A novel 3D technique to study the kinematics of lensed galaxies

We present a 3D Bayesian method to model the kinematics of strongly lensed galaxies from spatially-resolved emission-line observations. This technique enables us to simultaneously recover the lens-mass distribution and the source kinematics directly from the 3D data cube. We have tested this new method with simulated OSIRIS observations for nine star-forming lensed galaxies with different kinematic properties. The simulated rotation curves span a range of shapes which are prototypes of different morphological galaxy types, from dwarf to massive spiral galaxies. We have found that the median relative accuracy on the inferred lens and kinematic parameters are at the level of 1 and 2 per cent, respectively. We have also tested the robustness of the technique against different inclination angles, signal-to-noise ratios, the presence of warps or non-circular motions and we have found that the accuracy stays within a few per cent in most cases. This technique represents a significant step forward with respect to the methods used until now, as the lens parameters and the kinematics of the source are derived from the same 3D data. This enables us to study the possible degeneracies between the two and estimate the uncertainties on all model parameters consistently.Comment: Accepted for publication in MNRA

The cost of context repair: Presupposition accomodation

In the present experiment, the processing costs and time-course of presupposition accommodation were studied, as compared to presupposition satisfaction and independently of the presupposition trigger in use. Two main results emerged from the data collected. First, presupposition accommodation requires greater processing costs than satisfaction, reflecting a process of context repair where both a linking and an updating process are needed. Second, presupposition accommodation takes places immediately just as the trigger becomes available and proceeds incrementally during the sentence processing. This result suggests that presuppositions are processed on-line and that, independently of the type of trigger in use, they are accommodated before the asserted content is computed

Modelling the positioning of single needle electrodes for the treatment of breast cancer in a clinical case

Background: Breast cancer is the most common cancer in women worldwide and is the second most common cause of cancer death in women. Electrochemotherapy (ECT) used in early-phase clinical trials for the treatment of primary breast cancer resulted in a not complete tumor necrosis in most cases. The present study was undertaken to analyze the feasibility to use ECT to treat patients with histologically proven unifocal ductal breast cancer. In particular, results of ECT treatment in a clinical case are compared with the ones of a simplified 3D dosimetric model. Methods: This clinical study was conducted with the pulse generator Cliniporator Vitae (IGEA, Carpi, Italy). ECT procedures were performed according to ESOPE standard operating procedures. Five single needle electrodes were used with one positioned in the center of the tumor, and the other four distributed around the nodule. Histological images of the resected tumor are compared with the maps of the electric field obtained with a simplified 3D model in Comsol Multiphysics v 4.3. Results: The results of the clinical case demonstrated a reduced efficacy of the ECT treatment described. The proposed simple numerical model of the breast tumor located in a low conductive tissue suggests that this is due to the reduced electric field induced inside the tumor with such 5 electrodes placement. However, where the electric field is predicted higher than the reversible electroporation threshold (E > 400 V/cm), also the histological images confirm the necrosis of the target with a good agreement between the modeled and clinical results. Conclusions: The results suggest the dependence of the effectiveness of the treatment on the careful placement of the electrodes. A detailed planned procedure for the tumor analysis after the treatment is also needed in order to better correlate the single electrode positions and the histological images. Simulation models could be used to identify better electrodes configuration in planning the experimental protocol for ECT treatment of breast tumors

The development of presupposition: Pre-schoolers' understanding of regret and too

Little is known about presuppositional skills in pre-school years. Developmental research has mostly focused on children’s understanding of too and evidence is mixed: some studies show that the comprehension of too is not adult-like at least until school age, while more recent findings suggest that even pre-schoolers can interpret too-sentences in more age-appropriate tasks. Importantly, no study has tested directly, within the same experiment, pre-schoolers’ presupposition understanding in satisfaction versus accommodation, nor with respect to other trigger types. Yet, it is well known that adults’ processing of a presupposition is costlier when accommodation is required and that the type of trigger influences the processing demands. Therefore, both the trigger type and the contextual availability of a presupposition might influence young children’s comprehension. We tested this with a story completion task that assessed 3–5-year-olds’ comprehension of presuppositions activated by either regret or too in contexts that either satisfied the presupposition or required accommodation. Results reveal that pre-schoolers overall exhibit an understanding of presupposition. Crucially, this starkly improves between the age of 3 and 5 and the developmental trajectory depends on both context and trigger type: understanding the presupposition of regret seems easier than that of too for younger children, and less difficulties emerge when the context satisfies the presupposition. Thus, the development of presupposition comprehension in pre-schoolers depends both on the type of trigger and the contextual availability of the presupposition – satisfied versus requiring failure repair

Testing the Causal Theory of Reference

Theories of reference are a crucial research topic in analytic philosophy. Since the publication of Kripke\u2019s Naming and Necessity, most philosophers have endorsed the causal/historical theory of reference. The goal of this paper is twofold: (i) to discuss a method for testing experimentally the causal theory of ref- erence for proper names by investigating linguistic usage and (ii) to present the results from two exper- iments conducted with that method. Data collected in our experiments confirm the causal theory of reference for people proper names and for geographical proper names. A secondary but interesting result is that the semantic domain affects reference assignment: while with people proper names speakers tend to assign the semantic reference, with geographical proper names they are prompted to assign the speak- er\u2019s reference

Absorption and scattering properties of carbon nanohorn-based nanofluids for direct sunlight absorbers

In the present work, we investigated the scattering and spectrally resolved absorption properties of nanofluids consisting in aqueous and glycol suspensions of single-wall carbon nanohorns. The characteristics of these nanofluids were evaluated in view of their use as sunlight absorber fluids in a solar device. The observed nanoparticle-induced differences in optical properties appeared promising, leading to a considerably higher sunlight absorption with respect to the pure base fluids. Scattered light was found to be not more than about 5% with respect to the total attenuation of light. Both these effects, together with the possible chemical functionalization of carbon nanohorns, make this new kind of nanofluids very interesting for increasing the overall efficiency of the sunlight exploiting device

The Clinical Relevance of Artificial Intelligence in Migraine

: Migraine is a burdensome neurological disorder that still lacks clear and easily accessible diagnostic biomarkers. Furthermore, a straightforward pathway is hard to find for migraineurs' management, so the search for response predictors has become urgent. Nowadays, artificial intelligence (AI) has pervaded almost every aspect of our lives, and medicine has not been missed. Its applications are nearly limitless, and the ability to use machine learning approaches has given researchers a chance to give huge amounts of data new insights. When it comes to migraine, AI may play a fundamental role, helping clinicians and patients in many ways. For example, AI-based models can increase diagnostic accuracy, especially for non-headache specialists, and may help in correctly classifying the different groups of patients. Moreover, AI models analysing brain imaging studies reveal promising results in identifying disease biomarkers. Regarding migraine management, AI applications showed value in identifying outcome measures, the best treatment choices, and therapy response prediction. In the present review, the authors introduce the various and most recent clinical applications of AI regarding migraine

Beyond Pain: The Effects of OnabotulinumtoxinA Therapy on Sensitization and Interictal Symptoms in Chronic Migraine

: Chronic migraine is a disease with a high burden on patients from both a working and quality of life point of view. The pathophysiology of this subtype of migraine is due to several factors, such as medication overuse. Nevertheless, the detrimental recurring of headache attacks with central and peripheral sensitization plays a central role and explains some additional symptoms complained about by these patients even in the interictal phase. OnabotulinumtoxinA is a therapy indicated for chronic migraine since it has proven to reduce peripheral sensitization, showing even efficacy on central symptoms. The aim of this narrative review is to present the current evidence regarding the effect of OnabotulinumtoxinA on sensitization and interictal symptoms