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retracted: Artificial intelligence point-to-point signal communication network optimization based on ubiquitous clouds

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International Journal of Communication Systems 2020年第6期34卷

作者： Lin Hong Lianbing deng daming Li Harry Haoxiang Wang School of Management Beijing Normal University at Zhuhai Zhuhai China The Post-Doctoral Research Center Zhuhai Da Hengqin Science and Technology Development Co. Ltd Zhuhai China Department of R&D Guangdong Qinzhi Science and Technology Research Institute Zhuhai China Department of R&D Huazhong University of Science and Technology Wuhan China Institute of Data Science City University of Macau Macau China Department of R&D GoPerception Laboratory Ithaca New York USA

At present, the application of communication network has spread to every area of social life. The progress of network technology has driven the development of information technology industry and the advancement of cloud computing. With the application of artificial intelligence and deep learning technology, the network becomes more and more intelligent, so the application of artificial intelligence theory in communication network optimization modeling is more extensive. In this paper, we propose the ubiquitous clouds framework and apply the artificial intelligence optimization scheme to the point-to-point (P2P) signal transmission network optimization scheme. For different application scenarios, this paper analyzes and experiments the proposed method. The experimental results show that the proposed method makes full use of the advantages of communication network resources which improves the efficiency of communication network optimization and also reduces the optimization cost to a certain extent compared with the state-of-the-art approaches.

关键词： artificial intelligence communication network neural network optimization particle swarm optimization (PSO) point-to-point transmission ubiquitous clouds

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Computational Assessment of Chemical Saturation of Analogue Series under Varying Conditions

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ACS OMEGA 2018年第11期3卷 15799-15808页

作者： Yonchev, dimitar Vogt, Martin Stumpfe, dagmar Kunimoto, ryo Miyao, Tomoyuki Bajorath, Juergen Rheinische Friedrich Wilhelms Univ LIMES Program Unit Chem Biol & Med Chem Dept Life Sci Informat B IT Endenicher Allee 19c D-53115 Bonn Germany Nara Inst Sci & Technol Data Sci Ctr 8916-5 Takayama Cho Nara 6300192 Japan Nara Inst Sci & Technol Grad Sch Sci & Technol 8916-5 Takayama Cho Nara 6300192 Japan Daichi Sankyo Co Ltd Shinagawa R&D Ctr R&D Div Shinagawa KuMed Chem Management GrpRes Funct 1-2-58 Hiromachi Tokyo 1408710 Japan

Assessing the degree to which analogue series are chemically saturated is of major relevance in compound optimization. decisions to continue or discontinue series are typically made on the basis of subjective judgment. Currently, only very few methods are available to aid in decision making. We further investigate and extend a computational concept to quantitatively assess the progression and chemical saturation of a series. To these ends, existing analogues and virtual candidates are compared in chemical space and compound neighborhoods are systematically analyzed. A large number of analogue series from different sources are studied, and alternative chemical space representations and virtual analogues of different designs are explored. Furthermore, evolving analogue series are distinguished computation-ally according to different saturation levels. Taken together, our findings provide a basis for practical applications of computational saturation analysis in compound optimization.

关键词： Saturation Medicinal chemistry Structure activity relationship Testing and assessment Optimization

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OPTIMA: Improve care for patients with prostate, breast, and lung cancer through artificial intelligence

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ANNALS OF ONCOLOGY 2022年第7期33卷 S966-S966页

作者： N'dow, J. Smith, E. J. Polychronopoulos, K. Cannon, A. roobol, M. Auweter, S. Thomas, M. Kremer, A. de Meulder, B. dellamonica, d. Alhambra, d. P. Asiimwe, A. Bussmann, M. Ji, X. Torremante, P. Keller, S. Kube, F. Krueger, H. Univ Aberdeen Acad Urol Unit Aberdeen Scotland EAU European Assoc Urol Guideline Off Arnhem Netherlands Univ Vienna Dept Innovat & Digitalisat Law Vienna Austria Genentech Inc Hillsboro OR USA Erasmus Univ Med Ctr Erasmus MC Canc Inst Rotterdam Netherlands Smart Reporting GmbH Sci Project Management Munich Germany F Hoffmann Roche AG Global Med Affairs Basel Switzerland R&D Informat Technol Translat Med Luxembourg Luxembourg EISBM Assoc EISBM Vourles France AstraZeneca AG Europe & Canada Oncol Zug Switzerland Univ Oxford CSM NDORMS Oxford England Bayer AG Open Innovat Private Publ Partnerships Leverkusen Germany Helmholtz Zentrum Dresden Rossen dorf Ctr Adv Syst Understanding Dresden Germany Pfizer Inc Data Sci & Adv Analyt CoE Pfizer Digital Collegeville PA USA ARTTIC Innovat GmbH Munich Germany Pfizer Pharma GmbH Oncol Berlin Germany Pfizer Pharma GmbH Med Affairs Oncol Karlsruhe Germany Pfizer Pharma GmbH Med Affairs Oncol Berlin Germany

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OP0276 PrEFErENCES FOr TrEATMENTS TO PrEVENT rHEUMATOId ArTHrITIS: dISCrETE CHOICE SUrVEY OF rHEUMATOId ArTHrITIS PATIENTS' FIrST-dEGrEE rELATIVES IN THE UNITEd KINGdOM ANd GErMANY.

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Annals of the rheumatic diseases 2022年 81卷 183-184页

作者： G. Simons J. Veldwijk r. disantostefano M. Englbrecht C. radawski L. Valor J. Humphreys I.N. Bruce K. raza M. Falahee University of Birmingham Rheumatology Research Group Institute of Inflammation and Ageing Birmingham United Kingdom Erasmus University Rotterdam Erasmus School of Health Policy and Management and Erasmus Choice Modelling Centre Rotterdam Netherlands Utrecht University Julius Centre for Health Sciences and Primary Care University Medical Centre Utrecht Utrecht Netherlands Janssen R&D NJ United States of America Freelance Data Scientist Eckental Germany Eli Lilly and Company Indianapolis United States of America Friedrich-Alexander-University Erlangen Erlangen Germany University of Manchester Centre for Epidemiology Versus Arthritis Centre for Musculoskeletal Research Manchester Academic Health Science Centre Manchester United Kingdom Manchester University NHS Foundation Trust Kellgren Centre for Rheumatology Manchester United Kingdom Manchester University NHS Foundation Trust Manchester Academic Health Science Centre NIHR Manchester Biomedical Research Centre Manchester United Kingdom University of Manchester Division of Musculoskeletal and Dermatological Sciences School of Biological Sciences Faculty of Biology Medicine and Health Manchester United Kingdom University of Birmingham Research Into Inflammatory Arthritis Centre Versus Arthritis and MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research Birmingham United Kingdom Sandwell and West Birmingham NHS Trust Rheumatology Department Birmingham United Kingdom

Background There is a growing research focus on the development of interventions to reduce risk of rheumatoid arthritis (rA) in at-risk individuals.(1) A recent survey of the general population asked to assume a 60% risk of rA established that hypothetical preventive treatments were acceptable to most participants.(2) However the preferences of individuals who actually have an elevated risk of rA, such as first-degree relatives (Fdrs) of rA patients, are not well understood. Objectives To quantify Fdrs' preferences for preventive treatments for rA. Methods Adult Fdrs in the UK and Germany were invited to take part in a web-based survey via patients with clinician-confirmed rA either during a rheumatology clinic visit or by mail. In addition, Fdrs taking part in a UK-based prospective cohort (PrEVeNT-rA) were invited via email. Participants received information about rA followed by questions to check comprehension, and an introduction to the survey including warm-up questions. They were asked to imagine they were experiencing arthralgia and had positive autoantibody tests indicating a 60% chance of developing rA in the next two years. Using a discrete choice experiment, participants were offered a series of 15 choices between no treatment and two unlabeled hypothetical treatments to reduce risk of rA. Treatments were defined by six attributes with varying levels, describing benefits, risks, and frequency/route of administration ( Table 1 ). Attribute selection and presentation was informed by qualitative research, ranking surveys, systematic literature review, and expert opinion. Survey layout was informed by patient research partners and qualitative pre-testing. A two-class latent class analysis was used to estimate preferences and calculate relative importance of treatment attributes and predicted uptake. A panel mixed logit model was used to obtain maximum acceptable risk estimates. Table 1 . Treatment attributes and levels Attribute Levels Chance of developing rA

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Primary analysis from dS8201-A-U105: A 2-part, open label, phase Ib trial assessing trastuzumab deruxtecan (T-dXd) with nivolumab (nivo) in patients (pts) with HEr2-expressing advanced breast cancer

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ANNALS OF ONCOLOGY 2022年 33卷 S196-S196页

作者： Hamilton, E. P. Shapiro, C. L. Boni, V. Jimenez, M. Martin del Conte, G. Cortes, J. Agrawal, L. Arkenau, H-T. Tan, A. r. debruyne, P. r. Minchom, A. r. rutten, A. Valdes-Albini, F. Yu, E. Suto, F. Cheng, F-C. Augustine, B. Cheng, B. Barrios, d. Hurvitz, S. A. Sarah Cannon Res Inst Tennessee Oncol Breast & Gynecol Canc Res Program Nashville TN USA Icahn Sch Med Mt Sinai Med Hematol & Med Oncol New York NY 10029 USA Quironsalud Univ Hosp START Madrid CIOCC & NEXT Oncol Phase 1 Madrid Spain Hosp Gen Univ Gregorio Maranon Med Oncol Madrid Spain IRCCS Osped San Raffaele Oncol Milan Italy Int Breast Canc Ctr IBCC Grp Quiron Madrid Spain Int Breast Canc Ctr IBCC Grp Quiron Barcelona Spain Norton Canc Inst Med Oncol Louisville KY USA Sarah Cannon Res Inst UK London England Atrium Hlth Levine Canc Inst Dept Solid Tumor Oncol & Invest Therapeut Charlotte NC USA AZ Groeninge Med Oncol Kortrijk Belgium Anglia Ruskin Univ Sch Life Sci Cambridge England Royal Marsden Hosp Drug Dev Unit Inst Canc Res London England GZA Hosp Sint Augustinus Med Oncol Antwerp Belgium Univ Miami Dept Med Oncol Miami FL USA Univ Washington Med Seattle WA 98195 USA Fred Hutchinson Canc Res Ctr Seattle WA USA Daiichi Sankyo Inc Translat Sci Basking Ridge NJ USA Daiichi Sankyo Inc Biostat & Data Management Basking Ridge NJ USA Daiichi Sankyo Inc Global Oncol R&D Basking Ridge NJ USA Daiichi Sankyo Inc CSPV Basking Ridge NJ USA Daiichi Sankyo Inc R&D Basking Ridge NJ USA Univ Calif Los Angeles Jonsson Comprehens Canc Ctr Hematol Oncol Los Angeles CA 90024 USA

162O

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Skin disease detection using artificial intelligence

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AIP Conference Proceedings 2022年第1期2393卷

作者： S. Kuzhaloli L. M. Varalakshmi Kamal Gulati Makarand Upadhyaya Narinder Kumar Bhasin Vijayakumar Peroumal 1EEE Department Vel Tech RangarajanDr.Sagunthala R&D Institute of Science and Technology Chennai India 2Dept of ICE Sri ManakulaVinayagar Engineering College Puducherry India 3Data Analytics Amity School of Insurance Banking and Actuarial Science Amity University Noida India 4Department of Management & Marketing College of Business Administration Kingdom of Bahrain Bahrain 5CSIT Amity School of Insurance Banking and Actuarial Science Amity University Noida India 6School of Electronics Engineering Vellore Institute of Technology Chennai India

Artificial intelligence (AI) algorithms for automated classification of skin diseases are available to the consumer market. Studies of their diagnostic accuracy are rare. We assessed the diagnostic accuracy of an open-access AI application for recognition of skin diseases. The AI algorithm classified the images giving 5 differential diagnoses, which were then compared to the diagnoses made clinically by the dermatologists and/or histological. The level of diagnostic accuracy varied considerably for diagnostic groups. The online application demonstrated low diagnostic accuracy compared to a dermatologist evaluation and needs further development. Input signs have been developed to classify the disorder. With the aid of experts in the area, we received symptoms of 10 skin diseases. The symptom data were trained by various classifiers. We observed that high quality AI-based support for clinical decision making enhances the accurate diagnosis of either AI or doctors alone and that less skilled physicians are better served by AI.

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Measuring the aggregation of CHO cells prior to single cell cloning allows a more accurate determination of the probability of clonality

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BIOTECHNOLOGY PrOGrESS 2018年第3期34卷 593-601页

作者： Klottrup, Kerensa J. Miro-Quesada, Guillermo Flack, Layla Pereda, Ivan Hawley-Nelson, Pamela MedImmune Cell Culture & Fermentat Sci Biopharmaceut Dev Cambridge CB21 6GH England MedImmune Data Management & Quantitat Sci Biopharmaceut Dev Gaithersburg MD 20878 USA Artimis Fed Gaithersburg MD 20878 USA AstraZeneca R&D Informat Cambridge CB21 6GH England MedImmune Biopharmaceut Dev Cell Culture & Fermentat Sci Gaithersburg MD 20878 USA

The manufacturing process for biotherapeutics is closely regulated by the Food and drug Administration (FdA), European Medicines Agency (EMA) and other regulatory agencies worldwide. To ensure consistency of the product of a manufacturing cell line, International Committee on Harmonization guidelines (Q5d, 1997) state that the cell substrate should be derived from a single cell progenitor, i.e., *** lines in suspension culture may naturally revert to cell adhesion in the form of doublets, triplets and higher order structures of clustered cells. We can show evidence of a single colony from limiting dilution cloning or in semi-solid media, but we cannot determine the number of cells from which the colony originated. To address this, we have used the ViCELL (r) Xr (Beckman Coulter, High Wycombe, UK) cell viability analyzer to determine the proportion of clusters of two or more cells in a sample of the cell suspension immediately prior to cloning. Here, we show data to define the accuracy of the ViCELL for characterizing a cell suspension and summarize the statistical model combining two or more rounds of cloning to derive the probability of clonality. The resulting statistical model is applied to cloning in semi-solid medium, but could equally be applied to a limiting dilution cloning process. We also describe approaches to reduce cell clusters to generate a cell line with a high probability of clonality from a CHO host lineage. (c) 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:593-601, 2018

关键词： ClonePixFL single cell cloning mammalian cell line development ViCell probability of clonality

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rainfall Monitoring Using Microwave Links from Cellular Communication Networks: The dutch Experience

Rainfall Monitoring Using Microwave Links from Cellular Comm...

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Aart Overeem Hidde Leijnse remko Uijlenhoet Hydrology and Quantitative Water Management Group Wageningen University & Research R&D Observations and Data Technology Royal Netherlands Meteorological Institute (KNMI)

Microwave links from commercial cellular communication networks have been used for rainfall monitoring in The Netherlands since 2003. Here we report on the start of our work on this topic using a dedicated microwave link in 1999, our first trails with commercial microwave links (CMLs) from Vodafone in 2003, our first published results in 2007, our work on sources of error and uncertainties in rainfall retrievals using microwave links of different lengths and frequencies, and finally the fruitful collaboration with T-Mobile NL, which lead to areal rainfall estimation for the rotterdam metropolitan area in 2009 and 2010 and country-wide rainfall mapping for the entire land surface area of The Netherlands since 2012. Our current work on this topic follows three lines of research: (1) further refinement of our rainfall retrieval and mapping algorithm; (2) further quantification of sources of error and uncertainties using a dedicated experimental setup of multiple microwave links and a line configuration of disdrometers for ground validation; (3) promotion of the international replication of this method for rainfall monitoring through collaboration with partners in Europe and beyond.

关键词： Microwave communication Microwave measurement rain Attenuation Monitoring Communication networks

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Association between circulating ketone bodies and subclinical atherosclerosis: Multi-Ethnic Study of Atherosclerosis (MESA)

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Journal of cardiovascular computed tomography 2025年

作者： Parag Anilkumar Chevli Alexander C razavi Joni K Evans richard Kazibwe Margery A Connelly Sadiya S Khan Ambarish Pandey Matthew C Tattersall James H Stein Michael d Shapiro Section on Cardiovascular Medicine Department of Internal Medicine Wake Forest University School of Medicine Winston-Salem NC USA. Emory Center for Heart Disease Prevention Emory University School of Medicine Atlanta GA USA. Department of Biostatistics and Data Science Wake Forest University School of Medicine Winston-Salem NC USA. Department of Internal Medicine Wake Forest University School of Medicine Winston-Salem NC USA. Diagnostics R&D Labcorp Morrisville NC USA. Division of Cardiology Departments of Medicine and Preventive Medicine Northwestern University Feinberg School of Medicine Chicago IL USA. Division of Cardiology Department of Internal Medicine University of Texas Southwestern Medical Center Dallas TX USA. Department of Medicine Division of Cardiovascular Medicine University of Wisconsin School of Medicine and Public Health Madison WI USA. Center for the Prevention of Cardiovascular Disease Section on Cardiovascular Medicine Wake Forest University School of Medicine Winston-Salem NC USA. Electronic address: mdshapir@wakehealth.edu.

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Citizen science’s transformative impact on science, citizen empowerment and socio-political processes

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Socio-Ecological Practice research 2023年第1期5卷 11-33页

作者： von Gönner, Julia Herrmann, Thora M. Bruckermann, Till Eichinger, Michael Hecker, Susanne Klan, Friederike Lorke, Julia richter, Anett Sturm, Ulrike Voigt-Heucke, Silke Brink, Wiebke Liedtke, Christin Premke-Kraus, Matthias Altmann, Carolin Bauhus, Wilhelm Bengtsson, Luiza Büermann, Andrea dietrich, Peter dörler, daniel Eich-Brod, regina Ferschinger, Laura Freyberg, Linda Grützner, Agnes Hammel, Gertrud Heigl, Florian Heyen, Nils B. Hölker, Franz Johannsen, Carolin Kluß, Thorsten Kluttig, Thekla Knobloch, Jörn Munke, Martin Mortega, Kim Pathe, Carsten Soßdorf, Anna Stämpfli, Tiina Thiel, Christian Tönsmann, Susanne Valentin, Anke Wagenknecht, Katherin Wegener, robert Woll, Silvia Bonn, Aletta Department of Ecosystem Services Helmholtz Centre for Environmental Research - UFZ Permoserstr. 15 Leipzig 04318 Germany Institute of Biodiversity Friedrich Schiller University Jena Dornburgerstr. 159 Jena 07743 Germany German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Puschstr. 4 Leipzig 04103 Germany Institute of Education Leibniz University Hannover Schloßwenderstr. 1 Hannover 30159 Germany Center for Preventive Medicine and Digital Health Medical Faculty Mannheim Heidelberg University Ludolf-Krehl-Str. 7-11 Mannheim 68167 Germany Institute of Medical Biostatistics Epidemiology and Informatics University Medical Center of the Johannes Gutenberg University Mainz Obere Zahlbacher Str. 69 Mainz 55131 Germany Leibniz Institute for Evolution and Biodiversity Science Museum Für Naturkunde Berlin Invalidenstr. 43 Berlin 10115 Germany Institute of Data Science German Aerospace Center (DLR) Mälzerstr. 3-5 Jena 07745 Germany Leibniz Institute for Science and Mathematics Education Olshausenstr. 62 Kiel 24118 Germany Thünen-Institute of Biodiversity Bundesallee 65 Brunswick 38116 Germany Wissenschaft Im Dialog Charlottenstr. 80 Berlin 10117 Germany Helmholtz Association Berlin Head Office Anna-Louisa-Karsch-Str. 2 Berlin 10178 Germany Leibniz Association Berlin Head Office Chausseestr.111 Berlin 10115 Germany Research Transfer Office University of Münster Robert-Koch-Str.40 Münster 48149 Germany Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association Robert-Rössle-Str.10 Berlin 13125 Germany Department of Monitoring and Exploration Technologies Helmholtz Centre for Environmental Research - UFZ Permoserstr. 15 Leipzig 04318 Germany Institute of Zoology University of Natural Resources and Life Sciences Vienna Gregor-Mendel-Str. 33 Vienna 1180 Austria Institute for Energy and Climate Research IEK8 Forschungszentrum Jülich GmbH Jülich 52425 Germany Heinrich Heine University Duesseldorf Universitä

Citizen science (CS) can foster transformative impact for science, citizen empowerment and socio-political processes. To unleash this impact, a clearer understanding of its current status and challenges for its development is needed. Using quantitative indicators developed in a collaborative stakeholder process, our study provides a comprehensive overview of the current status of CS in Germany, Austria and Switzerland. Our online survey with 340 responses focused on CS impact through (1) scientific practices, (2) participant learning and empowerment, and (3) socio-political processes. With regard to scientific impact, we found that data quality control is an established component of CS practice, while publication of CS data and results has not yet been achieved by all project coordinators (55%). Key benefits for citizen scientists were the experience of collective impact (“making a difference together with others”) as well as gaining new knowledge. For the citizen scientists’ learning outcomes, different forms of social learning, such as systematic feedback or personal mentoring, were essential. While the majority of respondents attributed an important value to CS for decision-making, only few were confident that CS data were indeed utilized as evidence by decision-makers. Based on these results, we recommend (1) that project coordinators and researchers strengthen scientific impact by fostering data management and publications, (2) that project coordinators and citizen scientists enhance participant impact by promoting social learning opportunities and (3) that project initiators and CS networks foster socio-political impact through early engagement with decision-makers and alignment with ongoing policy processes. In this way, CS can evolve its transformative impact. © 2023, The Author(s).

关键词： data quality Participatory research Political uptake recognition research data management Social learning

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