Diving with microparticles in acoustic fields

Sound can move particles. A good example of this phenomenon is the Chladni plate, in which an acoustic wave is induced in a metallic plate and particles migrate to the nodes of the acoustic wave. For several years, acoustophoresis has been used to manipulate microparticles in microscopic scales. In this fluid dynamics video, submitted to the 30th Annual Gallery of Fluid Motion, we show the basic mechanism of the technique and a simple way of visualize it. Since acoustophoretic phenomena is essentially a three-dimensional effect, we employ a simple technique to visualize the particles in 3D. The technique is called Astigmatism Particle Tracking Velocimetry and it consists in the use of cylindrical lenses to induce a deformation in the particle shape, which will be then correlated with its distance from the observer. With this method we are able to dive with the particles and observe in detail particle motion that would otherwise be missed. The technique not only permits visualization but also precise quantitative measurements that can be compared with theory and simulations.Comment: Fluid dynamics video for the 30th Annual Gallery of Fluid Motion, Entry #84160 65th Annual Meeting of the American Physical Society, Division of Fluid Dynamics San Diego, CA, Nov 201

Ultrasound-induced acoustophoretic motion of microparticles in three dimensions

We derive analytical expressions for the three-dimensional (3D) acoustophoretic motion of spherical microparticles in rectangular microchannels. The motion is generated by the acoustic radiation force and the acoustic streaming-induced drag force. In contrast to the classical theory of Rayleigh streaming in shallow, infinite, parallel-plate channels, our theory does include the effect of the microchannel side walls. The resulting predictions agree well with numerics and experimental measurements of the acoustophoretic motion of polystyrene spheres with nominal diameters of 0.537 um and 5.33 um. The 3D particle motion was recorded using astigmatism particle tracking velocimetry under controlled thermal and acoustic conditions in a long, straight, rectangular microchannel actuated in one of its transverse standing ultrasound-wave resonance modes with one or two half-wavelengths. The acoustic energy density is calibrated in situ based on measurements of the radiation dominated motion of large 5-um-diam particles, allowing for quantitative comparison between theoretical predictions and measurements of the streaming induced motion of small 0.5-um-diam particles.Comment: 13 pages, 8 figures, Revtex 4.

EUCLID: EdUcational curriculum for the usage of LInked data

Linked Data has established itself as an emerging standard for the publication of structured data over the Web, enjoying amazing growth in terms of the number of organizations committing to use its best practices and technologies for ex- posing and interlinking data sets for seamless exchange, integration, and reuse. More and more ICT ventures offer innovative data management services on top of Linked (Open) Data, creating a demand for data practitioners with a back- ground in semantic technologies. Ensuring the availability of such expertise will prove crucial if European businesses are to reap the full benefits of the advanced data management technology, and the know-how accumulated over the past years by researchers, technology enthusiasts and early adopters in various European countries. EUCLID had a major contribution to this goal by providing a com- prehensive educational curriculum, supported by multi-modal training materials and state-of-the-art eLearning distribution channels, tailored to the real needs of data practitioners. Building upon experience reports from over twenty Linked Data projects with over forty companies and public offices in more than ten countries, complemented by feedback from hundreds of training events, and an in-depth analysis of the community discourse through mailing lists, discussion forums, Twitter, and the blogosphere, the curriculum focuses on techniques and software to integrate, query, and visualize Linked Data, as core areas in which practitioners state to require most assistance. It is realized as a combination of multi-modal learning resources, including an iBook published on iTunes U, and evaluated through webinars, f2f training, and continuous community feedback. By providing these key knowledge-transfer components, EUCLID will not only promote the industrial uptake of Linked Data best practices and technologies, but, most importantly, will contribute to their further development and consol- idation, and support the sustainability of the community, all essential aspects given the rapid pace at which the field has recently advanced

Model Stitching: Looking For Functional Similarity Between Representations

Model stitching (Lenc & Vedaldi 2015) is a compelling methodology to compare different neural network representations, because it allows us to measure to what degree they may be interchanged. We expand on a previous work from Bansal, Nakkiran & Barak which used model stitching to compare representations of the same shapes learned by differently seeded and/or trained neural networks of the same architecture. Our contribution enables us to compare the representations learned by layers with different shapes from neural networks with different architectures. We subsequently reveal unexpected behavior of model stitching. Namely, we find that stitching, based on convolutions, for small ResNets, can reach high accuracy if those layers come later in the first (sender) network than in the second (receiver), even if those layers are far apart.Comment: 5 pages, 2 figure

Frequency-selective near-field enhancement of radiative heat transfer via photonic-crystal slabs: a general computational approach for arbitrary geometries and materials

We demonstrate the possibility of achieving enhanced frequency-selective near-field radiative heat transfer between patterned (photonic crystal) slabs at designable frequencies and separations, exploiting a general numerical approach for computing heat transfer in arbitrary geometries and materials based on the finite-difference time-domain method. Our simulations reveal a tradeoff between selectivity and near-field enhancement as the slab--slab separation decreases, with the patterned heat transfer eventually reducing to the unpatterned result multiplied by a fill factor (described by a standard proximity approximation). We also find that heat transfer can be further enhanced at selective frequencies when the slabs are brought into a glide-symmetric configuration, a consequence of the degeneracies associated with the non-symmorphic symmetry group

The Roco protein family:a functional perspective

In this review, we discuss the evolutionary, biochemical, and functional data available for members of the Roco protein family. They are characterized by having a conserved supradomain that contains a Ras-like GTPase domain, called Roc, and a characteristic COR (C-terminal of Roc) domain. A kinase domain and diverse regulatory and protein protein interaction domains are also often found in Roco proteins. First detected in the slime mold Dictyostelium discoideum, they have a broad phylogenetic range, being present in both prokaryotes and eukaryotes. The functions of these proteins are diverse. The best understood are Dictyostelium Rocos, which are involved in cell division, chemotaxis, and development. However, this family has received extensive attention because mutations in one of the human Roco genes (LRRK2) cause familial Parkinson disease. Other human Rocos are involved in epilepsy and cancer. Biochemical data suggest that Roc domains are capable of activating kinase domains intramolecularly. Interestingly, some of the dominant, disease-causing mutations in both the GTPase and kinase domains of LRRK2 increase kinase activity. Thus, Roco proteins may act as stand-alone transduction units, performing roles that were thought so far to require multiple proteins, as occur in the Ras transduction pathway

Autonomous Needle Navigation in Retinal Microsurgery: Evaluation in ex vivo Porcine Eyes

Important challenges in retinal microsurgery include prolonged operating time, inadequate force feedback, and poor depth perception due to a constrained top-down view of the surgery. The introduction of robot-assisted technology could potentially deal with such challenges and improve the surgeon's performance. Motivated by such challenges, this work develops a strategy for autonomous needle navigation in retinal microsurgery aiming to achieve precise manipulation, reduced end-to-end surgery time, and enhanced safety. This is accomplished through real-time geometry estimation and chance-constrained Model Predictive Control (MPC) resulting in high positional accuracy while keeping scleral forces within a safe level. The robotic system is validated using both open-sky and intact (with lens and partial vitreous removal) ex vivo porcine eyes. The experimental results demonstrate that the generation of safe control trajectories is robust to small motions associated with head drift. The mean navigation time and scleral force for MPC navigation experiments are 7.208 s and 11.97 mN, which can be considered efficient and well within acceptable safe limits. The resulting mean errors along lateral directions of the retina are below 0.06 mm, which is below the typical hand tremor amplitude in retinal microsurgery