Yeah, Right, Uh-Huh: A Deep Learning Backchannel Predictor

Using supporting backchannel (BC) cues can make human-computer interaction more social. BCs provide a feedback from the listener to the speaker indicating to the speaker that he is still listened to. BCs can be expressed in different ways, depending on the modality of the interaction, for example as gestures or acoustic cues. In this work, we only considered acoustic cues. We are proposing an approach towards detecting BC opportunities based on acoustic input features like power and pitch. While other works in the field rely on the use of a hand-written rule set or specialized features, we made use of artificial neural networks. They are capable of deriving higher order features from input features themselves. In our setup, we first used a fully connected feed-forward network to establish an updated baseline in comparison to our previously proposed setup. We also extended this setup by the use of Long Short-Term Memory (LSTM) networks which have shown to outperform feed-forward based setups on various tasks. Our best system achieved an F1-Score of 0.37 using power and pitch features. Adding linguistic information using word2vec, the score increased to 0.39

Recurrent Selection for Transgene Activity Levels in Maize Results in Proxy Selection for a Native Gene with the Same Promoter

High activity levels of a transgene can be very useful, making a transgene easier to evaluate for safety and efficacy. High activity levels can also increase the economic benefit of the production of high value proteins in transgenic plants. The goal of this research is to determine if recurrent selection for activity of a transgene will result in higher activity, and if selection for activity of a transgene controlled by a native promoter will also increase protein levels of the native gene with the same promoter. To accomplish this goal we used transgenic maize containing a construct encoding green fluorescent protein controlled by the promoter for the maize endosperm-specific 27kDa gamma zein seed storage protein. We carried out recurrent selection for fluorescence intensity in two breeding populations. After three generations of selection, both selected populations were significantly more fluorescent and had significantly higher levels of 27kDa gamma zein than the unselected control populations. These higher levels of the 27kDa gamma zein occurred independently of the presence of the transgene. The results show that recurrent selection can be used to increase activity of a transgene and that selection for a transgene controlled by a native promoter can increase protein levels of the native gene with the same promoter via proxy selection. Moreover, the increase in native gene protein level is maintained in the absence of the transgene, demonstrating that proxy selection can be used to produce non-transgenic plants with desired changes in gene expression

An optimal linear solver for the Jacobian system of the extreme type-II Ginzburg--Landau problem

This paper considers the extreme type-II Ginzburg--Landau equations, a nonlinear PDE model for describing the states of a wide range of superconductors. Based on properties of the Jacobian operator and an AMG strategy, a preconditioned Newton--Krylov method is constructed. After a finite-volume-type discretization, numerical experiments are done for representative two- and three-dimensional domains. Strong numerical evidence is provided that the number of Krylov iterations is independent of the dimension $n$ of the solution space, yielding an overall solver complexity of O(n)

Generalized four-point characterization method for resistive and capacitive contacts

In this paper, a four-point characterization method is developed for resistive samples connected to either resistive or capacitive contacts. Provided the circuit equivalent of the complete measurement system is known including coaxial cable and connector capacitances as well as source output and amplifier input impedances, a frequency range and capacitive scaling factor can be determined, whereby four-point characterization can be performed. The technique is demonstrated with a discrete element test sample over a wide frequency range using lock-in measurement techniques from 1 Hz - 100 kHz. The data fit well with a circuit simulation of the entire measurement system. A high impedance preamplifier input stage gives best results, since lock-in input impedances may differ from manufacturer specifications. The analysis presented here establishes the utility of capacitive contacts for four-point characterizations at low frequency.Comment: 21 pages, 10 figure

A new pathway for heterogenization of molecular catalysts by non-covalent interactions with carbon nanoreactors

A novel approach to heterogenisation of catalytic molecules is demonstrated using the nanoscale graphitic step-edges inside hollow graphitised carbon nanofibres (GNFs). The presence of the fullerene C60 moiety within a fullerene-salen CuII complex is essential for anchoring the catalyst within the GNF nanoreactor as demonstrated by comparison with the analogous catalyst complex without the fullerene group. The presence of the catalyst at the step-edges of the GNFs is confirmed by high resolution transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDX) with UV/Vis spectroscopy demonstrating only negligible (c.a. 3 %) desorption of the fullerene-salen CuII complex from the GNFs into solution under typical reaction conditions. The catalyst immobilised in GNFs shows good catalytic activity and selectivity towards styrene epoxidation, comparable to the analogous catalyst in solution. Moreover, the fullerene-salen CuII complex in GNFs demonstrates excellent stability and recyclability as it can be readily separated from the reaction mixture and employed in multiple reaction cycles with minimal loss of activity, which is highly advantageous compared to catalysts not stabilised by the graphitic step-edges that desorb rapidly from GNFs

Time series of high resolution spectra of SN 2014J observed with the TIGRE telescope

We present a time series of high resolution spectra of the Type Ia supernova 2014J, which exploded in the nearby galaxy M82. The spectra were obtained with the HEROS echelle spectrograph installed at the 1.2 m TIGRE telescope. We present a series of 33 spectra with a resolution of R = 20, 000, which covers the important bright phases in the evolution of SN 2014J during the period from January 24 to April 1 of 2014. The spectral evolution of SN 2014J is derived empirically. The expansion velocities of the Si II P-Cygni features were measured and show the expected decreasing behaviour, beginning with a high velocity of 14,000 km/s on January 24. The Ca II infrared triplet feature shows a high velocity component with expansion velocities of > 20, 000 km/s during the early evolution apart from the normal component showing similar velocities as Si II. Further broad P-Cygni profiles are exhibited by the principal lines of Ca II, Mg II and Fe II. The TIGRE SN 2014J spectra also resolve several very sharp Na I D doublet absorption components. Our analysis suggests interesting substructures in the interstellar medium of the host galaxy M82, as well as in our Milky Way, confirming other work on this SN. We were able to identify the interstellar absorption of M82 in the lines of Ca II H & K at 3933 and 3968 A as well as K I at 7664 and 7698 A. Furthermore, we confirm several Diffuse Interstellar Bands, at wavelengths of 6196, 6283, 6376, 6379 and 6613 A and give their measured equivalent widths.Comment: 11 pages, 10 figures, accepted for publication in MNRA

Deconvolution of complex G protein-coupled receptor signaling in live cells using dynamic mass redistribution measurements

Label-free biosensor technology based on dynamic mass redistribution (DMR) of cellular constituents promises to translate GPCR signaling into complex optical 'fingerprints' in real time in living cells. Here we present a strategy to map cellular mechanisms that define label-free responses, and we compare DMR technology with traditional second-messenger assays that are currently the state of the art in GPCR drug discovery. The holistic nature of DMR measurements enabled us to (i) probe GPCR functionality along all four G-protein signaling pathways, something presently beyond reach of most other assay platforms; (ii) dissect complex GPCR signaling patterns even in primary human cells with unprecedented accuracy; (iii) define heterotrimeric G proteins as triggers for the complex optical fingerprints; and (iv) disclose previously undetected features of GPCR behavior. Our results suggest that DMR technology will have a substantial impact on systems biology and systems pharmacology as well as for the discovery of drugs with novel mechanisms