Identification of candidate genes at the corticoseptal boundary during development

Cortical midline glia are critical to the formation of the corpus callosum during development. The glial wedge is a Population of midline glia that is located at the corticoseptal boundary and expresses repulsive/growth-inhibitory molecules that guide callosal axons as they cross the midline. The glial wedge are the first cells within the cortex to express GFAP and thus may express molecules specific for glial maturation. The corticoseptal boundary is a genetically defined boundary between the cingulate cortex (dorsal telencephalon) and the septum (ventral telencephalon). The correct dorso-ventral position of this boundary is vital to the formation of both the glial wedge and the corpus callosum. Our aim was to identify genes expressed specifically within the glial wedge that might be involved in either glial differentiation, formation of the corticoseptal boundary or development of the corpus callosum. To identify such genes we have performed a differential display PCR screen comparing RNA isolated from the glial wedge with RNA isolated from control tissues such as the neocortex and septum, of embryonic day 17 mouse brains. Using 200 different combinations of primers, we identified and cloned 67 distinct gene fragments. In situ hybridization analysis confirmed the differential expression of many of the genes, and showed that clones G24F3, G39F8 and transcription factor LZIP have specific expression patterns in the telencephalon of embryonic and postnatal brains. An RNase Protection Assay (RPA) revealed that the expression of G39F8, G24173 and LZIP increase markedly in the telencephalon at E16 and continue to be expressed until at least PO, during the period when the corpus callosum is forming. (c) 2005 Elsevier B.V. All rights reserved.

Use of CLIMEX modelling to identify prospective areas for exploration to find new biological control agents for prickly acacia

Selection of biocontrol agents that are adapted to the climates in areas of intended release demands a thorough analysis of the climates of the source and release sites. We present a case study that demonstrates how use of the CLIMEX software can improve decision making in relation to the identification of prospective areas for exploration for agents to control the woody weed, prickly acacia Acacia nilotica ssp. indica in the arid areas of north Queensland.

Identification of the semaphorin receptor PLXNA2 as a candidate for susceptibility to schizophrenia

The discovery of genetic factors that contribute to schizophrenia susceptibility is a key challenge in understanding the etiology of this disease. Here, we report the identification of a novel schizophrenia candidate gene on chromosome 1q32, plexin A2 (PLXNA2), in a genome-wide association study using 320 patients with schizophrenia of European descent and 325 matched controls. Over 25 000 single-nucleotide polymorphisms (SNPs) located within approximately 14 000 genes were tested. Out of 62 markers found to be associated with disease status, the most consistent finding was observed for a candidate locus on chromosome 1q32. The marker SNP rs752016 showed suggestive association with schizophrenia (odds ratio (OR) = 1.49, P = 0.006). This result was confirmed in an independent case control sample of European Americans (combined OR = 1.38, P = 0.035) and similar genetic effects were observed in smaller subsets of Latin Americans (OR = 1.26) and Asian Americans (OR = 1.37). Supporting evidence was also obtained from two family-based collections, one of which reached statistical significance (OR = 2.2, P = 0.02). High-density SNP mapping showed that the region of association spans approximately 60 kb of the PLXNA2 gene. Eight out of 14 SNPs genotyped showed statistically significant differences between cases and controls. These results are in accordance with previous genetic findings that identified chromosome 1q32 as a candidate region for schizophrenia. PLXNA2 is a member of the transmembrane semaphorin receptor family that is involved in axonal guidance during development and may modulate neuronal plasticity and regeneration. The PLXNA2 ligand semaphorin 3A has been shown to be upregulated in the cerebellum of individuals with schizophrenia. These observations, together with the genetic results, make PLXNA2 a likely candidate for the 1q32 schizophrenia susceptibility locus.

Identification of residues controlling transport through the yeast aquaglyceroporin Fps1 using a genetic screen

Aquaporins and aquaglyceroporins mediate the transport of water and solutes across biological membranes. Saccharomyces cerevisiae Fps1 is an aquaglyceroporin that mediates controlled glycerol export during osmoregulation. The transport function of Fps1 is rapidly regulated by osmotic changes in an apparently unique way and distinct regions within the long N- and C-terminal extensions are needed for this regulation. In order to learn more about the mechanisms that control Fps1 we have set up a genetic screen for hyperactive Fps1 and isolated mutations in 14 distinct residues, all facing the inside of the cell. Five of the residues lie within the previously characterized N-terminal regulatory domain and two mutations are located within the approach to the first transmembrane domain. Three mutations cause truncation of the C-terminus, confirming previous studies on the importance of this region for channel control. Furthermore, the novel mutations identify two conserved residues in the channel-forming B-loop as critical for channel control. Structural modelling-based rationalization of the observed mutations supports the notion that the N-terminal regulatory domain and the B-loop could interact in channel control. Our findings provide a framework for further genetic and structural analysis to better understand the mechanism that controls Fps1 function by osmotic changes.

A structural method for the design of fault tolerant distributed control systems

Distributed digital control systems provide alternatives to conventional, centralised digital control systems. Typically, a modern distributed control system will comprise a multi-processor or network of processors, a communications network, an associated set of sensors and actuators, and the systems and applications software. This thesis addresses the problem of how to design robust decentralised control systems, such as those used to control event-driven, real-time processes in time-critical environments. Emphasis is placed on studying the dynamical behaviour of a system and identifying ways of partitioning the system so that it may be controlled in a distributed manner. A structural partitioning technique is adopted which makes use of natural physical sub-processes in the system, which are then mapped into the software processes to control the system. However, communications are required between the processes because of the disjoint nature of the distributed (i.e. partitioned) state of the physical system. The structural partitioning technique, and recent developments in the theory of potential controllability and observability of a system, are the basis for the design of controllers. In particular, the method is used to derive a decentralised estimate of the state vector for a continuous-time system. The work is also extended to derive a distributed estimate for a discrete-time system. Emphasis is also given to the role of communications in the distributed control of processes and to the partitioning technique necessary to design distributed and decentralised systems with resilient structures. A method is presented for the systematic identification of necessary communications for distributed control. It is also shwon that the structural partitions can be used directly in the design of software fault tolerant concurrent controllers. In particular, the structural partition can be used to identify the boundary of the conversation which can be used to protect a specific part of the system. In addition, for certain classes of system, the partitions can be used to identify processes which may be dynamically reconfigured in the event of a fault. These methods should be of use in the design of robust distributed systems.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

Attachment anxiety and friendship group identification under attachment threat:the moderating role of priming support network expectations

We examined the role of priming participants' own network expectations on their subsequent identification with their friendship group. We examined this prime alongside attachment anxiety and attachment threat, as predictors of friendship group identification. Previous research has suggested that attachment anxiety is associated with negative network expectations. In this study, we extended this work to show that when a network expectation prime was absent, higher attachment anxiety was associated with lower group identification under attachment threat, compared to a control condition. However, when expectations of support network were primed, attachment threat no longer affected group identification, so that only attachment anxiety predicted group identification. This suggests that priming participants who are high in attachment anxiety with their own network expectancies (which are negative), results in participants dis-identifying with their friendship group, regardless of whether or not they have experienced attachment threat. © 2012 Elsevier Ltd.

Parametric Identification and Diagnosis of Integrated Navigation Systems in Bench Test Process

Growth of complexity and functional importance of integrated navigation systems (INS) leads to high losses at the equipment refusals. The paper is devoted to the INS diagnosis system development, allowing identifying the cause of malfunction. The proposed solutions permit taking into account any changes in sensors dynamic and accuracy characteristics by means of the appropriate error models coefficients. Under actual conditions of INS operation, the determination of current values of the sensor models and estimation filter parameters rely on identification procedures. The results of full-scale experiments are given, which corroborate the expediency of INS error models parametric identification in bench test process.

‘Death talk’, ‘loss talk’ and identification in the process of ageing

In this paper, we examine the injunction issued by the prominent politician, broadcaster and older people's advocate, Baroness Joan Bakewell, to engage in ‘death talk’. We see positive ethical potential in this injunction, insofar as it serves as a call to confront more directly the prospects of death and dying, thereby releasing creative energies with which to change our outlook on life and ageing more generally. However, when set against a culture that valorises choice, independence and control, the positive ethical potential of such injunctions is invariably thwarted. We illustrate this with reference to one of Bakewell's interventions in a debate on scientific innovation and population ageing. In examining the context of her intervention, we affirm her intuition about its positive ethical potential, but we also point to an ambivalence that accompanies the formulation of the injunction – one that ultimately blunts the force and significance of her intuition. We suggest that Gilleard and Higgs' idea of the third age/fourth age dialectic, combined with the psycho-analytic concepts of fantasy and mourning, allow us to express this intuition better. In particular, we argue that the expression ‘loss talk’ (rather than ‘death talk’) better captures the ethical negotiations that should ultimately underpin the transformation processes associated with ageing, and that our theoretical contextualisation of her remarks can help us see this more clearly. In this view, deteriorations in our physical and mental capacities are best understood as involving changes in how we see ourselves, i.e. in our identifications, and so what is at stake are losses of identity and the conditions under which we can engage in new processes of identification.

Methods of Color Images Procession for Further Identification of the Object

The offered paper deals with the problems of color images preliminary procession. Among these are: interference control (local ones and noise) and extraction of the object from the background on the stage preceding the process of contours extraction. It was considered for a long time that execution of smoothing in segmentation through the boundary extraction is inadmissible, but the described methods and the obtained results evidence about expedience of using the noise control methods.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

Generalised Riccati solution and pinning control of complex stochastic networks

This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.