Mean-field descriptions of collective migration with strong adhesion

Random walk models based on an exclusion process with contact effects are often used to represent collective migration where individual agents are affected by agent-to-agent adhesion. Traditional mean field representations of these processes take the form of a nonlinear diffusion equation which, for strong adhesion, does not predict the averaged discrete behavior. We propose an alternative suite of mean-field representations, showing that collective migration with strong adhesion can be accurately represented using a moment closure approach.

Modeling ion channel dynamics through reflected stochastic differential equations

Ion channels are membrane proteins that open and close at random and play a vital role in the electrical dynamics of excitable cells. The stochastic nature of the conformational changes these proteins undergo can be significant, however current stochastic modeling methodologies limit the ability to study such systems. Discrete-state Markov chain models are seen as the "gold standard," but are computationally intensive, restricting investigation of stochastic effects to the single-cell level. Continuous stochastic methods that use stochastic differential equations (SDEs) to model the system are more efficient but can lead to simulations that have no biological meaning. In this paper we show that modeling the behavior of ion channel dynamics by a reflected SDE ensures biologically realistic simulations, and we argue that this model follows from the continuous approximation of the discrete-state Markov chain model. Open channel and action potential statistics from simulations of ion channel dynamics using the reflected SDE are compared with those of a discrete-state Markov chain method. Results show that the reflected SDE simulations are in good agreement with the discrete-state approach. The reflected SDE model therefore provides a computationally efficient method to simulate ion channel dynamics while preserving the distributional properties of the discrete-state Markov chain model and also ensuring biologically realistic solutions. This framework could easily be extended to other biochemical reaction networks. © 2012 American Physical Society.

(Ultra)fast catalyst-free macromolecular conjugation in aqueous environment at ambient temperature

Tailor-made water-soluble macromolecules, including a glycopolymer, obtained by living/controlled RAFT-mediated polymerization are demonstrated to react in water with diene-functionalized poly(ethylene glycol)s without pre- or post-functionalization steps or the need for a catalyst at ambient temperature. As previously observed in organic solvents, hetero-Diels-Alder (HDA) conjugations reached quantitative conversion within minutes when cyclopentadienyl moieties were involved. However, while catalysts and elevated temperatures were previously necessary for open-chain diene conjugation, additive-free HDA cycloadditions occur in water within a few hours at ambient temperature. Experimental evidence for efficient conjugations is provided via unambiguous ESI-MS, UV/vis, NMR, and SEC data.

Numerical methods for solving a two-dimensional variable-order anomalous subdiffusion equation

Anomalous subdiffusion equations have in recent years received much attention. In this paper, we consider a two-dimensional variable-order anomalous subdiffusion equation. Two numerical methods (the implicit and explicit methods) are developed to solve the equation. Their stability, convergence and solvability are investigated by the Fourier method. Moreover, the effectiveness of our theoretical analysis is demonstrated by some numerical examples. © 2011 American Mathematical Society.

Ozone-initiated particle formation, particle aging, and precursors in a laser printer

An increasing number of researchers have hypothesized that ozone may be involved in the particle formation processes that occur during printing, however no studies have investigated this further. In the current study, this hypothesis was tested in a chamber study by adding supplemental ozone to the chamber after a print job without measurable ozone emissions. Subsequent particle number concentration and size distribution measurements showed that new particles were formed minutes after the addition of ozone. The results demonstrated that ozone did react with printer-generated volatile organic compounds (VOCs) to form secondary organic aerosols (SOAs). The hypothesis was further confirmed by the observation of correlations among VOCs, ozone, and particles concentrations during a print job with measurable ozone emissions. The potential particle precursors were identified by a number of furnace tests, which suggested that squalene and styrene were the most likely SOA precursors with respect to ozone. Overall, this study significantly improved scientific understanding of the formation mechanisms of printer-generated particles, and highlighted the possible SOA formation potential of unsaturated nonterpene organic compounds by ozone-initiated reactions in the indoor environment. © 2011 American Chemical Society.

Amphiphilic silicone archtectures via anaerobic thiol - ene chemistry

Despite broad application, few silicone-based surfactants of known structure or, therefore, surfactancy have been prepared because of an absence of selective routes and instability of silicones to acid and base. Herein the synthesis of a library of explicit silicone-poly(ethylene glycol) (PEG) materials is reported. Pure silicone fragments were generated by the B(C(6)F(5))(3)-catalyzed condensation of alkoxysilanes and vinyl-functionalized hydrosilanes. The resulting pure products were coupled to thiol-terminated PEG materials using photogenerated radicals under anaerobic conditions.

Physicochemical characterization of particulate emissions from a compression ignition engine employing two injection technologies and three fuels

Alternative fuels and injection technologies are a necessary component of particulate emission reduction strategies for compression ignition engines. Consequently, this study undertakes a physicochemical characterization of diesel particulate matter (DPM) for engines equipped with alternative injection technologies (direct injection and common rail) and alternative fuels (ultra low sulfur diesel, a 20% biodiesel blend, and a synthetic diesel). Particle physical properties were addressed by measuring particle number size distributions, and particle chemical properties were addressed by measuring polycyclic aromatic hydrocarbons (PAHs) and reactive oxygen species (ROS). Particle volatility was determined by passing the polydisperse size distribution through a thermodenuder set to 300 °C. The results from this study, conducted over a four point test cycle, showed that both fuel type and injection technology have an impact on particle emissions, but injection technology was the more important factor. Significant particle number emission (54%–84%) reductions were achieved at half load operation (1% increase–43% decrease at full load) with the common rail injection system; however, the particles had a significantly higher PAH fraction (by a factor of 2 to 4) and ROS concentrations (by a factor of 6 to 16) both expressed on a test-cycle averaged basis. The results of this study have significant implications for the health effects of DPM emissions from both direct injection and common rail engines utilizing various alternative fuels.