Efficient metallic spintronic emitters of ultrabroadband terahertz radiation

Terahertz electromagnetic radiation is extremely useful for numerous applications such as imaging and spectroscopy. Therefore, it is highly desirable to have an efficient table-top emitter covering the 1-to-30-THz window whilst being driven by a low-cost, low-power femtosecond laser oscillator. So far, all solid-state emitters solely exploit physics related to the electron charge and deliver emission spectra with substantial gaps. Here, we take advantage of the electron spin to realize a conceptually new terahertz source which relies on tailored fundamental spintronic and photonic phenomena in magnetic metal multilayers: ultrafast photo-induced spin currents, the inverse spin-Hall effect and a broadband Fabry-P\'erot resonance. Guided by an analytical model, such spintronic route offers unique possibilities for systematic optimization. We find that a 5.8-nm-thick W/CoFeB/Pt trilayer generates ultrashort pulses fully covering the 1-to-30-THz range. Our novel source outperforms laser-oscillator-driven emitters such as ZnTe(110) crystals in terms of bandwidth, terahertz-field amplitude, flexibility, scalability and cost.Comment: 18 pages, 10 figure

Surface Morphology and Electrical Resistivity in Polycrystalline Au/Cu/Si(100) System

This work describes the analysis of morphology and electrical resistivity (ρ) obtained in the Au/Cu/Si system. The Au/Cu bilayers were deposited by thermal evaporation technique with thicknesses from 50 to 250 nm on SiOx/Si(100) substrates. The Au : Cu concentration ratio of the samples was of 25 : 75 at%. The bilayers were annealed into a vacuum oven with argon atmosphere at 660 K for one hour. The crystalline structures of AuCu and CuSi alloys were confirmed by X-ray diffraction analysis. The scanning electron microscopy (SEM), the atomic force microscopy (AFM), and the energy dispersive spectroscopy (EDS) were used to study the morphology, final thickness, and the atomic concentration of the alloys formed, respectively. The four-point probe technique was used to measure the electrical resistivity (ρ) in the prepared alloys as a function of thickness. The ρ value was measured and it was numerically compared with the Fuchs–Sondheimer (FS) and the Mayadas–Shatzkes (MS) models of resistivity. Results show values of electrical resistivity between 0.9 and 1.9 μΩ-cm. These values are four times smaller than the values of the AuCu systems reported in literature

Investigating Students' Experiences with Collaboration Analytics for Remote Group Meetings.

Remote meetings have become the norm for most students learning synchronously at a distance during the ongoing coronavirus pandemic. This has motivated the use of artificial intelligence in education (AIED) solutions to support the teaching and learning practice in these settings. However, the use of such solutions requires new research particularly with regards to the human factors that ultimately shape the future design and implementations. In this paper, we build on the emerging literature on human-centred AIED and explore students’ experiences after interacting with a tool that monitors their collaboration in remote meetings (i.e., using Zoom) during 10 weeks. Using the social translucence framework, we probed into the feedback provided by twenty students regarding the design and implementation requirements of the system after their exposure to the tool in their course. The results revealed valuable insights in terms of visibility (what should be made visible to students via the system), awareness (how can this information increase students’ understanding of collaboration performance), and accountability (to what extent students take responsibility of changing their behaviours based on the system’s feedback); as well as the ethical and privacy aspects related to the use of collaboration analytics tools in remote meetings. This study provides key suggestions for the future design and implementations of AIED systems for remote meetings in educational settings

From laboratory manipulations to Earth system models: scaling calcification impacts of ocean acidification

The observed variation in the calcification responses of coccolithophores to changes in carbonate chemistry paints a highly incoherent picture, particularly for the most commonly cultured "species", <i>Emiliania huxleyi</i>. The disparity between magnitude and potentially even sign of the calcification change under simulated end-of-century ocean surface chemical changes (higher <i>p</i>CO<sub>2</sub>, lower pH and carbonate saturation), raises challenges to quantifying future carbon cycle impacts and feedbacks because it introduces significant uncertainty in parameterizations used for global models. Here we compile the results of coccolithophore carbonate chemistry manipulation experiments and review how ocean carbon cycle models have attempted to bridge the gap from experiments to global impacts. Although we can rule out methodological differences in how carbonate chemistry is altered as introducing an experimental bias, the absence of a consistent calcification response implies that model parameterizations based on small and differing subsets of experimental observations will lead to varying estimates for the global carbon cycle impacts of ocean acidification. We highlight two pertinent observations that might help: (1) the degree of coccolith calcification varies substantially, both between species and within species across different genotypes, and (2) the calcification response across mesocosm and shipboard incubations has so-far been found to be relatively consistent. By analogy to descriptions of plankton growth rate vs. temperature, such as the "Eppley curve", which seek to encapsulate the net community response via progressive assemblage change rather than the response of any single species, we posit that progressive future ocean acidification may drive a transition in dominance from more to less heavily calcified coccolithophores. Assemblage shift may be more important to integrated community calcification response than species-specific response, highlighting the importance of whole community manipulation experiments to models in the absence of a complete physiological understanding of the underlying calcification process. However, on a century time-scale, regardless of the parameterization adopted, the atmospheric <i>p</i>CO<sub>2</sub> impact of ocean acidification is minor compared to other global carbon cycle feedbacks

Comparative Modelling of the Spectra of Cool Giants

Our ability to extract information from the spectra of stars depends on reliable models of stellar atmospheres and appropriate techniques for spectral synthesis. Various model codes and strategies for the analysis of stellar spectra are available today. We aim to compare the results of deriving stellar parameters using different atmosphere models and different analysis strategies. The focus is set on high-resolution spectroscopy of cool giant stars. Spectra representing four cool giant stars were made available to various groups and individuals working in the area of spectral synthesis, asking them to derive stellar parameters from the data provided. The results were discussed at a workshop in Vienna in 2010. Most of the major codes currently used in the astronomical community for analyses of stellar spectra were included in this experiment. We present the results from the different groups, as well as an additional experiment comparing the synthetic spectra produced by various codes for a given set of stellar parameters. Similarities and differences of the results are discussed. Several valid approaches to analyze a given spectrum of a star result in quite a wide range of solutions. The main causes for the differences in parameters derived by different groups seem to lie in the physical input data and in the details of the analysis method. This clearly shows how far from a definitive abundance analysis we still are.Comment: accepted for publication in A&A. This version includes also the online tables. Reference spectra will later be available via the CD

What does touch tell us about emotions in touchscreen-based gameplay?

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ACM. It is posted here by permission of ACM for your personal use. Not for redistribution.Nowadays, more and more people play games on touch-screen mobile phones. This phenomenon raises a very interesting question: does touch behaviour reflect the player’s emotional state? If possible, this would not only be a valuable evaluation indicator for game designers, but also for real-time personalization of the game experience. Psychology studies on acted touch behaviour show the existence of discriminative affective profiles. In this paper, finger-stroke features during gameplay on an iPod were extracted and their discriminative power analysed. Based on touch-behaviour, machine learning algorithms were used to build systems for automatically discriminating between four emotional states (Excited, Relaxed, Frustrated, Bored), two levels of arousal and two levels of valence. The results were very interesting reaching between 69% and 77% of correct discrimination between the four emotional states. Higher results (~89%) were obtained for discriminating between two levels of arousal and two levels of valence

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selection method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.Comment: Final version for proceedings of ECML/PKDD 201