Evidence of electron-irradiation activated creep in amorphous olivine at room temperature

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Analysis of CAD Model-based Visual Tracking for Microassembly using a New Block Set for MATLAB/Simulink.

International audienceMicroassembly is an innovative alternative to the microfabrication process of MOEMS which is quite complex. It usually implies the use of microrobots controlled by an operator. The reliability of this approach has been already confirmed for the micro-optical technologies. However, the characterization of assemblies has shown that the operator is the main source of inaccuracies in the teleoperated microassembly. Therefore, there is a great interest in automating the microassembly process. One of the constraints of automation in microscale is the lack of high precision sensors capable to provide the full information about the object position. Thus, the usage of visual-based feedback represents a very promising approach allowing to automate the microassembly process. The purpose of this paper is to characterize the techniques of object position estimation based on the visual data, i.e. visual tracking techniques from the ViSP library. These algorithms allows to get the 3D object pose using a single view of the scene and the CAD model of the object. The performance of three main types of model-based trackers is analyzed and quantified: edge-based, texture-based and hybrid tracker. The problems of visual tracking in microscale are discussed. The control of the micromanipulation station used in the framework of our project is performed using a new Simulink block set. Experimental results are shown and demonstrate thepossibility to obtain the repeatability below 1 micrometer

GUILGET: GUI Layout GEneration with Transformer

Sketching out Graphical User Interface (GUI) layout is part of the pipeline of designing a GUI and a crucial task for the success of a software application. Arranging all components inside a GUI layout manually is a time-consuming task. In order to assist designers, we developed a method named GUILGET to automatically generate GUI layouts from positional constraints represented as GUI arrangement graphs (GUI-AGs). The goal is to support the initial step of GUI design by producing realistic and diverse GUI layouts. The existing image layout generation techniques often cannot incorporate GUI design constraints. Thus, GUILGET needs to adapt existing techniques to generate GUI layouts that obey to constraints specific to GUI designs. GUILGET is based on transformers in order to capture the semantic in relationships between elements from GUI-AG. Moreover, the model learns constraints through the minimization of losses responsible for placing each component inside its parent layout, for not letting components overlap if they are inside the same parent, and for component alignment. Our experiments, which are conducted on the CLAY dataset, reveal that our model has the best understanding of relationships from GUI-AG and has the best performances in most of evaluation metrics. Therefore, our work contributes to improved GUI layout generation by proposing a novel method that effectively accounts for the constraints on GUI elements and paves the road for a more efficient GUI design pipeline.Comment: 12 pages, 5 figures, Canadian AI Conference 202

Detectivity optimization to detect of ultraweak light fluxes with an EM-CCD as binary photon counter array

For a wide range of purposes, one faces the challenge to detect light from extremely faint and spatially extended sources. In such cases, detector noises dominate over the photon noise of the source, and quantum detectors in photon counting mode are generally the best option. Here, we combine a statistical model with an in-depth analysis of detector noises and calibration experiments, and we show that visible light can be detected with an electron-multiplying charge-coupled devices (EM-CCD) with a signal-to-noise ratio (SNR) of 3 for fluxes less than 30 photon s- 1 cm- 2. For green photons, this corresponds to 12 aW cm- 2 X 9 x 10- 11 lux, i.e. 15 orders of magnitude less than typical daylight. The strong nonlinearity of the SNR with the sampling time leads to a dynamic range of detection of 4 orders of magnitude. To detect possibly varying light fluxes, we operate in conditions of maximal detectivity D rather than maximal SNR. Given the quantum efficiency QE(lambda) of the detector, we find D = 0.015 photon- 1 s(1/2) cm, and a non-negligible sensitivity to blackbody radiation for T > 50 degrees C. This work should help design highly sensitive luminescence detection methods and develop experiments to explore dynamic phenomena involving ultra-weak luminescence in biology, chemistry, and material sciences

Gold nanoplasmonic particles in tunable porous silicon 3D scaffolds for ultra-low concentration detection by SERS

A composite material of plasmonic nanoparticles embedded in the scaffold of nanoporous Silicon offers unmatched capabilities to use it as a SERS substrate. The marriage of these components presents an exclusive combination of tightly focused amplification of Localised Surface Plasmon (LSP) fields inside the material with extremely high surface-to-volume ratio. This provides favourable conditions for a single molecule or extremely low concentration detection by SERS. In this work the advantage of the composite is demonstrated by SERS detection of Methylene Blue at the concentration as low a few picomolars. We systematically investigate the plasmonic properties of the material by imaging its morphology, establishing composition and their effect on the LSP resonance optical spectra

Engineering of Structural Variants using CRISPR/Cas in Mice

Structural variations (SVs) contribute to the variability of our genome and are often associated with disease. Their study in model systems was hampered until now by labor-intensive genetic targeting procedures and multiple mouse crossing steps. Here we present the use of CRISPR/Cas for the fast (10 weeks) and efficient generation of SVs in mice. We specifically produced deletions, inversions, and also duplications at six different genomic loci ranging from 1.1 kb to 1.6 Mb with efficiencies up to 42%. After PCR-based selection, clones were successfully used to create mice via aggregation. To test the practicability of the method, we reproduced a human 500 kb disease-associated deletion and were able to recapitulate the human phenotype in mice. Furthermore, we evaluated the regulatory potential of a large genomic interval by deleting a 1.5 Mb fragment. The method presented permits rapid in vivo modeling of genomic rearrangements

Amino Acids Are an Ineffective Fertilizer for Dunaliella spp. Growth

Autotrophic microalgae are a promising bioproducts platform. However, the fundamental requirements these organisms have for nitrogen fertilizer severely limit the impact and scale of their cultivation. As an alternative to inorganic fertilizers, we investigated the possibility of using amino acids from deconstructed biomass as a nitrogen source in the genus Dunaliella. We found that only four amino acids (glutamine, histidine, cysteine, and tryptophan) rescue Dunaliella spp. growth in nitrogen depleted media, and that supplementation of these amino acids altered the metabolic profile of Dunaliella cells. Our investigations revealed that histidine is transported across the cell membrane, and that glutamine and cysteine are not transported. Rather, glutamine, cysteine, and tryptophan are degraded in solution by a set of oxidative chemical reactions, releasing ammonium that in turn supports growth. Utilization of biomass-derived amino acids is therefore not a suitable option unless additional amino acid nitrogen uptake is enabled through genetic modifications of these algae

Nonlinear Spectral Synthesis of Soliton Gas in Deep-Water Surface Gravity Waves

Soliton gases represent large random soliton ensembles in physical systems that exhibit integrable dynamics at the leading order. Despite significant theoretical developments and observational evidence of ubiquity of soliton gases in fluids and optical media, their controlled experimental realization has been missing. We report a controlled synthesis of a dense soliton gas in deep-water surface gravity waves using the tools of nonlinear spectral theory [inverse scattering transform (IST)] for the one-dimensional focusing nonlinear Schrödinger equation. The soliton gas is experimentally generated in a one-dimensional water tank where we demonstrate that we can control and measure the density of states, i.e., the probability density function parametrizing the soliton gas in the IST spectral phase space. Nonlinear spectral analysis of the generated hydrodynamic soliton gas reveals that the density of states slowly changes under the influence of perturbative higher-order effects that break the integrability of the wave dynamics

Datamama, bringing pregnancy research into the future: design, development, and evaluation of a citizen science pregnancy mobile application

Background: Pregnancy mobile applications (apps) have grown in popularity over the past decade, with some being used to promote study recruitment or health behaviors. However, no app serves as an all-in-one solution for collecting general data for research purposes and providing women with useful and desirable features. Aim: To create and develop a Swiss pregnancy mobile app as an innovative means to collect research data and provide users with reliable information. Methods: Determining the key features of the app involved a review of the literature and assessment of popular apps in the Swiss AppStore. A team of engineers developed the app, which includes a pregnancy timeline, questionnaires for data collection, medical and psychological articles and a checklist with appointment reminders. The content was written and reviewed by healthcare providers considered experts in the topics adressed. The questionnaires are distributed based on the user’s gestational age, by a chatbot. The project was authorized by the ethics commission in the canton of Vaud. An online survey of ten questions, advertised on Datamama’s home screen, was conducted to assess the users’ use of the app (27.11- 19.12.2022). Results: A review of 84 articles and 25 popular apps showed the need for a comprehensive pregnancy app. The development of Datamama took 2 years and included the creation of 70 medical and psychological articles and 29 questionnaires covering 300 unique variables. Six months after the launch, there were 800 users with a 73% average participation rate in the questionnaires. Sixty-five women completed the survey, with 70.8% using the app once to multiple times per week. The primary reason for using the app was to help research by answering the questionnaires, followed by access to reliable medical information. The reason most frequently ranked first for using the app was to help research by answering the questionnaires (42/65, 67% of women rated it first), followed by access to reliable medical information (34/65, 54% women rated it second). Women rated the information as clear, understandable, and interesting with a trust rating in data handling at 98.5%. The average grade for recommending the app was 8/10, with suggestions for increasing the amount of medical content and tailoring it based on gestational age. Conclusion: Datamama is the first pregnancy app to address the needs of both patients and researchers. Initial feedback from users was positive, highlighting future challenges for success. Future work will consist in improving the app, validating the data and use it to answer specific pregnancy-related research questions

Ocean convergence and the dispersion of flotsam

Floating oil, plastics, and marine organisms are continually redistributed by ocean surface currents. Prediction of their resulting distribution on the surface is a fundamental, long-standing, and practically important problem. The dominant paradigm is dispersion within the dynamical context of a nondivergent flow: objects initially close together will on average spread apart but the area of surface patches of material does not change. Although this paradigm is likely valid at mesoscales, larger than 100 km in horizontal scale, recent theoretical studies of submesoscales (less than ∼10 km) predict strong surface convergences and downwelling associated with horizontal density fronts and cyclonic vortices. Here we show that such structures can dramatically concentrate floating material. More than half of an array of ∼200 surface drifters covering ∼20 × 20 km2 converged into a 60 × 60 m region within a week, a factor of more than 105 decrease in area, before slowly dispersing. As predicted, the convergence occurred at density fronts and with cyclonic vorticity. A zipperlike structure may play an important role. Cyclonic vorticity and vertical velocity reached 0.001 s−1 and 0.01 ms−1, respectively, which is much larger than usually inferred. This suggests a paradigm in which nearby objects form submesoscale clusters, and these clusters then spread apart. Together, these effects set both the overall extent and the finescale texture of a patch of floating material. Material concentrated at submesoscale convergences can create unique communities of organisms, amplify impacts of toxic material, and create opportunities to more efficiently recover such material