906 resultados para Turn signals.


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By applying methods of cognitive metaphor theory, Jaworska examines metaphorical scenarios employed in the discourse of anti-Slavism, which featured prominently in radical nationalist propaganda in Germany at the turn of the twentieth century. She does so by analysing metaphorical expressions used to refer to the Polish population living in the eastern provinces of Prussia, in the so-called Ostmark. Her article is based on an analysis of a range of pamphlets and newspaper articles written by some of the leading figures of two nationalist organizations: the Pan-German League (Alldeutscher Verband) and the Eastern Marches Society(Ostmarkenverein). The main research questions it addresses are: What kind of metaphoric scenarios were used to depict the Polish minority, and to what extent were the metaphorical patterns of anti-Slavic imagery similar to those employed in the antisemitic propaganda of the Nazi era? Is there a discursive continuity between the radical nationalism of imperial Germany and the National Socialism of the Third Reich at the level of metaphorical scenarios? Ultimately, Jaworska attempts to contribute to a better understanding of the cognitive mechanisms underlying radical and essentially racist attitudes.

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We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signals that are previously unwanted and need to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40 % and at least 10 % higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds and a positive correlation in non-drizzling clouds, where, for large optical depths, it asymptotes to 10 μm. This asymptotic behaviour in non-drizzling clouds is found in both the droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.

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This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

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The ethical turn in international development relates to a tendency to question the deleterious impact of international development action on local populations and environment. As a consequence, new courses of action are proposed in order to generate socially just and environmentally sustainable global change. This tendency is most prominent in relation to the development impacts of globalization of production and trade but also appears across a wide range of development sectors.

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In multiple-input multiple-output (MIMO) radar systems, the transmitters emit orthogonal waveforms to increase the spatial resolution. New frequency hopping (FH) codes based on chaotic sequences are proposed. The chaotic sequences have the characteristics of good encryption, anti-jamming properties and anti-intercept capabilities. The main idea of chaotic FH is based on queuing theory. According to the sensitivity to initial condition, these sequences can achieve good Hamming auto-correlation while also preserving good average correlation. Simulation results show that the proposed FH signals can achieve lower autocorrelation side lobe level and peak cross-correlation level with the increasing of iterations. Compared to the LFM signals, this sequence has higher range-doppler resolution.

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Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

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Although the adult brain contains neural stem cells (NSCs) that generate new neurons throughout life, these astrocyte-like populations are restricted to two discrete niches. Despite their terminally differentiated phenotype, adult parenchymal astrocytes can re-acquire NSC-like characteristics following injury, and as such, these 'reactive' astrocytes offer an alternative source of cells for central nervous system (CNS) repair following injury or disease. At present, the mechanisms that regulate the potential of different types of astrocytes are poorly understood. We used in vitro and ex vivo astrocytes to identify candidate pathways important for regulation of astrocyte potential. Using in vitro neural progenitor cell (NPC)-derived astrocytes, we found that exposure of more lineage-restricted astrocytes to either tumor necrosis factor alpha (TNF-α) (via nuclear factor-κB (NFκB)) or the bone morphogenetic protein (BMP) inhibitor, noggin, led to re-acquisition of NPC properties accompanied by transcriptomic and epigenetic changes consistent with a more neurogenic, NPC-like state. Comparative analyses of microarray data from in vitro-derived and ex vivo postnatal parenchymal astrocytes identified several common pathways and upstream regulators associated with inflammation (including transforming growth factor (TGF)-β1 and peroxisome proliferator-activated receptor gamma (PPARγ)) and cell cycle control (including TP53) as candidate regulators of astrocyte phenotype and potential. We propose that inflammatory signalling may control the normal, progressive restriction in potential of differentiating astrocytes as well as under reactive conditions and represent future targets for therapies to harness the latent neurogenic capacity of parenchymal astrocytes.

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The purported migrations that have formed the peoples of Britain have been the focus of generations of scholarly controversy. However, this has not benefited from direct analyses of ancient genomes. Here we report nine ancient genomes (~1 x) of individuals from northern Britain: seven from a Roman era York cemetery, bookended by earlier Iron-Age and later Anglo-Saxon burials. Six of the Roman genomes show affinity with modern British Celtic populations, particularly Welsh, but significantly diverge from populations from Yorkshire and other eastern English samples. They also show similarity with the earlier Iron-Age genome, suggesting population continuity, but differ from the later Anglo-Saxon genome. This pattern concords with profound impact of migrations in the Anglo-Saxon period. Strikingly, one Roman skeleton shows a clear signal of exogenous origin, with affinities pointing towards the Middle East, confirming the cosmopolitan character of the Empire, even at its northernmost fringes.

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For over three decades, negotiated planning obligations have been the primary form of land value capture in England. Diffusing and evolving over the last decade, a significant policy innovation has been the use of financial calculations to estimate the extent to which policies on planning obligations for actual, proposed development projects and in plan making affect the financial viability of development. This paper assesses the extent to which the use of financial appraisals has provided a robust, just and practical procedure to support land value capture. It is concluded that development viability appraisals are saturated with intrinsic uncertainty and that land value capture that is based on such calculations is, to some extent, capricious. In addition, clear incentives for developers and land owners to bias viability calculations, the economic dependence of many viability consultants on developers and land owners, a lack of transparency, contested or ambiguous guidance and the opportunities created by input uncertainty for bias are further failings. It is argued that how viability calculations are applied has been, is being and will continue to be shaped by power relations.

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Against a background of shrinking new homes and forebodings of “rabbit hutch Britain”, the relationship between size of living space and subjective well-being has never been more topical in the UK. Using the British Household Panel Survey (BHPS) and fixed effects regressions, this paper is the first to examine this relationship comprehensively. Two pathways are proposed between space and subjective well-being. First, space facilitates values and activities. Second, space signals wealth which in turn influences social status. It is proposed that wealth is a more important determinant of status for men than women, and that pathway two is therefore gendered. Part one of the paper examines the effect of a change in number of rooms per person on housing satisfaction and subjective well-being in the BHPS as a whole. Despite having a similar effect on the housing satisfaction of both genders, an increase in living space has only a (weak) positive linear effect on the life satisfaction and mental health of men. This suggests that space affects subjective well-being through pathway two, status. Part two of the paper tracks the housing satisfaction and subjective well-being over time of those individuals who move for “larger accommodation”. Consistent with various theories of adaptation, housing satisfaction increases in the year of the move; then decreases slightly before levelling out. Moving for “larger accommodation” has no positive impact on subjective well-being. Overall the results imply a weak positive relationship between size of living space and subjective well-being, but only for men.