Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.Comment: 69 pages, 16 figures, Submitted to Springer Applied Mathematical Sciences Serie

Real-Time Imaging of Rabbit Retina with Retinal Degeneration by Using Spectral-Domain Optical Coherence Tomography

Background: Recently, a transgenic rabbit with rhodopsin Pro 347 Leu mutation was generated as a model of retinitis pigmentosa (RP), which is characterized by a gradual loss of vision due to photoreceptor degeneration. The purpose of the current study is to noninvasively visualize and assess time-dependent changes in the retinal structures of a rabbit model of retinal degeneration by using speckle noise-reduced spectral-domain optical coherence tomography (SD-OCT). Methodology/Principal Findings: Wild type (WT) and RP rabbits (aged 4–20 weeks) were investigated using SD-OCT. The total retinal thickness in RP rabbits decreased with age. The thickness of the outer nuclear layer (ONL) and between the external limiting membrane and Bruch’s membrane (ELM–BM) were reduced in RP rabbits around the visual streak, compared to WT rabbits even at 4 weeks of age, and the differences increased with age. However, inner nuclear layer (INL) thickness in RP rabbits did not differ from that of WT during the observation period. The ganglion cell complex (GCC) thickness in RP rabbits increased near the optic nerve head but not around the visual streak in the later stages of the observation period. Hyper-reflective change was widely observed in the inner segments (IS) and outer segments (OS) of the photoreceptors in the OCT images of RP rabbits. Ultrastructural findings in RP retinas included the appearance of small rhodopsin-containing vesicles scattered in the extracellular space around the photoreceptors

The study of atmospheric ice-nucleating particles via microfluidically generated droplets

Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

Contributions of biogenic material to the atmospheric ice-nucleating particle population in North Western Europe

A minute fraction of atmospheric particles exert a disproportionate effect on the phase of mixed-phase clouds by acting as ice-nucleating particles (INPs). To understand the effects of these particles on weather and climate, both now and into the future, we must first develop a quantitative understanding of the major INP sources worldwide. Previous work has demonstrated that aerosols such as desert dusts are globally important INPs, but the role of biogenic INPs is unclear, with conflicting evidence for their importance. Here, we show that at a temperate site all INPs active above −18 °C at concentrations >0.1 L−1 are destroyed on heating, consistent with these INPs being of biological origin. Furthermore, we show that a global model of desert dust INPs dramatically underestimates the measured INP concentrations, but is consistent with the thermally-stable component. Notably, the heat sensitive INPs are active at temperatures where shallow cloud layers in Northern Europe are frequently observed to glaciate. Hence, we suggest that biogenic material is important for primary ice production in this region. The prevalence of heat sensitive, most likely biogenic, INPs in this region highlights that, as a community, we need to quantify the sources and transport of these particles as well as determine their atmospheric abundance across the globe and at cloud altitudes

Reassessment of pre-industrial fire emissions strongly affects anthropogenic aerosol forcing

Uncertainty in pre-industrial natural aerosol emissions is a major component of the overall uncertainty in the radiative forcing of climate. Improved characterisation of natural emissions and their radiative effects can therefore increase the accuracy of global climate model projections. Here we show that revised assumptions about pre-industrial fire activity result in significantly increased aerosol concentrations in the pre-industrial atmosphere. Revised global model simulations predict a 35% reduction in the calculated global mean cloud albedo forcing over the Industrial Era (1750–2000 CE) compared to estimates using emissions data from the Sixth Coupled Model Intercomparison Project. An estimated upper limit to pre-industrial fire emissions results in a much greater (91%) reduction in forcing. When compared to 26 other uncertain parameters or inputs in our model, pre-industrial fire emissions are by far the single largest source of uncertainty in pre-industrial aerosol concentrations, and hence in our understanding of the magnitude of the historical radiative forcing due to anthropogenic aerosol emissions

A review of the anthropogenic influence on biogenic secondary organic aerosol

Because of the climate and air quality effects of organic aerosol, it is important to quantify the influence of anthropogenic emissions on the aerosol burden, both globally and regionally, and both in terms of mass and number. Methods exist with which the fractions of organic aerosol resulting directly from anthropogenic and biogenic processes can be estimated. However, anthropogenic emissions can also lead to an enhancement in secondary organic aerosol formation from naturally emitted precursors. We term this enhanced biogenic secondary organic aerosol (eBSOA). Here, we review the mechanisms through which such an effect may occur in the atmosphere and describe a work flow via which it may be quantified, using existing measurement techniques. An examination of published data reveals support for the existence of the enhancement effect. © 2011 Author(s)

A review of the anthropogenic influence on biogenic secondary organic aerosol

Because of the climate and air quality effects of organic aerosol, it is important to quantify the influence of anthropogenic emissions on the aerosol burden, both globally and regionally, and both in terms of mass and number. Methods exist with which the fractions of organic aerosol resulting directly from anthropogenic and biogenic processes can be estimated. However, anthropogenic emissions can also lead to an enhancement in secondary organic aerosol formation from naturally emitted precursors. We term this enhanced biogenic secondary organic aerosol (eBSOA). Here, we review the mechanisms through which such an effect may occur in the atmosphere and describe a work flow via which it may be quantified, using existing measurement techniques. An examination of published data reveals support for the existence of the enhancement effect. © 2011 Author(s)