Don't sit so close to me: Unconsciously elicited affect automatically provokes social avoidance

Behavior may be automatically prompted by cues in our social environment. Previous research has focused on cognitive explanations for such effects. Here we hypothesize that affective processes are susceptible to similar automatic influences. We propose that exposure to groups stereotyped as dangerous or violent may provoke an anxiety response and, thus, a tendency to move away. In the present experiment, we subliminally exposed participants to images of such a group, and found that they displayed greater avoidance in a subsequent interaction. Critically, this effect was explained by their increased sensitivity to threat-related information. These findings demonstrate an affective mechanism responsible for nonconscious priming effects on interpersonal behavior

Seeing more than we can know: Visual attention and category activation

Extending existing work on the conditional automaticity of category activation, the present research investigated the extent to which category activation is moderated by the resolution of visual attention. As visual attention gates access to material in semantic memory, so too should it regulate the activation of social categories when triggering verbal labels are encountered. Accordingly, only when triggering stimuli fall within the spotlight of attention did we expect category activation to occur. The results of two studies supported this prediction. We consider the implications of our findings for recent treatments of category automaticity

" Women! Your Country Needs You! " Fleeing Feminism or Gendering Citizenship in Great War Britain?

doi erroné : 10.3172/MIN.4.2.26International audienceWhen war broke out in August 1914, the National Union of Women's Suffrage Societies suspended its political work on behalf of women's suffrage and plunged into relief work for women and children. Because it appeared to conform to the reigning ideology of separate spheres, this response has been presented as conclusive evidence of British feminism's ideological collapse in the face of war. This article argues a contrario that the National Union's response is further evidence of feminism's ideological resilience in this period. Relief work, it shows, was one aspect of a broader project aimed at " gendering " the concept and language of citizenship in order to appropriate them for women. The result was an insistence on women's identity as " citizens, " an identity that in turn had important consequences for the kind of feminism that could be articulated in its name

Priming in interpersonal contexts: Implications for affect and behavior

Priming stereotypes can lead to a variety of behavioral outcomes, including assimilation, contrast, and response behaviors. However, the conditions that give rise to each of these outcomes are unspecified. Furthermore, theoretical accounts posit that prime-to-behavior effects are either direct (i.e., unmediated) or mediated by cognitive processes, whereas the role of affective processes has been largely unexplored. The present research directly investigated both of these issues. Three experiments demonstrated that priming a threatening social group ("hoodies") influences both affect and behavior in an interpersonal context. Hoodie priming produced both behavioral avoidance and several affective changes (including social apprehension, threat sensitivity, and self-reported anxiety and hostility). Importantly, avoidance following hoodie priming was mediated by anxiety and occurred only under conditions of other-(but not self-) focus. These results highlight multiple routes through which primes influence affect and behavior, and suggest that attention to self or others determine the nature of priming effects

When not thinking leads to being and doing: Stereotype suppression and the self

Suppressing stereotypes often results in more stereotype use, an effect attributed to heightened stereotype activation. The authors report two experiments examining the consequences of suppression on two self-relevant outcomes: the active self-concept and overt behavior. Participants who suppressed stereotypes incorporated stereotypic traits into their self-concepts and demonstrated stereotype-congruent behavior compared to those who were exposed to the same stereotypes but did not suppress them. These findings address issues emerging from current theories of suppression, priming, and the active self

Practical comparison of sparse methods for classification of Arabica and Robusta coffee species using near infrared hyperspectral imaging

In the present work sparse-based methods are applied to the analysis of hyperspectral images with the aim at studying their capability of being adequate methods for variable selection in a classification framework. The key aspect of sparse methods is the possibility of performing variable selection by forcing the model coefficients related to irrelevant variables to zero. In particular, two different sparse classification approaches, i.e. sPCA+kNN and sPLS-DA, were compared with the corresponding classical methods (PCA + kNN and PLS-DA) to classify Arabica and Robusta coffee species. Green coffee samples were analyzed using near infrared hyperspectral imaging and the average spectra from each hyperspectral image were used to build training and test sets; furthermore a test image was used to evaluate the performances of the considered methods at pixel-level. In our case, sparse methods led to similar results as classical methods, with the advantage of obtaining more interpretable and parsimonious models. An important result to highlight is that variable selection performed with two different sparse classification approaches converged to the selection of same spectral regions, which implies the chemical relevance of those regions in the discrimination of Arabica and Robusta coffee species

Fast exploration and classification of large hyperspectral image datasets for early bruise detection on apples

Hyperspectral imaging allows to easily acquire tens of thousands of spectra for a single sample in few seconds; though valuable, this data-richness poses many problems due to the difficulty of handling a representative amount of samples altogether. For this reason, we recently proposed an approach based on the idea of reducing each image into a one-dimensional signal, named hyperspectrogram, which accounts both for spatial and for spectral information. In this manner, a dataset of hyperspectral images can be easily and quickly converted into a set of signals (2D data matrix), which in turn can be analyzed using classical chemometric techniques. In this work, the hyperspectrograms obtained from a dataset of 800 NIR-hyperspectral images of two different apple varieties were used to discriminate bruised from sound apples using iPLS-DA as variable selection algorithm, which allowed to efficiently detect the presence of bruises. Moreover, the reconstruction as images of the selected variables confirmed that the automated procedure led to the exact identification of the spatial features related to the onset and to the subsequent evolution with time of the bruise defect

Noise reduction in muon tomography for detecting high density objects

The muon tomography technique, based on multiple Coulomb scattering of cosmic ray muons, has been proposed as a tool to detect the presence of high density objects inside closed volumes. In this paper a new and innovative method is presented to handle the density fluctuations (noise) of reconstructed images, a well known problem of this technique. The effectiveness of our method is evaluated using experimental data obtained with a muon tomography prototype located at the Legnaro National Laboratories (LNL) of the Istituto Nazionale di Fisica Nucleare (INFN). The results reported in this paper, obtained with real cosmic ray data, show that with appropriate image filtering and muon momentum classification, the muon tomography technique can detect high density materials, such as lead, albeit surrounded by light or medium density material, in short times. A comparison with algorithms published in literature is also presented

Precision measurements of Linear Scattering Density using Muon Tomography

We demonstrate that muon tomography can be used to precisely measure the properties of various materials. The materials which have been considered have been extracted from an experimental blast furnace, including carbon (coke) and iron oxides, for which measurements of the linear scattering density relative to the mass density have been performed with an absolute precision of 10%. We report the procedures that are used in order to obtain such precision, and a discussion is presented to address the expected performance of the technique when applied to heavier materials. The results we obtain do not depend on the specific type of material considered and therefore they can be extended to any application.Comment: 16 pages, 4 figure