Inhomogeneous Point-Processes to Instantaneously Assess Affective Haptic Perception through Heartbeat Dynamics Information

This study proposes the application of a comprehensive signal processing framework, based on inhomogeneous point-process models of heartbeat dynamics, to instantaneously assess affective haptic perception using electrocardiogram-derived information exclusively. The framework relies on inverse-Gaussian point-processes with Laguerre expansion of the nonlinear Wiener-Volterra kernels, accounting for the long-term information given by the past heartbeat events. Up to cubic-order nonlinearities allow for an instantaneous estimation of the dynamic spectrum and bispectrum of the considered cardiovascular dynamics, as well as for instantaneous measures of complexity, through Lyapunov exponents and entropy. Short-term caress-like stimuli were administered for 4.3?25?seconds on the forearms of 32 healthy volunteers (16 females) through a wearable haptic device, by selectively superimposing two levels of force, 2?N and 6?N, and two levels of velocity, 9.4?mm/s and 65?mm/s. Results demonstrated that our instantaneous linear and nonlinear features were able to finely characterize the affective haptic perception, with a recognition accuracy of 69.79% along the force dimension, and 81.25% along the velocity dimension

Dissociation of virtual photons in events with a leading proton at HERA

The ZEUS detector has been used to study dissociation of virtual photons in events with a leading proton, gamma^* p -> X p, in e^+p collisions at HERA. The data cover photon virtualities in two ranges, 0.03<Q^2<0.60 GeV^2 and 2<Q^2<100 GeV^2, with M_X>1.5 GeV, where M_X is the mass of the hadronic final state, X. Events were required to have a leading proton, detected in the ZEUS leading proton spectrometer, carrying at least 90% of the incoming proton energy. The cross section is presented as a function of t, the squared four-momentum transfer at the proton vertex, Phi, the azimuthal angle between the positron scattering plane and the proton scattering plane, and Q^2. The data are presented in terms of the diffractive structure function, F_2^D(3). A next-to-leading-order QCD fit to the higher-Q^2 data set and to previously published diffractive charm production data is presented

Railway-induced ground vibrations – a review of vehicle effects

This paper is a review of the effect of vehicle characteristics on ground- and track borne-vibrations from railways. It combines traditional theory with modern thinking and uses a range of numerical analysis and experimental results to provide a broad analysis of the subject area. First, the effect of different train types on vibration propagation is investigated. Then, despite not being the focus of this work, numerical approaches to vibration propagation modelling within the track and soil are briefly touched upon. Next an in-depth discussion is presented related to the evolution of numerical models, with analysis of the suitability of various modelling approaches for analysing vehicle effects. The differences between quasi-static and dynamic characteristics are also discussed with insights into defects such as wheel/rail irregularities. Additionally, as an appendix, a modest database of train types are presented along with detailed information related to their physical attributes. It is hoped that this information may provide assistance to future researchers attempting to simulate railway vehicle vibrations. It is concluded that train type and the contact conditions at the wheel/rail interface can be influential in the generation of vibration. Therefore, where possible, when using numerical approach, the vehicle should be modelled in detail. Additionally, it was found that there are a wide variety of modelling approaches capable of simulating train types effects. If non-linear behaviour needs to be included in the model, then time domain simulations are preferable, however if the system can be assumed linear then frequency domain simulations are suitable due to their reduced computational demand

Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis

Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson?s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity

Correlation between Ionic Liquid Cytotoxicity and Liposome-Ionic Liquid Interactions

This study aims at extending the understanding of the toxicity mechanism of ionic liquids (ILs) using various analytical methods and cytotoxicity assays. The cytotoxicity of eight ILs and one zwitterionic compound was determined using mammalian and bacterial cells. The time dependency of the IL toxicity was assessed using human corneal epithelial cells. Hemolysis was performed using human red blood cells and the results were compared with destabilization data of synthetic liposomes upon addition of ILs. The effect of the ILs on the size and zeta potential of liposomes revealed information on changes in the lipid bilayer. Differential scanning calorimetry was used to study the penetration of the ILs into the lipid bilayer. Pulsed field gradient nuclear magnetic resonance spectroscopy was used to determine whether the ILs occurred as unimers, micelles, or if they were bound to liposomes. The results show that the investigated ILs can be divided into three groups based on the cytotoxicity mechanism: cell wall disrupting ILs, ILs exerting toxicity through both cell wall penetration and metabolic alteration, and ILs affecting solely on cell metabolism.Peer reviewe

Engineering context-aware systems and applications:A survey

Context-awareness is an essential component of systems developed in areas like Intelligent Environments, Pervasive & Ubiquitous Computing and Ambient Intelligence. In these emerging fields, there is a need for computerized systems to have a higher understanding of the situations in which to provide services or functionalities, to adapt accordingly. The literature shows that researchers modify existing engineering methods in order to better fit the needs of context-aware computing. These efforts are typically disconnected from each other and generally focus on solving specific development issues. We encourage the creation of a more holistic and unified engineering process that is tailored for the demands of these systems. For this purpose, we study the state-of-the-art in the development of context-aware systems, focusing on: (A) Methodologies for developing context-aware systems, analyzing the reasons behind their lack of adoption and features that the community wish they can use; (B) Context-aware system engineering challenges and techniques applied during the most common development stages; (C) Context-aware systems conceptualization