Responsive glyco-poly(2-oxazoline)s: synthesis, cloud point tuning, and lectin binding

A new sugar-substituted 2-oxazoline monomer was prepared using the copper-catalyzed alkyne-azide cycloaddition (CuAAC) reaction. Its copolymerization with 2-ethyl-2-oxazoline as well as 2-(dec-9-enyl)-2-oxazoline, yielding well-defined copolymers with the possibility to tune the properties by thiol-ene "click" reactions, is described. Extensive solubility studies on the corresponding glycocopolymers demonstrated that the lower critical solution temperature behavior and pH-responsiveness of these copolymers can be adjusted in water and phosphate-buffered saline (PBS) depending on the choice of the thiol. By conjugation of 2,3,4,6-tetra-O-acetyl-1-thio-beta-D-glucopyranose and subsequent deprotection of the sugar moieties, the hydrophilicity of the copolymer could be increased significantly, allowing a cloud-point tuning in the physiological range. Furthermore, the binding capability of the glycosylated copoly(2-oxazoline) to concanavalin A was investigated

Meere und Kuestenraeume, Haefen und Verkehr Vortraege und Arbeitsberichte

TIB: RN 9170 (2) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

Time-resolved tomographic cardiac imaging using an angiographic C-arm device may support clinicians during minimally invasive therapy by enabling a thorough analysis of the heart function directly in the catheter laboratory. However, clinically feasible acquisition protocols entail a highly challenging reconstruction problem which suffers from sparse angular sampling of the trajectory. Compressed sensing theory promises that useful images can be recovered despite massive undersampling by means of sparsity-based regularization. For a multitude of reasons-most notably the desired reduction of scan time, dose and contrast agent required-it is of great interest to know just how little data is actually sufficient for a certain task. In this work, we apply a convex optimization approach based on primaldual splitting to 4D cardiac C-arm computed tomography. We examine how the quality of spatially and temporally total-variation-regularized reconstruction degrades when using as few as 6.9 ± 1.2 projection views per heart phase. First, feasible regularization weights are determined in a numerical phantom study, demonstrating the individual benefits of both regularizers. Secondly, a task-based evaluation is performed in eight clinical patients. Semi-automatic segmentation-based volume measurements of the left ventricular blood pool performed on strongly undersampled images show a correlation of close to 99% with measurements obtained from less sparsely sampled data

A flexible framework for mobile device forensics based on cold boot attacks

Mobile devices, like tablets and smartphones, are common place in everyday life. Thus, the degree of security these devices can provide against digital forensics is of particular interest. A common method to access arbitrary data in main memory is the cold boot attack. The cold boot attack exploits the remanence effect that causes data in DRAM modules not to lose the content immediately in case of a power cut-off. This makes it possible to restart a device and extract the data in main memory. In this paper, we present a novel framework for cold boot-based data acquisition with a minimal bare metal application on a mobile device. In contrast to other cold boot approaches, our forensics tool overwrites only a minimal amount of data in main memory. This tool requires no more than three kilobytes of constant data in the kernel code section. We hence sustain all of the data relevant for the analysis of the previously running system. This makes it possible to analyze the memory with data acquisition tools. For this purpose, we extend the memory forensics tool Volatility in order to request parts of the main memory dynamically from our bare metal application. We show the feasibility of our approach on the Samsung Galaxy S4 and Nexus 5 mobile devices along with an extensive evaluation. First, we compare our framework to a traditional memory dump-based analysis. In the next step, we show the potential of our framework by acquiring sensitive user data