Connecting people through physiosocial technology

Social connectedness is one of the most important predictors of health and well-being. The goal of this dissertation is to investigate technologies that can support social connectedness. Such technologies can build upon the notion that disclosing emotional information has a strong positive influence on social connectedness. As physiological signals are strongly related to emotions, they might provide a solid base for emotion communication technologies. Moreover, physiological signals are largely lacking in unmediated communication, have been used successfully by machines to recognize emotions, and can be measured relatively unobtrusively with wearable sensors. Therefore, this doctoral dissertation examines the following research question: How can we use physiological signals in affective technology to improve social connectedness? First, a series of experiments was conducted to investigate if computer interpretations of physiological signals can be used to automatically communicate emotions and improve social connectedness (Chapters 2 and 3). The results of these experiments showed that computers can be more accurate at recognizing emotions than humans are. Physiological signals turned out to be the most effective information source for machine emotion recognition. One advantage of machine based emotion recognition for communication technology may be the increase in the rate at which emotions can be communicated. As expected, experiments showed that increases in the number of communicated emotions increased feelings of closeness between interacting people. Nonetheless, these effects on feelings of closeness are limited if users attribute the cause of the increases in communicated emotions to the technology and not to their interaction partner. Therefore, I discuss several possibilities to incorporate emotion recognition technologies in applications in such a way that users attribute the communication to their interaction partner. Instead of using machines to interpret physiological signals, the signals can also be represented to a user directly. This way, the interpretation of the signal is left to be done by the user. To explore this, I conducted several studies that employed heartbeat representations as a direct physiological communication signal. These studies showed that people can interpret such signals in terms of emotions (Chapter 4) and that perceiving someone's heartbeat increases feelings of closeness between the perceiver and sender of the signal (Chapter 5). Finally, we used a field study (Chapter 6) to investigate the potential of heartbeat communication mechanisms in practice. This again confirmed that heartbeat can provide an intimate connection to another person, showing the potential for communicating physiological signals directly to improve connectedness. The last part of the dissertation builds upon the notion that empathy has positive influences on social connectedness. Therefore, I developed a framework for empathic computing that employed automated empathy measurement based on physiological signals (Chapter 7). This framework was applied in a system that can train empathy (Chapter 8). The results showed that providing users frequent feedback about their physiological synchronization with others can help them to improve empathy as measured through self-report and physiological synchronization. In turn, this improves understanding of the other and helps people to signal validation and caring, which are types of communication that improve social connectedness. Taking the results presented in this dissertation together, I argue that physiological signals form a promising modality to apply in communication technology (Chapter 9). This dissertation provides a basis for future communication applications that aim to improve social connectedness

Role of low-ll component in deformed wave functions near the continuum threshold

The structure of deformed single-particle wave functions in the vicinity of zero energy limit is studied using a schematic model with a quadrupole deformed finite square-well potential. For this purpose, we expand the single-particle wave functions in multipoles and seek for the bound state and the Gamow resonance solutions. We find that, for the $K^{\pi}=0^{+}$ states, where $K$ is the $z$-component of the orbital angular momentum, the probability of each multipole components in the deformed wave function is connected between the negative energy and the positive energy regions asymptotically, although it has a discontinuity around the threshold. This implies that the $K^{\pi}=0^{+}$ resonant level exists physically unless the $l=0$ component is inherently large when extrapolated to the well bound region. The dependence of the multipole components on deformation is also discussed

Transformation of 1,1,1-trichloroethane in an anaerobic packed-bed reactor at various concentrations of 1,1,1-trichloroethane, acetate and sulfate

Biotransformation of 1,1,1-trichloroethane (CH3CCl3) was observed in an anaerobic packed-bed reactor under conditions of both sulfate reduction and methanogenesis. Acetate (1 mM) served as an electron donor. CH3CCl3 was completely converted up to the highest investigated concentration of 10 µM. 1,1-Dichloroethane and chloroethane were found to be the main transformation products. A fraction of the CH3CCl3 was completely dechlorinated via an unknown pathway. The rate of transformation and the transformation products formed depended on the concentrations of CH3CCl3, acetate and sulfate. With an increase in sulfate and CH3CCl3 concentrations and a decrease in acetate concentration, the degree of CH3CCl3 dechlorination decreased. Both packed-bed reactor studies and batch experiments with bromoethanesulfonic acid, an inhibitor of methanogenesis, demonstrated the involvement of methanogens in CH3CCl3 transformation. Batch experiments with molybdate showed that sulfate-reducing bacteria in the packed-bed reactor were also able to transform CH3CCl3. However, packed-bed reactor experiments indicated that sulfate reducers only had a minor contribution to the overall transformation in the packed-bed reactor.

A Prototype Sensor for Estimating Light Interception by Plants in a Greenhouse

Light interception is one of the most important factors for plant growth. The intercepted amount depends on the incoming radiation in the greenhouse and the percentage of interception by the crop and is directly related to the leaf area. Proper crop management requires the measurement of the most important growing factors. In case of application of crop growing models the simulation of the leaf area is one of the major uncertainties in the results of the models. Automatic calibration of the model based on radiation interception increases the accuracy of the model results. For the determination of the crop¿s light interception in a greenhouse, a radiation sensor was used which determines the ratio of the incoming radiation from the upper side and the reflection at a specific wavelength from the lower side. The ratio of reflected radiation versus intercepted radiation can be used to estimate light interception as well as leaf area. However, the measurement of this fraction can only be used after filtering out erroneous data due to technical errors, insufficient diffuseness, insufficient solar height, etc. This paper describes the boundary conditions to be taken into account for proper measurement of reflected radiation. Time series measurements of incoming, reflected and global radiation are used, to filter the data acquired by the sensor. The sensor functioned well during tests on a cucumber crop in a commercial greenhouse

Personalized Empathic Computing (PEC)

Until a decade ago, computers were only used by experts, for professional purposes solely. Nowadays, the personal computer (PC) is standard equipment in most western housekeepings and is used to gather information, play games, communicate, etc. In parallel, users' expectations increase and, consequently, PCs are more and more adapted to our needs. The next phase in PC evolution is Personalized Empathic Computing (PEC). When thinking of PEC, questions emerge such as: Who is the user and how to model his or her characteristics? In addition, both possibilities and constraints of technology have to be taken into account. To unravel human emotional state, psychophysiological techniques are employed. Audio and visual information processing is needed to handle the multimedia input. Virtual Reality can be employed to realize high level interaction between users and PEC systems. The realization of PEC requires the cooperation among a broad range of disciplines; e.g., psychology, physiology, computer science, agent technology, interface design, and multimedia analysis. All will be illustrated by running projects, industrial applications, and the latest scientific research. Both the strength and the limitations of current state-of-the-art techniques will be indicated. With that we will look forward, to the future, which is not that far away anymore ..

Regulation of Genetic and Other Health Information in a Comparative Perspective

FDR De bescherming van fundamentele rechten in een integrerend Europa ou

Identification of a Baeyer-Villiger monooxygenase sequence motif

Baeyer-Villiger monooxygenases (BVMOs) form a distinct class of flavoproteins that catalyze the insertion of an oxygen atom in a C-C bond using dioxygen and NAD(P)H. Using newly characterized BVMO sequences, we have uncovered a BVMO-identifying sequence motif: FXGXXXRXXXW(P/D). Studies with site-directed mutants of 4-hydroxyacetophenone monooxygenase from Pseudomonas fluorescens ACB suggest that this fingerprint sequence is critically involved in catalysis. Further sequence analysis showed that the BVMOs belong to a novel superfamily that comprises three known classes of FAD-dependent monooxygenases: the so-called flavin-containing monooxygenases (FMOs), the N-hydroxylating monooxygenases (NMOs), and the BVMOs. Interestingly, FMOs contain an almost identical sequence motif when compared to the BVMO sequences: FXGXXXHXXX(Y/F). Using these novel amino acid sequence fingerprints, BVMOs and FMOs can be readily identified in the protein sequence databank. (C) 2002 Federation of European Biochemical Societies. Published by Elsevier Science B.V. All rights reserved