Laser-induced thermoelastic effects can evoke tactile sensations

Humans process a plethora of sensory information that is provided by various entities in the surrounding environment. Among the five major senses, technology for touch, haptics, is relatively young and has relatively limited applications largely due to its need for physical contact. In this article, we suggest a new way for non-contact haptic stimulation that uses laser, which has potential advantages such as mid-air stimulation, high spatial precision, and long working distance. We demonstrate such tactile stimulation can be enabled by laser-induced thermoelastic effects by means of physical and perceptual studies, as well as simulations. In the physical study, the mechanical effect of laser on a human skin sample is detected using low-power radiation in accordance with safety guidelines. Limited increases (< similar to 2.5 degrees C) in temperature at the surface of the skin, examined by both thermal camera and the Monte Carlo simulation, indicate that laser does not evoke heat-induced nociceptive sensation. In the human EEG study, brain responses to both mechanical and laser stimulation are consistent, along with subjective reports of the non-nociceptive sensation of laser stimuli.close1

Computer supported argument maps as a policy memory

This paper investigates to what extent Computer Supported Argument Visualisation can be designed to encourage debate and deliberation by citizens on public issues. Such argument maps use icons and arrows to represent the structure of a series of related viewpoints, reducing the amount of text necessary to convey the ideas, thereby clarifying the issue under consideration. Argument maps have the potential to provide a readily accessible medium by which citizens can follow and join in public debates on policy issues. In this paper we describe our approach, type of maps we have chosen to use and then demonstrate the potential of a collection of maps to form a ‘policy memory’ to support policy development. Our case study is the development of the ‘Smoking in Public Places’ policy in the Scottish Parliament. Our overall aim is to engage citizens in democratic decision-making leading to better policy-making and a more engaged citizenry

Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations.

Many closed-form analytical models have been proposed to relate the diffusion-weighted magnetic resonance imaging (DW-MRI) signal to microstructural features of white matter tissues. These models generally make assumptions about the tissue and the diffusion processes which often depart from the biophysical reality, limiting their reliability and interpretability in practice. Monte Carlo simulations of the random walk of water molecules are widely recognized to provide near groundtruth for DW-MRI signals. However, they have mostly been limited to the validation of simpler models rather than used for the estimation of microstructural properties. This work proposes a general framework which leverages Monte Carlo simulations for the estimation of physically interpretable microstructural parameters, both in single and in crossing fascicles of axons. Monte Carlo simulations of DW-MRI signals, or fingerprints, are pre-computed for a large collection of microstructural configurations. At every voxel, the microstructural parameters are estimated by optimizing a sparse combination of these fingerprints. Extensive synthetic experiments showed that our approach achieves accurate and robust estimates in the presence of noise and uncertainties over fixed or input parameters. In an in vivo rat model of spinal cord injury, our approach provided microstructural parameters that showed better correspondence with histology than five closed-form models of the diffusion signal: MMWMD, NODDI, DIAMOND, WMTI and MAPL. On whole-brain in vivo data from the human connectome project (HCP), our method exhibited spatial distributions of apparent axonal radius and axonal density indices in keeping with ex vivo studies. This work paves the way for microstructure fingerprinting with Monte Carlo simulations used directly at the modeling stage and not only as a validation tool