Femtosecond resolution timing jitter correction on a TW scale Ti:sapphire laser system for FEL pump-probe experiments

Intense ultrashort pulse lasers are used for fs resolution pumpprobe experiments more and more at large scale facilities, such as free electron lasers (FEL). Measurement of the arrival time of the laser pulses and stabilization to the machine or other sub-systems on the target, is crucial for high time-resolution measurements. In this work we report on a single shot, spectrally resolved, non-collinear cross-correlator with sub-fs resolution. With a feedback applied we keep the output of the TW class Ti:sapphire amplifier chain in time with the seed oscillator to ~3 fs RMS level for several hours. This is well below the typical pulse duration used at FELs and supports fs resolution pump-probe experiments. Short term jitter and long term timing drift measurements are presented. Applicability to other wavelengths and integration into the timing infrastructure of the FEL are also covered to show the full potential of the device

Normality of I-V Measurements Using ML

Electrochemistry ecosystems are promising for accelerating the design and discovery of electrochemical systems for energy storage and conversion, by automating significant parts of workflows that combine synthesis and characterization experiments with computations. They require the integration of flow controllers, solvent containers, pumps, fraction collectors, and potentiostats, all connected to an electrochemical cell. These are specialized instruments with custom software that is not originally designed for network integration. We developed network and software solutions for electrochemical workflows that adapt system and instrument settings in real-time for multiple rounds of experiments. We demonstrate this automated workflow by remotely operating the instruments and collecting their measurements to generate a voltammogram (I-V profile) of an electrolyte solution in an electrochemical cell. These measurements are made available at the remote computing system and used for subsequent analysis. In this paper, we focus on a novel, analytically validated machine learning (ML) method for an electrochemistry ecosystem to ensure that I-V measurements are consistent with the normal experimental conditions, and to detect abnormal conditions, such as disconnected electrodes or low cell content volume.Comment: published at eScience 202

Decentralized 3D Collision Avoidance for Multiple UAVs in Outdoor Environments

The use of multiple aerial vehicles for autonomous missions is turning into commonplace. In many of these applications, the Unmanned Aerial Vehicles (UAVs) have to cooperate and navigate in a shared airspace, becoming 3D collision avoidance a relevant issue. Outdoor scenarios impose additional challenges: (i) accurate positioning systems are costly; (ii) communication can be unreliable or delayed; and (iii) external conditions like wind gusts affect UAVs’ maneuverability. In this paper, we present 3D-SWAP, a decentralized algorithm for 3D collision avoidance with multiple UAVs. 3D-SWAP operates reactively without high computational requirements and allows UAVs to integrate measurements from their local sensors with positions of other teammates within communication range. We tested 3D-SWAP with our team of custom-designed UAVs. First, we used a Software-In-The-Loop simulator for system integration and evaluation. Second, we run field experiments with up to three UAVs in an outdoor scenario with uncontrolled conditions (i.e., noisy positioning systems, wind gusts, etc). We report our results and our procedures for this field experimentation.European Union’s Horizon 2020 research and innovation programme No 731667 (MULTIDRONE

Diagnosis and prognosis of slow speed bearing behavior under grease starvation condition

This document is the Accepted Manuscript version. The final, definitive version of this paper has been published in Structural Health Monitoring, April 2017, DOI: https://doi.org/10.1177/1475921717704620, published by SAGE Publishing, All rights reserved.The monitoring and diagnosis of rolling element bearings with acoustic emission and vibration measurements has evolved as one of the much used techniques for condition monitoring and diagnosis of rotating machinery. Furthermore, recent developments indicate the drive toward integration of diagnosis and prognosis algorithms in future integrated machine health management systems. With this in mind, this article is an experimental study of slow speed bearings in a starved lubricated contact. It investigates the influence of grease starvation conditions on detection and monitoring natural defect initiation and propagation using acoustic emission approach. The experiments are also aimed at a comparison of results acquired by acoustic emission and vibration diagnosis on full-scale axial bearing. In addition to this, the article concentrates on the estimation of the remaining useful life for bearings while in operation. To implement this, a multilayer artificial neural network model has been proposed to correlate the selected acoustic emission features with corresponding bearing wear throughout laboratory experiments. Experiments confirm that the obtained results were promising and selecting this appropriate signal processing technique can significantly affect the defect identification.Peer reviewedFinal Accepted Versio

Biexciton recombination rates in self-assembled quantum dots

The radiative recombination rates of interacting electron-hole pairs in a quantum dot are strongly affected by quantum correlations among electrons and holes in the dot. Recent measurements of the biexciton recombination rate in single self-assembled quantum dots have found values spanning from two times the single exciton recombination rate to values well below the exciton decay rate. In this paper, a Feynman path-integral formulation is developed to calculate recombination rates including thermal and many-body effects. Using real-space Monte Carlo integration, the path-integral expressions for realistic three-dimensional models of InGaAs/GaAs, CdSe/ZnSe, and InP/InGaP dots are evaluated, including anisotropic effective masses. Depending on size, radiative rates of typical dots lie in the regime between strong and intermediate confinement. The results compare favorably to recent experiments and calculations on related dot systems. Configuration interaction calculations using uncorrelated basis sets are found to be severely limited in calculating decay rates.Comment: 11 pages, 4 figure

Intensity interrogation near cutoff resonance for label-free cellular profiling

We report a method enabling intensity-based readout for label-free cellular assays, and realize a reader device with the same footprint as a microtiter plate. For unambiguous resonance intensity measurements in resonance waveguide grating (RWG) sensors, we propose to apply resonances near the substrate cutoff wavelength. This method was validated in bulk refractive index, surface bilayer and G protein-coupled receptor (GPCR) experiments. The significantly reduced size of the reader device opens new opportunities for easy integration into incubators or liquid handling systems

MAVIS: Multi-Camera Augmented Visual-Inertial SLAM using SE2(3) Based Exact IMU Pre-integration

We present a novel optimization-based Visual-Inertial SLAM system designed for multiple partially overlapped camera systems, named MAVIS. Our framework fully exploits the benefits of wide field-of-view from multi-camera systems, and the metric scale measurements provided by an inertial measurement unit (IMU). We introduce an improved IMU pre-integration formulation based on the exponential function of an automorphism of SE_2(3), which can effectively enhance tracking performance under fast rotational motion and extended integration time. Furthermore, we extend conventional front-end tracking and back-end optimization module designed for monocular or stereo setup towards multi-camera systems, and introduce implementation details that contribute to the performance of our system in challenging scenarios. The practical validity of our approach is supported by our experiments on public datasets. Our MAVIS won the first place in all the vision-IMU tracks (single and multi-session SLAM) on Hilti SLAM Challenge 2023 with 1.7 times the score compared to the second place.Comment: video link: https://youtu.be/Q_jZSjhNFf

Gene regulatory network modelling with evolutionary algorithms -an integrative approach

Building models for gene regulation has been an important aim of Systems Biology over the past years, driven by the large amount of gene expression data that has become available. Models represent regulatory interactions between genes and transcription factors and can provide better understanding of biological processes, and means of simulating both natural and perturbed systems (e.g. those associated with disease). Gene regulatory network (GRN) quantitative modelling is still limited, however, due to data issues such as noise and restricted length of time series, typically used for GRN reverse engineering. These issues create an under-determination problem, with many models possibly fitting the data. However, large amounts of other types of biological data and knowledge are available, such as cross-platform measurements, knockout experiments, annotations, binding site affinities for transcription factors and so on. It has been postulated that integration of these can improve model quality obtained, by facilitating further filtering of possible models. However, integration is not straightforward, as the different types of data can provide contradictory information, and are intrinsically noisy, hence large scale integration has not been fully explored, to date. Here, we present an integrative parallel framework for GRN modelling, which employs evolutionary computation and different types of data to enhance model inference. Integration is performed at different levels. (i) An analysis of cross-platform integration of time series microarray data, discussing the effects on the resulting models and exploring crossplatform normalisation techniques, is presented. This shows that time-course data integration is possible, and results in models more robust to noise and parameter perturbation, as well as reduced noise over-fitting. (ii) Other types of measurements and knowledge, such as knock-out experiments, annotated transcription factors, binding site affinities and promoter sequences are integrated within the evolutionary framework to obtain more plausible GRN models. This is performed by customising initialisation, mutation and evaluation of candidate model solutions. The different data types are investigated and both qualitative and quantitative improvements are obtained. Results suggest that caution is needed in order to obtain improved models from combined data, and the case study presented here provides an example of how this can be achieved. Furthermore, (iii), RNA-seq data is studied in comparison to microarray experiments, to identify overlapping features and possibilities of integration within the framework. The extension of the framework to this data type is straightforward and qualitative improvements are obtained when combining predicted interactions from single-channel and RNA-seq datasets

Planetary Radio Interferometry and Doppler Experiment (PRIDE) technique: A test case of the Mars Express Phobos fly-by

Context. The closest ever fly-by of the Martian moon Phobos, performed by the European Space Agency’s Mars Express spacecraft, gives a unique opportunity to sharpen and test the Planetary Radio Interferometry and Doppler Experiments (PRIDE) technique in the interest of studying planet–satellite systems. Aims. The aim of this work is to demonstrate a technique of providing high precision positional and Doppler measurements of planetary spacecraft using the Mars Express spacecraft. The technique will be used in the framework of Planetary Radio Interferometry and Doppler Experiments in various planetary missions, in particular in fly-by mode. Methods. We advanced a novel approach to spacecraft data processing using the techniques of Doppler and phase-referenced very long baseline interferometry spacecraft tracking. Results. We achieved, on average, mHz precision (30 μm/s at a 10 s integration time) for radial three-way Doppler estimates and sub-nanoradian precision for lateral position measurements, which in a linear measure (at a distance of 1.4 AU) corresponds to ~50 m