Oscillatory regulation of Hes1: discrete stochastic delay modelling and simulation

Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein

Effect of zeolite topology and reactor configuration on the direct conversion of CO2 to light olefins and aromatics

The direct transformation of CO2 into high-value-added hydrocarbons (i.e., olefins and aromatics) has the potential to make a decisive impact in our society. However, despite the efforts of the scientific community, no direct synthetic route exists today to synthesize olefins and aromatics from CO2 with high productivities and low undesired CO selectivity. Herein, we report the combination of a series of catalysts comprising potassium superoxide doped iron oxide and a highly acidic zeolite (ZSM-5 and MOR) that directly convert CO2 to either light olefins (in MOR) or aromatics (in ZSM-5) with high space–time yields (STYC2-C4= = 11.4 mmol·g–1·h–1; STYAROM = 9.2 mmol·g–1·h–1) at CO selectivities as low as 12.8% and a CO2 conversion of 49.8% (reaction conditions: T = 375 °C, P = 30 bar, H2/CO2 = 3, and 5000 mL·g–1·h–1). Comprehensive solid-state nuclear magnetic resonance characterization of the zeolite component reveals that the key for the low CO selectivity is the formation of surface formate species on the zeolite framework. The remarkable difference in selectivity between the two zeolites is further rationalized by first-principles simulations, which show a difference in reactivity for crucial carbenium ion intermediates in MOR and ZSM-5

Non-fragile H∞ control with randomly occurring gain variations, distributed delays and channel fadings

This study is concerned with the non-fragile H∞ control problem for a class of discrete-time systems subject to randomly occurring gain variations (ROGVs), channel fadings and infinite-distributed delays. A new stochastic phenomenon (ROGVs), which is governed by a sequence of random variables with a certain probabilistic distribution, is put forward to better reflect the reality of the randomly occurring fluctuation of controller gains implemented in networked environments. A modified stochastic Rice fading model is then exploited to account for both channel fadings and random time-delays in a unified representation. The channel coefficients are a set of mutually independent random variables which abide by any (not necessarily Gaussian) probability density function on [0, 1]. Attention is focused on the analysis and design of a non-fragile H∞ outputfeedback controller such that the closed-loop control system is stochastically stable with a prescribed H∞ performance. Through intensive stochastic analysis, sufficient conditions are established for the desired stochastic stability and H∞ disturbance attenuation, and the addressed non-fragile control problem is then recast as a convex optimisation problem solvable via the semidefinite programme method. An example is finally provided to demonstrate the effectiveness of the proposed design method