Convolutional sparse coding for high dynamic range imaging

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low dynamic range (LDR) images, (ii) modifying existing hardware and capturing different exposures simultaneously with multiple sensors, or (iii) reconstructing a single image with spatially-varying pixel exposures. In this paper, we propose a novel algorithm to recover high-quality HDRI images from a single, coded exposure. The proposed reconstruction method builds on recently-introduced ideas of convolutional sparse coding (CSC); this paper demonstrates how to make CSC practical for HDR imaging. We demonstrate that the proposed algorithm achieves higher-quality reconstructions than alternative methods, we evaluate optical coding schemes, analyze algorithmic parameters, and build a prototype coded HDR camera that demonstrates the utility of convolutional sparse HDRI coding with a custom hardware platform

Evidence of Hepatitis E Virus (HEV) infection in human and pigs in Sardinia, Italy

Introduction. The aim of this study was to determine the seroprevalence of anti-HEV antibodies in humans sera and to study HEV prevalence in swine from different Sardinian farms, testing viral HEV-RNA in bile samples. Methods. In the first six months of 2008, 532 subjects of whom 402 blood donors and 130 workers at zoonotic risk, were enrolled. Anti-HEV were determined with an enzyme linked immunosorbent assay (ELISA). In positive subjects, RNA was extracted and tested by RT-Nested-PCR. From July 2006 to March 2007, 95 bile samples were collected from randomly selected pigs. RNA was extracted from 250 ?l of bile and tested by RT-Nested-PCR. Results. The overall prevalence of anti-HEV antibodies was 4.3%; 5.0% among blood donors and 2.3% among workers at zoonotic risk, with no statistically significant differences between sex, age classes and occupation. The search for HEV-RNA in the subjects positive for antibodies, gave negative results. HEV genome was detected in 6 of the 95 swine bile samples tested. Sequences were clustered within the genotype 3 and are edited on GenBank under accession number: from FJ850960 to FJ850962 and from FJ883000 to FJ883002. Discussion. The overall prevalence of anti-HEV shows that the virus circulates without giving origin to cases of acute hepatitis. The low prevalence value found in workers at zoonotic risk do not apparently support the hypothesis of professional risk. In this study, HEV-RNA was isolated from pigs in Sardinia for the first time confirming the role of swine as HEV reservoir and the possibility of virus transmission to humans

Nuclear neutron radius and weak mixing angle measurements from latest COHERENT CsI and atomic parity violation Cs data

The COHERENT collaboration observed coherent elastic neutrino nucleus scattering using a 14.6 kg cesium iodide (CsI) detector in 2017 and recently published the updated results before decommissioning the detector. Here, we present the legacy determination of the weak mixing angle and of the average neutron rms radius of Cs-133 and I-127 obtained with the full CsI dataset, also exploiting the combination with the atomic parity violation (APV) experimental result, that allows us to achieve a precision as low as similar to 4.5% and to disentangle the contributions of the Cs-133 and I-127 nuclei. Interestingly, we show that the COHERENT CsI data show a 6 sigma evidence of the nuclear structure suppression of the full coherence. Moreover, we derive a data-driven APV+COHERENT measurement of the low-energy weak mixing angle with a percent uncertainty, independent of the value of the average neutron rms radius of Cs-133 and I-127, that is allowed to vary freely in the fit. Additionally, we extensively discuss the impact of using two different determinations of the theoretical parity non-conserving amplitude in the APV fit. Our findings show that the particular choice can make a significant difference, up to 6.5% on R-n(Cs) and 11% on the weak mixing angle. Finally, in light of the recent announcement of a future deployment of a 10 kg and a similar to 700 kg cryogenic CsI detectors, we provide future prospects for these measurements, comparing them with other competitive experiments that are foreseen in the near future

ROBOT-MEDIATED AND CLINICAL SCALES EVALUATION AFTER UPPER LIMB BOTULINUM TOXIN TYPE A INJECTION IN CHILDREN WITH HEMIPLEGIA

Objective: The aim of this pilot study was to examine changes in different aspects of impairment, including spasticity in the upper limbs, of hemiplegic children following botulinum toxin type A intervention. Progress was assessed using standard clinical measurements and a robotic device. Design: Pre-post multiple baseline. Subjects: Six children with hemiplegia. Methods: Botulinium toxin type A injections were administered into the affected upper limb muscles. Outcomes were evaluated before and one month after the injection. Outcome assessments included: Melbourne Scale, Modified Ashworth Scale (MAS) and Passive Range of Motion. Furthermore, a robotic device was employed as an evaluation tool. Results: Patients treated with botulinum toxin type A had significantly greater reduction in spasticity (MAS, p < 0.01), which explains an improvement in upper limb function and quality movement measured with the Melbourne Scale (p < 0.01). These improvements are consistent with robot-based evaluation results that showed statistically significant changes (p < 0.01) following botulinum toxin type A injections. Conclusion: The upper limb performs a wide variety of movements. The multi-joint nature of the task during the robotmediated evaluation required active control of joint interaction forces. There was good correlation between clinical scales and robotic evaluation. Hence the robot-mediated assessment may be used as an additional tool to quantify the degree of motor improvement after botulinum toxin type A injections

A robot-aided visuomotor wrist training induces motor and proprioceptive learning that transfers to the untrained ipsilateral elbow

Background: Learning of a visuomotor task not only leads to changes in motor performance but also improves proprioceptive function of the trained joint/limb system. Such sensorimotor learning may show intra-joint transfer that is observable at a previously untrained degrees of freedom of the trained joint. Objective: Here, we examined if and to what extent such learning transfers to neighboring joints of the same limb and whether such transfer is observable in the motor as well as in the proprioceptive domain. Documenting such intra-limb transfer of sensorimotor learning holds promise for the neurorehabilitation of an impaired joint by training the neighboring joints. Methods: Using a robotic exoskeleton, 15 healthy young adults (18-35 years) underwent a visuomotor training that required them to make continuous, increasingly precise, small amplitude wrist movements. Wrist and elbow position sense just-noticeable-difference (JND) thresholds and spatial movement accuracy error (MAE) at wrist and elbow in an untrained pointing task were assessed before and immediately after, as well as 24&nbsp;h after training. Results: First, all participants showed evidence of proprioceptive and motor learning in both trained and untrained joints. The mean JND threshold decreased significantly by 30% in trained wrist (M: 1.26° to 0.88°) and by 35% in untrained elbow (M: 1.96° to 1.28°). Second, mean MAE in untrained pointing task reduced by 20% in trained wrist and the untrained elbow. Third, after 24&nbsp;h the gains in proprioceptive learning persisted at both joints, while transferred motor learning gains had decayed to such extent that they were no longer significant at the group level. Conclusion: Our findings document that a one-time sensorimotor training induces rapid learning gains in proprioceptive acuity and untrained sensorimotor performance at the practiced joint. Importantly, these gains transfer almost fully to the neighboring, proximal joint/limb system

ScanGAN360: a generative model of realistic scanpaths for 360 images

Understanding and modeling the dynamics of human gaze behavior in 360° environments is crucial for creating, improving, and developing emerging virtual reality applications. However, recruiting human observers and acquiring enough data to analyze their behavior when exploring virtual environments requires complex hardware and software setups, and can be time-consuming. Being able to generate virtual observers can help overcome this limitation, and thus stands as an open problem in this medium. Particularly, generative adversarial approaches could alleviate this challenge by generating a large number of scanpaths that reproduce human behavior when observing new scenes, essentially mimicking virtual observers. However, existing methods for scanpath generation do not adequately predict realistic scanpaths for 360° images. We present ScanGAN360, a new generative adversarial approach to address this problem. We propose a novel loss function based on dynamic time warping and tailor our network to the specifics of 360° images. The quality of our generated scanpaths outperforms competing approaches by a large margin, and is almost on par with the human baseline. ScanGAN360 allows fast simulation of large numbers of virtual observers, whose behavior mimics real users, enabling a better understanding of gaze behavior, facilitating experimentation, and aiding novel applications in virtual reality and beyond

An Application of IoT in a Drone Inspection Service for Environmental Control

This paper presents an exploratory activity with a drone inspection service for environmental control. The aim of the service is to provide technical support to decision-makers in environmental risk management. The proposed service uses IoT for the interaction between a mobile application, a Smart City platform, and an Unmanned Aircraft System (UAS). The mobile application allows the users to report risky situations, such as fire ignition, spills of pollutants in water, or illegal dumping; the user has only to specify the class of the event, while the geographical coordinates are automatically taken from device-integrated GPS. The message sent from the mobile application arrives to a Smart City platform, which shows all the received alerts on a 3D satellite map, to support decision-makers in choosing where a drone inspection is required. From the Smart City platform, the message is sent to the drone service operator; a CSV file defining the itinerary of the drone is automatically built and shown through the platform; the drone starts the mission providing a video, which is used by the decision-makers to understand whether the situation calls for immediate action. An experimental activity in an open field was carried out to validate the whole chain, from the alert to the drone mission, enriched by a Smart City platform to enable a decision-maker to better manage the situation