Stochastic chemical kinetics and the quasi-steady-state assumption : application to the stochastic simulation algorithm and chemical master equation

Recently the application of the quasi-steady-state approximation (QSSA) to the stochastic simulation algorithm (SSA) was suggested for the purpose of speeding up stochastic simulations of chemical systems that involve both relatively fast and slow chemical reactions [Rao and Arkin, J. Chem. Phys. 118, 4999 (2003)] and further work has led to the nested and slow-scale SSA. Improved numerical efficiency is obtained by respecting the vastly different time scales characterizing the system and then by advancing only the slow reactions exactly, based on a suitable approximation to the fast reactions. We considerably extend these works by applying the QSSA to numerical methods for the direct solution of the chemical master equation (CME) and, in particular, to the finite state projection algorithm [Munsky and Khammash, J. Chem. Phys. 124, 044104 (2006)], in conjunction with Krylov methods. In addition, we point out some important connections to the literature on the (deterministic) total QSSA (tQSSA) and place the stochastic analogue of the QSSA within the more general framework of aggregation of Markov processes. We demonstrate the new methods on four examples: Michaelis–Menten enzyme kinetics, double phosphorylation, the Goldbeter–Koshland switch, and the mitogen activated protein kinase cascade. Overall, we report dramatic improvements by applying the tQSSA to the CME solver.

Accelerated computation of cyclic steady state for simulated-moving-bed processes

Industrial applications of the simulated-moving-bed (SMB) chromatographic technology have brought an emergent demand to improve the SMB process operation for higher efficiency and better robustness. Improved process modelling and more-efficient model computation will pave a path to meet this demand. However, the SMB unit operation exhibits complex dynamics, leading to challenges in SMB process modelling and model computation. One of the significant problems is how to quickly obtain the steady state of an SMB process model, as process metrics at the steady state are critical for process design and real-time control. The conventional computation method, which solves the process model cycle by cycle and takes the solution only when a cyclic steady state is reached after a certain number of switching, is computationally expensive. Adopting the concept of quasi-envelope (QE), this work treats the SMB operation as a pseudo-oscillatory process because of its large number of continuous switching. Then, an innovative QE computation scheme is developed to quickly obtain the steady state solution of an SMB model for any arbitrary initial condition. The QE computation scheme allows larger steps to be taken for predicting the slow change of the starting state within each switching. Incorporating with the wavelet-based technique, this scheme is demonstrated to be effective and efficient for an SMB sugar separation process. Moreover, investigations are also carried out on when the computation scheme should be activated and how the convergence of the scheme is affected by a variable stepsize.

Volatile properties of particles emitted by compressed natural gas and diesel buses during steady state and transient driving modes

Volatile properties of particle emissions from four compressed natural gas (CNG) and four diesel buses were investigated under steady state and transient driving modes on a chassis dynamometer. The exhaust was diluted utilising a full-flow continuous volume sampling system and passed through a thermodenuder at controlled temperature. Particle number concentration and size distribution were measured with a condensation particle counter and a scanning mobility particle sizer, respectively. We show that, while almost all the particles emitted by the CNG buses were in the nanoparticle size range, at least 85% and 98% were removed at 100ºC and 250ºC, respectively. Closer analysis of the volatility of particles emitted during transient cycles showed that volatilisation began at around 40°C with the majority occurring by 80°C. Particles produced during hard acceleration from rest exhibited lower volatility than that produced during other times of the cycle. Based on our results and the observation of ash deposits on the walls of the tailpipes, we suggest that these non-volatile particles were composed mostly of ash from lubricating oil. Heating the diesel bus emissions to 100ºC removed ultrafine particle numbers by 69% to 82% when a nucleation mode was present and just 18% when it was not.

How long does it take for aquifer recharge or aquifer discharge processes to reach steady state?

Groundwater flow models are usually characterized as being either transient flow models or steady state flow models. Given that steady state groundwater flow conditions arise as a long time asymptotic limit of a particular transient response, it is natural for us to seek a finite estimate of the amount of time required for a particular transient flow problem to effectively reach steady state. Here, we introduce the concept of mean action time (MAT) to address a fundamental question: How long does it take for a groundwater recharge process or discharge processes to effectively reach steady state? This concept relies on identifying a cumulative distribution function, $F(t;x)$, which varies from $F(0;x)=0$ to $F(t;x) \to \infty$ as $t\to \infty$, thereby providing us with a measurement of the progress of the system towards steady state. The MAT corresponds to the mean of the associated probability density function $f(t;x) = \dfrac{dF}{dt}$, and we demonstrate that this framework provides useful analytical insight by explicitly showing how the MAT depends on the parameters in the model and the geometry of the problem. Additional theoretical results relating to the variance of $f(t;x)$, known as the variance of action time (VAT), are also presented. To test our theoretical predictions we include measurements from a laboratory–scale experiment describing flow through a homogeneous porous medium. The laboratory data confirms that the theoretical MAT predictions are in good agreement with measurements from the physical model.

Volatile properties of CNG and Diesel bus emissions produced during steady state and transient driving modes

An analysis of the emissions from 14 CNG and 5 Diesel buses was conducted during April & May, 2006. Studies were conducted at both steady state and transient driving modes on a vehicle dynamometer utilising a CVS dilution system. This article will focus on the volatile properties of particles from 4 CNG and 4 Diesel vehicles from within this group with a priority given to the previously un-investigated CNG emissions produced at transient loads. Particle number concentration data was collected by three CPC’s (TSI 3022, 3010 & 3782WCPC) having D50 cut-offs set to 5nm, 10nm & 20nm respectively. Size distribution data was collected using a TSI 3080 SMPS with a 3025 CPC during the steady state driving modes. During transient cycles mono-disperse “slices” of between 5nm & 25nm were measured. The volatility of these particles was determined by placing a thermodenuder before the 3022 and the SMPS and measuring the reduction in particle number concentration as the temperature in the thermodenuder was increased. This was then normalised against the total particle count given by the 3010 CPC to provide high resolution information on the reduction in particle concentration with respect to temperature.

Nanoparticle emissions from a fleet of CNG buses in transient and steady state operation

Particle emission measurements from a fleet of 14 CNG and 5 Diesel buses were measured both for transient and steady state mode s on a chassis dynamometer with a CVS dilution system. Several transient DT80 cycles and 4 steady sate modes (0, 25, 50 100% of maximum load) were measured for each bus tested. Particle number concentration data was collected by three CPC’s (TSI 3022, 3010 3782WCPC) having D50 cut-offs set to 5, 10 and 20nm respectively. The size distributions were measured with a TSI 3080 SMPS with a 3025 CPC during the steady state modes. Particle mass emissions were measured with a TSI Dustrak. Particle mass emissions for Diesel buses were upto 2 orders of magnitude higher than for CNG buses. Particle number emissions during steady state modes for Diesel busses were 2 to 5 times higher than for CNG busses for all of the tested loads. On the other hand for the DT80 transient cycle particle number emissions were up to 3 times higher for the CNG buses. More detailed analysis of the transient cycles revealed that the reason for this was due to high particle number emissions from CNG busses during the acceleration parts of the cycles. Particles emitted by the CNG busses during acceleration were in the nucleation mode with the majority being smaller than 10nm. Volatility measurements have also shown that they were highly volatile.

Steady state and transient dynamometer vehicle emission measurements using a DiSC

Analysis of the particulate size and number concentration emissions from a fleet of inner city medium duty CNG buses was conducted using the newly available Diffusion Size Classifier in comparison with more traditional SMPS's and CPC's. Studies were conducted at both steady state and transient driving modes on a vehicle dynamometer utilising a CVS dilution system. Comparative analysis of the results showed that the DiSC provided equivalent information during steady state conditions and was able to provide additional information during transient conditions, namely, the modal diameter of the particle size distribution.

Steady state genuine multipartite entanglement in harmonic oscillator ensembles with a common environment

Steady state entanglement in ensembles of harmonic oscillators with a common squeezed reservoir is studied. Under certain conditions the ensemble features genuine multipartite entanglement in the steady state. Several analytic results regarding the bipartite and multipartite entanglement properties of the system are derived. We also discuss a possible experimental implementation which may exhibit steady state genuine multipartite entanglement.

Examining the neural correlates of choice behavior in a gambling task using steady state topography

The present study investigated the behavioral and neuropsychological characteristics of decision-making behavior during a gambling task as well as how these characteristics may relate to the Somatic Marker Hypothesis and the Frequency of Gain model. The applicability to intertemporal choice was also discussed. Patterns of card selection during a computerized interpretation of the Iowa Gambling Task were assessed for 10 men and 10 women. Steady State Topography was employed to assess cortical processing throughout this task. Results supported the hypothesis that patterns of card selection were in line with both theories. As hypothesized, these 2 patterns of card selection were also associated with distinct patterns of cortical activity, suggesting that intertemporal choice may involve the recruitment of right dorsolateral prefrontal cortex for somatic labeling, left fusiform gyrus for object representations, and the left dorsolateral prefrontal cortex for an analysis of the associated frequency of gain or loss. It is suggested that processes contributing to intertemporal choice may include inhibition of negatively valenced options, guiding decisions away from those options, as well as computations favoring frequently rewarded options.

Steady state visually evoked potential correlates of static and dynamic emotional face processing

While the neural regions associated with facial identity recognition are considered to be well defined, the neural correlates of non-moving and moving images of facial emotion processing are less clear. This study examined the brain electrical activity changes in 26 participants (14 males M = 21.64, SD = 3.99; 12 females M = 24.42, SD = 4.36), during a passive face viewing task, a scrambled face task and separate emotion and gender face discrimination tasks. The steady state visual evoked potential (SSVEP) was recorded from 64-electrode sites. Consistent with previous research, face related activity was evidenced at scalp regions over the parieto-temporal region approximately 170 ms after stimulus presentation. Results also identified different SSVEP spatio-temporal changes associated with the processing of static and dynamic facial emotions with respect to gender, with static stimuli predominately associated with an increase in inhibitory processing within the frontal region. Dynamic facial emotions were associated with changes in SSVEP response within the temporal region, which are proposed to index inhibitory processing. It is suggested that static images represent non-canonical stimuli which are processed via different mechanisms to their more ecologically valid dynamic counterparts.

Steady-state dendritic cells expressing cognate antigen terminate memory CD8+ T-cell responses

Antigen stimulation of naive T cells in conjunction with strong costimulatory signals elicits the generation of effector and memory populations. Such terminal differentiation transforms naive T cells capable of differentiating along several terminal pathways in response to pertinent environmental cues into cells that have lost developmental plasticity and exhibit heightened responsiveness. Because these cells exhibit little or no need for the strong costimulatory signals required for full activation of naive T cells, it is generally considered memory and effector T cells are released from the capacity to be inactivated. Here, we show that steadystate dendritic cells constitutively presenting an endogenously expressed antigen inactivate fully differentiated memory and effector CD8+ T cells in vivo through deletion and inactivation. These findings indicate that fully differentiated effector and memory T cells exhibit a previously unappreciated level of plasticity and provide insight into how memory and effector T-cell populations may be regulated. © 2008 by The American Society of Hematology.

Particle and gaseous emissions from compressed natural gas and ultralow sulphur diesel-fuelled buses at four steady engine loads

Exhaust emissions from thirteen compressed natural gas (CNG) and nine ultralow sulphur diesel in-service transport buses were monitored on a chassis dynamometer. Measurements were carried out at idle and at three steady engine loads of 25%, 50% and 100% of maximum power at a fixed speed of 60 kmph. Emission factors were estimated for particle mass and number, carbon dioxide and oxides of nitrogen for two types of CNG buses (Scania and MAN, compatible with Euro 2 and 3 emission standards, respectively) and two types of diesel buses (Volvo Pre-Euro/Euro1 and Mercedez OC500 Euro3). All emission factors increased with load. The median particle mass emission factor for the CNG buses was less than 1% of that from the diesel buses at all loads. However, the particle number emission factors did not show a statistically significant difference between buses operating on the two types of fuel. In this paper, for the very first time, particle number emission factors are presented at four steady state engine loads for CNG buses. Median values ranged from the order of 1012 particles min-1 at idle to 1015 particles km-1 at full power. Most of the particles observed in the CNG emissions were in the nanoparticle size range and likely to be composed of volatile organic compounds The CO2 emission factors were about 20% to 30% greater for the diesel buses over the CNG buses, while the oxides of nitrogen emission factors did not show any difference due to the large variation between buses.

Workflow simulation for operational decision support

Simulation is widely used as a tool for analyzing business processes but is mostly focused on examining abstract steady-state situations. Such analyses are helpful for the initial design of a business process but are less suitable for operational decision making and continuous improvement. Here we describe a simulation system for operational decision support in the context of workflow management. To do this we exploit not only the workflow’s design, but also use logged data describing the system’s observed historic behavior, and incorporate information extracted about the current state of the workflow. Making use of actual data capturing the current state and historic information allows our simulations to accurately predict potential near-future behaviors for different scenarios. The approach is supported by a practical toolset which combines and extends the workflow management system YAWL and the process mining framework ProM.