We report on in vitro wound-healing and cell-growth studies under the influence of radio-frequency (rf) cell stimuli. These stimuli are supplied either by piezoactive surface acoustic waves (SAWs) or by microelectrode-generated electric fields, both at frequencies around 100 MHz. Employing live-cell imaging, we studied the time- and power-dependent healing of artificial wounds on a piezoelectric chip for different cell lines. If the cell stimulation is mediated by piezomechanical SAWs, we observe a pronounced, significant maximum of the cell-growth rate at a specific SAW amplitude, resulting in an increase of the wound-healing speed of up to 135 ± 85% as compared to an internal reference. In contrast, cells being stimulated only by electrical fields of the same magnitude as the ones exposed to SAWs exhibit no significant effect. In this study, we investigate this effect for different wavelengths, amplitude modulation of the applied electrical rf signal, and different wave modes. Furthermore, to obtain insight into the biological response to the stimulus, we also determined both the cell-proliferation rate and the cellular stress levels. While the proliferation rate is significantly increased for a wide power range, cell stress remains low and within the normal range. Our findings demonstrate that SAW-based vibrational cell stimulation bears the potential for an alternative method to conventional ultrasound treatment, overcoming some of its limitations.

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We investigate investment flows into more than 5,300 social trading portfolios that are issued as structured products and are tradable at a regular exchange. We find that investment flows chase past performance. However, in contrast to mutual fund flows, the flow-performance relation exists nearly exclusively for the best performing social trading portfolios. Flows follow raw returns rather than factor model alphas. Additionally, flows are highly persistent. Finally, social trading portfolios with higher visibility on the web page of the social trading platform as well as traders communicating actively to investors via public comments attract higher inflows.

One of the most important, still unsolved problems in computer graphics is the generation of predictive imagery, i.e., images that represent perfect renditions of reality. Such perfect images are required in application areas like Virtual Prototyping for making reliable decisions in the costly design development of novel products like cars and airplanes. Recently, measured material properties received significant attention since they enable generation of highly accurate images that appear to be predictive at a first glance.In this work we investigate the degree of realism that can be achieved using measured bidirectional texture functions (BTFs) by comparing photographs and rendered images at two scales. To analyze the realism of rendered images at a coarse scale, we compare the light distribution resulting from standard materials to the one from measured BTFs by automatic procedures. At a fine scale, accurate reproduction of material structures is checked by a psychophysical study. Our results show that measured BTFs lead to much more accurate results than standard materials at both scales.