Aggregation and clogging phenomena of rigid microparticles in microfluidics

We developed a numerical tool to investigate the phenomena of aggregation and clogging of rigid microparticles suspended in a Newtonian fluid transported through a straight microchannel. In a first step, we implement a time-dependent one-way coupling Discrete Element Method (DEM) technique to simulate the movement and effect of adhesion on rigid microparticles in two- and three-dimensional computational domains. The Johnson–Kendall–Roberts (JKR) theory of adhesion is applied to investigate the contact mechanics of particle–particle and particle–wall interactions. Using the one-way coupled solver, the agglomeration, aggregation and deposition behavior of the microparticles is studied by varying the Reynolds number and the particle adhesion. In a second step, we apply a two-way coupling CFD–DEM approach, which solves the equation of motion for each particle, and transfers the force field corresponding to particle–fluid interactions to the CFD toolbox OpenFOAM. Results for the one-way (DEM) and two-way (CFD–DEM) coupling techniques are compared in terms of aggregate size, aggregate percentages, spatial and temporal evaluation of aggregates in 2D and 3D. We conclude that two-way coupling is the more realistic approach, which can accurately capture the particle–fluid dynamics in microfluidic applications.     

Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions

Data Mining and Knowledge Discovery - Discrete Markov chains are frequently used to analyse transition behaviour in sequential data. Here, the transition probabilities can be estimated using...     

Solid state NMR study of segmented polymer networks: fine-tuning of phase morphology via their molecular design

Segmented polymer networks (SPNs) based on thermo-sensitive poly(N-isopropyl acryl amide) (PNIPAA) and poly(tetrahydrofuran) (PTHF) have been synthesized by free radical copolymerization of PTHF bis-macromonomers with N-isopropyl acrylamide. The nature of the polymerizable end group on the bis-macromonomer has been varied, respectively from acrylate to acrylamide end groups. The multiphase behaviour of the corresponding SPNs has been examined as a function of the nature of the end group by making use of solid-state ¹³C CP/MAS NMR relaxometry, ¹H wideline NMR relaxometry and dynamic mechanical analysis (DMA). When PTHF with acrylate end groups was used during the SPN formation, analysis of proton spin-lattice relaxation times (T_1H) and proton spin-lattice relaxation times in the rotating frame (T_1ρH) revealed phase separation with domain sizes larger than 5 nm when the PTHF fraction exceeds 10 wt%. Only for lower PTHF-amounts, the SPNs were homogeneous on the nanometer scale. On the other hand, when PTHF with acrylamide end groups was used as macromolecular cross-linker, the NMR results showed the absence of any domain formation for SPNs with PTHF fractions up to 50 wt%. The major impact of the molecular design on the ultimate phase morphology of bicomponent polymer networks has been confirmed in all cases by DMA-analysis.     

Improving accuracy in detecting acoustic onsets.

In current cognitive psychology, naming latencies are commonly measured by electronic voice keys that detect when sound exceeds a certain amplitude threshold. However, recent research (e.g., K. Rastle & M. H. Davis, 2002) has shown that these devices are particularly inaccurate in precisely detecting acoustic onsets. In this article, the authors discuss the various problems and solutions that have been put forward with respect to this issue and show that classical voice keys may trigger several tens of milliseconds later than acoustic onset. The authors argue that a solution to this problem may come from voice keys that use a combination of analogue and digital noise (nonspeech sound) detection. It is shown that the acoustic onsets detected by such a device are only a few milliseconds delayed and correlate highly (up to .99) with reaction time values obtained by visual waveform inspection. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of nitrogen lewis basicity in boronate affinity chromatography of nucleosides

Urinary modified nucleosides have a potential role as cancer biomarkers, and most of the methods used in their study have utilized low-pressure phenylboronate affinity chromatography materials for the purification of the cis-diol-containing nucleosides. In this study, a boronate HPLC column was surprisingly shown not to trap the nucleosides as would be expected from experience with the classic Affigel 601 resin but showed only partial selectivity toward cis-diol groups while other groups exhibited better retention. In aprotic conditions, trapping of nucleosides was possible; however, the selectivity toward cis-diol-containing compounds was lost with the Lewis basicity of available nitrogens being the main determinant of retention. The experimental findings are compared to and confirmed by DFT calculations.     

The Progress of Intestinal Epithelial Models from Cell Lines to Gut-On-Chip

Over the past years, several preclinical in vitro and ex vivo models have been developed that helped to understand some of the critical aspects of intestinal functions in health and disease such as inflammatory bowel disease (IBD). However, the translation to the human in vivo situation remains problematic. The main reason for this is that these approaches fail to fully reflect the multifactorial and complex in vivo environment (e.g., including microbiota, nutrition, and immune response) in the gut system. Although conventional models such as cell lines, Ussing chamber, and the everted sac are still used, increasingly more sophisticated intestinal models have been developed over the past years including organoids, InTESTine™ and microfluidic gut-on-chip. In this review, we gathered the most recent insights on the setup, advantages, limitations, and future perspectives of most frequently used in vitro and ex vivo models to study intestinal physiology and functions in health and disease.     

Filter-resistant code injection on ARM

Code injection attacks are one of the most powerful and important classes of attacks on software. In these attacks, the attacker sends malicious input to a software application, where it is stored in memory. The malicious input is chosen in such a way that its representation in memory is also a valid representation of a machine code program that performs actions chosen by the attacker. The attacker then triggers a bug in the application to divert the control flow to this injected machine code. A typical action of the injected code is to launch a command interpreter shell, and hence the malicious input is often called shellcode. Attacks are usually performed against network facing applications, and such applications often perform validations or encodings on input. Hence, a typical hurdle for attackers, is that the shellcode has to pass one or more filtering methods before it is stored in the vulnerable application??s memory space. Clearly, for a code injection attack to succeed, the malicious input must survive such validations and transformations. Alphanumeric input (consisting only of letters and digits) is typically very robust for this purpose: it passes most filters and is untouched by most transformations. This paper studies the power of alphanumeric shellcode on the ARM architecture. It shows that the subset of ARM machine code programs that (when interpreted as data) consist only of alphanumerical characters is a Turing complete subset. This is a non-trivial result, as the number of instructions that consist only of alphanumeric characters is very limited. To craft useful exploit code (and to achieve Turing completeness), several tricks are needed, including the use of self-modifying code.