A prolegomenon to the construct of the native speaker: heritage speaker bilinguals are natives too!

This Forum challenges the generally accepted position in the linguistic sciences—conscious or not—that monolingualism and nativeness are essentially synonymous in an exclusive way. We discuss two consequences of our position that naturalistic bilinguals and multilinguals exposed to a language in early childhood are also native speakers: (i) that bi-/multilinguals have multiple native languages;and (ii) nativeness can be applicable to a state of linguistic knowledge that is characterized by significant differences to the monolingual baseline.

Is it me? Self-recognition bias across sensory modalities and its relationship to autistic traits

Background Atypical self-processing is an emerging theme in autism research, suggested by lower self-reference effect in memory, and atypical neural responses to visual self-representations. Most research on physical self-processing in autism uses visual stimuli. However, the self is a multimodal construct, and therefore, it is essential to test self-recognition in other sensory modalities as well. Self-recognition in the auditory modality remains relatively unexplored and has not been tested in relation to autism and related traits. This study investigates self-recognition in auditory and visual domain in the general population and tests if it is associated with autistic traits. Methods Thirty-nine neurotypical adults participated in a two-part study. In the first session, individual participant’s voice was recorded and face was photographed and morphed respectively with voices and faces from unfamiliar identities. In the second session, participants performed a ‘self-identification’ task, classifying each morph as ‘self’ voice (or face) or an ‘other’ voice (or face). All participants also completed the Autism Spectrum Quotient (AQ). For each sensory modality, slope of the self-recognition curve was used as individual self-recognition metric. These two self-recognition metrics were tested for association between each other, and with autistic traits. Results Fifty percent ‘self’ response was reached for a higher percentage of self in the auditory domain compared to the visual domain (t = 3.142; P < 0.01). No significant correlation was noted between self-recognition bias across sensory modalities (τ = −0.165, P = 0.204). Higher recognition bias for self-voice was observed in individuals higher in autistic traits (τ AQ = 0.301, P = 0.008). No such correlation was observed between recognition bias for self-face and autistic traits (τ AQ = −0.020, P = 0.438). Conclusions Our data shows that recognition bias for physical self-representation is not related across sensory modalities. Further, individuals with higher autistic traits were better able to discriminate self from other voices, but this relation was not observed with self-face. A narrow self-other overlap in the auditory domain seen in individuals with high autistic traits could arise due to enhanced perceptual processing of auditory stimuli often observed in individuals with autism.

Sex and STEM occupation predict Autism-spectrum Quotient (AQ) scores in half a million people

This study assesses Autism-Spectrum Quotient (AQ) scores in a ‘big data’ sample collected through the UK Channel 4 television website, following the broadcasting of a medical education program. We examine correlations between the AQ and age, sex, occupation, and UK geographic region in 450,394 individuals. We predicted that age and geography would not be correlated with AQ, whilst sex and occupation would have a correlation. Mean AQ for the total sample score was m = 19.83 (SD = 8.71), slightly higher than a previous systematic review of 6,900 individuals in a non-clinical sample (mean of means = 16.94) This likely reflects that this big-data sample includes individuals with autism who in the systematic review score much higher (mean of means = 35.19). As predicted, sex and occupation differences were observed: on average, males (m = 21.55, SD = 8.82) scored higher than females (m = 18.95; SD = 8.52), and individuals working in a STEM career (m = 21.92, SD = 8.92) scored higher than individuals non-STEM careers (m = 18.92, SD = 8.48). Also as predicted, age and geographic region were not meaningfully correlated with AQ. These results support previous findings relating to sex and STEM careers in the largest set of individuals for which AQ scores have been reported and suggest the AQ is a useful self-report measure of autistic traits

A new calibrated sunspot group series since 1749: statistics of active day fractions

Although the sunspot-number series have existed since the mid-19th century, they are still the subject of intense debate, with the largest uncertainty being related to the "calibration" of the visual acuity of individual observers in the past. Daisy-chain regression methods are applied to inter-calibrate the observers which may lead to significant bias and error accumulation. Here we present a novel method to calibrate the visual acuity of the key observers to the reference data set of Royal Greenwich Observatory sunspot groups for the period 1900-1976, using the statistics of the active-day fraction. For each observer we independently evaluate their observational thresholds [S_S] defined such that the observer is assumed to miss all of the groups with an area smaller than S_S and report all the groups larger than S_S. Next, using a Monte-Carlo method we construct, from the reference data set, a correction matrix for each observer. The correction matrices are significantly non-linear and cannot be approximated by a linear regression or proportionality. We emphasize that corrections based on a linear proportionality between annually averaged data lead to serious biases and distortions of the data. The correction matrices are applied to the original sunspot group records for each day, and finally the composite corrected series is produced for the period since 1748. The corrected series displays secular minima around 1800 (Dalton minimum) and 1900 (Gleissberg minimum), as well as the Modern grand maximum of activity in the second half of the 20th century. The uniqueness of the grand maximum is confirmed for the last 250 years. It is shown that the adoption of a linear relationship between the data of Wolf and Wolfer results in grossly inflated group numbers in the 18th and 19th centuries in some reconstructions.

Constraining the aerosol influence on cloud fraction

Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.

Antipyretic and anti-inflammatory properties of the ethanolic extract, dichloromethane fraction and costunolide from Magnolia ovata (Magnoliaceae)

Aim of the study: Magnolia ovata (A.St.-Hil.) Spreng (formerly Talauma ovata), known as ""pinha-do-brejo"" or ""baguacu"", is a large tree widely distributed in Brazil. Its trunk bark has been used in folk medicine against fever. However, no data have been published to support the antipyretic ethnopharmacological use. This study investigated the antipyretic and anti-inflammatory effects of the ethanolic extract (EEMO). dichloromethane fraction (DCM), and the isolated compound costunolide. Materials and methods: The antipyretic and anti-inflammatory activities were evaluated in experimental models of fever and inflammation in mice. Results: The oral administration of EEMO, DCM and costunolide inhibited carrageenan (Cg)-induced paw oedema (ID(50) 72.35 (38.64-135.46) mg/kg, 5.8 (2.41-14.04) mg/kg and 0.18 (0.12-0.27) mg/kg, respectively) and was effective in abolishing lipopolysaccharide (LPS)-induced fever (30 mg/kg, 4.5 mg/kg and 0.15 mg/kg, respectively). EEMO was also effective in reducing cell migration in the pleurisy model. Intraplantar injection of costunolide also reduced the paw oedema, myeloperoxidase and N-acetyl-glucosaminidase activity induced by Cg in mice. Conclusions: Collectively, these results show, for the first time, that extracts obtained from Magnolia ovata possess antipyretic and anti-inflammatory properties, and costunolide appears to be the compound responsible for these effects. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Proteomics of the neurotoxic fraction from the sea anemone Bunodosoma cangicum venom: Novel peptides belonging to new classes of toxins

In contrast to the many studies on the venoms of scorpions, spiders, snakes and cone snails, tip to now there has been no report of the proteomic analysis of sea anemones venoms. In this work we report for the first time the peptide mass fingerprint and some novel peptides in the neurotoxic fraction (Fr III) of the sea anemone Bunodosoma cangicum venom. Fr III is neurotoxic to crabs and was purified by rp-HPLC in a C-18 column, yielding 41 fractions. By checking their molecular masses by ESI-Q-Tof and MALDI-Tof MS we found 81 components ranging from near 250 amu to approximately 6000 amu. Some of the peptidic molecules were partially sequenced through the automated Edman technique. Three of them are peptides with near 4500 amu belonging to the class of the BcIV, BDS-I, BDS-II, APETx1, APETx2 and Am-II toxins. Another three peptides represent a novel group of toxins (similar to 3200 amu). A further three molecules (similar to similar to 4900 amu) belong to the group of type 1 sodium channel neurotoxins. When assayed over the crab leg nerve compound action potentials, one of the BcIV- and APETx-like peptides exhibits an action similar to the type 1 sodium channel toxins in this preparation, suggesting the same target in this assay. On the other hand one of the novel peptides, with 3176 amu, displayed an action similar to potassium channel blockage in this experiment. In summary, the proteomic analysis and mass fingerprint of fractions from sea anemone venoms through MS are valuable tools, allowing us to rapidly predict the occurrence of different groups of toxins and facilitating the search and characterization of novel molecules without the need of full characterization of individual components by broader assays and bioassay-guided purifications. It also shows that sea anemones employ dozens of components for prey capture and defense. (C) 2008 Elsevier Inc. All rights reserved.

A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

EXPLOITING A GENERIC APPROACH TO CONSTRUCT COMPONENT-BASED SYSTEMS SOFTWARE IN LINUX ENVIRONMENTS

Component-based software engineering has recently emerged as a promising solution to the development of system-level software. Unfortunately, current approaches are limited to specific platforms and domains. This lack of generality is particularly problematic as it prevents knowledge sharing and generally drives development costs up. In the past, we have developed a generic approach to component-based software engineering for system-level software called OpenCom. In this paper, we present OpenComL an instantiation of OpenCom to Linux environments and show how it can be profiled to meet a range of system-level software in Linux environments. For this, we demonstrate its application to constructing a programmable router platform and a middleware for parallel environments.

Magnetic hysteresis loop shift in NiFe(2)O(4) nanocrystalline powder with large grain boundary fraction

Magnetic properties of nanocrystalline NiFe(2)O(4) spinel mechanically processed for 350 h have been studied using temperature dependent from both zero-field and in-field (57)Fe Mossbauer spectrometry and magnetization measurements. The hyperfine structure allows us to distinguish two main magnetic contributions: one attributed to the crystalline grain core, which has magnetic properties similar to the NiFe(2)O(4) spinel-like structure (n-NiFe(2)O(4)) and the other one due to the disordered grain boundary region, which presents topological and chemical disorder features(d-NiFe(2)O(4)). Mossbauer spectrometry determines a large fraction for the d-NiFe(2)O(4) region(62% of total area) and also suggests a speromagnet-like structure for it. Under applied magnetic field, the n-NiFe(2)O(4) spins are canted with angle dependent on the applied field magnitude. Mossbauer data also show that even under 120 kOe no magnetic saturation is observed for the two magnetic phases. In addition, the hysteresis loops, recorded for scan field of 50 kOe, are shifted in both field and magnetization axes, for temperatures below about 50 K. The hysteresis loop shifts may be due to two main contributions: the exchange bias field at the d-NiFe(2)O(4)/n-NiFe(2)O(4) interfaces and the minor loop effect caused by a high magnetic anisotropy of the d-NiFe(2)O(4) phase. It has also been shown that the spin configuration of the spin-glass like phase is modified by the consecutive field cycles, consequently the n-NiFe(2)O(4)/d-NiFe(2)O(4) magnetic interaction is also affected in this process. (C) 2010 Elsevier B.V. All rights reserved.