty$), we obtain a continuous transition with the density of activated edges $\Phi$ growing like $\Phi \sim \epsilon^1$ and with the diameter-expansion coefficient $\Upsilon$ growing like $\Upsilon\sim \epsilon^2$ in the regular network, and first-order transitions with discontinuous jumps in $\Phi$ and $\Upsilon$ at $\epsilon=0$ for the small-world (SW) network and the Barab\'asi-Albert scale-free (SF) network. The asymptotic scaling behavior sets in when $N\gg N_c$, where the crossover size scales as $N_c\sim \epsilon^{-2}$ for the regular network, $N_c \sim \exp[\alpha \epsilon^{-2}]$ for the SW network, and $N_c \sim \exp[\alpha |\ln \epsilon| \epsilon^{-2}]$ for the SF network. In a transient regime with $N\ll N_c$, there is an infinite-order transition with $\Phi\sim \Upsilon \sim \exp[-\alpha / (\epsilon^2 \ln N)]$ for the SW network and $\sim \exp[ -\alpha / (\epsilon^2 \ln N/\ln\ln N)]$ for the SF network. It shows that the transport pattern is practically most stable in the SF network.Comment: 9 pages, 7 figur

Microscopic multifrequency MR elastography for mapping viscoelasticity in zebrafish

Purpose: The zebrafish (Danio rerio) has become an important animal model in a wide range of biomedical research disciplines. Growing awareness of the role of biomechanical properties in tumor progression and neuronal development has led to an increasing interest in the noninvasive mapping of the viscoelastic properties of zebrafish by elastography methods applicable to bulky and nontranslucent tissues. Methods: Microscopic multifrequency MR elastography is introduced for mapping shear wave speed (SWS) and loss angle (φ) as markers of stiffness and viscosity of muscle, brain, and neuroblastoma tumors in postmortem zebrafish with 60 µm in-plane resolution. Experiments were performed in a 7 Tesla MR scanner at 1, 1.2, and 1.4 kHz driving frequencies. Results: Detailed zebrafish viscoelasticity maps revealed that the midbrain region (SWS = 3.1 ± 0.7 m/s, φ = 1.2 ± 0.3 radian [rad]) was stiffer and less viscous than telencephalon (SWS = 2.6 ± 0. 5 m/s, φ = 1.4 ± 0.2 rad) and optic tectum (SWS = 2.6 ± 0.5 m/s, φ = 1.3 ± 0.4 rad), whereas the cerebellum (SWS = 2.9 ± 0.6 m/s, φ = 0.9 ± 0.4 rad) was stiffer but less viscous than both (all p < .05). Overall, brain tissue (SWS = 2.9 ± 0.4 m/s, φ = 1.2 ± 0.2 rad) had similar stiffness but lower viscosity values than muscle tissue (SWS = 2.9 ± 0.5 m/s, φ = 1.4 ± 0.2 rad), whereas neuroblastoma (SWS = 2.4 ± 0.3 m/s, φ = 0.7 ± 0.1 rad, all p < .05) was the softest and least viscous tissue. Conclusion: Microscopic multifrequency MR elastography-generated maps of zebrafish show many details of viscoelasticity and resolve tissue regions, of great interest in neuromechanical and oncological research and for which our study provides first reference values

A Flexible, Adaptive System for Data-Stream Processing in Energy-Constrained Ad-hoc Networks

Today's generation of sensor networks reflect several changes in system characteristics over traditional sensor networks. These changes affect three key aspects: energy as a fundamental resource, stream data processing, and the inherently dynamic structure of the overall system. In this paper we extract and present eight distinct challenges aligned to the key aspects which need to be addressed in the future. We use data of ongoing science and research projects to extract the most important challenges. These challenges need to be tackled in order to provide the basis for a flexible and adaptive system design which supports data-stream processing in energy-constrained ad-hoc networks