Discriminating Taxonomic Categories and Domains in Mental Simulations of Concepts of Varying Concreteness

Most studies of conceptual knowledge in the brain focus on a narrow range of concrete conceptual categories, rely on the researchers' intuitions about which object belongs to these categories, and assume a broadly taxonomic organization of knowledge. In this fMRI study, we focus on concepts with a variety of concreteness levels; we use a state of the art lexical resource (WordNet 3.1) as the source for a relatively large number of category distinctions and compare a taxonomic style of organization with a domain-based model (associating concepts with scenarios). Participants mentally simulated situations associated with concepts when cued by text stimuli. Using multivariate pattern analysis, we find evidence that all Taxonomic categories and Domains can be distinguished from fMRI data and also observe a clear concreteness effect: Tools and Locations can be reliably predicted for unseen participants, but less concrete categories (e.g., Attributes, Communications, Events, Social Roles) can only be reliably discriminated within participants. A second concreteness effect relates to the interaction of Domain and Taxonomic category membership: Domain (e.g., relation to Law vs. Music) can be better predicted for less concrete categories. We repeated the analysis within anatomical regions, observing discrimination between all/most categories in the left middle occipital and temporal gyri, and more specialized discrimination for concrete categories Tool and Location in the left precentral and fusiform gyri, respectively. Highly concrete/abstract Taxonomic categories and Domain were segregated in frontal regions. We conclude that both Taxonomic and Domain class distinctions are relevant for interpreting neural structuring of concrete and abstract concepts.

A SPECIFICATION OF A COMPLEX PROGRAMMING LANGUAGE STATEMENT

A formal specification of a complex programming language statement is presented. The subject matter was selected as being typical of the kind confronting a small software house. It is shown that formal specification notations may be applied, with benefit, to 'messy' problems. Emphasis is placed upon producing a specification which is readable by, and useful to a reader not familiar with formal notations.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Polarisation independent resistively loaded frequency selective surface absorber with optimum oblique incidence performance

This study presents the design of a thin electromagnetic absorber which exhibits radar backscatter suppression that is independent of the wave polarisation at large incidence angles. The structure consists of a metal backed printed frequency selective surface (FSS), with resistors placed across narrow gaps inserted in the middle of each of the four sides of the conductor loops. The geometry of the periodic array and the value of the vertical and horizontal resistor pairs are carefully chosen to present a real impedance of 377 Ω at the centre operating frequency for both TE and TM polarised waves. Angular sensitivity and reflectivity bandwidth have been investigated for FSS absorber designs with thicknesses of 1, 2 and 3 mm. Each of the three structures was optimised to work at a centre frequency of 10 GHz and an incident angle of 45°. The design methodology is verified by measuring the radar backscatter suppression from a 3 mm (l / 10) thick screen in the frequency range 8–12 GHz. The absorber construction was simplified by filling the four metal gaps in each unit cell with shielding paint, and selecting the ink thickness to give the two required surface resistance values.

A Four-element Antenna System for Mobile Phones

In this letter, a multiantenna system with four printed monopoles is presented. The monopoles that occupy relatively small area are positioned at the four corners of a printed circuit board, so that the four-element antenna system can be equipped on the lid of a folder-type mobile phone, leaving enough space for the circuits and reducing the effect of human hands. Based on simulation, a prototype for the Universal Mobile Telecommunications System (UMTS) operation has been constructed and tested. The measured -10-dB impedance bandwidths of the four elements are larger than 320 MHz with higher than 11.5-dB isolation. Moreover, the proposed antenna can provide spatial and pattern diversity in a diversity/multiple-input-multiple-output (MIMO) system.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

Genetic assessment of parentage in the caridean rock shrimp Rhynchocinetes typus based on microsatellite markers

Over the past decade, the common rock shrimp, Rhynchocinetes typus H. Milne Edwards, 1837, has been the focus of extensive investigations on mating behaviour. The species is now perceived as a model system for the study of reproductive strategies and sexual conflict in crustaceans displaying external fertilization. Using molecular markers, the current study assesses whether social mating behaviour in common rock shrimp translates into true genetic parentage. In a large mesocosm tank with >200 individuals of both sexes, the analysis of 15 families (22 eggs per female) for three informative microsatellites unambiguously confirmed multiple paternity in 11 instances (73%) involving, in each case, two to four males. Where more than one male was identified siring a particular brood, reproductive skew was apparent towards a single individual. Results suggest that multiple paternity in this species results from subordinate male coercive behaviour, female solicitation of multiple male matings or a combination of both.

A DIRECT INVERSION METHOD FOR SURFACE-STRUCTURE DETERMINATION FROM LEED INTENSITIES

LOW-ENERGY electron diffraction (LEED) has become the most successful technique in surface crystallography1, but because of the complexity of the surface-electron scattering interactions, analyses of LEED data are still conducted on a trial-and-error basis: a direct-inversion method for treating LEED intensity data remains an attractive goal2. Building on recent theoretical and experimental developments in electron holography from surface structures3-16, we show here that three-dimensional images with atomic resolution can be obtained by a direct transform of conventional LEED intensity spectra.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

A spatio-temporal contrast of the predatory impact of an invasive freshwater crustacean

Aim: Impacts of invasive species may vary across invasion gradients, owing to trait-based sorting of individuals through dispersal: those aggregating at invasion fronts may be more aggressive and voracious. We examine, in the field and laboratory, variation in the predatory impacts of an invasive Ponto-Caspian crustacean Hemimysis anomala G.O. Sars, 1907 at two sites along a spatio-temporal gradient of invasion.

Location: Republic of Ireland.

Methods: We used reciprocal transplant field-deployed mesocosms to compare predation rates of invasion front and well-established H. anomala on natural zooplankton assemblages. In the laboratory, we measured the functional response (relationship between predation rate and prey supply) of H. anomala from both sites, for a per capita mechanistic comparison of predation efficiency. We also assessed prey selectivity of H. anomala in the mesocosm experiments to further compare feeding behaviour. Finally, we used a correlative approach to assess the community impact of H. anomala across sites, including a nearby uninvaded site, by comparing zooplankton diversities and densities.

Results: Invasion front H. anomala had higher predation rates than well-established H. anomala at high in situ zooplankton densities. Invasion front H. anomala also had higher functional responses - in particular showing higher 'attack rates' - indicating a heightened ability to locate and capture prey. Prey selectivity was consistent across the spatio-temporal contrast, with positive selection for cladocerans. Zooplankton diversity and density declined with time since H. anomala invasion, both being maximal at the uninvaded site.

Main conclusions: Our study, for the first time, (1) reveals differences in predatory per capita effects and associated behavioural traits between two sites along a spatio-temporal invasion gradient and (2) shows a negative community-level impact of the invasive H. anomala in natural water bodies. Further spatio-temporal comparisons of predatory per capita effects of invaders are needed to assess the generality of these results.

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.

Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.

Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 X 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 X 10(-11)), cholesterol transport (P = 2.96 X 10(-9)), and proteasome-ubiquitin activity (P = 1.34 X 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05).

Conclusions: The immime response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. (C) 2015 Published by Elsevier Inc. on behalf of The Alzheimer's Association.