Implementation of a new atomic basis for the He i equilibrium line ratio technique for electron temperature and density diagnostic in the SOL for H-mode plasmas in DIII-D

Evaluating the ratio of selected helium lines allows for measurement of electron densities and temperatures. This technique is applied for L-mode plasmas at TEXTOR (O. Schmitz et al., Plasma Phys. Control. Fusion 50 (2008) 115004). We report our first efforts to extend it to H-mode plasma diagnostics in DIII-D. This technique depends on the accuracy of the atomic data used in the collisional radiative model (CRM). We present predictions for the electron temperatures and densities by using recently calculated R-Matrix With Pseudostates (RMPS) and Convergent Close-Coupling (CCC) electron-impact excitation and ionization data. We include contributions from higher Rydberg states by means of the projection matrix. These effects become significant for high electron density conditions, which are typical in H-mode. We apply a non-equilibrium model for the time propagation of the ionization balance to predict line emission profiles from experimental H-mode data from DIII-D. © 2010 Elsevier B.V. All rights reserved.

In my ‘Mind’s Eye’: introspectionism, detectivism, and the basis of authoritative self-knowledge

It is widely accepted that knowledge of certain of one’s own mental states is authoritative in being epistemically more secure than knowledge of the mental states of others, and theories of self-knowledge have largely appealed to one or the other of two sources to explain this special epistemic status. The first, ‘detectivist’, position, appeals to an inner perception-like basis, whereas the second, ‘constitutivist’, one, appeals to the view that the special security awarded to certain self-knowledge is a conceptual matter. I argue that there is a fundamental class of cases of authoritative self-knowledge, ones in which subjects are consciously thinking about their current, conscious intentional states, that is best accounted for in terms of a theory that is,
broadly speaking, introspectionist and detectivist. The position developed has an intuitive plausibility that has inspired many who work in the Cartesian tradition, and the potential to yield a single treatment of the basis of authoritative self-knowledge for both intentional states and sensation states.

In My 'Mind's Eye': Introspectionism, Detectivism, and the Basis of Authoritative Self-Knowledge

It is widely accepted that knowledge of certain of one’s own mental states is authoritative in being epistemically more secure than knowledge of the mental states of others, and theories of self-knowledge have largely appealed to one or the other of two sources to explain this special epistemic status. The first, ‘detectivist’, position, appeals to an inner perception-like basis, whereas the second, ‘constitutivist’, one, appeals to the view that the special security awarded to certain self-knowledge is a conceptual matter. I argue that there is a fundamental class of cases of authoritative self-knowledge, ones in which subjects are consciously thinking about their current, conscious intentional states, that is best accounted for in terms of a theory that is, broadly speaking, introspectionist and detectivist. The position developed has an intuitive plausibility that has inspired many who work in the Cartesian tradition, and the potential to yield a single treatment of the basis of authoritative self-knowledge for both intentional states and sensation states.

The genetic basis of psychological traits in infancy: Implications for understanding the causes of developmental psychopathology

This chapter reviews genetic studies that have aimed to identify genes influencing psychological traits in infancy (from birth to age 12 months), and considers how this research informs us about the causes of developmental psychopathology. Specifically, this chapter systematically reviews findings from studies that associated common genetic variants with individual variation in infants’ attention, temperament and behaviour, and attachment disorganisation. DRD4 and 5-HTTLPR genes were the most frequently studied candidate genes. Possibly the most coherent set of results relates to the L-DRD4 genotype, which is significantly associated with infant attention, temperament, and attachment style. Research in infant genetics has been strengthened by a careful focus on uniform age ranges within studies, by several longitudinal studies, and by exploration of gene-environment interactions between genes and maternal characteristics. However there is also considerable inconsistency in results in this field and possible reasons for this are discussed. The chapter outlines the main genetic methods that have been used and what new genetic approaches such as polygenic risk scoring could offer infant genetics. Recent findings suggest that some traits during infancy predict individual differences in developmental psychopathology in childhood. It is argued that infant genetic research has considerable potential for the identification of populations at risk for psychopathology in later life, and this remains an area open for future research.

Thin-zone TAP reactor as a basis of �state-by-state transient screening

Thin-zone TAP reactor is presented as a basis of the new state-by-state transient screening approach which has been proposed by the authors for non-steady-state kinetic characterization of industrial catalysts. The general thin-zone TAP reactor model is described, and its mathematical status is justified analytically. It is shown that this model provides high enough accuracy to be applicable in the wide conversion interval (up to 90%), which is an important advantage of this approach compared with the traditional differential reactor.

A new Jacobian matrix for optimal learning of single-layer neural networks

This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.

Molecular basis of Yersinia enterocolitica temperature-dependent resistance to antimicrobial peptides

Antimicrobial peptides (APs) belong to the arsenal of weapons of the innate immune system against infections. In the case of gram-negative bacteria, APs interact with the anionic lipid A moiety of the lipopolysaccharide (LPS). In yersiniae most virulence factors are temperature regulated. Studies from our laboratory demonstrated that Yersinia enterocolitica is more susceptible to polymyxin B, a model AP, when grown at 37°C than at 22°C (J. A. Bengoechea, R. Díaz, and I. Moriyón, Infect. Immun. 64:4891-4899, 1996), and here we have extended this observation to other APs, not structurally related to polymyxin B. Mechanistically, we demonstrate that the lipid A modifications with aminoarabinose and palmitate are downregulated at 37°C and that they contribute to AP resistance together with the LPS O-polysaccharide. Bacterial loads of lipid A mutants in Peyer's patches, liver, and spleen of orogastrically infected mice were lower than those of the wild-type strain at 3 and 7 days postinfection. PhoPQ and PmrAB two-component systems govern the expression of the loci required to modify lipid A with aminoarabinose and palmitate, and their expressions are also temperature regulated. Our findings support the notion that the temperature-dependent regulation of loci controlling lipid A modifications could be explained by H-NS-dependent negative regulation alleviated by RovA. In turn, our data also demonstrate that PhoPQ and PmrAB regulate positively the expression of rovA, the effect of PhoPQ being more important. However, rovA expression reached wild-type levels in the phoPQ pmrAB mutant background, hence indicating the existence of an unknown regulatory network controlling rovA expression in this background.

Genetic basis of Congenital Erythrocytosis:mutation update and online databases

Congenital Erythrocytosis (CE), or congenital polycythemia, represents a rare and heterogeneous clinical entity. It is caused by deregulated red blood cell production where erythrocyte overproduction results in elevated hemoglobin and hematocrit levels. Primary congenital familial erythrocytosis is associated with low erythropoietin (Epo) levels and results from mutations in the Epo receptor gene (EPOR). Secondary congenital erythrocytosis arises from conditions causing tissue hypoxia and results in increased Epo production. These include hemoglobin variants with increased affinity for oxygen (HBB, HBA mutations), decreased production of 2,3-bisphosphoglycerate due to BPGM mutations, or mutations in the genes involved in the hypoxia sensing pathway (VHL, EPAS1 and EGLN1). Depending on the affected gene, CE can be inherited either in an autosomal dominant or recessive mode, with sporadic cases arising de novo. Despite recent important discoveries in the molecular pathogenesis of CE, the molecular causes remain to be identified in about 70% of the patients. With the objective of collecting all the published and unpublished cases of CE the COST action MPN&MPNr-Euronet developed a comprehensive internet-based database focusing on the registration of clinical history, hematological, biochemical and molecular data (http://www.erythrocytosis.org/). In addition, unreported mutations are also curated in the corresponding Leiden Open Variation Database (LOVD). This article is protected by copyright. All rights reserved.

Molecular basis of non-mutational derepression of ramA in Klebsiella pneumoniae

Objectives: The ram locus, consisting of the romA–ramA genes, is repressed by the tetracycline-type regulator RamR, where regulation is abolished due to loss-of-function mutations within the protein or ligand interactions. The aim of this study was to determine whether the phenothiazines (chlorpromazine and thioridazine) directly interact with RamR to derepress ramA expression.

Methods: Quantitative real-time PCR analyses were performed to determine expression levels of the romA–ramA genes after exposure to the phenothiazines. Electrophoretic mobility shift assays (EMSAs) and in vitro transcription experiments were performed to show direct binding to and repression by RamR. Direct binding of the RamR protein to the phenothiazines was measured by fluorescence spectroscopy experiments and molecular docking models were generated using the RamR crystal structure.

Results: Exposure to either chlorpromazine or thioridazine resulted in the up-regulation of the romA–ramA genes. EMSAs and in vitro transcription experiments demonstrated that both agents reduce/abolish binding and enhance transcription of the target PI promoter upstream of the ramR–romA genes in Klebsiella pneumoniae compared with RamR alone. Fluorescence spectroscopy measurements demonstrated that RamR directly binds both chlorpromazine and thioridazine with micromolar affinity. Molecular docking analyses using the RamR crystal structure demonstrated that the phenothiazines interact with RamR protein through contacts described for other ligands, in addition to forming unique strong polar interactions at positions D152 and K63.

Conclusions: These data demonstrate that phenothiazines can modulate loci linked to the microbe–drug response where RamR is an intracellular target for the phenothiazines, thus resulting in a transient non-mutational derepression of ramA concentrations.

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

The Teaching Space Allocation Problem with splitting

A standard problem within universities is that of teaching space allocation which can be thought of as the assignment of rooms and times to various teaching activities. The focus is usually on courses that are expected to fit into one room. However, it can also happen that the course will need to be broken up, or ‘split’, into multiple sections. A lecture might be too large to fit into any one room. Another common example is that of seminars or tutorials. Although hundreds of students may be enrolled on a course, it is often subdivided into particular types and sizes of events dependent on the pedagogic requirements of that particular course. Typically, decisions as to how to split courses need to be made within the context of limited space requirements. Institutions do not have an unlimited number of teaching rooms, and need to effectively use those that they do have. The efficiency of space usage is usually measured by the overall ‘utilisation’ which is basically the fraction of the available seat-hours that are actually used. A multi-objective optimisation problem naturally arises; with a trade-off between satisfying preferences on splitting, a desire to increase utilisation, and also to satisfy other constraints such as those based on event location and timetabling conflicts. In this paper, we explore such trade-offs. The explorations themselves are based on a local search method that attempts to optimise the space utilisation by means of a ‘dynamic splitting’ strategy. The local moves are designed to improve utilisation and satisfy the other constraints, but are also allowed to split, and un-split, courses so as to simultaneously meet the splitting objectives.