Motion streaks do not influence the perceived position of stationary flashed objects

In the present study, we investigated whether motion streaks, produced by fast moving dots Geisler 1999, distort the positional map of stationary flashed objects producing the well-known motion-induced position shift illusion (MIPS). The illusion relies on motion-processing mechanisms that induce local distortions in the positional map of the stimulus which is derived by shape-processing mechanisms. To measure the MIPS, two horizontally offset Gaussian blobs, placed above and below a central fixation point, were flashed over two fields of dots moving in opposite directions. Subjects judged the position of the top Gaussian blob relative to the bottom one. The results showed that neither fast (motion streaks) nor slow moving dots influenced the perceived spatial position of the stationary flashed objects, suggesting that background motion does not interact with the shape-processing mechanisms involved in MIPS

Effects of crowding and attention on high-levels of motion processing and motion adaptation

The motion after-effect (MAE) persists in crowding conditions, i.e., when the adaptation direction cannot be reliably perceived. The MAE originating from complex moving patterns spreads into non-adapted sectors of a multi-sector adapting display (i.e., phantom MAE). In the present study we used global rotating patterns to measure the strength of the conventional and phantom MAEs in crowded and non-crowded conditions, and when attention was directed to the adapting stimulus and when it was diverted away from the adapting stimulus. The results show that: (i) the phantom MAE is weaker than the conventional MAE, for both non-crowded and crowded conditions, and when attention was focused on the adapting stimulus and when it was diverted from it, (ii) conventional and phantom MAEs in the crowded condition are weaker than in the non-crowded condition. Analysis conducted to assess the effect of crowding on high-level of motion adaptation suggests that crowding is likely to affect the awareness of the adapting stimulus rather than degrading its sensory representation, (iii) for high-level of motion processing the attentional manipulation does not affect the strength of either conventional or phantom MAEs, neither in the non-crowded nor in the crowded conditions. These results suggest that high-level MAEs do not depend on attention and that at high-level of motion adaptation the effects of crowding are not modulated by attention

Equilibrium models of rotating compact stars: an application to the post-merger phase of GW170817

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“BATTLES OVER ISSUES” IN NETWORKED PUBLICS: INVESTIGATING THE DISCURSIVE MOBILIZATION OF THE ANTIFASCIST FRAME ON TWITTER

In this article we explore the discursive mobilization of movement frames within networked publics—a form of unorganized digital activism through which movement organizations, activists, and citizens politicize ordinary conversations by engaging in adversarial meaningmaking dynamics online. Leaning on large-scale semantic network analysis and content analysis, we investigate the mobilization of the frame of antifascism within the conversation that sparked on Twitter after the brutal shooting of a group of African citizens by an Italian neofascist militant in 2018. We pay particular attention to how the discursive mobilization of the frame of antifascism occurs immediately after the shooting and how it evolves particularly in connection with offline protests. Our results shed light on the fluid nature of discursive mobilization patterns which underpin both the identification with the antifascist tradition and attempts to delegitimize this instance of collective action

Interactions between motion and form processing in the human visual system

The predominant view of motion and form processing in the human visual system assumes that these two attributes are handled by separate and independent modules. Motion processing involves filtering by direction-selective sensors, followed by integration to solve the aperture problem. Form processing involves filtering by orientation-selective and size-selective receptive fields, followed by integration to encode object shape. It has long been known that motion signals can influence form processing in the well-known Gestalt principle of common fate; texture elements which share a common motion property are grouped into a single contour or texture region. However, recent research in psychophysics and neuroscience indicates that the influence of form signals on motion processing is more extensive than previously thought. First, the salience and apparent direction of moving lines depends on how the local orientation and direction of motion combine to match the receptive field properties of motion-selective neurons. Second, orientation signals generated by “motion-streaks” influence motion processing; motion sensitivity, apparent direction and adaptation are affected by simultaneously present orientation signals. Third, form signals generated by human body shape influence biological motion processing, as revealed by studies using point-light motion stimuli. Thus, form-motion integration seems to occur at several different levels of cortical processing, from V1 to STS

Constructing arithmetic subgroups of unipotent groups

Let G be a unipotent algebraic subgroup of some GL_m(C) defined over Q. We describe an algorithm for finding a finite set of generators of the subgroup G(Z) = G \cap GL_m(Z). This is based on a new proof of the result (in more general form due to Borel and Harish-Chandra) that such a finite generating set exists.Comment: 19 page

On the rank of 3x3x3 -tensors

Let U, V and W be finite dimensional vector spaces over the same field. The rank of a tensor t in U???V???W is the minimum dimension of a subspace of U???V???W containing t and spanned by fundamental tensors, i.e. tensors of the form u???v???w for some u in U, v in V and w in W. We prove that if U, V and W have dimension three, then the rank of a tensor in U???V???W is at most six, and such a bound cannot be improved, in general. Moreover, we discuss how the techniques employed in the proof might be extended to prove upper bounds for the rank of a tensor in U???V???W when the dimensions of U, V and W are higher

Jet-environment interplay in magnetized binary neutron star mergers

GRB 170817A, the first short gamma-ray burst (sGRB) to be detected in coincidence with a gravitational wave signal, demonstrated that merging binary neutron star (BNS) systems can power collimated ultra-relativistic jets and, in turn, produce sGRBs. Moreover, it revealed that sGRB jets possess an intrinsic angular structure that is imprinted in the observable prompt and afterglow emission. Advanced numerical simulations represent the leading approach to investigate the physical processes underlying the evolution of sGRB jets breaking out of post-merger environments, and thus connect the final angular structure and energetics with specific jet launching conditions. In a previous paper, we carried out the first three-dimensional (3D) special-relativistic hydrodynamic simulations of incipient (top-hat) sGRB jets propagating across the realistic environment resulting from a general-relativistic (GR) hydrodynamic BNS merger simulation. While the above work marked an important step toward a consistent end-to-end description of sGRB jets from BNS mergers, those simulations did not account for the presence of magnetic fields, which are expected to play a key role. Here, we overcome this limitation, reporting the first 3D special-relativistic magnetohydrodynamic (MHD) simulation of a magnetized (structured and rotating) sGRB jet piercing through a realistic magnetized post-merger environment, wherein the initial conditions of the latter are directly imported from the outcome of a previous GRMHD BNS merger simulation.Comment: 16 pages, 15 figures, accepted for publication in MNRA

Short gamma-ray burst jet propagation in binary neutron star merger environments

The multimessenger event GW170817/GRB 170817A confirmed that binary neutron star (BNS) mergers can produce short gamma-ray burst (SGRB) jets. This evidence promoted new investigations on the mechanisms through which a BNS merger remnant can launch such a powerful relativistic outflow and on the propagation of the latter across the surrounding post-merger environment. In particular, great strides have been made in jet propagation models, establishing connections between the initial jet launching conditions, including the incipient jet launching time (with respect to merger) and the injection parameters, and the observable SGRB prompt and afterglow emission. However, present semi-analytical models and numerical simulations (with one notable exception) adopt simple hand-made prescriptions to account for the post-merger environment, lacking a direct association with any specific merging BNS system. Here, we present the first three-dimensional relativistic hydrodynamics simulations of incipient SGRB jets propagating through a post-merger environment that is directly imported from the outcome of a previous general relativistic BNS merger simulation. Our results show that the evolution and final properties of the jet can be largely affected by the anisotropies and the deviations from axisymmetry and homologous expansion characterizing more realistic BNS merger environments. In addition, we find that the inclusion of the gravitational pull from the central compact object, often overlooked, can have a major impact. Finally, we consider different jet launching times referred to the same BNS merger model and discuss the consequences for the ultimate jet properties.Comment: 16 pages, 20 figure

GURLS: A Least Squares Library for Supervised Learning

We present GURLS, a least squares, modular, easy-to-extend software library for efficient supervised learning. GURLS is targeted to machine learning practitioners, as well as non- specialists. It offers a number state-of-the-art training strategies for medium and large-scale learning, and routines for efficient model selection. The library is particularly well suited for multi-output problems (multi-category/multi-label). GURLS is currently available in two independent implementations: Matlab and C++. It takes advantage of the favorable properties of regularized least squares algorithm to exploit advanced tools in linear algebra. Routines to handle computations with very large matrices by means of memory-mapped storage and distributed task execution are available. The package is distributed under the BSD license and is available for download at https://github.com/LCSL/GURLS