Strict error bounds for linear solid mechanics problems using a subdomain-based flux-free method

We discuss, in this paper, a flux-free method for the computation of strict upper bounds of the energy norm of the error in a Finite Element (FE) computation. The bounds are strict in the sense that they refer to the difference between the displacement computed on the FE mesh and the exact displacement, solution of the continuous equations, rather than to the difference between the displacements computed on two FE meshes, one coarse and one refined. This method is based on the resolution of a series of local problems on patches of elements and does not require the resolution of a previous problem of flux equilibration, as happens with other methods. The paper concentrates more specifically on linear solid mechanics issues, and on the assessment of the energy norm of the error, seen as a necessary tool for the estimation of the error in arbitrary quantities of interest (linear functional outputs). Applications in both 2D and 3D are presented.Peer ReviewedPostprint (author’s final draft

StereoSpike: Depth Learning with a Spiking Neural Network

Depth estimation is an important computer vision task, useful in particular for navigation in autonomous vehicles, or for object manipulation in robotics. Here we solved it using an end-to-end neuromorphic approach, combining two event-based cameras and a Spiking Neural Network (SNN) with a slightly modified U-Net-like encoder-decoder architecture, that we named StereoSpike. More specifically, we used the Multi Vehicle Stereo Event Camera Dataset (MVSEC). It provides a depth ground-truth, which was used to train StereoSpike in a supervised manner, using surrogate gradient descent. We propose a novel readout paradigm to obtain a dense analog prediction -- the depth of each pixel -- from the spikes of the decoder. We demonstrate that this architecture generalizes very well, even better than its non-spiking counterparts, leading to state-of-the-art test accuracy. To the best of our knowledge, it is the first time that such a large-scale regression problem is solved by a fully spiking network. Finally, we show that low firing rates (<10%) can be obtained via regularization, with a minimal cost in accuracy. This means that StereoSpike could be efficiently implemented on neuromorphic chips, opening the door for low power and real time embedded systems

RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions

Depth estimation from monocular images is pivotal for real-world visual perception systems. While current learning-based depth estimation models train and test on meticulously curated data, they often overlook out-of-distribution (OoD) situations. Yet, in practical settings -- especially safety-critical ones like autonomous driving -- common corruptions can arise. Addressing this oversight, we introduce a comprehensive robustness test suite, RoboDepth, encompassing 18 corruptions spanning three categories: i) weather and lighting conditions; ii) sensor failures and movement; and iii) data processing anomalies. We subsequently benchmark 42 depth estimation models across indoor and outdoor scenes to assess their resilience to these corruptions. Our findings underscore that, in the absence of a dedicated robustness evaluation framework, many leading depth estimation models may be susceptible to typical corruptions. We delve into design considerations for crafting more robust depth estimation models, touching upon pre-training, augmentation, modality, model capacity, and learning paradigms. We anticipate our benchmark will establish a foundational platform for advancing robust OoD depth estimation.Comment: NeurIPS 2023; 45 pages, 25 figures, 13 tables; Code at https://github.com/ldkong1205/RoboDept

tRNS boosts visual perceptual learning in participants with bilateral macular degeneration

Perceptual learning (PL) has shown promise in enhancing residual visual functions in patients with age-related macular degeneration (MD), however it requires prolonged training and evidence of generalization to untrained visual functions is limited. Recent studies suggest that combining transcranial random noise stimulation (tRNS) with perceptual learning produces faster and larger visual improvements in participants with normal vision. Thus, this approach might hold the key to improve PL effects in MD. To test this, we trained two groups of MD participants on a contrast detection task with (n = 5) or without (n = 7) concomitant occipital tRNS. The training consisted of a lateral masking paradigm in which the participant had to detect a central low contrast Gabor target. Transfer tasks, including contrast sensitivity, near and far visual acuity, and visual crowding, were measured at pre-, mid and post-tests. Combining tRNS and perceptual learning led to greater improvements in the trained task, evidenced by a larger increment in contrast sensitivity and reduced inhibition at the shortest target to flankers’ distance. The overall amount of transfer was similar between the two groups. These results suggest that coupling tRNS and perceptual learning has promising potential applications as a clinical rehabilitation strategy to improve vision in MD patients

A Stochastic Multi-scale Approach for Numerical Modeling of Complex Materials - Application to Uniaxial Cyclic Response of Concrete

In complex materials, numerous intertwined phenomena underlie the overall response at macroscale. These phenomena can pertain to different engineering fields (mechanical , chemical, electrical), occur at different scales, can appear as uncertain, and are nonlinear. Interacting with complex materials thus calls for developing nonlinear computational approaches where multi-scale techniques that grasp key phenomena at the relevant scale need to be mingled with stochastic methods accounting for uncertainties. In this chapter, we develop such a computational approach for modeling the mechanical response of a representative volume of concrete in uniaxial cyclic loading. A mesoscale is defined such that it represents an equivalent heterogeneous medium: nonlinear local response is modeled in the framework of Thermodynamics with Internal Variables; spatial variability of the local response is represented by correlated random vector fields generated with the Spectral Representation Method. Macroscale response is recovered through standard ho-mogenization procedure from Micromechanics and shows salient features of the uniaxial cyclic response of concrete that are not explicitly modeled at mesoscale.Comment: Computational Methods for Solids and Fluids, 41, Springer International Publishing, pp.123-160, 2016, Computational Methods in Applied Sciences, 978-3-319-27994-

Charge-radius change and nuclear moments in the heavy tin isotopes from laser spectroscopy: Charge radius of 132^{132}Sn

NESTER ACCLaser spectroscopy measurements have been carried out on the neutron-rich tin isotopes with the COMPLIS experimental setup. Using the $5s^25p^2$ $^3P_0 \rightarrow 5s^25_p6s$ $^3P_1$ optical transition, hyperfine spectra of $^{126-132}$Sn and $^{125,127,129-131}Sn^m$ were recorded for the first time. The nuclear moments and the mean square charge radius variation ($\delta) were extracted. From the quadrupole moment values, these nuclei appear to be spherical. The magnetic moments measured are thus compared with those predicted by spherical basis approaches. From the measured$\delta, the absolute charge radii of these isotopes were deduced in particular that of the doubly magic $^{132}$Sn nucleus. The comparison of the results with several mean-field-type calculations have shown that dynamical effects play an important role in the tin isotopes

Integrative analysis of a phase 2 trial combining lenalidomide with CHOP in angioimmunoblastic T-cell lymphoma.

Angioimmunoblastic T-cell lymphoma (AITL) is a frequent T-cell lymphoma in the elderly population that has a poor prognosis when treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) therapy. Lenalidomide, which has been safely combined with CHOP to treat B-cell lymphoma, has shown efficacy as a single agent in AITL treatment. We performed a multicentric phase 2 trial combining 25 mg lenalidomide daily for 14 days per cycle with 8 cycles of CHOP21 in previously untreated AITL patients aged 60 to 80 years. The primary objective was the complete metabolic response (CMR) rate at the end of treatment. Seventy-eight of the 80 patients enrolled were included in the efficacy and safety analysis. CMR was achieved in 32 (41%; 95% confidence interval [CI], 30%-52.7%) patients, which was below the prespecified CMR rate of 55% defined as success in the study. The 2-year progression-free survival (PFS) was 42.1% (95% CI, 30.9%-52.8%), and the 2-year overall survival was 59.2% (95% CI, 47.3%-69.3%). The most common toxicities were hematologic and led to treatment discontinuation in 15% of patients. This large prospective and uniform series of AITL treatment data was used to perform an integrative analysis of clinical, pathologic, biologic, and molecular data. TET2, RHOA, DNMT3A, and IDH2 mutations were present in 78%, 54%, 32%, and 22% of patients, respectively. IDH2 mutations were associated with distinct pathologic and clinical features and DNMT3A was associated with shorter PFS. In conclusion, the combination of lenalidomide and CHOP did not improve the CMR in AITL patients. This trial clarified the clinical impact of recurrent mutations in AITL. This trial was registered at www.clincialtrials.gov as #NCT01553786

Gaze-grasp coordination in obstacle avoidance: differences between binocular and monocular viewing

Most adults can skillfully avoid potential obstacles when acting in everyday cluttered scenes. We examined how gaze and hand movements are normally coordinated for obstacle avoidance and whether these are altered when binocular depth information is unavailable. Visual fixations and hand movement kinematics were simultaneously recorded, while 13 right-handed subjects reached-to-precision grasp a cylindrical household object presented alone or with a potential obstacle (wine glass) located to its left (thumb's grasp side), right or just behind it (both closer to the finger's grasp side) using binocular or monocular vision. Gaze and hand movement strategies differed significantly by view and obstacle location. With binocular vision, initial fixations were near the target's centre of mass (COM) around the time of hand movement onset, but usually shifted to end just above the thumb's grasp site at initial object contact, this mainly being made by the thumb, consistent with selecting this digit for guiding the grasp. This strategy was associated with faster binocular hand movements and improved end-point grip precision across all trials than with monocular viewing, during which subjects usually continued to fixate the target closer to its COM despite a similar prevalence of thumb-first contacts. While subjects looked directly at the obstacle at each location on a minority of trials and their overall fixations on the target were somewhat biased towards the grasp side nearest to it, these gaze behaviours were particularly marked on monocular vision-obstacle behind trials which also commonly ended in finger-first contact. Subjects avoided colliding with the wine glass under both views when on the right (finger side) of the workspace by producing slower and straighter reaches, with this and the behind obstacle location also resulting in 'safer' (i.e. narrower) peak grip apertures and longer deceleration times than when the goal object was alone or the obstacle was on its thumb side. But monocular reach paths were more variable and deceleration times were selectively prolonged on finger-side and behind obstacle trials, with this latter condition further resulting in selectively increased grip closure times and corrections. Binocular vision thus provided added advantages for collision avoidance, known to require intact dorsal cortical stream processing mechanisms, particularly when the target of the grasp and potential obstacle to it were fairly closely separated in depth. Different accounts of the altered monocular gaze behaviour converged on the conclusion that additional perceptual and/or attentional resources are likely engaged compared to when continuous binocular depth information is available. Implications for people lacking binocular stereopsis are briefly considered