COVID-19 forecasting with deep learning: a distressing survey

<div>This document pretends to provide an overview about the lights and shadows on the latest trends in this specific area.</div><div>Unlike previously released literature reviews, that are providing a wide overview about any type of AI techniques applied to overall aspects of the pandemics, this document will focus specifically on the use of DL techniques applied to COVID-19 time series forecasting. The production in this field within the last months has become quite large.</div><div>After setting a group of quality criteria, related to problem definition, dataset manipulation, model identification and evaluation, 96 papers has been screened.</div><div>Most of the analysed papers did not meet the common quality standards of scientific work: none of them positively scored in all of the criteria, while only about one third scored positively in at least half of the defined criteria. The emergency character of this scientific production led to getting away from some of the basic requirements for quality scientific work.</div>

COVID-19 forecasting with deep learning: a distressing survey

<div>This document pretends to provide an overview about the lights and shadows on the latest trends in this specific area.</div><div>Unlike previously released literature reviews, that are providing a wide overview about any type of AI techniques applied to overall aspects of the pandemics, this document will focus specifically on the use of DL techniques applied to COVID-19 time series forecasting. The production in this field within the last months has become quite large.</div><div>After setting a group of quality criteria, related to problem definition, dataset manipulation, model identification and evaluation, 96 papers has been screened.</div><div>Most of the analysed papers did not meet the common quality standards of scientific work: none of them positively scored in all of the criteria, while only about one third scored positively in at least half of the defined criteria. The emergency character of this scientific production led to getting away from some of the basic requirements for quality scientific work.</div>

Complex manipulation with a simple robotic hand through contact breaking and caging

Humans use all surfaces of the hand for contact-rich manipulation. Robot hands, in contrast, typically use only the fingertips, which can limit dexterity. In this work, we leveraged a potential energy–based whole-hand manipulation model, which does not depend on contact wrench modeling like traditional approaches, to design a robotic manipulator. Inspired by robotic caging grasps and the high levels of dexterity observed in human manipulation, a metric was developed and used in conjunction with the manipulation model to design a two-fingered dexterous hand, the Model W. This was accomplished by simulating all planar finger topologies composed of open kinematic chains of up to three serial revolute and prismatic joints, forming symmetric two-fingered hands, and evaluating their performance according to the metric. We present the best design, an unconventional robot hand capable of performing continuous object reorientation, as well as repeatedly alternating between power and pinch grasps—two contact-rich skills that have often eluded robotic hands—and we experimentally characterize the hand’s manipulation capability. This hand realizes manipulation motions reminiscent of thumb–index finger manipulative movement in humans, and its topology provides the foundation for a general-purpose dexterous robot hand.

Manipulating placebo analgesia and nocebo hyperalgesia by changing brain excitability

Harnessing placebo and nocebo effects has significant implications for research and medical practice. Placebo analgesia and nocebo hyperalgesia, the most well-studied placebo and nocebo effects, are thought to initiate from the dorsal lateral prefrontal cortex (DLPFC) and then trigger the brain’s descending pain modulatory system and other pain regulation pathways. Combining repeated transcranial direct current stimulation (tDCS), an expectancy manipulation model, and functional MRI, we investigated the modulatory effects of anodal and cathodal tDCS at the right DLPFC on placebo analgesia and nocebo hyperalgesia using a randomized, double-blind and sham-controlled design. We found that compared with sham tDCS, active tDCS could 1) boost placebo and blunt nocebo effects and 2) modulate brain activity and connectivity associated with placebo analgesia and nocebo hyperalgesia. These results provide a basis for mechanistic manipulation of placebo and nocebo effects and may lead to improved clinical outcomes in medical practice.

A Two-Day Case Study: Comparison of Turbulence Data from an Unmanned Aircraft System with a Model Chain for Complex Terrain

The airborne measurement platform MASC-3 (Multi-Purpose Airborne Sensor Carrier) is used for measurements over a forested escarpment in the Swabian Alps to evaluate the wind field. Data from flight legs between 20 and 200 m above the ground on two consecutive days with uphill (westerly) flow in September 2018 are analyzed. In the lowest 140 m above the ground a speed-up is found with increased turbulence and changes in wind direction directly over the escarpment, whereas in the lowest 20 to 50 m above the ground a deceleration of the flow is measured. Additionally, simulation results from a numerical model chain based on the Weather Research and Forecasting (WRF) model and an OpenFOAM (Open Source Field Operation and Manipulation) model, developed for complex terrain, are compared to the data captured by MASC-3. The models and measurements compare well for the mean wind speed and inclination angle.

Zonation of Positively Buoyant Jets Interacting with the Water-Free Surface Quantified by Physical and Numerical Modelling

The evolution of positively buoyant jets was studied with non-intrusive techniques—Particle Image Velocimetry (PIV) and Laser Induce Fluorescence (LIF)—by analyzing four physical tests in their four characteristic zones: momentum dominant zone (jet-like), momentum to buoyancy transition zone (jet to plume), buoyancy dominant zone (plume-like), and lateral dispersion dominant zone. Four configurations were tested modifying the momentum and the buoyancy of the effluent through variations of flow discharge and the thermal gradient with the receiving water body, respectively. The physical model results were used to evaluate the performance of numerical models to describe such flows. Furthermore, a new method to delimitate the four characteristic zones of positively buoyant jets interacting with the water-free surface was proposed using the angle (α) shaped by the tangent of the centerline trajectory and the longitudinal axis. Physical model results showed that the dispersion of mass (concentrations) was always greater than the dispersion of energy (velocity) during the evolution of positively buoyant jets. The semiempirical models (CORJET and VISJET) underestimated the trajectory and overestimated the dilution of positively buoyant jets close to the impact zone with the water-free surface. The computational fluid dynamics (CFD) model (Open Field Operation And Manipulation model (OpenFOAM)) is able to reproduce the behavior of positively buoyant jets for all the proposed zones according to the physical results.