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Concerted alterations of functional connectivity and WM integrity in relationship to early amyloid deposition

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Alzheimer's & Dementia 2022年第S1期18卷

作者： Luigi Lorenzini Beatrice Orso David Vállez García Giuseppe Pontillo Silvia Ingala Sven Haller Kaj Blennow Giovanni B Frisoni Gael Chetelat Pierre Payoux Pablo Martinez-Lage Michael Ewers Adam Waldman Craig W. Ritchie Juan Domingo Gispert Pieter Jelle Visser Henri JMM Mutsaerts Betty M. Tijms Alle Meije Wink Frederik Barkhof Department of Radiology and Nuclear Medicine Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands Department of Radiology and Nuclear Medicine Amsterdam UMC Location VuMC Vijre Universiteit Amsterdam Amsterdam Netherlands Department of Neuroscience Rehabilitation Ophthalmology Genetics Maternal and Child Health (DINOGMI) University of Genoa Genova Italy Department of Radiology & Nuclear Medicine Amsterdam UMC location VUmc Amsterdam Netherlands Department of Advanced Biomedical Sciences University “Federico II” Naples Italy Department of Electrical Engineering and Information Technology University of Naples “Federico II” Naples Italy University of Geneva Faculty of Medicine Geneva Switzerland Uppsala University Uppsala Sweden Department of Psychiatry and Neurochemistry The Sahlgrenska Academy at the University of Gothenburg Mölndal Sweden Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli Brescia Italy Geneva Memory Center Department of Rehabilitation and Geriatrics Geneva University Hospitals Geneva Switzerland ToNIC Toulouse NeuroImaging Center Université de Toulouse Inserm UPS Toulouse France INSERM Imagerie cérébrale et handicaps neurologiques Toulouse France CITA-Alzheimer Foundation San Sebastian Spain German Center for Neurodegenerative Diseases (DZNE) Munich Germany Imperial College London London United Kingdom Centre for Clinical Brain Sciences The University of Edinburgh Edinburgh United Kingdom Centre for Dementia Prevention at the University of Edinburgh Edinburgh United Kingdom Centro de Investigación Biomédica en Red Bioingeniería Biomateriales y Nanomedicina Madrid Spain Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain Universitat Pompeu Fabra Barcelona Spain Alzheimer Centrum Limburg Maastricht Univ

Background Early amyloid deposition results in functional and structural brain alterations in predementia stages of Alzheimer's disease (AD). However, how early functional and structural brain changes are related to each other remains unclear. Investigating the simultaneous disruptions of functional-structural brain features within individuals in relation to amyloid deposition may increase our understanding of the neuropathological processes underlying AD. Method We included 648 non-demented participants from the European Prevention for Alzheimer’s Dementia (EPAD) cohort vIMI baseline data release. The cut-off for cerebrospinal fluid (CSF) amyloid-β positivity (A+) was defined at <1000pg/mL (Elecsys assay). Functional connectivity was estimated with functional eigenvector centrality (EC) from the resting state functional MRI. White matter (WM) integrity was estimated with fractional anisotropy (FA), computed on diffusion MRI. Both measures were computed at the voxel level within the gray and white matter, respectively. First, we used linear regression models to investigate differences between A+ and A- participants within each modality separately, adjusting for age, sex, and site. In the whole group, we performed sparse canonical correlation analysis (sCCA) on functional and structural measures, identifying shared components between the two modalities. Individual sCCA scores were compared between amyloid groups using a generalized linear model (GLM). To evaluate this association in A+ individuals, the same sCCA analysis was performed normalizing the structural and functional matrices using the mean and SD from A- participants. Results Sample characteristics are provided in Table 1 . Differences in voxelwise EC and FA between amyloid groups are shown in Figure 1 . In the whole group, sCCA analysis showed that EC in the default mode, executive and cerebellar networks covary with FA in parietal, temporal and cerebellar areas ( Figure 2 ). sCCA projections were differen

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Author Correction: Anak Krakatau triggers volcanic freezer in the upper troposphere

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Scientific reports 2020年第1期10卷 7279页

作者： A T Prata A Folch A J Prata R Biondi H Brenot C Cimarelli S Corradini J Lapierre A Costa Barcelona Supercomputing Center Computer Applications in Science and Engineering Barcelona Spain. andrew.prata@bsc.es. Barcelona Supercomputing Center Computer Applications in Science and Engineering Barcelona Spain. AIRES Pty. Ltd. Mt Eliza Victoria Australia. Visiting Professor School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia. Università degli Studi di Padova Dipartimento di Geoscienze Padua Italy. Royal Belgian Institute for Space Aeronomy Brussels Belgium. Department of Earth and Environmental Sciences Ludwig-Maximilians-Universität München Germany. Istituto Nazionale di Geofisica e Vulcanologia Osservatorio Nazionale Terremoti Rome Italy. Earth Networks Inc. Germantown MD United States. Istituto Nazionale di Geofisica e Vulcanologia Sezione di Bologna Bologna Italy.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Eavesdropping and countermeasures for backflash side channel in quantum cryptography

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arXiv 2018年

作者： Pinheiro, Paulo Vinicius Pereira Chaiwongkhot, Poompong Sajeed, Shihan Horn, Rolf T. Bourgoin, Jean-Philippe Jennewein, Thomas Lütkenhaus, Norbert Makarov, Vadim Engineering Department Paraíso Faculty of Ceará Juazeiro do Norte Ceará63010-465 Brazil Department of Teleinformatic Engineering Federal University of Ceará C.P.6007 Campus do Pici Fortaleza Brazil Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Toronto M5S 3G4 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Quantum Information Science Program Canadian Institute for Advanced Research TorontoON Canada Russian Quantum Center MISIS University Moscow Russia

Quantum key distribution (QKD) promises information theoretic secure key as long as the device performs as assumed in the theoretical model. One of the assumptions is an absence of information leakage about individual photon detection outcomes of the receiver unit. Here we investigate the information leakage from a QKD receiver due to photon emission caused by detection events in single-photon detectors (backflash). We test commercial silicon avalanche photodiodes and a photomultiplier tube, and find that the former emit backflashes. We study the spectral, timing and polarization characteristics of these backflash photons. We experimentally demonstrate on a free-space QKD receiver that an eavesdropper can distinguish which detector has clicked inside it, and thus acquire secret information. A set of countermeasures both in theory and on the physical devices are discussed. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum cryptography

Comments on a privacy preserving public auditing mechanism for shared cloud data 17

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Comments on a privacy preserving public auditing mechanism f...

4th Multidisciplinary International Social Networks Conference, MISNC 2017

作者： Wu, Tsu-Yang Lin, Yueshan Wang, King-Hang Chen, Chien-Ming Pan, Jeng-Shyang Wu, Mu-En Fujian Provincial Key Laboratory of Big Data Mining and Applications National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou350118 China Harbin Institute of Technology Shenzhen Graduate School Shenzhen518055 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Department of Mathematic Soochow University Taipei Taiwan

ISBN: (纸本)9781450348812

Auditing mechanisms are received much attentions from researchers due to the developing of cloud storage. Recently, Wang et al. proposed a privacy preserving public auditing mechanism for shared cloud data with supporting group dynamic. However, we find some security flaws in their mechanism. In this paper, a forgery attack and a data corruption attack are proposed to demonstrate the insecurity. Then, we propose a modified scheme based on their mechanism. The security analysis is demonstrated that our improvement can resist the mentioned two attacks. © 2017 ACM.

关键词： Cloud storage

Joint offloading and computing optimization in wireless powered mobile-edge computing systems

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arXiv 2017年

作者： Wang, Feng Xu, Jie Wang, Xin Cui, Shuguang School of Information Engineering Guangdong University of Technology Guangzhou China Shanghai Institute for Advanced Communication and Data Science Department of Communication Science and Engineering Fudan University Shanghai China Department of Electrical and Computer Engineering University of California DavisCA95616 United States Shenzhen Research Institute of Big Data

Mobile-edge computing (MEC) and wireless power transfer (WPT) have been recognized as promising techniques in the Internet of Things (IoT) era to provide massive low-power wireless devices with enhanced computation capability and sustainable energy supply. In this paper, we propose a unified MEC-WPT design by considering a wireless powered multiuser MEC system, where a multi-antenna access point (AP) (integrated with an MEC server) broadcasts wireless power to charge multiple users and each user node relies on the harvested energy to execute computation tasks. With MEC, these users can execute their respective tasks locally by themselves or offload all or part of them to the AP based on a time division multiple access (TDMA) protocol. Building on the proposed model, we develop an innovative framework to improve the MEC performance, by jointly optimizing the energy transmit beamforming at the AP, the central processing unit (CPU) frequencies and the numbers of offloaded bits at the users, as well as the time allocation among users. Under this framework, we address a practical scenario where latency-limited computation is required. In this case, we develop an optimal resource allocation scheme that minimizes the AP's total energy consumption subject to the users' individual computation latency constraints. Leveraging the state-of-the-art optimization techniques, we derive the optimal solution in a semi-closed form. Numerical results demonstrate the merits of the proposed design over alternative benchmark schemes. Copyright © 2017, The Authors. All rights reserved.

关键词： Convex optimization

Quantum computing at the frontiers of biological sciences

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arXiv 2019年

作者： Emani, Prashant S. Warrell, Jonathan Anticevic, Alan Bekiranov, Stefan Gandal, Michael McConnell, Michael J. Sapiro, Guillermo Aspuru-Guzik, Alán Baker, Justin Bastiani, Matteo McClure, Patrick Murray, John Sotiropoulos, Stamatios N. Taylor, Jacob Senthil, Geetha Lehner, Thomas Gerstein, Mark B. Harrow, Aram W. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Yale School of Medicine Department of Psychiatry New HavenCT06511 United States University of Virginia School of Medicine Department of Biochemistry and Molecular Genetics CharlottesvilleVA22903 United States Department of Psychiatry Semel Institute David Geffen School of Medicine University of California–Los Angeles 695 Charles E. Young Drive South Los AngelesCA90095 United States Univ. of Virginia School of Medicine Department of Neuroscience CharlottesvilleVA22903 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Chemistry University of Toronto 80 St. George Street TorontoONM5S 3H6 Canada TorontoONM5S 1M1 Canada CIFAR Artificial Intelligence Research Chair Vector Institute TorontoONM5S 1M1 Canada Department of Computer Science University of Toronto 40 St. George Street TorontoONM5S 2E4 Canada Schizophrenia and Bipolar Disorder Program McLean Hospital BelmontMA02478 United States Department of Psychiatry Harvard Medical School BostonMA02114 United States Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham NottinghamNG7 2RD United Kingdom Machine Learning Team National Institute of Mental Health BethesdaMD20892 United States Section on Functional Imaging Methods National Institute of Mental Health BethesdaMD20892 United States Department of Psychiatry Yale University School of Medicine New HavenCT06511 United States Department of Physics Yale University New HavenCT06511 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States National Institute of Standards and Technology GaithersburgMD20899 United States Office of Genomics Research Coordination N

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Alert classification for the ALeRCE broker system: The light curve classifier

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arXiv 2020年

作者： Sánchez-Sáez, Paula Reyes, I. Valenzuela, C. Förster, F. Eyheramendy, S. Elorrieta, F. Bauer, F.E. Cabrera-Vives, G. Estévez, P.A. Catelan, M. Pignata, G. Huijse, P. de Cicco, D. Arévalo, P. Carrasco-Davis, R. Abril, J. Kurtev, R. Borissova, J. Arredondo, J. Castillo-Navarrete, E. Rodriguez, D. Ruz-Mieres, D. Moya, A. Sabatini-Gacitúa, L. Sepúlveda-Cobo, C. Camacho-Iñiguez, E. Nuncio Monseñor Sótero Sanz 100 Providencia Santiago Chile Instituto de Astrofísica Facultad de Física Pontificia Universidad Católica de Chile Casilla 306 Santiago 22 Chile Faculty of Engineering and Sciences Universidad Adolfo Ibañez Diagonal Las Torres 2700 Peñalolén Santiago Chile Center for Mathematical Modeling Universidad de Chile Beauchef 851 North building 7th floor Santiago8320000 Chile Department of Electrical Engineering Universidad de Chile Av. Tupper 2007 Santiago8320000 Chile Data Observatory Diagonal Las Torres 2640 Peñalolén Santiago Chile Departmento de Matemáticas Facultad de Ciencia Universidad de Santiago de Chile Estación Central Av. Libertador Bernardo O'Higgins 3663 Santiago Chile Departamento de Astronomía Universidad de Chile Casilla 36D Santiago Chile Centro de Astroingeniería Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Space Science Institute 4750 Walnut Street Suite 205 BoulderCO80301 United States Department of Computer Science University of Concepcón Edmundo Larenas 219 Concepción Chile Departamento de Ciencias Fisícas Universidad Andres Bello Avda. Republica 252 Santiago Chile Informatics Institute Universidad Austral de Chile General Lagos 2086 Valdivia Chile Instituto de Física y Astronomía Facultad de Ciencias Universidad de Valparaíso Gran Bretana No. 1111 Playa Ancha Valparaíso Chile Alonso de Córdova 3107 Vitacura Santiago Chile - Unidad Asociada al CSIC Plaza San Juan 1 TeruelE-44001 Spain

We present the first version of the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory. The ALeRCE light curve classifier uses variability features computed from the ZTF alert stream, and colors obtained from AllWISE and ZTF photometry. We apply a Balanced Random Forest algorithm with a two-level scheme, where the top level classifies each source as periodic, stochastic, or transient, and the bottom level further resolves each of these hierarchical classes, amongst 15 total classes. This classifier corresponds to the first attempt to classify multiple classes of stochastic variables (including core- and host-dominated active galactic nuclei, blazars, young stellar objects, and cataclysmic variables) in addition to different classes of periodic and transient sources, using real data. We created a labeled set using various public catalogs (such as the Catalina Surveys and Gaia DR2 variable stars catalogs, and the Million Quasars catalog), and we classify all objects with ≥ 6 g-band or ≥ 6 r-band detections in ZTF (868,371 sources as of 2020/06/09), providing updated classifications for sources with new alerts every day. For the top level we obtain macro-averaged precision and recall scores of 0.96 and 0.99, respectively, and for the bottom level we obtain macro-averaged precision and recall scores of 0.57 and 0.76, respectively. Updated classifications from the light curve classifier can be found at the ALeRCE Explorer website. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

Modeling of minibands for Si/Sc quantum dot superlattice solar cells 11

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Modeling of minibands for Si/Sc quantum dot superlattice sol...

11th Annual TechConnect World Innovation Conference and Expo, Held Jointly with the 20th Annual Nanotech Conference and Expo, and the 2017 National SBIR/STTR Conference

作者： Tsai, Yi-Chia Lee, Ming-Yi Li, Yiming Samukawa, Seiji Parallel and Scientific Computing Laboratory National Chiao Tung University Hsinchu300 Taiwan Institute of Communications Engineering National Chiao Tung University Hsinchu300 Taiwan Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu300 Taiwan Institute of Fluid Science Tohoku University Aoba-ku Sendai Miyagi9808577 Japan WPI-Advanced Institute for Materials Research Tohoku University Sendai Miyagi9808577 Japan

ISBN: (纸本)9780997511796

The silicon (Si)/silicon carbide (SiC) quantum dot superlattice solar cells (SiC-QDSL) with aluminum oxide (A12O3-QDSL) passivation approaches a high short-circuit current (Jsc) of 4.77 mA/cm2 under AMI.5 and one sun illumination due to the quantum enhancement on effective bandgap and minimum transition energy. This value matches well with experimental measurement of 4.75 mA/cm2. To further optimize the conversion efficiency through the geometry of Al2O3-QDSL, we introduce several parameters to define a complete QDSL configuration. A high conversion efficiency of 17.4% is optimized by using the QD geometry from experiment and applying hexagonal QDSL formation with an inter-dot spacing of 0.3 nm.

关键词： Solar cells

Accelerating circuit realization via a collaborative gateway of innovations 9

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Accelerating circuit realization via a collaborative gateway...

9th International Workshop on science Gateways, IWSG 2017

作者： Taylor, Ian J. Brinckman, Adam Deelman, Ewa da Silva, Rafael Ferreira Gupta, Sandeep Nabrzyski, Jarek Park, Soowang Vahi, Karan Center for Research Computing University of Notre Dame Notre DameIN United States School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Information Sciences Institute University of Southern California Marina del ReyCA United States Department of Electrical Engineering University of Southern California Los AngelesCA United States

The CRAFT repository seeks to develop new fast-track circuit-design methods, multiple sources for integrated circuit fabrication, and a technology repository. This paper presents the design decisions and implementation to build a collaborative repository that capitalizes on the recent advances in open-source collaborative frameworks, and answers the needs for the DARPA’s CRAFT program. The repository has been developed as an EmberJS application (front-end), which interacts with an instance of the Open science Framework (OSF). © 2017 CEUR-WS. All rights reserved.

关键词： Timing circuits