Ionization of clusters in strong X-ray laser pulses

The effect of intense X-ray laser interaction on argon clusters is studied theoretically with a mixed quantum/classical approach. In comparison to a single atom we find that ionization of the cluster is suppressed, which is in striking contrast to the observed behavior of rare-gas clusters in intense optical laser pulses. We have identified two effects responsible for this phenomenon: A high space charge of the cluster in combination with a small quiver amplitude and delocalization of electrons in the cluster. We elucidate their impact for different field strengths and cluster sizes.Comment: 4 pages, 4 figure

Buttons, Handles, and Keys: Advances in Continuous-Control Keyboard Instruments

This is the peer reviewed version of the following article: Buttons, Handles, and Keys: Advances in Continuous-Control Keyboard Instruments, which has been published in final form at http://dx.doi.org/10.1162/COMJ_a_00297. This article may be used for non-commercial purposes in accordance with MIT Press Journal's Terms and Conditions for Self-Archiving. © 2015, MIT Press Journal

Light scattering and phase behavior of Lysozyme-PEG mixtures

Measurements of liquid-liquid phase transition temperatures (cloud points) of mixtures of a protein (lysozyme) and a polymer, poly(ethylene glycol) (PEG) show that the addition of low molecular weight PEG stabilizes the mixture whereas high molecular weight PEG was destabilizing. We demonstrate that this behavior is inconsistent with an entropic depletion interaction between lysozyme and PEG and suggest that an energetic attraction between lysozyme and PEG is responsible. In order to independently characterize the lysozyme/PEG interactions, light scattering experiments on the same mixtures were performed to measure second and third virial coefficients. These measurements indicate that PEG induces repulsion between lysozyme molecules, contrary to the depletion prediction. Furthermore, it is shown that third virial terms must be included in the mixture's free energy in order to qualitatively capture our cloud point and light scattering data. The light scattering results were consistent with the cloud point measurements and indicate that attractions do exist between lysozyme and PEG.Comment: 5 pages, 2 figures, 1 tabl

Computing ecosystems: neural networks and embedded hardware platforms

Presented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsPresented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsPresented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsPresented at the CHI2023 Workshop [WS2] - Beyond Prototyping Boards: Future Paradigms for Electronics ToolkitsEmbedded hardware platforms such as single-board computers (e.g., Raspberry Pi, Bela) or microcontrollers (e.g., Teensy, Arduino Uno) offer an entry point for beginners into physical computing. However, deploying neural networks into these platforms is challenging for various reasons: It requires lower-level software development skills, as machine learning toolkits are typically not incorporated into these platforms. Besides, the long compilation times burden debugging and quick prototyping and experimentation. Due to the low-resource nature of embedded hardware platforms, neural networks are usually trained on a host machine, which involves a back-and-forth of data, platforms and programming languages. We inquire how these computing ecosystems might be designed to facilitate prototyping and experimentation and integrate into existing programming workflows

Asymmetric emission of high energy electrons in the two-dimensional hydrodynamic expansion of large xenon clusters irradiated by intense laser fields

Energy spectra and angular distributions have been measured of electrons that are emitted upon disassembly of $Xe_{150000}$ following irradiation by intense (10$^{15}-10^{16}$ W cm$^{-2}$) laser pulses whose durations are varied over the 100-2200 fs range. The cluster explosion dynamics occur in the hydrodynamic regime. Electron emission is found to be unexpectedly asymmetric and exhibits a resonance when the laser pulse duration is $\sim$1 ps. These results are rationalized by extending the hydrodynamic model to also take into account the force that the light field exerts on the polarization charge that is induced on surface of the cluster. We show that the magnitude of this electrostrictive force is comparable to those of Coulombic and the hydrodynamic forces, and it exhibits resonance behavior. Contrary to earlier understanding, we find that low-energy electrons are connected to the resonance in energy absorption by the cluster. The high-energy electrons seem to be produced by a mechanism that is not so strongly influenced by the resonance.Comment: 1 Revtex file, 8 figs. in eps forma

Microscopy with ultraviolet surface excitation for rapid slide-free histology.

Histologic examination of tissues is central to the diagnosis and management of neoplasms and many other diseases, and is a foundational technique for preclinical and basic research. However, commonly used bright-field microscopy requires prior preparation of micrometre-thick tissue sections mounted on glass slides, a process that can require hours or days, that contributes to cost, and that delays access to critical information. Here, we introduce a simple, non-destructive slide-free technique that within minutes provides high-resolution diagnostic histological images resembling those obtained from conventional haematoxylin-and-eosin-histology. The approach, which we named microscopy with ultraviolet surface excitation (MUSE), can also generate shape and colour-contrast information. MUSE relies on ~280-nm ultraviolet light to restrict the excitation of conventional fluorescent stains to tissue surfaces, and it has no significant effects on downstream molecular assays (including fluorescence in situ hybridization and RNA-seq). MUSE promises to improve the speed and efficiency of patient care in both state-of-the-art and low-resource settings, and to provide opportunities for rapid histology in research

Self-Sabotage Workshop: a starting point to unravel sabotaging of instruments as a design practice

Within the music improvisation and jazz scenes, playing a wrong note may be seen as a source of creativity and novelty, where an initially undesired factor (the mistaken note) invites the musician to leverage their skills to transform it into new musical material. How does this idea, however, translate into more experimental scenes like NIME, where control and virtuosity are not necessarily the performance's aim? Moreover, within NIME communities the addition of randomness or constraints to musical instruments is often an intended aesthetic decision rather than a source of mistakes. To explore this contrast, we invited four NIME practitioners to participate in the Self-Sabotage Workshop, where each practitioner had to build their own sabotaging elements for their musical instruments and to give a short demonstration with them. We gathered participants' impressions of self-sabotating in a focus group, inquiring about control and musicality, and also the strategies they developed for coping with the self-sabotaged instruments. We discuss the emergent ideas of planned and unplanned sabotaging, and we propose a starting point towards the idea of self-sabotaging as a continuous design and musical process where designers/musicians try to overcome barriers that they impose upon themselves

Pipeline for recording datasets and running neural networks on the Bela embedded hardware platform

Deploying deep learning models on embedded devices is an arduous task: oftentimes, there exist no platform-specific instructions, and compilation times can be considerably large due to the limited computational resources available on-device. Moreover, many music-making applications de- mand real-time inference. Embedded hardware platforms for audio, such as Bela, offer an entry point for beginners into physical audio computing; however, the need for cross- compilation environments and low-level software develop- ment tools for deploying embedded deep learning models imposes high entry barriers on non-expert users. We present a pipeline for deploying neural networks in the Bela embedded hardware platform. In our pipeline, we include a tool to record a multichannel dataset of sen- sor signals. Additionally, we provide a dockerised cross- compilation environment for faster compilation. With this pipeline, we aim to provide a template for programmers and makers to prototype and experiment with neural networks for real-time embedded musical applications