Machine Learning and Physics: a long standing relation?
Seminar by Gorka Muñoz-Gil from ICFO, Barcelona, Spain.
In this talk, I will review the recent advances in single trajectory characterization via Machine Learning methods. Then, I will introduce the AnDi challenge, a competition which aims at bringing together a vibrating and multidisciplinary community of scientists working on the problem of anomalous diffusion.
Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting.
Seminar by Jesús Pineda from the Universidad Tecnologica de Bolivar, Cartagena, Colombia.
The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in terms of accuracy, fast acquisition, and processing. In this work, we present a wide-field 3D imaging system for the 3D reconstruction of the SPT, and we propose an automated method for the measurement of the skin wheals. The automated measurement is based on pyramidal decomposition and parametric 3D surface fitting for estimating the sizes of the wheals directly. We proposed two parametric models for the diameter estimation. Model 1 is based on an inverted Elliptical Paraboloid function, and model 2 on a super-Gaussian function. The accuracy of the 3D imaging system was evaluated with validation objects obtaining transversal and depth accuracies within ± 0.1 mm and ± 0.01 mm, respectively. We tested the method on 80 SPTs conducted in volunteer subjects, which resulted in 61 detected wheals. We analyzed the accuracy of the models against manual reference measurements from a physician and obtained that the parametric model 2 on average yields diameters closer to the reference measurements (model 1: -0.398 mm vs. model 2: -0.339 mm) with narrower 95% limits of agreement (model 1: [-1.58, 0.78] mm vs. model 2: [-1.39, 0.71] mm) in a Bland-Altman analysis. In one subject, we tested the reproducibility of the method by registering the forearm under five different poses obtaining a maximum coefficient of variation of 5.24% in the estimated wheal diameters. The proposed method delivers accurate and reproducible measurements of the SPT .
Jesus Pineda, Raul Vargas, Lenny A. Romero, Javier Marrugo, Jaime Meneses & Andres G. Marrugo (2019) Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting. PLOS ONE 14(10), e0223623.
Yu-Wei Chang is an engineer at the Digital Medicine Center at National Yang-Ming University in Taiwan, working on a machine learning approach for phenotyping psychiatric disorders.
He will visit us for 2 months from February 29, 2020, to April 30, 2020, and he will be working on deep learning for Alzheimer’s Disease as well as the development of BRAPH 2.0 (March-April 2020).
Polymers under local active forces: a simplified stochastic model for motor-induced translocations.
Seminar by Laura Natali from the University of Rome “La Sapienza”, Rome, Italy.
Molecular motors are a wide class of enzymes that can transport even large macromolecules by converting chemical into mechanical energy, through the process of ATP-hydrolysis. Among those, active nanopore translocation is a common mechanism to carry proteins across biological membranes. The phospholipid bilayer is impenetrable for the folded protein, that requires to be unfolded and pulled across channels such as alpha-hemolysin . Exploiting the translocation process, we can acquire information about the target proteins’ structure, such as the intermediate configurations between the folded and denatured structures . Here follows the interest in modeling the motor proteins complex in a simple simulation setup.
First of all, we characterized the active polymer’s features in free space and subsequently, we confined it inside a nanopore model. The study in free space aims to investigate how activity affects both the global and the local polymer properties. The chosen model for the active force is an Active Ornstein-Uhlenbeck Particle, a model closely related to Active Brownian Particles . The presence of the catalytic head affects the end-to-end distance of the polymer, which describes its degree of compactness. The active chain can be studied through the Rouse mode decomposition , which allowed us to analyze the dependence of the second moment of the end-to-end distance as a function of the persistence time of the activity. We considered also the distance between consecutive monomers, which provides an insight into the local effects of the active force and how it is transmitted along the chain.
In this work, we were inspired by an experiment employing the ClpXP complex , a protein-degradation machine responsible for unfolding and digesting malfunctioning proteins through unidirectional transport across the nanopore. In the model we propose, we enclose the polymer chain in a confining potential, simulating the effect of the nanopore. The energy generated by the molecular motor translocates the polymers, which means they cross the pore from side to side. In our setup, the effect of the molecular motor  is represented as a potential barrier combined with a region that makes active the monomers that are crossing it. The translocation pathways have a step-wise profile typical of their biological counterparts.
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Controlled generation of high power optical vortex arrays, and their frequency-doubling characteristics
Seminar by Harshith Bachimanchi from the Indian Institute of Science Education and Research, Pune (IISER Pune).
Optical vortices, beams carrying orbital angular momentum (OAM) per photon are of supreme interest in recent times for their wide variety of applications in quantum information, micro-manipulation, and material lithography [1, 2, 3]. Due to a helical phase variation in propagation, and an undefined phase at the centre, these beams have a phase singularity in their wavefront, resulting in the doughnut-shaped intensity distribution. Though the vortex beams have been widely explored in the past, the recent advancements on multiple particle trapping, single-shot material lithography, and multiplexing in quantum information  demand an array of optical vortices in a simple experimental scheme.
While the majority of the existing mode converters transform the Gaussian beam into a single vortex beam, the intrinsic advantage of the dynamic phase modulation through holographic technique allow the spatial light modulators (SLMs) to generate vortex arrays directly from a Gaussian beam. However, the low damage threshold of SLMs restricts their usage for high power vortex array applications.
Here, we elaborate a simple experimental scheme to generate high power, ultrafast, higher order optical vortex arrays. Simply by using a dielectric Microlens array (MLA) and a plano-convex lens we generate an array of beams carrying the spatial property of the input beam. Though we’ve verified the technique for the case of optical vortices, it holds true for a useful subset of structured optical beams. Considering the MLA as a 2D sinusoidal phase grating, we have numerically calculated the intensity pattern of the array beams in close agreement with the experimental results. We have also theoretically derived the parameters controlling the intensity pattern, size and the pitch of array and verified experimentally. The single-pass frequency doubling of the vortex array at 1064 nm in a 1.2 mm BiBO crystal produced green vortex arrays of orders as high as lsh = 12, twice the order of the pump array beam, with a conversion efficiency as high as ∼3.65% .
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Harshith, B.S., Samanta, G.K. Controlled generation of array beams of higher order orbital angular momentum and study of their frequency-doubling characteristics. Sci Rep9, 10916 (2019).
Light driven colloidal micro swimmers Seminar by Juliane Simmchen
from TU Dresden, Germany
In the last decade the generation of motion on the microscale has evolved into a fascinating field of modern science. We have learned to activate and control Janus particles in a regime dominated by low Reynolds numbers, where motion is not influenced by inertia. This implements several principles to take into account for the engineering of artificial microswimmers and often meant that toxic fuels had to be used to achieve propulsion. To move one step further towards possible applications in the environmental or biomedical field, we are now using light sensitive materials to explore new propulsion strategies.
Place: Soliden 3rd floor Time: 11 June 2019, 10:00
Reinforcement Learning in a Large Scale Photonic Network
Seminar by Daniel Brunner from FEMTO-ST Institute/Optics Department, CNRS & University Bourgogne Franche-Comté, Besançon Cedex, France
We experimentally create a neural network via a spatial light modulator, implementing connections between 2025 in parallel based on diffractive coupling. We numerically validate the scheme for at least 34.000 photonic neurons. Based on a digital micro-mirror array we demonstrate photonic reinforcement learning and predict a chaotic time-series via our optical neural network. The prediction error efficiently converges. Finally, we give insight based on the first investigation of effects to be encountered in neural networks physically implemented in analogue substrates.
Meltem Elitas is visiting from Sabanci University in Istanbul from 1st May until 28th June 2019.
Meltem Elitas is a faculty member at the Mechatronics Program at Sabanci University in Istanbul, Turkey. Her background is Electrical and Mechatronics Engineering; she obtained her doctorate from Bioengineerieng and Biotechnology Department at École Polytechnique Fédérale de Lausanne. She performed her postdoctoral studies at Yale University Biomedical Engineering Department. She has published more than 25 papers and conference proceedings in reputed journals. Her research interests are biomechatronics, cellular heterogeneity, cellular interactions, tumor microenvironment, live cell imaging and development of microfabricated tools for quantitative biology. She is visiting the Soft Matter Lab as part of her ongoing Marie Skłodowska-Curie project.
Sandra Heckel is visiting from the Technical University of Dresden from 26th March until 12th April 2019.
Sandra has a Bachelor degree in chemistry from TU Dresden and a Master degree in chemistry from TU Dresden and MIT, where she worked on a Master thesis about near-infrared bioimaging with semiconductor quantum dots.
In her PhD, she is working in the group of Juliane Simmchen on visible light-driven microswimmers and communication mechanisms among them.
If you would like to know more about Sandra Heckel and Juliane Simmchen’s research please visit their webpage.