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Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease

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Computers in Biology and Medicine 2024年 176卷 108588-108588页

作者： Gómez-Pascual, Alicia Naccache, Talel Xu, Jin Hooshmand, Kourosh Wretlind, Asger Gabrielli, Martina Lombardo, Marta Tiffany Shi, Liu Buckley, Noel J. Tijms, Betty M. Vos, Stephanie J.B. ten Kate, Mara Engelborghs, Sebastiaan Sleegers, Kristel Frisoni, Giovanni B. Wallin, Anders Lleó, Alberto Popp, Julius Martinez-Lage, Pablo Streffer, Johannes Barkhof, Frederik Zetterberg, Henrik Visser, Pieter Jelle Lovestone, Simon Bertram, Lars Nevado-Holgado, Alejo J. Gualerzi, Alice Picciolini, Silvia Proitsi, Petroula Verderio, Claudia Botía, Juan A. Legido-Quigley, Cristina Department of Information and Communications Engineering Faculty of Informatics University of Murcia Murcia Spain Steno Diabetes Center Copenhagen Herlev Denmark Department of Data Science City University of London United Kingdom Institute of Pharmaceutical Science King's College London London United Kingdom CNR Institute of Neuroscience Vedano al Lambro20854 Italy School of Medicine and Surgery University of Milano-Bicocca 20126 Italy Oxford United Kingdom Department of Psychiatry University of Oxford United Kingdom Kavli Institute for Nanoscience Discovery Denmark Alzheimer Center VU University Medical Center Amsterdam Netherlands Department of Psychiatry and Neuropsychology Alzheimer Centrum Limburg Maastricht University Maastricht Netherlands Department of Biomedical Sciences University of Antwerp Antwerp Belgium Vrije Universiteit Brussel Brussels Belgium Complex Genetics Group VIB Center for Molecular Neurology VIB Antwerp Belgium Institute Born-Bunge Department of Biomedical Sciences University of Antwerp Antwerp Belgium University of Geneva Geneva Switzerland IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli Brescia Italy Institute of Neuroscience and Physiology Sahlgrenska Academy at University of Gothenburg Gothenburg Sweden Barcelona Spain Old age psychiatry University Hospital of Lausanne University of Lausanne Switzerland Department of Geriatric Psychiatry University Hospital of Psychiatry Zürich University of Zürich Switzerland CITA-Alzheimer Foundation San Sebastian Spain AC Immune SA formerly Janssen R&D LLC. Beerse Belgium at the time of study conduct Lausanne Switzerland Department of Radiology and Nuclear Medicine Amsterdam UMC Vrije Universiteit Netherlands Queen Square Institute of Neurology and Centre for Medical Image Computing University College London United Kingdom Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden Department of Psychiatry and Neurochemistry Institute of

Background: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. Method: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. Results: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. Conclusions: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways. © 2024 The Authors

关键词： Metabolites

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SARS-CoV-2 Wastewater Genomic Surveillance: Approaches, Challenges, and Opportunities

arXiv

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arXiv 2023年

作者： Munteanu, Viorel Saldana, Michael A. Dreifuss, David Ouyang, Wenhao O. Ferdous, Jannatul Mohebbi, Fatemeh Schlueter, Jessica Ciorba, Dumitru Bostan, Viorel Gordeev, Victor Su, Justin Maine Kasianchuk, Nadiia Sharma, Nitesh Kumar Knyazev, Sergey Aßmann, Eva Lobiuc, Andrei Covasa, Mihai Crandall, Keith A. Wu, Nicholas C. Mason, Christopher E. Tierney, Braden T. Lucaci, Alexander G. Ophoff, Roel A. Gibas, Cynthia Rzymski, Piotr Skums, Pavel Solo-Gabriele, Helena Niko, Beerenwinkel Zelikovsky, Alex Hölzer, Martin Smith, Adam Mangul, Serghei Department of Computers Informatics and Microelectronics Technical University of Moldova Chisinau2045 Moldova Department of Biological and Morphofunctional Sciences College of Medicine and Biological Sciences Stefan cel Mare University of Suceava Suceava720229 Romania Astani Department of Civil and Environmental Engineering University of Southern California 3620 South Vermont Avenue Los AngelesCA90089 United States Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland SIB Swiss Institute of Bioinformatics Lausanne Switzerland Department of Biochemistry University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Bioinformatics and Genomics University of North Carolina Charlotte United States Department of Clinical Pharmacy School of Pharmacy University of Southern California 1540 Alcazar Street Los AngelesCA90033 United States Department of Computers Informatics and Microelectronics Technical University of Moldova Chisinau2045 Moldova Titus Family Department of Clinical Pharmacy USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences University of Southern California Los AngelesCA90089 United States Faculty of Biology Adam Mickiewicz University Poznan61-712 Poland Faculty of Pharmacy Bogomolets National University Kyiv01601 Ukraine Kyiv School of Economics Kyiv02000 Ukraine Titus Family Department of Clinical Pharmacy USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences University of Southern California 1540 Alcazar Street Los AngelesCA90033 United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Method Development and Research Infrastructure Robert Koch Institute Berlin13353 Germany Robert Koch Institute Berlin13353 Germany College of Medicine and Biological Sciences University of Suceava Suceava720229 Romania College of Osteopathic Medicine of the Pacific

During the SARS-CoV-2 pandemic, wastewater-based genomic surveillance (WWGS) emerged as an efficient virus surveillance tool capable of accounting for asymptomatic cases, identifying known and novel mutations, and assigning them to lineages and sublineages of the virus. WWGS also offers the potential to uncover novel or cryptic lineages, although identifying and defining these lineages solely from wastewater presents challenges. Besides the significant advantages of WWGS for monitoring SARS-CoV-2 viral spread, technical challenges remain, including coverage dropouts and poor quality of wastewater sequencing (WWS) data due to viral RNA fragmentation and degradation. Subsequently, WWGS analysis requires advanced computational tools that are yet to be developed and benchmarked. The existing bioinformatics tools used to analyze WWS data are often based on previously developed computational methods for variant calling, de-novo assembly, or quantifying the expression of transcripts. Those methods were not specifically developed for WWS data and must be optimized to address unique challenges associated with wastewater analysis. While specialized tools for analyzing WWS data have also been developed recently, it remains to be seen how they will perform given the ongoing evolution of SARS-CoV-2 and the decline in testing and patient-based genomic surveillance. Here, we explore opportunities and challenges associated with WWGS, including aspects such as sample preparation, sequencing technology, and bioinformatics methods. We also highlight its potential role in monitoring infectious diseases and informing public health responses by complementing other surveillance systems. We also critically examine the practical applications and ethical considerations of WWGS, emphasizing the need for a robust framework and its translation into sustainable wastewater surveillance programs to fully realize its potential for public health. © 2023, CC BY.

关键词： Coronavirus

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Motivation of DDOS attack-aware link assignment between switches to SDN controllers 1

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10th International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage, SpaCCS 2017

作者： Ali, Sameer Tan, Saw Chin Kwang, Lee Ching Yusoff, Zulfadzli Haque, Reazul Kaspin, Ir. Rizaludin Ziri, Salvatore Renato Faculty of Computing and Informatics Multimedia University Cyberjaya63100 Malaysia Faculty of Engineering Multimedia University Cyberjaya63100 Malaysia Telekom Malaysia Research and Development TM Innovation Centre Lingkaran Tecknokrat Cyberjaya Malaysia

ISBN: (数字)9783319723891

ISBN: (纸本)9783319723884

In this paper, we are going to investigate the attack-aware link assignment for the connectivity of switches to SDN controllers under DDoS attacks. The infected or broken link of switch to controller will create disconnection in network and interruption in services. As a result, such as reliability and availability will be impaired. Therefore, on the basis of the analysis, we are going to highlight the importance of the attack-aware link-assignment for SDN switches to controllers. © 2017, Springer International Publishing AG.

关键词： Controllers

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Experience of using the WELCOME remote monitoring system on patients with COPD and comorbidities 3rd

Experience of using the WELCOME remote monitoring system on ...

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3rd International Conference on Biomedical and Health informatics, ICBHI 2017

作者： Kaimakamis, E. Perantoni, E. Serasli, E. Kilintzis, V. Chouvarda, I. Kayyali, R. Nabhani-Gebara, S. Chang, J. Siva, R. Hibbert, R. Philips, N. Karamitros, D. Raptopoulos, A. Frerichs, I. Wacker, J. Maglaveras, N. Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Ag. Dimitriou street Thessaloniki Greece Pulmonary Department General Hospital "G. Papanikolaou" Thessaloniki Greece Faculty of Science Engineering and Computing Kingston University Kingston-upon-Thames United Kingdom Chest Clinic and Research and Development Croydon University Hospital Croydon United Kingdom EXUS Company Athens Greece Department of Anesthesiology and Intensive Care Medicine University Medical Centre Schleswig-Holstein Kiel Germany CSEM Company Neuchatel Switzerland

ISBN: (纸本)9789811074189

The WELCOME system is an innovative telemonitoring system designed to provide constant monitoring of COPD patients also suffering from other major comorbidities. It consists of a sensors vest capable of recording various vital parameters in real time and transmitting them to the cloud via a tablet PC and wireless connection. In addition, peripheral devices record extra physiological data which is coupled with responses to validated health questionnaires that the patient responds to via the tablet. A dedicated medical decision support system (DSS) and a medical professional user interface support the system in providing automated detection of abnormal conditions. The obtained signals included Heart and Respiratory Rate, Body Posture, SpO2, multi-lead ECG, Auscultation and Electric Impedance Tomography. The system is tested with pilot studies in two European countries, Greece and UK. The preliminary results from the Greek pilot study are presented in this paper, highlighting the main findings from the first operational use of the WELCOME infrastructure. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Decision support systems

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Android library for recognition of activities of daily living: Implementation considerations, challenges, and solutions

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Open Bioinformatics Journal 2018年第1期11卷 61-88页

作者： Pires, Ivan Miguel Teixeira, Maria Canavarro Pombo, Nuno Garcia, Nuno M. Flórez-Revuelta, Francisco Spinsante, Susanna Goleva, Rossitza Zdravevski, Eftim Instituto de Telecomunicações Universidade da Beira Interior Covilhã Portugal Altran portugal Lisbon Portugal ALLab - Assisted Living Computing and Telecommunications Laboratory Computing Science Department Universidade da Beira Interior Covilhã Portugal UTC de Recursos Naturais e Desenvolvimento Sustentável Polytechnique Institute of Castelo Branco Castelo Branco Portugal CERNAS - Research Centre for Natural Resources Environment and Society Polytechnique Institute of Castelo Branco Castelo Branco Portugal Department of Computer Technology Universidad de Alicante Alicante Spain Department of Information Engineering Marche Polytechnic University Ancona Italy Department of Informatics New Bulgarian University Sofia Bulgaria Faculty of Computer Science and Engineering University Ss Cyril and Methodius Skopje North Macedonia

Background: Off-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the development of Ambient Assisted Living (AAL) systems, using mobile devices for the acquisition of the different types of data related to the physical and physiological conditions of the subjects and the environments. Mobile devices with the Android Operating Systems are the least expensive and exhibit the biggest market while providing a variety of models and onboard sensors. Objective: This paper describes the implementation considerations, challenges and solutions about a framework for the recognition of ADL and the environments, provided as an Android library. The framework is a function of the number of sensors available in different mobile devices and utilizes a variety of activity recognition algorithms to provide a rapid feedback to the user. Methods: The Android library includes data fusion, data processing, features engineering and classification methods. The sensors that may be used are the accelerometer, the gyroscope, the magnetometer, the Global Positioning System (GPS) receiver and the microphone. The data processing includes the application of data cleaning methods and the extraction of features, which are used with Deep Neural Networks (DNN) for the classification of ADL and environment. Throughout this work, the limitations of the mobile devices were explored and their effects have been minimized. Results: The implementation of the Android library reported an overall accuracy between 58.02% and 89.15%, depending on the number of sensors used and the number of ADL and environments recognized. Compared with the results available in the literature, the performance of the library reported a mean improvement of 2.93%, and they do not differ at the maximum found in prior work, that based on the Student’s t-test. Conclusion: Thi

关键词： Activities of daily living Android library Artificial neural networks Data fusion Mobile devices Pattern recognition Recognition Sensors

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Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study

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The Lancet Digital Health 2021年第5期3卷 e317-e329页

作者： Tan, Tien-En Anees, Ayesha Chen, Cheng Li, Shaohua Xu, Xinxing Li, Zengxiang Xiao, Zhe Yang, Yechao Lei, Xiaofeng Ang, Marcus Chia, Audrey Lee, Shu Yen Wong, Edmund Yick Mun Yeo, Ian Yew San Wong, Yee Ling Hoang, Quan V Wang, Ya Xing Bikbov, Mukharram M Nangia, Vinay Jonas, Jost B Chen, Yen-Po Wu, Wei-Chi Ohno-Matsui, Kyoko Rim, Tyler Hyungtaek Tham, Yih-Chung Goh, Rick Siow Mong Lin, Haotian Liu, Hanruo Wang, Ningli Yu, Weihong Tan, Donald Tiang Hwee Schmetterer, Leopold Cheng, Ching-Yu Chen, Youxin Wong, Chee Wai Cheung, Gemmy Chui Ming Saw, Seang-Mei Wong, Tien Yin Liu, Yong Ting, Daniel Shu Wei Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Duke-National University of Singapore Medical School Singapore Institute of High Performance Computing Agency for Science Technology and Research (A*STAR) Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Essilor International Singapore Department of Ophthalmology Columbia University New York NY United States Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore Beijing Institute of Ophthalmology Beijing Tongren Eye Center Beijing Tongren Hospital Capital Medical University Beijing China Ufa Eye Research Institute Ufa Bashkortostan Russian Federation Suraj Eye Institute Nagpur India Department of Ophthalmology Medical Faculty Mannheim Heidelberg University Germany Department of Ophthalmology Chang Gung Memorial Hospital Taoyuan Taiwan Department of Ophthalmology and Visual Science Tokyo Medical and Dental University Tokyo Japan Zhongshan Ophthalmic Center Sun Yat-sen University Guangzhou China Peking Union Medical College Hospital Beijing China Department of Clinical Pharmacology and Center for Medical Physics and Biomedical Engineering Medical University of Vienna Austria Institute of Molecular and Clinical Ophthalmology Basel Switzerland

Background: By 2050, almost 5 billion people globally are projected to have myopia, of whom 20% are likely to have high myopia with clinically significant risk of sight-threatening complications such as myopic macular degeneration. These are diagnoses that typically require specialist assessment or measurement with multiple unconnected pieces of equipment. Artificial intelligence (AI) approaches might be effective for risk stratification and to identify individuals at highest risk of visual loss. However, unresolved challenges for AI medical studies remain, including paucity of transparency, auditability, and traceability. Methods: In this retrospective multicohort study, we developed and tested retinal photograph-based deep learning algorithms for detection of myopic macular degeneration and high myopia, using a total of 226 686 retinal images. First we trained and internally validated the algorithms on datasets from Singapore, and then externally tested them on datasets from China, Taiwan, India, Russia, and the UK. We also compared the performance of the deep learning algorithms against six human experts in the grading of a randomly selected dataset of 400 images from the external datasets. As proof of concept, we used a blockchain-based AI platform to demonstrate the real-world application of secure data transfer, model transfer, and model testing across three sites in Singapore and China. Findings: The deep learning algorithms showed robust diagnostic performance with areas under the receiver operating characteristic curves [AUC] of 0·969 (95% CI 0·959–0·977) or higher for myopic macular degeneration and 0·913 (0·906–0·920) or higher for high myopia across the external testing datasets with available data. In the randomly selected dataset, the deep learning algorithms outperformed all six expert graders in detection of each condition (AUC of 0·978 [0·957–0·994] for myopic macular degeneration and 0·973 [0·941–0·995] for high myopia). We also successfully used b

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Search for Gamma-Ray Spectral Lines from Dark Matter Annihilation up to 100 TeV toward the Galactic Center with MAGIC

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Physical Review Letters 2023年第6期130卷 061002-061002页

作者： H. Abe S. Abe V. A. Acciari T. Aniello S. Ansoldi L. A. Antonelli A. Arbet Engels C. Arcaro M. Artero K. Asano D. Baack A. Babić A. Baquero U. Barres de Almeida J. A. Barrio I. Batković J. Baxter J. Becerra González W. Bednarek E. Bernardini M. Bernardos A. Berti J. Besenrieder W. Bhattacharyya C. Bigongiari A. Biland O. Blanch G. Bonnoli Ž. Bošnjak I. Burelli G. Busetto R. Carosi M. Carretero-Castrillo G. Ceribella Y. Chai A. Chilingarian S. Cikota E. Colombo J. L. Contreras J. Cortina S. Covino G. D’Amico V. D’Elia P. Da Vela F. Dazzi A. De Angelis B. De Lotto A. Del Popolo M. Delfino J. Delgado C. Delgado Mendez D. Depaoli F. Di Pierro L. Di Venere E. Do Souto Espiñeira D. Dominis Prester A. Donini D. Dorner M. Doro D. Elsaesser G. Emery V. Fallah Ramazani L. Fariña A. Fattorini L. Font C. Fruck S. Fukami Y. Fukazawa R. J. García López M. Garczarczyk S. Gasparyan M. Gaug J. G. Giesbrecht Paiva N. Giglietto F. Giordano P. Gliwny N. Godinović J. G. Green D. Green D. Hadasch A. Hahn T. Hassan L. Heckmann J. Herrera D. Hrupec M. Hütten R. Imazawa T. Inada R. Iotov K. Ishio I. Jiménez Martínez J. Jormanainen D. Kerszberg Y. Kobayashi H. Kubo J. Kushida A. Lamastra D. Lelas F. Leone E. Lindfors L. Linhoff S. Lombardi F. Longo R. López-Coto M. López-Moya A. López-Oramas S. Loporchio A. Lorini E. Lyard B. Machado de Oliveira Fraga P. Majumdar M. Makariev G. Maneva N. Mang M. Manganaro S. Mangano K. Mannheim M. Mariotti M. Martínez A. Mas Aguilar D. Mazin S. Menchiari S. Mender S. Mićanović D. Miceli T. Miener J. M. Miranda R. Mirzoyan E. Molina H. A. Mondal A. Moralejo D. Morcuende V. Moreno T. Nakamori C. Nanci L. Nava V. Neustroev M. Nievas Rosillo C. Nigro K. Nilsson K. Nishijima T. Njoh Ekoume K. Noda S. Nozaki Y. Ohtani T. Oka J. Otero-Santos S. Paiano M. Palatiello D. Paneque R. Paoletti J. M. Paredes L. Pavletić M. Persic M. Pihet F. Podobnik P. G. Prada Moroni E. Prandini G. Principe C. Priyadarshi I. Puljak W. Rhode M. Ribó J. Rico C. Righi A. Rugliancich N. Sahakyan T. Saito S. Sakurai K. Satalecka F. G. Sat Japanese MAGIC Group: Institute for Cosmic Ray Research (ICRR) The University of Tokyo Kashiwa 277-8582 Chiba Japan Instituto de Astrofísica de Canarias and Departamento de Astrofísica Universidad de La Laguna E-38200 La Laguna Tenerife Spain National Institute for Astrophysics (INAF) I-00136 Rome Italy Università di Udine and INFN Trieste I-33100 Udine Italy Max-Planck-Institut für Physik D-80805 München Germany Università di Padova and INFN I-35131 Padova Italy Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology (BIST) E-08193 Bellaterra (Barcelona) Spain Technische Universität Dortmund D-44221 Dortmund Germany Croatian MAGIC Group: University of Zagreb Faculty of Electrical Engineering and Computing (FER) 10000 Zagreb Croatia IPARCOS Institute and EMFTEL Department Universidad Complutense de Madrid E-28040 Madrid Spain Centro Brasileiro de Pesquisas Físicas (CBPF) 22290-180 URCA Rio de Janeiro (RJ) Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics 90-236 Lodz Poland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n 18008 Granada Spain Deutsches Elektronen-Synchrotron (DESY) D-15738 Zeuthen Germany ETH Zürich CH-8093 Zürich Switzerland Università di Pisa and INFN Pisa I-56126 Pisa Italy Universitat de Barcelona ICCUB IEEC-UB E-08028 Barcelona Spain Armenian MAGIC Group: A. Alikhanyan National Science Laboratory 0036 Yerevan Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas E-28040 Madrid Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group: INFN Sezione di Catania and Dipartimento di Fisica e Astronomia University of Catania I-95123 Catania Italy INFN MAGIC Group: INFN Sezione di Torino and Università degli Studi di Torino I-10125 Torino Italy INFN MAGIC Group: INFN Sezione di Bari and Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari I-70125 Bari Italy

Linelike features in TeV γ rays constitute a “smoking gun” for TeV-scale particle dark matter and new physics. Probing the Galactic Center region with ground-based Cherenkov telescopes enables the search for TeV spectral features in immediate association with a dense dark matter reservoir at a sensitivity out of reach for satellite γ-ray detectors, and direct detection and collider experiments. We report on 223 hours of observations of the Galactic Center region with the MAGIC stereoscopic telescope system reaching γ-ray energies up to 100 TeV. We improved the sensitivity to spectral lines at high energies using large-zenith-angle observations and a novel background modeling method within a maximum-likelihood analysis in the energy domain. No linelike spectral feature is found in our analysis. Therefore, we constrain the cross section for dark matter annihilation into two photons to ⟨σv⟩≲5×10−28 cm3 s−1 at 1 TeV and ⟨σv⟩≲1×10−25 cm3 s−1 at 100 TeV, achieving the best limits to date for a dark matter mass above 20 TeV and a cuspy dark matter profile at the Galactic Center. Finally, we use the derived limits for both cuspy and cored dark matter profiles to constrain supersymmetric wino models.

关键词： Dark matter Gamma ray astronomy Particle dark matter Milky Way Cosmic ray & astroparticle detectors Cosmic rays & astroparticles Electromagnetic radiation astronomy Telescopes

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Comparative and demographic analysis of orang-utan genomes (vol 469, pg 529, 2011)

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NATURE 2022年第7924期608卷 E36-E36页

作者： Locke, Devin P. Hillier, LaDeana W. Warren, Wesley C. Worley, Kim C. Nazareth, Lynne V. Muzny, Donna M. Yang, Shiaw-Pyng Wang, Zhengyuan Chinwalla, Asif T. Minx, Pat Mitreva, Makedonka Cook, Lisa Delehaunty, Kim D. Fronick, Catrina Schmidt, Heather Fulton, Lucinda A. Fulton, Robert S. Nelson, Joanne O. Magrini, Vincent Pohl, Craig Graves, Tina A. Markovic, Chris Cree, Andy Dinh, Huyen H. Hume, Jennifer Kovar, Christie L. Fowler, Gerald R. Lunter, Gerton Meader, Stephen Heger, Andreas Ponting, Chris P. Marques-Bonet, Tomas Alkan, Can Chen, Lin Cheng, Ze Kidd, Jeffrey M. Eichler, Evan E. White, Simon Searle, Stephen Vilella, Albert J. Chen, Yuan Flicek, Paul Ma, Jian Raney, Brian Suh, Bernard Burhans, Richard Herrero, Javier Haussler, David Faria, Rui Fernando, Olga Darre, Fleur Farre, Domenec Gazave, Elodie Oliva, Meritxell Navarro, Arcadi Roberto, Roberta Capozzi, Oronzo Archidiacono, Nicoletta Della Valle, Giuliano Purgato, Stefania Rocchi, Mariano Konkel, Miriam K. Walker, Jerilyn A. Ullmer, Brygg Batzer, Mark A. Smit, Arian F. A. Hubley, Robert Casola, Claudio Schrider, Daniel R. Hahn, Matthew W. Quesada, Victor Puente, Xose S. Ordonez, Gonzalo R. Lopez-Otin, Carlos Vinar, Tomas Brejova, Brona Ratan, Aakrosh Harris, Robert S. Miller, Webb Kosiol, Carolin Lawson, Heather A. Taliwal, Vikas Martins, Andre L. Siepel, Adam RoyChoudhury, Arindam Ma, Xin Degenhardt, Jeremiah Bustamante, Carlos D. Gutenkunst, Ryan N. Mailund, Thomas Dutheil, Julien Y. Hobolth, Asger Schierup, Mikkel H. Ryder, Oliver A. Yoshinaga, Yuko de Jong, Pieter J. Weinstock, George M. Rogers, Jeffrey Mardis, Elaine R. Gibbs, Richard A. Wilson, Richard K. The Genome Center at Washington University Washington University School of Medicine Saint Louis Missouri USA Human Genome Sequencing Center Department of Molecular and Human Genetics Baylor College of Medicine One Baylor Plaza Houston Texas USA MRC Functional Genomics Unit and Department of Physiology Anatomy and Genetics University of Oxford Le Gros Clark Building Oxford UK Wellcome Trust Centre for Human Genetics Oxford UK Department of Genome Sciences University of Washington School of Medicine Seattle Washington USA IBE Institut de Biologia Evolutiva (UPF-CSIC) Universitat Pompeu Fabra PRBB Doctor Aiguader 88 Barcelona Spain Howard Hughes Medical Institute Seattle Washington USA CIBIO Centro de Investigação em Biodiversidade e Recursos Genéticos Universidade do Porto Campus Agrário de Vairão Vairão Portugal Instituto de Tecnologia Química e Biológica Universidade Nova de Lisboa Oeiras Portugal ICREA (Institució Catalana de Recerca i Estudis Avançats) and INB (Instituto Nacional de Bioinformática) PRBB Doctor Aiguader 88 Barcelona Spain Wellcome Trust Sanger Institute Wellcome Trust Genome Campus Cambridge UK European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton Cambridge UK Center for Biomolecular Science and Engineering University of California Santa Cruz California USA Center for Comparative Genomics and Bioinformatics Penn State University University Park Pennsylvania USA Department of Biology University of Bari Bari Italy Department of Biology University of Bologna Bologna Italy Department of Biological Sciences Louisiana State University Baton Rouge Louisiana USA Center for Computation and Technology Department of Computer Sciences Louisiana State University Baton Rouge Louisiana USA Institute for Systems Biology Seattle Washington USA Department of Biology and School of Informatics and Computing Indiana University Bloomington Indiana USA Instituto Universitario de Oncologia Departamento de Bioquimica y Biol

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An environment for sustainable research software in Germany and beyond: Current state, open challenges, and call for action

arXiv

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arXiv 2020年

作者： Anzt, Hartwig Bach, Felix Druskat, Stephan Löffler, Frank Loewe, Axel Renard, Bernhard Y. Seemann, Gunnar Struck, Alexander Achhammer, Elke Aggarwal, Piush Appel, Franziska Bader, Michael Brusch, Lutz Busse, Christian Chourdakis, Gerasimos Dabrowski, Piotr W. Ebert, Peter Flemisch, Bernd Friedl, Sven Fritzsch, Bernadette Funk, Maximilian D. Gast, Volker Goth, Florian Grad, Jean-Noël Hermann, Sibylle Hohmann, Florian Janosch, Stephan Kutra, Dominik Linxweiler, Jan Muth, Thilo Peters-Kottig, Wolfgang Rack, Fabian Raters, Fabian H.C. Rave, Stephan Reina, Guido Reißig, Malte Ropinski, Timo Schaarschmidt, Joerg Seibold, Heidi Thiele, Jan P. Uekerman, Benjamin Unger, Stefan Weeber, Rudolf Germany Innovative Computing Lab University of Tennessee KnoxvilleTN United States Department of English Studies Friedrich Schiller University Jena Germany Germany Department of Computer Science Humboldt-Universität zu Berlin Germany Heinz Nixdorf Chair for Distributed Information Systems Friedrich Schiller University Jena Germany Michael Stifel Center Jena Germany Center for Computation and Technology Louisiana State University Baton Rouge United States Germany Robert Koch Institute Berlin Germany Hasso Plattner Institute Faculty of Digital Engineering University of Potsdam Germany Institute for Experimental Cardiovascular Medicine University Heart Centre Freiburg Bad Krozingen Germany Faculty of Medicine University of Freiburg Freiburg Germany Matters of Activity. Image Space Material. Cluster of Excellence at Humboldt-Universität zu Berlin Germany Technische Universität München Germany Language Technology Lab Universität Duisburg-Essen Germany Germany Department of Informatics Technical University of Munich Germany Technische Universität Dresden Germany Deutsches Krebsforschungszentrum Heidelberg Germany Scientific Computing in Computer Science Technical University Munich Germany School of Computing Communication and Business Hochschule für Technik und Wirtschaft Berlin Germany Center for Bioinformatics Saar Saarland Informatics Campus Germany Institute for Modelling Hydraulic and Environmental Systems University of Stuttgart Germany Berlin Institute of Health Germany Scientific Computing Alfred Wegener Institute Helmholtz Center for Polar and Marine Research Bremerhaven Germany Max-Planck-Gesellschaft e.V. Institut für Theoretische Physik und Astrophysik Universität Würzburg Germany Institut für Computerphysik University of Stuttgart Germany University Library University of Stuttgart Germany Universität Bremen Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany European Molecular Biology Laboratory Heidelb

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin. Copyright © 2020, The Authors. All rights reserved.

关键词： Software design

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Introduction and background

SpringerBriefs in Computer Science

引用

SpringerBriefs in Computer Science 2017年第9783319614083期 1-7页

作者： Earnshaw, Rae Centre for Visual Computing Faculty of Engineering and Informatics University of Bradford Bradford United Kingdom School of Creative Arts Wrexham Glyndŵr University Wrexham United Kingdom

The development of digital media is reviewed and definitions are provided. The advantages of digital media over traditional media are set out, and the current challenges are summarized. The convergence of IT, telecommunications, and media is bringing about a revolution in the way information is collected, stored and accessed. There are three principal reasons why this is happening – reducing cost, increasing quality, and increasing bandwidth. Digital media preserves content accuracy (e.g. digital television) in a way other systems do not. High bandwidth transmission from one place to another on the planet is now possible. Information is ubiquitous and globally accessible, and can be held and accessed just as easily on a global network as on a local personal computer or in a local library. Thus anyone generating state of the art content can produce an impact on the global network. Devices are increasingly intelligent and are network-ready. User interfaces are becoming more adaptable and flexible, and can be tailored to particular application domains. Digital intelligence is becoming seamless and invisible, enabling more attention to be paid to the content and the user’s interaction with it. Digital media includes a wide range of applications such as computer games, multimedia production, animation, graphics and video editing, and digital video film making. Media content is now created in digital form and can be repurposed across different media types such as DVD, Internet, or traditional print. This offers scope for different forms of advertising, and providing added value to consumers by providing dynamic links to other relevant information. This provides new value chains and ecosystems. This is turn affects social and cultural contexts, and interacts with them. The user as content creator, publisher, and broadcaster is changing the traditional roles of news media, publishers, and entertainment corporations. This in turn changes social and governmental structures an

关键词： Digital storage

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