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IEEE International Workshop on Metrology for the Sea;Learning to Measure Sea Health Parameters (MetroSea)

作者： Maurizio Ingrosso Beatriz Tintoré Laura Macrina Giulia Cipriano Thodoris Tsimpidis Anastasia Miliou Roberto Carlucci Guido Pietroluongo Department of Biosciences Biotechnology and Environment Archipelagos Institute of Marine Conservation University of Bari Aldo Moro Bari Italy Department of Mechanical Engineering Archipelagos Institute of Marine Conservation Brunel University London Pythagorio Greece Marine Science Program Biological and Environmental Science and Engineering Division KAUST Red Sea Research Center Archipelagos Institute of Marine Conservation King Abdullah University of Science and Technology (KAUST) Pythagorio Greece Department of Biosciences Biotechnology and Environment University of Bari Aldo Moro Bari Italy Archipelagos Institute of Marine Conservation Pythagorio Greece Department of Comparative Biomedicine and Food Science University of Padova Legnaro Italy

The Mediterranean population of Mediterranean monk seal (Monachus monachus) is reported as "Critically endangered" by IUCN Red List and its spatial distribution seems to be fragmented in colonies, mainly found around the Ionian and Aegean *** seals are proved to be highly affected by human pressure such as boat traffic and fishery. Previous studies highlighted the occurrence of net depredation and interactions with artisanal small-scale fisheries. Accordingly, a source of concern is the little quantitative information on various aspects of the Greek small-scale fisheries. Thus, the landings composition of the Marathokampos Bay’s fleet between 2009 and 2011 has been analysed. Then, a dietary overlap index and multivariate analysis were used to analyse the overlap between resources exploited by fisheries and those consumed by monk *** show that for a total of 565 days at sea, 57 % of those fishing days were performed with Trammel nets, 11.3 % with 8-9 mm Gillnets, 18.4 % with Longline, 12.6 % with Boat seine, 0.5 % with Kalami and 0.2 % for the Purse seine. The total landing biomass of 14.3 tons was composed of 68 species. Monk seal’s diets considered in the analysis showed the highest resource overlap with the Boat seines and the lowest with the Purse seines. Results of the cluster analysis showed that the similarity at 0.2 similarity level revealed a big group composed only by fishing métiers (Longline, Trammel net, Purse seine and total fleet).This study suggests that filling this gap of knowledge could support the implementation of conservation actions. Furthermore, some preliminary results regarding the characteristic of the Marathokampos Bay’s fishing fleet are provided, and the need to gather further data able to better quantify the impacts of both monk seals and fishery on the resources is underlined.

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SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： de Franca, F.O. Virgolin, M. Kommenda, M. Majumder, M.S. Cranmer, M. Espada, G. Ingelse, L. Fonseca, A. Landajuela, M. Petersen, B. Glatt, R. Mundhenk, N. Lee, C.S. Hochhalter, J.D. Randall, D.L. Kamienny, P. Zhang, H. Dick, G. Simon, A. Burlacu, B. Kasak, Jaan Machado, Meera Wilstrup, Casper Cavaz, W.G.L. Federal University of ABC Santo Andre Brazil Evolutionary Intelligence group Centrum Wiskunde and Informatica Science Park Amsterdam Netherlands University of Applied Sciences Upper Austria Hagenberg Austria Computational Health Informatics Program Boston Children’s Hospital Harvard Medical School Boston USA Center for Computational Astrophysics Flatiron Institute and Department of Astrophysical Sciences of Princeton University USA LASIGE Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Computational Engineering Division Lawrence Livermore National Laboratory Livermore USA Department of Mechanical Engineering University of Utah Utah USA Meta FAIR France Victoria University of Wellington School of Engineering and Computer Science New Zealand University of otago Department of Information Science New Zealand Institut für Angewandte Physik Universität TübingenMax Planck Institute for Intelligent Systems Tübingen Germany Abzu AI Orient Plads 1 Nordhavn Denmark

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main promise of this approach is that it may return an interpretable model that can be insightful to users, while maintaining high accuracy. The current standard for benchmarking these algorithms is SRBench, which evaluates methods on hundreds of datasets that are a mix of real-world and simulated processes spanning multiple domains. At present, the ability of SRBench to evaluate interpretability is limited to measuring the size of expressions on real-world data, and the exactness of model forms on synthetic data. In practice, model size is only one of many factors used by subject experts to determine how interpretable a model truly is. Furthermore, SRBench does not characterize algorithm performance on specific, challenging sub-tasks of regression such as feature selection and evasion of local minima. In this work, we propose and evaluate an approach to benchmarking SR algorithms that addresses these limitations of SRBench by 1) incorporating expert evaluations of interpretability on a domain-specific task, and 2) evaluating algorithms over distinct properties of data science tasks. We evaluate 12 modern symbolic regression algorithms on these benchmarks and present an in-depth analysis of the results, discuss current challenges of symbolic regression algorithms and highlight possible improvements for the benchmark itself. Authors

关键词： Benchmarking

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Simultaneous high-speed x-ray transmission imaging and absolute dynamic absorptance measurements during high-power laser-metal processing 11

Simultaneous high-speed x-ray transmission imaging and absol...

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11th CIRP Conference on Photonic Technologies, LANE 2020

作者： Simonds, Brian J. Tanner, Jack Artusio-Glimpse, Alexandra Williams, Paul A. Parab, Niranjan Zhao, Cang Sun, Tao Applied Physics Division Physical Measurements Laboratory National Institute of Standards and Technology BoulderCO80305 United States X-ray Science Division Advanced Photon Source Argonne National Laboratory LemontIL60439 United States Department of Mechanical Engineering Tsinghua University Beijing China Department of Materials Science and Engineering University of Virginia CharlottesvilleVA United States

During high-power laser metal processing, the absorbed light is intimately related to the molten metal cavity shape. For the first time, this relationship is observed directly and simultaneously by implementing state-of-the-art techniques of high-speed x-ray imaging and integrating-sphere radiometry. Experiments were performed on Ti-6Al-4V solid and powder under single spot laser illumination for laser conditions that cause keyhole formation and collapse. The data from x-ray imaging corroborates that a dramatic rise in laser absorption is due to keyhole formation. We also find that the keyhole area correlates most strongly with energy absorption followed closely by keyhole depth. Furthermore, time synchronization reveals correlations between keyhole fluctuations and sinusoidal variations in energy absorption that occur during nominally "stable" keyhole conditions. Absorption data show a 24 % periodic change in absorbed laser power at a 50 kHz frequency. The absorption peaks correlate to relatively large, open keyholes, whereas images taken at the troughs reveal keyholes with substantial undulations of the keyhole sidewalls. These observations give crucial, quantitative data for computational modeling whose aim is to predict porosity and defect formation. © 2020 The Authors. Published by Elsevier B.V.

关键词： 3D printers

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Optically-generated focused ultrasound for noninvasive brain stimulation with ultrahigh precision

arXiv

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arXiv 2022年

作者： Li, Yueming Jiang, Ying Lan, Lu Ge, Xiaowei Cheng, Ran Zhan, Yuewei Chen, Guo Shi, Linli Wang, Runyu Zheng, Nan Yang, Chen Cheng, Ji-Xin Department of Mechanical Engineering Boston University BostonMA02215 United States Graduate Program for Neuroscience Boston University BostonMA02215 United States Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Chemistry Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BostonMA02215 United States

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological diseases. Current non-invasive neuromodulation methods offer limited precision at the millimeter-level. Here, we report optically-generated focused ultrasound (OFUS) for non-invasive brain stimulation with ultrahigh precision. OFUS is generated by a soft optoacoustic pad (SOAP) fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane film. SOAP generates a transcranial ultrasound focus at 15 MHz with an ultrahigh lateral resolution of 83 µm, which is two orders of magnitude smaller than that of conventional transcranial focused ultrasound (tFUS). Here, we show effective OFUS neurostimulation in vitro with a single ultrasound cycle. We demonstrate submillimeter transcranial stimulation of the mouse motor cortex in vivo. An acoustic energy of 0.6 mJ/cm2, four orders of magnitude less than that of tFUS, is sufficient for successful OFUS neurostimulation. OFUS offers new capabilities for neuroscience studies and disease treatments by delivering a focus with ultrahigh precision non-invasively. Copyright © 2022, The Authors. All rights reserved.

关键词： Silicones

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Experimental implementation of an efficient test of quantumness

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physical Review A 2024年第1期109卷 012610-012610页

作者： Laura Lewis Daiwei Zhu Alexandru Gheorghiu Crystal Noel Or Katz Bahaa Harraz Qingfeng Wang Andrew Risinger Lei Feng Debopriyo Biswas Laird Egan Thomas Vidick Marko Cetina Christopher Monroe Institute for Quantum Information and Matter and Department of Computing and Mathematical Sciences California Institute of Technology Pasadena California 91125 USA Division of Physics Mathematics and Astronomy California Institute of Technology Pasadena California 91125 USA Joint Quantum Institute Departments of Physics and Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Joint Center for Quantum Information and Computer Science NIST/University of Maryland College Park Maryland 20742 USA IonQ Inc. College Park Maryland 20740 USA Departments of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Institute for Theoretical Studies ETH Zürich Zürich CH 8001 Switzerland Duke Quantum Center and Department of Physics Duke University Durham North Carolina 27708 USA Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA Chemical Physics Program and Institute for Physical Science and Technology University of Maryland College Park Maryland 20742 USA

A test of quantumness is a protocol where a classical user issues challenges to a quantum device to determine if it exhibits nonclassical behavior, under certain cryptographic assumptions. Recent attempts to implement such tests on current quantum computers rely on either interactive challenges with efficient verification or noninteractive challenges with inefficient (exponential time) verification. In this paper, we execute an efficient noninteractive test of quantumness on an ion-trap quantum computer. Our results significantly exceed the bound for a classical device's success.

关键词： Quantum cryptography Quantum information with trapped ions Quantum protocols Quantum verification

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BEAST DB: Grand-Canonical Database of Electrocatalyst Properties

arXiv

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arXiv 2024年

作者： Tezak, Cooper Clary, Jacob Gerits, Sophie Quinton, Joshua Rich, Benjamin Singstock, Nicholas Alherz, Abdulaziz Aubry, Taylor Clark, Struan Hurst, Rachel Ben, Mauro Del Sutton, Christopher Sundararaman, Ravishankar Musgrave, Charles Vigil-Fowler, Derek Department of Chemical and Biological Engineering University of Colorado Boulder BoulderCO80309 United States Materials Chemical and Computational Science Directorate National Renewable Energy Laboratory GoldenCO80401 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States Department of Chemistry University of Colorado Boulder BoulderCO80309 United States Department of Mechanical Engineering University of Colorado Boulder BoulderCO80309 United States Department of Chemical Engineering College of Engineering and Petroleum Kuwait University Safat13060 Kuwait Applied Mathematics & Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Chemistry and Biochemistry University of South Carolina ColumbiaSC29208 United States Department of Materials Science and Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Materials Science and Engineering Program University of Colorado Boulder BoulderCO80309 United States Renewable and Sustainable Energy Institute University of Colorado Boulder BoulderCO80309 United States Department of Chemical Engineering University of Utah Salt Lake CityUT84112 United States

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogenous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage. Copyright © 2024, The Authors. All rights reserved.

关键词： Database systems

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Nanomaterials in the treatment and diagnosis of rheumatoid arthritis: Advanced approaches

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SLAS technology 2024年第4期29卷 100146-100146页

作者： Angela, Stefanny Fadhilah, Gianna Hsiao, Wesley Wei-Wen Lin, Hsuan-Yi Ko, Joshua Lu, Steven Che-Wei Lee, Cheng-Chung Chang, Yu-Sheng Lin, Ching-Yu Chang, Huan-Cheng Chiang, Wei-Hung Department of Chemical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu Taiwan Ph.D. Program for Translational Medicine College of Medical Science and Technology Taipei Medical University Taipei Taiwan Division of Allergy Immunology and Rheumatology Department of Internal Medicine Shuang Ho Hospital New Taipei City Taiwan Division of Allergy Immunology and Rheumatology Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan The Ph.D. Program in Medical Biotechnology College of Medical Science and Technology Taipei Medical University Taipei Taiwan School of Medical Laboratory Science and Biotechnology College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Chemical Engineering National Taiwan University of Science and Technology Taipei Taiwan Institute of Atomic and Molecular Sciences Academia Sinica Taipei Taiwan Department of Chemistry National Taiwan Normal University Taipei Taiwan Department of Chemical Engineering National Taiwan University of Science and Technology Taipei Taiwan Sustainable Electrochemical Energy Development (SEED) Center National Taiwan University of Science and Technology Taipei Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taipei Taiwan. Electronic address: weshsiao@mail.ntust.edu.tw

Rheumatoid arthritis (RA), a chronic inflammatory condition that affects persons between the ages of 20 and 40, causes synovium inflammation, cartilage loss, and joint discomfort as some of its symptoms. Diagnostic techniques for RA have traditionally been split into two main categories: imaging and serological tests. However, significant issues are associated with both of these methods. Imaging methods are costly and only helpful in people with obvious symptoms, while serological assays are time-consuming and require specialist knowledge. The drawbacks of these traditional techniques have led to the development of novel diagnostic approaches. The unique properties of nanomaterials make them well-suited as biosensors. Their compact dimensions are frequently cited for their outstanding performance, and their positive impact on the signal-to-noise ratio accounts for their capacity to detect biomarkers at low detection limits, with excellent repeatability and a robust dynamic range. In this review, we discuss the use of nanomaterials in RA theranostics. Scientists have recently synthesized, characterized, and modified nanomaterials and biomarkers commonly used to enhance RA diagnosis and therapy capabilities. We hope to provide scientists with the promising potential that nanomaterials hold for future theranostics and offer suggestions on further improving nanomaterials as biosensors, particularly for detecting autoimmune disorders. Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

关键词： Biomarker Biosensor Diagnosis Nanomaterials Rheumatoid arthritis Therapy

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Real-time Ocean Probabilistic Forecasts, Reachability Analysis, and Adaptive Sampling in the Gulf of Mexico

Real-time Ocean Probabilistic Forecasts, Reachability Analys...

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OCEANS

作者： P.F.J. Lermusiaux P.J. Haley C. Mirabito E.M. Mule S.F. DiMarco A. Dancer X. Ge A.H. Knap Y. Liu S. Mahmud U.C. Nwankwo S. Glenn T.N. Miles D. Aragon K. Coleman M. Smith M. Leber R. Ramos J. Storie G. Stuart J. Marble P. Barros E.P. Chassignet A. Bower H.H. Furey B. Jaimes de la Cruz L.K. Shay M. Tenreiro E. Pallas Sanz J. Sheinbaum P. Perez-Brunius D. Wilson J. van Smirren R. Monreal-Jiménez D.A. Salas-de-León V.K. Contreras Tereza M. Feldman M. Khadka Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA Department of Oceanography Texas A&M University Department of Marine and Coastal Sciences Rutgers University Woods Hole Group Inc. Fugro Department of Earth Ocean and Atmospheric Science Florida State University Physical Oceanography Woods Hole Oceanographic Institution Rosenstiel School of Marine Atmospheric and Earth Science University of Miami Department of Oceanography CICESE University of the Virgin Islands Ocean Sierra Universidad Nacional Autónoma de México Mexican Institute of Water Technology Gulf Research Program NASEM

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

The first steps towards integrating autonomous monitoring, probabilistic forecasting, reachability analysis, and adaptive sampling for the Gulf of Mexico were demonstrated in real-time during the collaborative Mini-Adaptive Sampling Test Run (MASTR) ocean experiment, which took place from February to April 2024. The emphasis of this contribution is on the use of the MIT Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS) including Error Subspace Statistical Estimation (ESSE) large-ensemble forecasting and path planning systems to predict ocean fields and uncertainties, forecast reachable sets and optimal paths for gliders, and guide sampling aircraft and ocean vehicles toward the most informative observations. Deterministic and probabilistic ocean forecasts are exemplified and linked to the variability of the Loop Current (LC) and LC Eddies, demonstrating predictive skill by real-time comparisons to independent data. Risk forecasts in terms of probabilities of currents exceeding 1.5 kt were provided. The most informative sampling patterns for Remote Ocean Current Imaging System (ROCIS) flights were forecast using mutual information between surface currents and density anomaly. Finally, we guided four underwater gliders using probabilistic reachability and path-planning forecasts.

关键词： Oceans Atmospheric modeling Estimation Predictive models Probabilistic logic Real-time systems Wind forecasting Reachability analysis Integrated circuit modeling Forecasting

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Real-Time Probabilistic Reachability Forecasting for Gliders in the Gulf of Mexico

Real-Time Probabilistic Reachability Forecasting for Gliders...

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OCEANS

作者： E.M. Mule P.J. Haley C. Mirabito S.F. DiMarco S. Mahmud A. Dancer X. Ge A.H. Knap Y. Liu U.C. Nwankwo S. Glenn T.N. Miles D. Aragon K. Coleman M. Smith M. Leber R. Ramos J. Storie G. Stuart J. Marble P. Barros E.P. Chassignet A. Bower H.H. Furey B. Jaimes De La Cruz L.K. Shay M. Tenreiro E. Pallas Sanz J. Sheinbaum P. Perez-Brunius D. Wilson J. Van Smirren R. Monreal-Jiménez D.A. Salas-de-León V.K. Contreras Tereza M. Feldman M. Khadka P.F.J. Lermusiaux Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA Department of Oceanography Texas A&M University Department of Marine and Coastal Sciences Rutgers University Woods Hole Group Inc. Fugro Department of Earth Ocean and Atmospheric Science Florida State University Physical Oceanography Woods Hole Oceanographic Institution Rosenstiel School of Marine Atmospheric and Earth Science University of Miami Department of Oceanography CICESE University of the Virgin Islands Ocean Sierra Universidad Nacional Autónoma de Mexico Mexican Institute of Water Technology Gulf Research Program NASEM

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

As part of the Mini-Adaptive Sampling Test Run (MASTR) experiment in the Gulf of Mexico (GoM) region from February to April 2024, we demonstrated real-time deterministic and probabilistic reachability analysis and time-optimal path planning to guide a fleet of four ocean gliders. The governing differential equations for reachability analysis and time-optimal path planning were numerically integrated in real-time and forced by currents from our large-ensemble ocean forecasts. We illustrate the real-time deterministic and probabilistic forward reachability analyses, reachability and path planning for glider pickups, time-optimal path planning for gliders in distress, and planning of future glider deployments. Results show that the actual paths of gliders were contained within our reachable set forecasts and in accord with the dynamic reachability fronts. Our time-optimal headings and paths also predicted real glider motions, even for longer-range predictions of weeks to a month duration. Reachability and time-optimal path planning forecasts were successfully employed for glider recovery. They also enabled exploring options for future glider deployments.

关键词： Uncertainty Oceans Dynamics Differential equations Probabilistic logic Path planning Real-time systems Hazards Reachability analysis Vehicle dynamics

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Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks

arXiv

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arXiv 2023年

作者： Zhou, Meng Wagner, Matthias W. Tabori, Uri Hawkins, Cynthia Ertl-Wagner, Birgit B. Khalvati, Farzad Department of Computer Science University of Toronto Canada Neurosciences & Mental Health Research Program The Hospital for Sick Children Canada Department of Diagnostic and Interventional Radiology The Hospital for Sick Children Canada Division of Neuroradiology Neurooncology The Hospital for Sick Children Canada Paediatric Laboratory Medicine Division of Pathology The Hospital for Sick Children Canada Institute of Medical Science University of Toronto Canada Department of Medical Imaging University of Toronto Canada Department of Mechanical and Industrial Engineering University of Toronto Canada Department of Neuroradiology University Hospital Augsburg Germany

Medical image analysis has significantly benefited from advancements in deep learning, particularly in the application of Generative Adversarial Networks (GANs) for generating realistic and diverse images that can augment training datasets. However, the effectiveness of such approaches is often limited by the amount of available data in clinical settings. Additionally, the common GAN-based approach is to generate entire image volumes, rather than solely the region of interest (ROI) such as the tumor region. Research on deep learning-based brain tumor classification using MRI has shown that it is easier to classify the tumor ROIs compared to the entire image volumes. In this work, we present a novel framework that uses vector-quantization GAN and a transformer incorporating masked token modeling to generate high-resolution and diverse 3D brain tumor ROIs that can be directly used as augmented data for the classification of brain tumor ROI. We apply our method to two imbalanced datasets where we augment the minority class: (1) the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2019 dataset to generate new low-grade glioma (LGG) ROIs to balance with high-grade glioma (HGG) class;(2) the internal pediatric LGG (pLGG) dataset tumor ROIs with BRAF V600E Mutation genetic marker to balance with BRAF Fusion genetic marker class. We show that the proposed method outperforms various baseline models in both qualitative and quantitative measurements. The generated data was used to tackle the problem of imbalanced data in the brain tumor types classification task. Using the augmented data, our approach demonstrates superior performance, surpassing baseline models by up to 6.4% in the area under the ROC curve (AUC), 3.4% in F1-score, and 5.4% in Accuracy in the BraTS 2019 dataset;4.3% in AUC, 7.3% in F1-score, and 9.2% in Accuracy on our internal pLGG dataset. The results indicate the generated tumor ROIs can effectively address the imbalanced data problem. Our proposed met

关键词： Generative adversarial networks

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