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STATISTICAL PROCESS-CONTROL FOR SOFTWARE IN THE MAINTENANCE PHASE

NAVAL ENGINEERS JOURNAL 1993年第3期105卷 192-200页

作者： LUKE, SR JACOBS, DA REED, BM Stephen R. Luke:is a registered professional engineer in the Commonwealth of Virginia. He received his B.S. in mechanical engineering from Virginia Polytechnic Institute in 1983 and is presently pursuing a master's degree in engineering management at Old Dominion University. Mr. Luke is experienced as a test engineer at the Norfolk Naval Shipyard (1978–1989) and as a reliability/quality engineer at the Naval Undersea Warfare Center Detachment Norfolk (1989-Present). Currently he is the group leader of the RMA/QA group for the AN/SQQ-89(V) Antisubmarine Warfare System at Naval Undersea Warfare Center Detachment Norfolk. Mr. Luke is a member of ASNE IEEE (Reliability Society) and ASQC and is an ASQC certified quality engineer and reliability engineer. Derya Alasya Jacobs:is an assistant professor in the Engineering Management Department at Old Dominion University (ODU). She has a B.S. in computer science and an M.S. and Ph.D in engineering management from the University of Missouri-Rolla. Prior to joining ODU Dr. Jacobs worked as a research engineer at the Center for Technology Transfer and Economic Development at the University of Missouri-Rolla. During the same period she served as a consultant in software development for Missouri Enterprise Rolla Missouri. Dr. Jacobs' research interests are in the areas of applied artificial intelligence decision support systems operations research and computer integrated manufacturing. Billie M. Reed:is an assistant professor in the Engineering Management Department at Old Dominion University. He received a B.S. degree in mechanical engineering from Auburn University in 1971. After completing undergraduate studies Dr. Reed was commissioned as an officer in the U.S. Navy where he served in the nuclear submarine force until 1982. Following his military career Dr. Reed worked for nine years as a systems engineer and human-machine interface designer of complex interactive computer based systems for use in aircraft space and ship systems. He received his M.S. and Ph

As technology advances and our dependency on software increases, the requirement to develop the correct means to improve quality in both the deveiopment phase and the maintenance phase of software life cycle support becomes increasingly significant. The focus of this paper is on the dilemma facing software engineering in maintaining quality within the constraints of the maintenance phase. The paper further proposes that the software maintenance process can also be analvzed and improved using statistical process control (SPC) techniques. The methods discussed in this paper have been proposed for use in the Software Maintenance project at NUWC Detachment Norfolk. Upon successful testing at NUWC Detachment Norfolk, they will be forwarded to the AN/SQQ-89(V) (interagencv) Software Quality Evaluation Committee for use by other agencies which are developing and maintaining AN/SQQ-89(V) software.

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POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021)

arXiv

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arXiv 2022年

作者： Suwalska, Aleksandra Tobiasz, Joanna Prazuch, Wojciech Socha, Marek Foszner, Pawel Piotrowski, Damian Gruszczynska, Katarzyna Sliwinska, Magdalena Walecki, Jerzy Popiela, Tadeusz Przybylski, Grzegorz Nowak, Mateusz Fiedor, Piotr Pawlowska, Malgorzata Flisiak, Robert Simon, Krzysztof Zapolska, Gabriela Gizycka, Barbara Szurowska, Edyta Marczyk, Michal Cieszanowski, Andrzej Polanska, Joanna Oronowicz-Jaskowiak, Agnieszka Golebiewski, Bogumil Sliwinska, Magdalena Rataj, Mateusz Chmielarz, Przemyslaw Tur, Adrianna Drabik, Grzegorz Kozub, Justyna Kozanecka, Anna Hildebrandt, Sebastian Krutul-Walenciej, Katarzyna Baron, Jan Jaroszewicz, Jerzy Walecki, Jerzy Wasilewski, Piotr Mazur, Samuel Klaude, Krzysztof Rataj, Katarzyna Golębiewski, Bogumil Pawlowska, Malgorzata Rabiko, Piotr Rajewski, Pawel Gizycka, Barbara Blewaska, Piotr Sznajder, Katarzyna Plesniak, Robert Department of Data Science and Engineering Silesian University of Technology Gliwice Poland Department of Computer Graphics Vision and Digital Systems Silesian University of Technology Gliwice Poland Department of Infectious Diseases and Hepatology Medical University of Silesia Katowice Poland Department of Radiology and Nuclear Medicine Medical University of Silesia Katowice Poland Department of Diagnostic Imaging Voivodship Specialist Hospital Wroclaw Poland Department of Diagnostic Radiology Central Clinical Hospital The Ministry of Internal Affairs and Administration Warsaw Poland Department of Radiology Jagiellonian University Medical College Krakow Poland Department of Lung Diseases Cancer and Tuberculosis Kujawsko-Pomorskie Pulmonology Center Bydgoszcz Poland Department of Radiology Silesian Hospital Cieszyn Poland Department of General and Transplantation Surgery Medical University of Warsaw Warsaw Poland Department of Infectious Diseases and Hepatology Collegium Medicum in Bydgoszcz Nicolaus Copernicus University Torun Poland Department of Infectious Diseases and Hepatology Medical University of Bialystok Bialystok Poland Department of Infectious Diseases and Hepatology Wroclaw Medical University Wroclaw Poland Department of Radiology Czerniakowski Hospital Warsaw Poland Department of Imaging Diagnostics MEGREZ Hospital Tychy Poland 2nd Department of Radiology Medical University of Gdansk Poland Yale Cancer Center Yale School of Medicine New HavenCT United States Department of Radiology I The Maria Sklodowska-Curie National Research Institute of Oncology Warsaw Poland The Maria Sklodowska-Curie National Research Institute of Oncology Warsaw Poland Voivodship Specialist Hospital Wroclaw Poland Prognostic Specialist Clinic Knurow Poland Collegium Medicum of the Jagiellonian University Krakow Poland Medical University of Silesia Katowice Poland Central Clinical Hospital of the Ministry of Interior in Warsaw Warsaw Poland Collegium Medicum

The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. With chest radiographs (CXR) being one of the most common COVID-19 diagnosis methods, many artificial intelligence tools for image-based COVID-19 detection have been developed, often trained on a small number of images from COVID-19-positive patients. Thus, the need for high-quality and well-annotated CXR image databases increased. This paper introduces POLCOVID dataset, containing chest X-ray (CXR) images of patients with COVID-19 or other-type pneumonia, and healthy individuals gathered from 15 Polish hospitals. The original radiographs are accompanied by the preprocessed images limited to the lung area and the corresponding lung masks obtained with the segmentation model. Moreover, the manually created lung masks are provided for a part of POLCOVID dataset and the other four publicly available CXR image collections. POLCOVID dataset can help in pneumonia or COVID-19 diagnosis, while the set of matched images and lung masks may serve for the development of lung segmentation solutions. © 2022, CC BY.

关键词： COVID-19

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GPAW: An open Python package for electronic-structure calculations

arXiv

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arXiv 2023年

作者： Mortensen, Jens Jørgen Larsen, Ask Hjorth Kuisma, Mikael Ivanov, Aleksei V. Taghizadeh, Alireza Peterson, Andrew Haldar, Anubhab Dohn, Asmus Ougaard Schäfer, Christian Jónsson, Elvar Örn Hermes, Eric D. Nilsson, Fredrik Andreas Kastlunger, Georg Levi, Gianluca Jónsson, Hannes Häkkinen, Hannu Fojt, Jakub Kangsabanik, Jiban Sødequist, Joachim Lehtomäki, Jouko Heske, Julian Enkovaara, Jussi Winther, Kirsten Trøstrup Dulak, Marcin Melander, Marko M. Ovesen, Martin Louhivuori, Martti Walter, Michael Gjerding, Morten Lopez-Acevedo, Olga Erhart, Paul Warmbier, Robert Würdemann, Rolf Kaappa, Sami Latini, Simone Boland, Tara Maria Bligaard, Thomas Skovhus, Thorbjørn Susi, Toma Maxson, Tristan Rossi, Tuomas Chen, Xi Schmerwitz, Yorick Leonard A. Schiøtz, Jakob Olsen, Thomas Jacobsen, Karsten Wedel Thygesen, Kristian Sommer CAMd Department of Physics Technical University of Denmark Kgs Lyngby2800 Denmark Riverlane Ltd St Andrews House 59 St Andrews Street CambridgeCB2 3BZ United Kingdom School of Engineering Brown University ProvidenceRI United States Department of Electrical and Computer Engineering Boston University United States Department of Physics Technical University of Denmark Lyngby2800 Denmark Science Institute Faculty of Physical Sciences VR-III University of Iceland Reykjavík107 Iceland Department of Physics Chalmers University of Technology GothenburgSE-412 96 Sweden Science Institute Faculty of Physical Sciences University of Iceland VR-III Reykjavík107 Iceland Quantum-Si 29 Business Park Drive BranfordCT06405 United States CatTheory Department of Physics Technical University of Denmark Kgs Lyngby2800 Denmark Departments of Physics and Chemistry Nanoscience Center University of Jyväskylä JyväskyläFI-40014 Finland Department of Applied Physics Aalto University P.O. Box 11100 Aalto00076 Finland CSC – IT Center for Science Ltd. P.O. Box 405 EspooFI-02101 Finland SUNCAT Center for Interface Science and Catalysis SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Department of Chemistry Nanoscience Center University of Jyväskylä JyväskyläFI-40014 Finland University of Freiburg FIT Freiburg Centre for Interactive Materials and Bioinspired Technologies Georges-Köhler-Allee 105 Freiburg79110 Germany Biophysics of Tropical Diseases Max Planck Tandem Group University of Antioquia UdeA Medellin050010 Colombia School of Physics Mandelstam Institute for Theoretical Physics University of the Witwatersrand 1 Jan Smuts Avenue Johannesburg2001 South Africa Freiburger Materialforschungszentrum Universität Freiburg Stefan-Meier-Straße 21 FreiburgD-79104 Germany Computational Physics Laboratory Tampere University P.O. Box 692 TampereFI-33014 Finland Nanomade Department of Physics Technical University of Denmark Kgs Lyngb

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE) providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation (BSE), variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support of GPU acceleration has been achieved with minor modifications of the GPAW code thanks to the CuPy library. We end the review with an outlook describing some future plans for GPAW. © 2023, CC BY-SA.

关键词： Python

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Quantum Games and interactive Tools for Quantum Technologies Outreach and Education

arXiv

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arXiv 2022年

作者： Seskir, Zeki C. Migdal, Piotr Weidner, Carrie Anupam, Aditya Case, Nicky Davis, Noah Decaroli, Chiara Ercan, İlke Foti, Caterina Gora, Pawel Jankiewicz, Klementyna La Cour, Brian R. Malo, Jorge Yago Maniscalco, Sabrina Naeemi, Azad Nita, Laurentiu Parvin, Nassim Scafirimuto, Fabio Sherson, Jacob F. Surer, Elif Wootton, James Yeh, Lia Zabello, Olga Chiofalo, Marilù Karlsruhe Institute of Technology ITAS Karlstraße 11 Karlsruhe76133 Germany Quantum Flytrap ul. Ceglowska 29 Warsaw01-809 Poland Quantum Engineering Technology Laboratories H.H. Wills Physics Laboratory Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom Georgia Institute of Technology School of Literature Media and Communication 686 Cherry St NW AtlantaGA30313 United States The University of Texas at Austin Center for Quantum Research Applied Research Laboratories 10000 Burnet Rd AustinTX78758 United States National Quantum Computing Center Oxfordshire DidcotOX11 0GD United Kingdom TU Delft Department of Microelectronics Mekelweg 4 Delft2628 CD Netherlands QPlayLearn Aalto University InstituteQ - The Finnish Quantum Institute Department of Applied Physics AaltoFI-00076 11000 Finland Quantum AI Foundation Sanocka 9/103 Warsaw02-110 Poland University of Pisa Department of Physics Largo Bruno Pontecorvo 3 PisaI-56126 Italy University of Helsinki InstituteQ - The Finnish Quantum Institute Department of Physics Helsinki Finland Georgia Institute of Technology School of Electrical and Computer Engineering 777 Atlantic Drive NW AtlantaGA30332 United States Quarks Interactive Strada Bailor 93a Miercurea-Ciuc Harghita4500 Romania IBM Quantum IBM Research - Zurich Säumerstrasse 4 Rüschlikon8803 Switzerland ScienceAtHome Fuglesangs Allé 4 Aarhus8210 Denmark Aarhus University Institute for Physics and Astronomy Ny Munkegade 120 Aarhus8000 Denmark Middle East Technical University Graduate School of Informatics Department of Modeling and Simulation Üniversiteler Mah. Dumlupınar Blv. No:1 Ankara06800 Turkey University of Oxford Department of Computer Science Wolfson Building Parks Road OxfordOX1 3QD United Kingdom IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States Offenburg University of Applied Sciences Department of Business and Industrial Eng

In this article, we provide an extensive overview of a wide range of quantum games and interactive tools that have been employed by the community in recent years. The paper presents selected tools, as described by their developers. The list includes Hello Quantum, Hello Qiskit, Particle in a Box, Psi and Delta, QPlayLearn, Virtual Lab by Quantum Flytrap, Quantum Odyssey, scienceAtHome, and The Virtual Quantum Optics Laboratory. Additionally, we present events for quantum game development: hackathons, game jams, and semester projects. Furthermore, we discuss the Quantum Technologies Education for Everyone (QUTE4E) pilot project, which illustrates an effective integration of these interactive tools with quantum outreach and education activities. Finally, we aim at providing guidelines for incorporating quantum games and interactive tools in pedagogic materials to make quantum technologies more accessible for a wider population. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

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Biomedical image analysis competitions: The state of current participation practice

arXiv

引用

arXiv 2022年

作者： Eisenmann, Matthias Reinke, Annika Weru, Vivienn Tizabi, Minu Dietlinde Isensee, Fabian Adler, Tim J. Godau, Patrick Cheplygina, Veronika Kozubek, Michal Maier-Hein, Klaus Jäger, Paul F. Kopp-Schneider, Annette Maier-Hein, Lena Ali, Sharib Gupta, Anubha Kybic, Jan Noble, Alison de Solórzano, Carlos Ortiz Pachade, Samiksha Petitjean, Caroline Sage, Daniel Wei, Donglai Wilden, Elizabeth Alapatt, Deepak Andrearczyk, Vincent Baid, Ujjwal Bakas, Spyridon Balu, Niranjan Bano, Sophia Bawa, Vivek Singh Bernal, Jorge Bodenstedt, Sebastian Casella, Alessandro Choi, Jinwook Commowick, Olivier Daum, Marie Depeursinge, Adrien Dorent, Reuben Egger, Jan Eichhorn, Hannah Engelhardt, Sandy Ganz, Melanie Girard, Gabriel Hansen, Lasse Heinrich, Mattias Heller, Nicholas Hering, Alessa Huaulmé, Arnaud Kim, Hyunjeong Li, Hongwei Bran Landman, Bennett Li, Jianning Ma, Jun Martel, Anne Martín-Isla, Carlos Menze, Bjoern Nwoye, Chinedu Innocent Oreiller, Valentin Padoy, Nicolas Pati, Sarthak Payette, Kelly Sudre, Carole van Wijnen, Kimberlin Vardazaryan, Armine Vercauteren, Tom Wagner, Martin Wang, Chuanbo Yap, Moi Hoon Yu, Zeyun Yuan, Chun Zenk, Maximilian Zia, Aneeq Zimmerer, David Bao, Rina Choi, Chanyeol Cohen, Andrew Dzyubachyk, Oleh Galdran, Adrian Gan, Tianyuan Guo, Tianqi Gupta, Pradyumna Haithami, Mahmood Ho, Edward Jang, Ikbeom Li, Zhili Luo, Zhengbo Lux, Filip Makrogiannis, Sokratis Müller, Dominik Oh, Young-Tack Pang, Subeen Pape, Constantin Polat, Gorkem Reed, Charlotte Rosalie Ryu, Kanghyun Scherr, Tim Thambawita, Vajira Wang, Haoyu Wang, Xinliang Xu, Kele Yeh, Hung Yeo, Doyeob Yuan, Yixuan Zeng, Yan Zhao, Xin Abbing, Julian Adam, Jannes Adluru, Nagesh Agethen, Niklas Ahmed, Salman Al Khalil, Yasmina Alenyà, Mireia Alhoniemi, Esa An, Chengyang Arega, Tewodros Weldebirhan Avisdris, Netanell Aydogan, Dogu Baran Bai, Yingbin Calisto, Maria Baldeon Basaran, Berke Doga Beetz, Marcel Bian, Hao Blansit, Kevin Bloch, Louise Bohnsack, Robert Bosticardo, Sara Breen, Jack Brudfors, Mikael Brüngel, Raphael Cabezas, Mariano Cacciola, Alb Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Biostatistics Germany Heidelberg Division of Medical Image Computing Germany Heidelberg HI Applied Vision Lab Germany IT University of Copenhagen Copenhagen Denmark Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Heidelberg Interactive Machine Learning Group Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg DKFZ University Hospital Heidelberg Germany School of Computing University of Leeds Leeds United Kingdom SBILab Department of ECE IIIT-Delhi India Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Biomedical Engineering University of Oxford United Kingdom Center for Applied Medical Research Pamplona Spain Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Université de Rouen Normandie France Lausanne Switzerland School of Engineering and Applied Science Harvard University United States ICube University of Strasbourg CNRS France Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Techno-Pôle 3 Sierre3960 Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Rue du Bugnon 46 LausanneCH-1011 Switzerland University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington United States Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Visual Artificial Intelligence Lab Oxford Brookes University Oxford United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Spain Dresden Fetscherstraße 74 PF 64 Dresden01307 Germany

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps. © 2022, CC BY.

关键词： Benchmarking

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A Temporally and Spatially Explicit, Mechanistic Estimation of Ragweed Pollen Concentrations Across Europe

SSRN

引用

SSRN 2023年

作者： Makra, László Matyasovszky, István Tusnády, Gábor Ziska, Lewis H. Hess, Jeremy J. Nyúl, László G. Chapman, Daniel S. Coviello, Luca Gobbi, Andrea Jurman, Giuseppe Furlanello, Cesare Brunato, Mauro Damialis, Athanasios Charalampopoulos, Athanasios Müller-Schärer, Heinz Schneider, Norbert Szabó, Bence Sümeghy, Zoltán Páldy, Anna Magyar, Donát Bergmann, Karl-Christian Deák, Áron József Mikó, Edit Thibaudon, Michel Oliver, Gilles Albertini, Roberto Bonini, Maira Šikoparija, Branko Radišić, Predrag Mitrović Josipović, Mirjana Gehrig, Regula Severova, Elena Rodinkova, Victoria Palamarchuk, Olena Stjepanović, Barbara Ianovici, Nicoleta Berger, Uwe Kofol Seliger, Andreja Rybníček, Ondřej Myszkowska, Dorota Dąbrowska-Zapart, Katarzyna Majkowska-Wojciechowska, Barbara Weryszko-Chmielewska, Elzbieta Grewling, Lukasz Rapiejko, Piotr Malkiewicz, Malgorzata Šaulienė, Ingrida Shalaboda, Valentina Prykhodo, Olexander Maleeva, Anna Ščevková, Jana Bullock, James M. Institute of Economics and Rural Development Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Department of Meteorology Eötvös Loránd University P.O.B. 32 Budapest1518 Hungary Alfréd Rényi Institute of Mathematics P.O.B 127 Budapest1364 Hungary Mailman School of Public Health Columbia University New YorkNY10032 United States Department of Global Health University of Washington SeattleWA98105 United States Department of Image Processing and Computer Graphics University of Szeged P.O.B. 652 Szeged6701 Hungary Biological and Environmental Sciences Faculty of Natural Sciences University of Stirling Scotland StirlingFK9 4LA United Kingdom University of Trento Enogis s.r.l. Trento Italy Bruno Kessler Foundation Trento Italy HK3 Lab Orobix Life Srl Rovereto Bergamo Italy Department of Information Engineering and Computer Science University of Trento Trento Italy Terrestrial Ecology and Climate Change Department of Ecology School of Biology Aristotle University of Thessaloniki ThessalonikiGR-54124 Greece Departement of Biology Unit of Ecology and Evolution University of Fribourg FribourgCH-1700 Switzerland National Institute of Environmental Health Albert Flórián út 2-6 Budapest1097 Hungary Institute of Allergology Charité Hindenburgdamm 30 Berlin12203 Germany Institute of Animal Science and Wildlife Management Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Réseau National de Surveillance Aérobiologique 11 chemin de la Creuzille Le Plat du Pin Brussieu696905 France Laboratory of Hygiene and Aerobiology Department of Medicine and Surgery University of Parma U.O. Medicina Interna di Continuità Azienda Ospedaliero-Universitaria di Parma Via Gramsci 14 Parma43126 Italy Hygiene and Public Health Service via Spagliardi 19 Parabiago Milan20015 Italy BioSensе Institute Research Institute for Information Technologies in Biosystems University of Novi Sad Dr

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant’s reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating annual total pollen concentrations than those of the GM approach. These are the first published modeled maps using altitude correction and phenology to recover missing pollen information. We created a web page (http://***/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions. © 2023, The Authors. All rights reserved.

关键词： Climate change

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Imaging and Molecular Annotation of Xenographs and Tumours (IMAXT): High throughput data and analysis infrastructure

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Biological imaging 2023年 3卷 e11页

作者： Eduardo A González-Solares Ali Dariush Carlos González-Fernández Aybüke Küpcü Yoldaş Alireza Molaeinezhad Mohammad Al Sa'd Leigh Smith Tristan Whitmarsh Neil Millar Nicholas Chornay Ilaria Falciatori Atefeh Fatemi Daniel Goodwin Laura Kuett Claire M Mulvey Marta Páez Ribes Fatime Qosaj Andrew Roth Ignacio Vázquez-García Spencer S Watson Jonas Windhager Samuel Aparicio Bernd Bodenmiller Ed Boyden Carlos Caldas Owen Harris Sohrab P Shah Simon Tavaré Dario Bressan Gregory J Hannon Nicholas A Walton Institute of Astronomy University of Cambridge Cambridge United Kingdom. CRUK Cambridge Institute Li Ka Shing Centre University of Cambridge Cambridge United Kingdom. McGovern Institute Department of Biological Engineering Massachusetts Institute of Technology Cambridge MA USA. McGovern Institute Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge MA USA. Department of Quantitative Biomedicine University of Zurich Zurich Switzerland. Institute of Molecular Life Sciences University of Zurich Zurich Switzerland. Department of Computer Science University of British Columbia Vancouver BC Canada. Herbert and Florence Irving Institute for Cancer Dynamics Columbia University New York NY USA. Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA. Department of Oncology and Ludwig Institute for Cancer Research University of Lausanne Lausanne Switzerland. Department of Pathology and Laboratory Medicine University of British Columbia Vancouver BC Canada. Howard Hughes Medical Institute Department of Physics Harvard University Cambridge MA USA. Howard Hughes Medical Institute Department of Chemistry and Chemical Biology Harvard University Cambridge MA USA. Cambridge Breast Unit Addenbrooke's Hospital Cambridge University Hospital NHS Foundation Trust and NIHR Cambridge Biomedical Research Centre Cambridge United Kingdom. Súil Interactive Dublin Ireland. New York Genome Center New York NY USA.

With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.

关键词： Data management data processing and analysis fluorescence microscopy imaging mass cytometry

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Preface

Proceedings of the 11th European Conference on Games Based L...

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Proceedings of the 11th European Conference on Games Based Learning, ECGBL 2017 2017年 viii-x页

作者： Pivec, Maja Gründler, Josef Admiraal, Wilfried Alemi, Minoo All, Anissa Almeida, Ana Amresh, Ashish Arnab, Sylvester Ask, Kristine Avouris, Nikolaos Awwal, Nafisa Hauge, Jannicke Baalsrud Badau, Dana Barata, Ana Barendregt, Wolmet Basaiawmoit, Rajiv Bellotti, Francesco Blanchfield, Peter Borit, Melania Boskic, Natasha Boyle, Liz Brady, Mairead Bratitsis, Tharrenos Brinch, Sara Brom, Cyril Brooks, Anthony Brown, David Brox, Ellen Busch, Carsten Caldeira, Carlos Callies, Sophie Cardoso, Tiago Carron, Thibault Casimir, Rommert De Castro, António Vieira Chang, Maiga Charalambis, Dimitris Charles, Darryl Charlier, Nathalie Chee, Yam San Chen, Ming-Puu Chiarello, Fabio Connolly, Thomas Crockett, Larry Darwish, Tamer Sigurdardottir, Helga Deliyannis, Ioannis Demirbilek, Muhammet Sigurdardottir, Helga Dis Duin, Heiko Dyer, Ronald Edgar, David Ejsing-Duun, Stine Escudeiro, Paula Felicia, Patrick Fesakis, Georgios Figueira, Ana Paula Fotaris, Panagiotis Fujimoto, Toru George, Sebastien Georgiadis, Panagiotis Gerodetti, Natalia Giannakoulopoulos, Andreas Gjedde, Lisa Goebel, Stefan Gomez-Martin, Pedro Pablo Gouscos, Dimitris Grigoriadou, Maria Guralnick, David Guttormsgaard, Vibeke Habgood, Jacob Hainey, O. Hanghoj, Thorkild Hawlitschek, Anja Hemben, Terseer Hlavacs, Helmut Hommedal, Silje Hole Hollins, Paul Idrus, Rozhan Wang, Alf Inge Ismail, Marina Jans, Ruben Juzeleniene, Saule Kalavassis, Fragiskos Kalogiannakis, Michail Karakostas, Anastasios Katzlinger-Felhofer, Elisabeth Ketamo, Harri Ketelhut, Diane Jass Kickmeier-Rust, Michael Kiili, Kristian Koeppen, Veit Kolås, Line Kordaki, Maria Korkut, Safak Kourti, Evangelia Li, Ken Lukosch, Heide MaCleod, Hamish Magnussen, Rikke Majgaard, Gunver Marchetti, Emanuela Marques, Bertil Marty, Jean-Charles Marzantowicz, Lukasz Mehm, Florian Meimaris, Michail Michel, Christine Moffat, David Montero-Fleta, Begoña Moseley, Alexander Mota, Dulce Mozelius, Peter Nadolski, Rob Nelson, Brian Neville, Karen Ng, Annie W.Y. Nixon, Darren Nocchi, Susanna Broin, Daire O. O'Mullane, John Skev Leiden University Leiden Netherlands Sharif University of Technology Iran IMinds-MICT-Ghent University Belgi Belgium Universidade de Coimbra Portugal Arizona State University United States Coventry University United Kingdom Norway University of Patras Greece University of Melbourne Australia Bremer Institut for Produktion und Logistik Germany University of Medicine and Pharmacy of Targu Mures Romania Portugal Gothenburg University Department of Applied IT Sweden Aarhus University Denmark University of Genoa Italy School of Computer Science University of Nottingham United Kingdom UiT - The Arctic Univeristy of Norway University of Troms Norway University of British Columbia Canada Univesity of the West of Scotland United Kingdom Open University of Cyprus Greece ESCP Europe France Trinity College Dublin Ireland University of Western Macedonia Greece KDU University College Malaysia Charles University Prague Czech Republic Aalborg University Denmark Nottingham Trent University United Kingdom Nord-Trøndelag University College Steinkjer Norway University of Applied Sciences HTW-Berlin Germany University of Evora Portugal UQAM Canada Universidade Nova de Lisboa Portugal LIP6 - Paris Université de Savoie France Tilburg University Netherlands Open University of the Natherlands Nederland United States Athabasca University Canada University of Athens Greece University of Ulster United Kingdom Catholic University of Leuven Belgium Nanyang Technological University Singapore Singapore National Taiwan Normal University Taiwan Italy University of West of Scotland United Kingdom Augsburg College United States Brunel University United Kingdom Ionian University Greece Suleyman Demirel University Turkey Glamorgan University United Kingdom BIBA - Bremer Institut for Produktion und Logistik GmbH Germany Managment School University of Liverpool United Kingdom Glasgow Caledonian University United Kingdom Aalborg Univ. Copenhagen Denmark Portugal Waterford Institute of

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