Mapping Gray's model of personality onto the Eysenck Personality Profiler (EPP)

The aim of this study was to determine how well Gray's model of personality [Gray, J.A. (1982). The neuropsychology of anxiety: an enquiry into the functions of the septo-hippocampal system. Oxfords: Oxford University Press, Gray, J.A. (1987). The psychology of fear and stress. Cambridge: Cambridge University Press], as measured by the Gray Wilson Personality Questionnaire (GWPQ), can provide a full description of personality as measured by the primary scales of the Eysenck Personality Profiler (EPP) and the type scales of the short version or the EPQ-R. Factor analysis of the GWPQ the Anxiety and linpulsivity scales of the EPP and the Learning Styles Questionnaire (LSQ) showed that the GWPQ seemed to measure general activation and inhibition factors, but not the finer features of Gray's theory. When the GWPQ scales were regressed against each scale of the EPP., it was round that they generally provide only a reasonable explanation of the EPP primary scales. It is concluded that the GWPQ measures general propel-ties of Gray's model, that the linpulsivity and Anxiety scales of the EPP also scent related to the GWPQ scales, and that Gray's model of personality provides only a partial explanation of personality in general. (C) 2002 Published by Elsevier Science Ltd. All rights reserved.

The Relative Frequency of the Synthetic End Composite Futures in the Newspaper Quest-France and some Observations on Distribution

Figures on the relative frequency of synthetic and composite future forms in Ouest-France are presented and compared with those of earlier studies on the passé simple and passé composé. The synthetic future is found to be dominant. Possible formal explanations for distribution are found to be inconclusive. Distribution across different text-types is found to be more promising, since contrastive functions of the two forms can be identified in texts where they co-occur. The composite future typically reports new proposals or plans as current news, while the synthetic future outlines details that will be realised at the time of implementation. Both functions are important in dailies, but current news is more often expressed in the present tense at the expense of the composite future.

Identification of T cell epitopes on the 33-kDa fragment of Plasmodium yoelii merozoite surface protein 1 and their antibody-independent protective role in immunity to blood stage malarial

Merozoite surface protein 1 (MSP1) of malaria parasites undergoes proteolytic processing at least twice before invasion into a new RBC. The 42-kDa fragment, a product of primary processing, is cleaved by proteolytic enzymes giving rise to MSP1(33), which is shed from the merozoite surface, and MSP1(19), which is the only fragment carried into a new RBC. In this study, we have identified T cell epitopes on MSP1(33) of Plasmodium yoelii and have examined their function in immunity to blood stage malaria. Peptides 20 aa in length, spanning the length of MSP1(33) and overlapping each other by 10 aa, were analyzed for their ability to induce T cell proliferation in immunized BALB/c and C57BL/6 mice. Multiple epitopes were recognized by these two strains of mice. Effector functions of the dominant epitopes were then investigated. Peptides Cm15 and Cm21 were of particular interest as they were able to induce effector T cells capable of delaying growth of lethal P. yoelii YM following adoptive transfer into immuno-deficient mice without inducing detectable Ab responses. Homologs of these epitopes could be candidates for inclusion in a subunit vaccine.

On the robustness of short-term interest rate models

This paper investigates the robustness of a range of short–term interest rate models. We examine the robustness of these models over different data sets, time periods, sampling frequencies, and estimation techniques. We examine a range of popular one–factor models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate. We find that parameter estimates are highly sensitive to all of these factors in the eight countries that we examine. Since parameter estimates are not robust, these models should be used with caution in practice.

Identifying the communication activities of older people with aphasia: Evidence from naturalistic observation

Background: Increasingly there is a call from clinicians and researchers for measures that document the impact of aphasia on a person's everyday communication. Do existing assessments of communication disability adequately sample communication activities relevant to our clients? Communication skills and networks change with age. A need exists to determine the everyday communication activities of older people and in particular those with aphasia. Aims: The primary aim of this study was to describe and compare the everyday communication activities of older people with aphasia and healthy older people who are living in the community. A secondary aim was to investigate the content validity of the American Speech-Language Hearing Association Functional Assessment of Communication Skills for Adults (ASHA FACS, 1997) for older Australians. Methods & Procedures: Naturalistic observation was the method of choice for detailing the everyday communication of 15 older people with chronic aphasia following stroke and a matched group of 15 healthy older people who were living in the community. Researchers, in the role of participant observer, took field notes for 8 hours, over three occasions within a week. A total of 240 hours of observation have been coded in terms of communication activity, topic, communication partners, and place of communication. A brief 5-day diary served to check the representativeness of the observational data. After each hour of observation, the researcher checked which ASHA FACS items had been observed. Outcomes & Results: Naturalistic observation provided a rich, rigorous, and systematic methodology for detailing the dynamics and complexities of authentic communication. The most common communication activities for both groups were conversations at home and in social groups. Real-life communication was revealed to serve the dual purposes of transaction and interaction. Results indicate that older people with aphasia engage in similar communication activities to healthy older people although differences were evident in the frequency of communication and in specific activities such as story telling, writing, commenting, and acknowledging. ASHA FACS items were generally relevant to older Australians living in the community. Conclusions: This study demonstrated that communication activity is multifaceted in terms of the type of communication and contextual factors. The observational data describe the effects of aphasia on a person's everyday communication activity and reveal the impact of aphasia on the social functions of communication including sharing information, maintaining and establishing relationships, and telling one's story. Functional communication assessment requires a greater focus on the interactional and uniquely interpersonal aspects of social communication.

Ataxia-telangiectasia-mutated (ATM) and NBS1-dependent phosphorylation of Chk1 on Ser-317 in response to ionizing radiation

In mammals, the ATM (ataxia-telangiectasia-mutated) and ATR (ATM and Rad3-related) protein kinases function as critical regulators of the cellular DNA damage response. The checkpoint functions of ATR and ATM are mediated, in part, by a pair of checkpoint effector kinases termed Chk1 and Chk2. In mammalian cells, evidence has been presented that Chk1 is devoted to the ATR signaling pathway and is modified by ATR in response to replication inhibition and UV-induced damage, whereas Chk2 functions primarily through ATM in response to ionizing radiation (IR), suggesting that Chk2 and Chk1 might have evolved to channel the DNA damage signal from ATM and ATR, respectively. We demonstrate here that the ATR-Chk1 and ATM-Chk2 pathways are not parallel branches of the DNA damage response pathway but instead show a high degree of cross-talk and connectivity. ATM does in fact signal to Chk1 in response to IR. Phosphorylation of Chk1 on Ser-317 in response to IR is ATM-dependent. We also show that functional NBS1 is required for phosphorylation of Chk1, indicating that NES1 might facilitate the access of Chk1 to ATM at the sites of DNA damage. Abrogation of Chk1 expression by RNA interference resulted in defects in IR-induced S and G2/M phase checkpoints; however, the overexpression of phosphorylation site mutant (S317A, S345A or S317A/S345A double mutant) Chk1 failed to interfere with these checkpoints. Surprisingly, the kinase-dead Chk1 (D130A) also failed to abrogate the S and G2 checkpoint through any obvious dominant negative effect toward endogenous Chk1. Therefore, further studies will be required to assess the contribution made by phosphorylation events to Chk1 regulation. Overall, the data presented in the study challenge the model in which Chk1 only functions downstream from ATR and indicate that ATM does signal to Chk1. In addition, this study also demonstrates that Chk1 is essential for IR-induced inhibition of DNA synthesis and the G2/M checkpoint.

Effect of the number of shells on the pressure and energy of two-dimensional free bubble clusters

We have performed Surface Evolver simulations of two-dimensional hexagonal bubble clusters consisting of a central bubble of area lambda surrounded by s shells or layers of bubbles of unit area. Clusters of up to twenty layers have been simulated, with lambda varying between 0.01 and 100. In monodisperse clusters (i.e., for lambda = 1) [M.A. Fortes, F Morgan, M. Fatima Vaz, Philos. Mag. Lett. 87 (2007) 561] both the average pressure of the entire Cluster and the pressure in the central bubble are decreasing functions of s and approach 0.9306 for very large s, which is the pressure in a bubble of an infinite monodisperse honeycomb foam. Here we address the effect of changing the central bubble area lambda. For small lambda the pressure in the central bubble and the average pressure were both found to decrease with s, as in monodisperse clusters. However, for large,, the pressure in the central bubble and the average pressure increase with s. The average pressure of large clusters was found to be independent of lambda and to approach 0.9306 asymptotically. We have also determined the cluster surface energies given by the equation of equilibrium for the total energy in terms of the area and the pressure in each bubble. When the pressures in the bubbles are not available, an approximate equation derived by Vaz et al. [M. Fatima Vaz, M.A. Fortes, F. Graner, Philos. Mag. Lett. 82 (2002) 575] was shown to provide good estimations for the cluster energy provided the bubble area distribution is narrow. This approach does not take cluster topology into account. Using this approximate equation, we find a good correlation between Surface Evolver Simulations and the estimated Values of energies and pressures. (C) 2008 Elsevier B.V. All rights reserved.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Geometric picture of generalized-CP and Higgs-family transformations in the two-Higgs-doublet model

In the two-Higgs-doublet model (THDM), generalized-CP transformations (phi(i) -> X-ij phi(*)(j) where X is unitary) and unitary Higgs-family transformations (phi(i) -> U-ij phi(j)) have recently been examined in a series of papers. In terms of gauge-invariant bilinear functions of the Higgs fields phi(i), the Higgs-family transformations and the generalized-CP transformations possess a simple geometric description. Namely, these transformations correspond in the space of scalar-field bilinears to proper and improper rotations, respectively. In this formalism, recent results relating generalized CP transformations with Higgs-family transformations have a clear geometric interpretation. We will review what is known regarding THDM symmetries, as well as derive new results concerning those symmetries, namely how they can be interpreted geometrically as applications of several CP transformations.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Role on serine protease inhibitors in the pathogenisis of Steinernema carpocapsae

Tese de Doutoramento, Biologia (Biologia Celular e Molecular), 18 de Novembro de 2013, Universidade dos Açores.

Mapping non-suicidal self-injury in adolescence: Development and confirmatory factor analysis of the impulse, self-harm and sucidal ideation questionnaire for adolescents (ISSIQ-A)

Non-suicidal self-injury (NSSI) is the deliberate, self-inflicted destruction of body tissue without suicidal intent and an important clinical phenomenon. Rates of NSSI appear to be disproportionately high in adolescents and young adults, and is a risk factor for suicidal ideation and behavior. The present study reports the psychometric properties of the Impulse, Self-harm and Suicide Ideation Questionnaire for Adolescents (ISSIQ-A), a measure designed to comprehensively assess the impulsivity, NSSI behaviors and suicide ideation. An additional module of this questionnaire assesses the functions of NSSI. Results of Confirmatory Factor Analysis (CFA) of the scale on 1722 youths showed items' suitability and confirmed a model of four different dimensions (Impulse, Self-harm, Risk-behavior and Suicide ideation) with good fit and validity. Further analysis showed that youth׳s engagement in self-harm may exert two different functions: to create or alleviate emotional states, and to influence social relationships. Our findings contribute to research and assessment on non-suicidal self-injury, suggesting that the ISSIQ-A is a valid and reliable measure to assess impulse, self-harm and suicidal thoughts, in adolescence.

Records of predatory, con-specific and human induced mauls on fish from the Northeast Atlantic and Black Sea

Present study aims to describe records of mauled and con-specific injures in various fish inhabiting different environment and to discuss possible impacts on fish behavior and ontogenesis. The fish specimens were collected from the Black Sea and Azores Islands (NE Atlantic). Individuals of European flounder, Pleuronectes flesus, common stingray, Dasyatis pastinaca and turbot, Scophthalmus maximus with missing dorsal and caudal fins and flesh, were found in the Black Sea. Specimens with severe mauls of the ocean sunfish, Mola mola, almaco jack, Seriola rivoliana and sargo, Diplodus sargus were recorded from the Azores Islands. All of them were caught alive and survived severe mauls caused by predators or by accidents with propellers, fishing nets. The NE Atlantic records, although possibly caused by natural predation, are more probably than not the result of negative interactions with human activity. Numerous records of mauled fish species from both regions show that the problem with adverse effects of fisheries is quite important. Predatory and con-specific injuries obviously are compatible with basic fish vital functions of described cases. The problem with negative anthropogenic interactions seems to be insufficiently investigated and need more attention by responsible managers and decision makers.

Regulation of histone H2A.Z expression is mediated by sirtuin 1 in prostate cancer

Histone variants seem to play a major role in gene expression regulation. In prostate cancer, H2A.Z and its acetylated form are implicated in oncogenes’ upregulation. SIRT1, which may act either as tumor suppressor or oncogene, reduces H2A.Z levels in cardiomyocytes, via proteasome-mediated degradation, and this mechanism might be impaired in prostate cancer cells due to sirtuin 1 downregulation. Thus, we aimed to characterize the mechanisms underlying H2A.Z and SIRT1 deregulation in prostate carcinogenesis and how they interact. We found that H2AFZ and SIRT1 were up- and downregulated, respectively, at transcript level in primary prostate cancer and high-grade prostatic intraepithelial neoplasia compared to normal prostatic tissues. Induced SIRT1 overexpression in prostate cancer cell lines resulted in almost complete absence of H2A.Z. Inhibition of mTOR had a modest effect on H2A.Z levels, but proteasome inhibition prevented the marked reduction of H2A.Z due to sirtuin 1 overexpression. Prostate cancer cells exposed to epigenetic modifying drugs trichostatin A, alone or combined with 5-aza-2’-deoxycytidine, increased H2AFZ transcript, although with a concomitant decrease in protein levels. Conversely, SIRT1 transcript and protein levels increased after exposure. ChIP revealed an increase of activation marks within the TSS region for both genes. Remarkably, inhibition of sirtuin 1 with nicotinamide, increased H2A.Z levels, whereas activation of sirtuin 1 by resveratrol led to an abrupt decrease in H2A.Z. Finally, protein-ligation assay showed that exposure to epigenetic modifying drugs fostered the interaction between sirtuin 1 and H2A.Z. We concluded that sirtuin 1 and H2A.Z deregulation in prostate cancer are reciprocally related. Epigenetic mechanisms, mostly histone post-translational modifications, are likely involved and impair sirtuin 1-mediated downregulation of H2A.Z via proteasome-mediated degradation. Epigenetic modifying drugs in conjunction with enzymatic modulators are able to restore the normal functions of sirtuin 1 and might constitute relevant tools for targeted therapy of prostate cancer patients

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.