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Functional hyperconnectivity is associated with higher levels of sPDGFRβ, a marker of blood brain barrier breakdown, in older adults

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Alzheimer's & Dementia 2022年第S1期18卷

作者： Joey A Contreras Kimiko Fujisaki Nancy E Ortega Giuseppe Barisano Abhay P Sagare Berislav V Zlokovic Arthur W. Toga Judy Pa Alzheimer's Disease Cooperative Study (ADCS) University of California San Diego La jolla CA USA Stevens Neuroimaging and Informatics Institute University of Southern California Los Angeles CA USA Neuroscience Graduate Program University of California San Diego San Diego CA USA Zilkha Neurogenetic Institute Keck School of Medicine University of Southern California Los Angeles CA USA Alzheimer's Disease Cooperative Study (ADCS) University of California San Diego San Diego CA USA

Background Apolipoprotein E4 ( APOE 4) has toxic effects on the cerebrovascular system, neuronal function, and functional connectivity of brain networks (e.g., default-mode, frontal-attention, and salience networks). The thalamus, a vital structure that acts as a relay station between many networks, has become of interest in AD research with studies showing atrophy among those with early AD and diminished cortical-thalamic connections among those with vascular impairment. Additionally, CSF soluble platelet-derived growth factor receptor-β (sPDGFRβ), a marker of blood-brain barrier breakdown, has been associated with AD risk, especially in APOE 4 carriers. The present study investigated the relationship between CSF sPDGFRβ and functional connectivity in APOE 4 carriers and non-carriers. Method One hundred sixty-six older adults from the Los Angeles area were selected from a larger cohort (96 females, mean age + SD=67.4 + 10.7, 68 APOE 4 carriers) based on availability of rsfMRI data. Image data was processed using CONN-toolbox v19c. Grey matter was parcellated using Harvard/Oxford brain atlas, excluding cerebellum. ROI-to-ROI analyses were conducted selecting the thalamus as seed region averaging mean connectivity between the left and right structure of other parcellated brain regions. Linear regression models evaluated significant associations between blood oxygen level-dependent (BOLD) and network connectivity among seed-target regions and CSF sPDGFRβvalues, while covarying for age and sex. Comparison of averaged functional connectivity values between seed and all target regions among APOE 4 carriers and non-carriers was also examined. Result Higher functional connectivity between the thalamus and resting state network hub regions were associated with higher CSF sPDGFRβ (Fig 1A, 1C). Cortical regions within the networks included posterior cingulate gyrus, anterior cingulate gyrus, and frontal eye field. Averaged functional connectivity between these areas was signi

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Using Systems of Systems to Manage Enterprise Contacts 4

Using Systems of Systems to Manage Enterprise Contacts

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4th IEEE International Forum on Research and Technologies for Society and Industry, RTSI 2018

作者： Wanderley, Gregory Moro Puppi Abel, Marie-Helene Barthes, Jean-Paul A. Paraiso, Emerson Cabrera Université de Technologie de Compiègne CNRS Sorbonne Universités UMR 7253Heudiasyc Compiègne France PPGIa-Graduate Program in Informatics Pontificia Universidade Católica Do Paraná Curitiba Brazil

This paper discusses how one could use a Systems of Systems Approach to manage contacts inside an enterprise. The major problem is the interoperability of existing systems in charge of handling information regarding a... 详细信息

ISBN: (纸本)9781538662823

关键词： System of systems

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Emotion recognition in doctor-patient interactions from real-world clinical video database: Initial development of artificial empathy

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Computer Methods and programs in Biomedicine 2023年 233卷 107480-107480页

作者： Huang, Chih-Wei Wu, Bethany C.Y. Nguyen, Phung Anh Wang, Hsiao-Han Kao, Chih-Chung Lee, Pei-Chen Rahmanti, Annisa Ristya Hsu, Jason C. Yang, Hsuan-Chia Li, Yu-Chuan Jack Taipei Medical University Taipei Taiwan Taipei Medical University Ringgold standard institution - Center for Simulation in Medical Education Taipei 116 Taiwan National Taiwan University Children and Family Research Center Sponsored by CTBC Charity Foundation Taipei Taiwan Clinical Data Center Office of Data Science Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University TMU Da'an Campus 15 F No. 172-1 Kee lung Road Section 2 Da-an District Taipei Taiwan Research Center of Big Data and Meta-analysis Wanfang Hospital Taipei Medical University Taipei Taiwan Department of Dermatology Wanfang Hospital Taipei Medical University Taiwan Department of Dermatology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Delta Research Center Taipei Taiwan Department of Health Policy and Management Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada Yogyakarta Indonesia International PhD Program in Biotech and Healthcare Management College of Management Taipei Medical University Taipei Taiwan Research Center of Data Science on Healthcare Industry College of Management Taipei Medical University Taipei Taiwan

Background and objective: The promising use of artificial intelligence (AI) to emulate human empathy may help a physician engage with a more empathic doctor-patient relationship. This study demonstrates the application of artificial empathy based on facial emotion recognition to evaluate doctor-patient relationships in clinical practice. Methods: A prospective study used recorded video data of doctor-patient clinical encounters in dermatology outpatient clinics, Taipei Municipal Wanfang Hospital, and Taipei Medical University Hospital collected from March to December 2019. Two cameras recorded the facial expressions of four doctors and 348 adult patients during regular clinical practice. Facial emotion recognition was used to analyze the basic emotions of doctors and patients with a temporal resolution of 1 second. In addition, a physician-patient satisfaction questionnaire was administered after each clinical session, and two standard patients gave impartial feedback to avoid bias. Results: Data from 326 clinical session videos showed that (1) Doctors expressed more emotions than patients (t [326] > = 2.998, p © 2023

关键词： Emotion Recognition

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Low energy performance boost through a hardware stereoscopic trigger between CTA LST-1 and MAGIC 38

Low energy performance boost through a hardware stereoscopic...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Baxter, J. Barrio, J.A. Bitossi, M. Donini, A. Mazin, D. Paoletti, R. Pérez Aguilera, A. Tejedor Álvarez, L.Á. Abe, H. Abe, K. Abe, S. Abhir, J. Acciari, V.A. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Aniello, T. Ansoldi, S. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Cornelia, A. Artero, M. Asano, K. Aubert, P. Baack, D. Babić, A. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Besenrieder, J. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Biland, A. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bošnjak, Ž. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Busetto, G. Campoy-Ordaz, A. Cardillo, M. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.S. Carretero-Castrillo, M. Cassol, F. Castro-Tirado, A.J. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chilingarian, A. Chytka, L. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Costantini, H. Covino, S. D’Amico, G. Dalchenko, M. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delfino, M. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Del Popolo, A. Depaoli, D. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Fariña, L. Fattorini, A. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Font, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Garczarczyk, M. Gasbarra, C. Gasparrini, D. Gasparyan, S. Gaug, M. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Green, J. Green, D. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid Spain Sezione di Pisa Pisa56127 Italy Osservatorio Astronomico di Roma Italy Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Università degli Studi di Siena via Roma 56 Siena53100 Italy Department of Physics Tokai University Japan ETH Zürich Switzerland Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain Instituto de Astrofísica de Andalucía-CSIC Spain EMFTEL department IPARCOS Universidad Complutense de Madrid Spain Italy INFN Sezione di Trieste Università degli Studi di Udine Italy Italy INAF Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy The Barcelona Institute of Science and Technology Spain LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Department of Physics TU Dortmund University Germany Croatia Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil Faculty of Physics and Applied Informatics University of Lodz Poland CIEMAT Spain INFN Sezione di Bari Politecnico di Bari Italy INAF Osservatorio Astronomico di Brera Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Departament de Física CERES-IEEC Universitat Autónoma de Barcelona Spain Italy Università di Pisa INFN Pisa Italy Aix Marseille Univ CNRS IN2P3 CPPM France INFN Sezione di Bari Università di Bari Italy INFN Sezione di Torino Italy ICRANet-Armenia at

The next generation facility for gamma-ray ground-based observations is the Cherenkov Telescope Array (CTA) observatory, which comprises three types of imaging atmospheric Cherenkov telescopes (IACTs). The Large-Sized Telescopes (LSTs) of CTA are the largest telescope type with a mirror dish of 23 m diameter. They cover the low energy end of the accessible gamma-ray energies for IACTs, starting from about 20 GeV up to a few TeV. The first LST prototype, known as LST-1, was officially inaugurated at the Observatorio del Roque de Los Muchachos in La Palma (Canary Islands, Spain) in 2018 and has since performed calibration observations of various known gamma-ray sources. Additionally, the site houses the MAGIC telescopes, two 17 m IACTs situated approximately 100 m away from LST-1, which have been performing stereo observations since 2009. Currently, joint observations between LST-1 and MAGIC are being carried on, and the data taken independently by the two IACT systems is analyzed by combining events via software. However, this method increases the energy threshold, as it discards all but the relatively high-energy events triggered by all three telescopes. To address this issue, we have developed a novel hardware stereo trigger system between LST-1 and MAGIC, which is capable of handling events triggered by any-two out of the three telescopes. In this contribution, we will report on the performance estimation of joint LST-1 and MAGIC observations using the hardware trigger. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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HFLTS-TOPSIS with Pseudo-distance in Determining the Best Lecturers 1

HFLTS-TOPSIS with Pseudo-distance in Determining the Best Le...

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1st Workshop on Environmental Science, Society, and Technology, WESTECH 2018

作者： Abdullah, Dahlan Hartono, H. Saddhono, Kundharu Kurniasih, Nuning Iskandar, Akbar Rianita, Dian Purwarno Setyawasih, Rianti Satria, Erwinsyah Nuryanto, Tato Herawati, Lilik Sujinah Sudarsana, I Ketut Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Department of Public Administrations Universitas Lancang Kuning Indonesia Faculty of Literature Universitas Islam Sumatera Utara Medan Indonesia Indonesia Department of Management Faculty of Economic Universitas Islam 45 Bekasi Indonesia Faculty of Teacher Training and Education Universitas Bung Hatta Padang Indonesia FITK IAIN Syekh Nurjati Cirebon Indonesia Department of Indonesian Language Teaching Institut Agama Islam Negeri Syekh Nurjati Cirebon Cirebon Indonesia Faculty of Education University Muhammadiyah of Surabaya Surabaya Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Indonesia

Decision making is sometimes faced with a situation where assessment is given in the form of linguistic variables, which have a certain range of values so that decision making cannot be given in the form of numerical values. One approach commonly used is Hesitant Fuzzy Linguistic Term Sets (HFLTS) which is a multi-criteria and multi-alternative decision making method. In TOPSIS which has the concept of distance measurement, basically the chosen one is the best alternative is an alternative that has the closest distance to a positive solution and the farthest distance with a negative solution. The incorporation of HFLTS-TOPSIS has the advantage that decision making can be done in the form of variable linguistics and also a situation where there are benefit criteria and cost criteria. This study will use the HFLTS-TOPSIS approach that has been modified in the distance calculation section so that distance calculation is based on the difference of preference degree between the two HFLTS. The results of research conducted by a number of researchers show that using pseudo-distance will provide advantages compared to the standard HLFTS-TOPSIS. Pseudo-distance HFLTS-TOPSIS will be applied in the selection of the best lecturers. The criteria used in this study are: Student Satisfaction, Research, Number of late, and number of complaints from students. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Web Application Vulnerability Detection Using Taint Analysis and Black-box Testing

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IOP Conference Series: Materials Science and Engineering 2020年第1期879卷

作者： Heribertus Yulianton Agung Trisetyarso Wayan Suparta Bahtiar Saleh Abbas Chul Ho Kang Computer Science Department Binus Graduate Program | Doctor of Computer Science Bina Nusantara University West Jakarta Indonesia Faculty of Information Technology Universitas Stikubank Semarang Department of Informatics Universitas Pembangunan Jaya

Web applications continue to grow however web attacks are also increasing, this shows an increase in web application vulnerabilities. Several methods have been used to detect vulnerabilities in web applications such as black-box testing, dynamic analysis, and static analysis. In this article, we propose a framework for detecting web application vulnerabilities by combining all three methods. The strengths of one method are used to overcome the weaknesses of another method. This framework is believed to provide better results than if each method was used separately.

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Observation of Active Galactic Nuclei with the Large-Sized Telescope prototype of the Cherenkov Telescope Array 38

Observation of Active Galactic Nuclei with the Large-Sized T...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Takeishi, R. Álvarez Crespo, N. Arbet-Engels, A. Baquero Larriva, A. Baxter, J. Biederbeck, N. Caroff, S. Di Marco, G. Fallah Ramazani, V. Green, D. Heckmann, L. Láinez, M. Nickel, L. Nievas Rosillo, M. Pons, E. Priyadarshi, C. Sanchez, D.A. Vázquez Acosta, M. Abe, K. Abe, S. Aguasca-Cabot, A. Agudo, I. Antonelli, L.A. Aramo, C. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Becerra González, J. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Bhattacharjee, P. Bigongiari, C. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Cardillo, M. Carosi, A. Carrasco, M.S. Cassol, F. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Gasbarra, C. Gasparrini, D. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heller, M. HerreraLlorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Iarlori, M. Imazawa, R. Inada, T. Inome, Y. Ioka, K. Iori, M. Ishio, K. Jimenez Martinez, I. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kohri, K. Kong, A. Kubo, H. Kushida, J. Lamanna, G. Lamastra, A. Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Grupo de Electronica Universidad Complutense de Madrid Av. Complutense s/n Madrid28040 Spain Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Faculty of Science and Technology Universidad del Azuay Cuenca Ecuador Department of Physics TU Dortmund University Otto-Hahn-Str. 4 Dortmund44227 Germany Univ. Savoie Mont Blanc CNRS Laboratoire d’Annecy de Physique des Particules - IN2P3 Annecy74000 France Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Tenerife La Laguna Spain Institut für Theoretische Physik Lehrstuhl IV: Plasma-Astroteilchenphysik Ruhr-Universität Bochum Universitätsstraße 150 Bochum44801 Germany The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain Department of Physics Tokai University Japan Departament de Física Quàntica i Astrofísica Institut de Ciències delCosmos Universitat de Barcelona IEEC-UB Spain Instituto de Astrofísica de Andalucía-CSIC Spain EMFTEL department IPARCOS Universidad Complutense de Madrid Spain INAF - Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil CIEMAT Spain INFN Sezione di Bari Politecnico di Bari Italy INAF - Osservatorio Astronomico di Brera Italy INFN Sezione di Trieste Università degli Studi di Udine Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Italy Aix Marseille Uni

Cherenkov Telescope Array (CTA) will be the next generation gamma-ray observatory. It will consist of three different sizes of telescopes, with a collective improvement of about an order of magnitude in sensitivity, compared with the current generation gamma-ray telescopes. LargeSized Telescopes (LSTs) will be the most sensitive at energies from tens of GeV up to a few TeVs, and will be the best suited to observe gamma-ray sources such as Active Galactic Nuclei (AGN). The first Large-Sized Telescope prototype (LST-1), inaugurated in 2018 and currently in commissioning phase, has accumulated more than one thousand hours of data to date. From 2020 to 2022, we have detected various gamma-ray sources, and prominent among them are several well-known AGN, like Mrk 421, Mrk 501, 1ES 1959+650, 1ES 0647+250, PG 1553+113, etc. We report on light curves and energy spectra reconstructed out of these observations down to energies of tens of GeV, which is very close to the energy threshold of LST-1. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Active Galactic Nuclei

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Co-Creation in the Game Industry:A Case Study in a Brazilian Developer

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Social Networking 2018年第1期7卷 63-78页

作者： Marcos Vinicius Cardoso Huoston Rodrigues Batista Ernani Marques da Silva Marcos Antonio Gaspar Ivanir Costa Fábio Luís Falchi de Magalhaes Universidade Anhembi Morumbi Sao PauloBrazil Graduate Program in Informatics and Knowledge Management Universidade Nove de Julho(UNINOVE)Sao PauloBrazil

The objective of this work is to understand how the process of co-creation occurs within the creative industry of video games. For this, concepts of the creative industry, co-creation, information and communication technologies (ICTs) and innovation were studied. Since this is an exploratory and qualitative research, a single case study was chosen as a method. The analysis was done in a Brazilian company that develops games for mobile devices. The results show that the consumer (gamer) participates in value creation in the company’s products, mainly in the initial production stages. In the later phases, after the launch and other steps of the life cycle, although there is a relationship with the users, the joint creation of value is little explored by the organization. Also, it was verified that the co-creation process is supported by different information and communication tools, which provide agility to the process.

关键词： Co-Creation Empirical Studies Gaming Communities Information and Communication Technologies Innovation

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Precision probiotics supplement strategy in aging population based on gut microbiome composition

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Briefings in bioinformatics 2024年第4期25卷 bbae351页

作者： Yi-Fang Chuang Kang-Chen Fan Yin-Yuan Su Ming-Fong Wu Yen-Ling Chiu Yi-Chien Liu Chen-Ching Lin School of Medicine National Yang Ming Chiao Tung University No. 155 Sec. 2 Linong St. Beitou Dist. Taipei City 112304 Taiwan. Institute of Public Health National Yang Ming Chiao Tung University No. 155 Sec. 2 Linong St. Beitou Dist. Taipei City 112304 Taiwan. Department of Psychiatry Far Eastern Memorial Hospital No. 21 Sec. 2 Nanya S. Rd. Banqiao Dist. New Taipei City 220216 Taiwan. Institute of Biomedical Informatics National Yang Ming Chiao Tung University No. 155 Sec. 2 Linong St. Beitou Dist. Taipei City 112304 Taiwan. Department of Medical Research Far Eastern Memorial Hospital No. 21 Sec. 2 Nanya S. Rd. Banqiao Dist. New Taipei City 220216 Taiwan. Graduate Program in Biomedical Informatics and Graduate Institute of Medicine Yuan Ze University No. 135 Yuandong Rd. Zhongli Dist. Taoyuan City 320315 Taiwan. Graduate Institute of Clinical Medicine National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei City 106319 Taiwan. Department of Neurology Cardinal Tien Hospital No. 362 Zhongzheng Rd. Xindian Dist. New Taipei City 231009 Taiwan.

With the increasing prevalence of age-related chronic diseases burdening healthcare systems, there is a pressing need for innovative management strategies. Our study focuses on the gut microbiota, essential for metabolic, nutritional, and immune functions, which undergoes significant changes with aging. These changes can impair intestinal function, leading to altered microbial diversity and composition that potentially influence health outcomes and disease progression. Using advanced metagenomic sequencing, we explore the potential of personalized probiotic supplements in 297 older adults by analyzing their gut microbiota. We identified distinctive Lactobacillus and Bifidobacterium signatures in the gut microbiota of older adults, revealing probiotic patterns associated with various population characteristics, microbial compositions, cognitive functions, and neuroimaging results. These insights suggest that tailored probiotic supplements, designed to match individual probiotic profile, could offer an innovative method for addressing age-related diseases and functional declines. Our findings enhance the existing evidence base for probiotic use among older adults, highlighting the opportunity to create more targeted and effective probiotic strategies. However, additional research is required to validate our results and further assess the impact of precision probiotics on aging populations. Future studies should employ longitudinal designs and larger cohorts to conclusively demonstrate the benefits of tailored probiotic treatments.

关键词： consensus clustering gut microbiome metagenomics non-negative matrix factorization older adults precision probiotics

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