Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Non-coding RNAs: the architects of eukaryotic complexity

Around 98% of all transcriptional output in humans is noncoding RNA. RNA-mediated gene regulation is widespread in higher eukaryotes and complex genetic phenomena like RNA interference, co-suppression, transgene silencing, imprinting, methylation, and possibly position-effect variegation and transvection, all involve intersecting pathways based on or connected to RNA signaling. I suggest that the central dogma is incomplete, and that intronic and other non-coding RNAs have evolved to comprise a second tier of gene expression in eukaryotes, which enables the integration and networking of complex suites of gene activity. Although proteins are the fundamental effectors of cellular function, the basis of eukaryotic complexity and phenotypic variation may lie primarily in a control architecture composed of a highly parallel system of trans-acting RNAs that relay state information required for the coordination and modulation of gene expression, via chromatin remodeling, RNA-DNA, RNA-RNA and RNA-protein interactions. This system has interesting and perhaps informative analogies with small world networks and dataflow computing.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Exact solution at integrable coupling of a model for the Josephson effect between small metallic grains

A model is introduced for two reduced BCS systems which are coupled through the transfer of Cooper pairs between the systems. The model may thus be used in the analysis of the Josephson effect arising from pair tunneling between two strongly coupled small metallic grains. At a particular coupling strength the model is integrable and explicit results are derived for the energy spectrum, conserved operators, integrals of motion, and wave function scalar products. It is also shown that form factors can be obtained for the calculation of correlation functions. Furthermore, a connection with perturbed conformal field theory is made.

Body size and latitudinal gradients in regional diversity of New World birds

Axe latitudinal gradients in regional diversity random or biased with respect to body size? Using data for the New World avifauna, I show that the slope of the increase in regional species richness from the Arctic to the equator is not independent of body size. The increase is steepest among small and medium-sized species, and shallowest among the largest species. This is reflected in latitudinal variation in the shape of frequency distributions of body sizes in regional subsets of the New World avifauna. Because species are added disproportionately in small and medium size classes towards low latitudes, distributions become less widely spread along the body size axis than expected from the number of species. These patterns suggest an interaction between the effects of latitude and body size on species richness, implying that mechanisms which vary with both latitude and body size may be important determinants of high tropical diversity in New World birds.

Read-only-memory-based quantum computation: Experimental explorations using nuclear magnetic resonance and future prospects

Read-only-memory-based (ROM-based) quantum computation (QC) is an alternative to oracle-based QC. It has the advantages of being less magical, and being more suited to implementing space-efficient computation (i.e., computation using the minimum number of writable qubits). Here we consider a number of small (one- and two-qubit) quantum algorithms illustrating different aspects of ROM-based QC. They are: (a) a one-qubit algorithm to solve the Deutsch problem; (b) a one-qubit binary multiplication algorithm; (c) a two-qubit controlled binary multiplication algorithm; and (d) a two-qubit ROM-based version of the Deutsch-Jozsa algorithm. For each algorithm we present experimental verification using nuclear magnetic resonance ensemble QC. The average fidelities for the implementation were in the ranges 0.9-0.97 for the one-qubit algorithms, and 0.84-0.94 for the two-qubit algorithms. We conclude with a discussion of future prospects for ROM-based quantum computation. We propose a four-qubit algorithm, using Grover's iterate, for solving a miniature real-world problem relating to the lengths of paths in a network.

Functionalized macrocyclic compounds: potential sensors of small molecules and ions

The potential applications of macrocycles in chemistry and at its interfaces with biology and physics continue to emerge, one of which is as receptors for small molecules and ions. This review illustrates these applications with examples from the last ten years employing complexation as the binding mechanism; some of the systems presented have already found real-world sensor applications. In any case, the challenges remain to design more selective and sensitive receptors for guests.

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

The International Consortium on Mental Health Policy and Services: objectives, design and project implementation

The concept of the burden of disease, introduced and estimated for a broad range of diseases in the World Bank report of 1993 illustrated that mental and neurological disorders not only entail a higher burden than cancer, but are responsible, in developed and developing countries, for more than 15% of the total burden of all diseases. As a consequence, over the past decade, mental disorders have ranked increasingly highly on the international agenda for health. However, the fact that mental health and nervous system disorders are now high on the international health agenda is by no means a guarantee that the fate of patients suffering from these disorders in developing countries will improve. In most developing countries the treatment gap for mental and neurological disorders is still unacceptably high. To address this problem, an international network of collaborating institutions in low-income countries has been set up. The establishment and the achievements of this network-the International Consortium on Mental Health Policy and Services-are reported. Sixteen institutions in developing countries collaborate (supported by a small number of scientific resource centres in industrialized nations) in projects on applied mental health systems research. Over a two-year period, the network produced the key elements of a national mental health policy; provided tools and methods for assessing a country's current mental health status (context, needs and demands, programmes, services and care and outcomes); established a global network of expertise, i.e., institutions and experts, for use by countries wishing to reform their mental health policy, services and care; and generated guidelines and examples for upgrading mental health policy with due regard to the existing mental health delivery system and demographic, cultural and economic factors.

Rheological Properties of Organoclay Suspensions in Epoxy Network Precursors

This paper deals with the evolution of the state of dispersion of organically modified montmorillonites in epoxy or amine precursors. The epoxy prepolymer is a diglycidyl ether of bisphenol A (DGEBA) and the curing agent is an aliphatic diamine with a polyoxypropylene backbone (Jeffamine D2000). The clay dispersion is evaluated at the platelet scale (nanoscopic scale) from X-ray spectrometry [wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS)] and at the aggregates scale (microscopic scale) from rheological analysis. The organoclays used form gels in the monomers above the percolation threshold if no shear is applied and present a mechanical gel/sol transition when shear stress increases. Gel strength and viscosity at high shear rates are linked to the nanometric state of dispersion and reveal the existence of two different organizations depending on organoclay/monomer interactions: (i) When the clay shows good interactions with the monomer, a significant swelling of the clay galleries by the monomer is obtained. These swollen particles lead to formation of weak gels which after shearing give high relative viscosity fluids. (ii) When the clay develops poor interactions with the monomer, the clay tends to reduce its exchange surface with the monomer and leads to a strongly connected gel. Shear breaks down this physical network leading to a very low relative viscosity fluid composed of nonswollen particles keeping a high aspect ratio. (C) 2003 Elsevier B.V All rights reserved.

Small regulatory RNAs in mammals

Mammalian cells harbor numerous small non-protein-coding RNAs, including small nucleolar RNAs (snoRNAs), microRNAs (miRNAs), short interfering RNAs (siRNAs) and small double-stranded RNAs, which regulate gene expression at many levels including chromatin architecture, RNA editing, RNA stability, translation, and quite possibly transcription and splicing. These RNAs are processed by multistep pathways from the introns and exons of longer primary transcripts, including protein-coding transcripts. Most show distinctive temporal- and tissue-specific expression patterns in different tissues, including embryonal stem cells and the brain, and some are imprinted. Small RNAs control a wide range of developmental and physiological pathways in animals, including hematopoietic differentiation, adipocyte differentiation and insulin secretion in mammals, and have been shown to be perturbed in cancer and other diseases. The extent of transcription of non-coding sequences and the abundance of small RNAs suggests the existence of an extensive regulatory network on the basis of RNA signaling which may underpin the development and much of the phenotypic variation in mammals and other complex organisms and which may have different genetic signatures from sequences encoding proteins.

Brain maps, great and small: lessons from comparative studies of primate visual cortical organization

In this paper, we review evidence from comparative studies of primate cortical organization, highlighting recent findings and hypotheses that may help us to understand the rules governing evolutionary changes of the cortical map and the process of formation of areas during development. We argue that clear unequivocal views of cortical areas and their homologies are more likely to emerge for 'core' fields, including the primary sensory areas, which are specified early in development by precise molecular identification steps. In primates, the middle temporal area is probably one of these primordial cortical fields. Areas that form at progressively later stages of development correspond to progressively more recent evolutionary events, their development being less firmly anchored in molecular specification. The certainty with which areal boundaries can be delimited, and likely homologies can be assigned, becomes increasingly blurred in parallel with this evolutionary/developmental sequence. For example, while current concepts for the definition of cortical areas have been vindicated in allowing a clarification of the organization of the New World monkey 'third tier' visual cortex (the third and dorsomedial areas, V3 and DM), our analyses suggest that more flexible mapping criteria may be needed to unravel the organization of higher-order visual association and polysensory areas.