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Anisotropic superconductivity and frozen electronic states at the (111) LaAlO3/SrTiO3 interface

Physical Review B 2018年第2期98卷 024504-024504页

作者： S. Davis Z. Huang K. Han Ariando T. Venkatesan V. Chandrasekhar Graduate Program in Applied Physics and Department of Physics and Astronomy Northwestern University 2145 Sheridan Road Evanston Illinois 60208 USA NUSNNI-Nanocore National University of Singapore 117411 Singapore Department of Physics National University of Singapore 117551 Singapore NUS Graduate School for Integrative Sciences & Engineering National University of Singapore 117456 Singapore Department of Physics National University of Singapore 117542 Singapore Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore Department of Material Science and Engineering National University of Singapore 117575 Singapore

We report measurements of the superconducting properties of the two-dimensional (2D) gas that forms at the interface between LaAlO3 (LAO) and SrTiO3 (STO) in the (111) crystal orientation, a system that permits in situ tuning of carrier density and disorder by means of a back-gate voltage Vg. Like the (001) oriented LAO/STO interface, superconductivity at the (111) LAO/STO interface can be tuned by Vg. The 2D superconductivity in these (111) LAO/STO samples shows an in-plane anisotropy, being different along different interface crystal directions, and “remembers” the disorder landscape at which they are cooled through the superconducting transition. The low energy scale and other characteristics of this memory effect distinguish it from charge-trapping effects previously observed in (001) interface samples.

关键词： electrical conductivity Impurities in superconductors Superconducting phase transition Superconductivity Interfaces Solid-solid interfaces Superconductors Two-dimensional electron gas Type-II superconductors Hall bar Resistivity measurements

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The redshirt in engineering consortium: Progress and early insights 125

The redshirt in engineering consortium: Progress and early i...

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125th ASEE Annual Conference and Exposition

作者： Riskin, Eve A. Milford, Jana Callahan, Janet Cosman, Pamela Schneider, John B. Pitts, Kevin Knaphus-Soran, Emily Llewellyn, Donna C. Delaney, Ann E. Myers, Beth A. Tetrick, Katherine Christine Cunningham, Sonya Ennis, Tanya D. O'Connor, Kevin Ferrez, Michelle Pan, Tiffany D. Baldis, Jessica EE Department University of Washington United States Engineering GoldShirt Program University of Colorado Boulder United States Micron School of Materials Science and Engineering Boise State University United States Department of Electrical and Computer Engineering University of California San Diego United States Voiland College of Engineering and Architecture United States Department of Physics University of Illinois Urbana-Champaign United States University of Washington United States Institute for STEM and Diversity Initiatives Boise State University United States Public Policy and Administration Boise State University United States Department of Analytics Assessment and Accreditation University of Colorado Boulder United States Program Washington State University United States University of Washington STARS Program Diversity and Access College of Engineering United States Engineering GoldShirt Program University of Colorado Boulder College of Engineering and Applied Science United States Department of Educational Psychology and Learning Sciences University of Colorado Boulder United States United States

The NSF-funded Redshirt in engineering Consortium was formed in 2016 with the goal of enhancing the ability of academically talented but underprepared students coming from low-income backgrounds to successfully graduate with engineering degrees. The Consortium takes its name from the practice of redshirting in college athletics, with the idea of providing an extra year and support to help promising engineering students complete a bachelor's degree. The Consortium builds on the success of three existing "academic redshirt" programs and expands the model to three new schools. The Existing Redshirt Institutions (ERIs) help mentor and train the new Student Success Partners (SSPs), and SSPs contribute their unique expertise to help ERIs improve existing Redshirt programs. The Redshirt model consists of seven main programmatic components aimed at improving the engagement, retention, and graduation of students underrepresented in engineering. These components include: "intrusive" academic advising and support services, an intensive first-year academic curriculum, community-building (including pre-matriculation summer programs), career awareness and vision, faculty mentorship, NSF S-STEM scholarships, and second-year support. Successful implementation of these activities is intended to produce two main long-term outcomes: a six-year graduation rate of 60%-75% for Redshirt students, and increased rates of enrollment and graduation of Pell-eligible, URM, and women students in engineering at participating universities. In the first year of the grant (AY 16-17), SSPs developed their own Redshirt programs, hired and trained staff, and got their programs off the ground. ERIs implemented faculty mentorship programs and expanded support to Redshirt students into their sophomore year. In the second year (AY 17-18), Redshirt programs were expanded at the ERIs while SSPs welcomed their first cohorts of Redshirt students. This Work in Progress paper describes the Redshirt programs at e

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Ten quick tips for deep learning in biology

arXiv

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Metasurfaces: Coherent Perfect Diffraction in Metagratings (Adv. Mater. 36/2020)

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Advanced Materials 2020年第36期32卷

作者： Ziying Zhang Ming Kang Xueqian Zhang Xi Feng Yuehong Xu Xieyu Chen Huifang Zhang Quan Xu Zhen Tian Weili Zhang Alex Krasnok Jiaguang Han Andrea Alù Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronics Information and Technology Tianjin University Tianjin 300072 P. R. China Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 USA School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 USA Photonics Initiative Advanced Science Research Center City University of New York New York NY 10031 USA Physics Program Graduate Center City University of New York New York NY 10016 USA

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Stakeholder Act as an IT and General Compliance Auditor

Stakeholder Act as an IT and General Compliance Auditor

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International Conference on Sustainable Information engineering and Technology (SIET)

作者： Surjandy Erick Fernando Meyliana Raymond Kosala Suhono Harso Supangkat Diani Dwiningrum Merry Marshela Angelica Renita Amalia Information Systems Audit Program Information Systems Department Bina Nusantara University Jakarta Indonesia Information Systems Departement Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781538674086;9781538674079

Recently, the Indonesian government requires auditors, the need for auditors around 40,000 auditors in 2016, currently has only about 10,800 auditors, however, the lack of the auditors impacting the risk of financial loss for the state. Referring to the problem, this experimental research was conducted. The experiment of the research was conducted two times and the audit topic is a compliance audit in the year 2017 and year 2018. The goal of this research is to know, can the stakeholder act as an IT and general compliance auditor? The experiment was conducted by 8 university students in 2017 and 19 university students in 2018, and the supporting tools of audit activities the university student use the smartphone to capture the object as evidence. The experiment results with descriptive method show university students can act as an auditor and found several pieces of evidence that might cause future impact to the institution.

关键词： Regulation Stakeholders Companies Libraries Finance

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Hybrid Beam Forming with Data Logging Scheduling(DLS) for wireless sensor network(WSN)

Hybrid Beam Forming with Data Logging Scheduling(DLS) for wi...

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2017 IEEE International Conference on applied System Innovation, ICASI 2017

作者： Renu, Sakthidasan Yen, Lei Belay, Abebe Lin, Hsin-Piao Jeng, Shiann-Shiun Department of International Graduate Program in Electrical Engineering and Computer Science National Taipei University of Technology Taiwan Department of Electronic Engineering National Taipei University of Technology Taiwan Department of Electrical Engineering National Dong Hwa University Taipei Taiwan

ISBN: (纸本)9781509048977

Improve of the overall network efficiency between source and destination relay selection and interference free communication is important criteria in WSN. In this paper we are proposing SON based algorithm capable of simultaneous Scheduling and Routing in WSN. The proposes scheme contains the three stages, in first stage the sensor nodes are classified into different clusters and each nodes having different weight based on distance from base station. In second stage the IRSS (Improvised Received Signal Strength) based scheme used select Routing path based on the Node weight, Residual Energy and Probability of Link Loss values of Relay Sensors. On the other side the channel estimation algorithm executed simultaneously with previous two stages. In final we are implementing the Data Logging based Scheduling and Routing scheme (DLSR) for WSN with Energy and Maximized Throughput. We are applying path recovery algorithm in presence of Void path or node failures. The proposed scheme additionally will form the virtual relay path to make communication with nearly zero loss. © 2017 IEEE.

关键词： Scheduling

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Generative Adversarial Networks Enable Cross-Modality Super-Resolution in Fluorescence Microscopy

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Microscopy and Microanalysis 2019年第S2期25卷 1228-1229页

作者： Hongda Wang Yair Rivenson Yiyin Jin Zhensong Wei Ronald Gao Harun Günaydın Laurent A. Bentolila Comert Kural Aydogan Ozcan Electrical & Computer Engineering Department University of California Los Angeles Los Angeles USA Bioengineering Department University of California Los Angeles Los Angeles USA California NanoSystems Institute University of California Los Angeles Los Angeles USA Computer Science Department University of California Los Angeles Los Angeles USA Department of Chemistry and Biochemistry University of California Los Angeles Los Angeles USA Department of Physics Ohio State University Columbus USA Biophysics Graduate Program Ohio State University Columbus USA Department of Surgery David Geffen School of Medicine University of California Los Angeles Los Angeles USA.

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High temperature structure detection in ferromagnets

arXiv

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arXiv 2018年

作者： Cao, Yuan Neykov, Matey Liu, Han Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Department of Statistics & Data Science Carnegie Mellon University PittsburghPA United States Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL United States

This paper studies structure detection problems in high temperature ferromagnetic (positive interaction only) Ising models. The goal is to distinguish whether the underlying graph is empty, i.e., the model consists of independent Rademacher variables, versus the alternative that the underlying graph contains a subgraph of a certain structure. We give matching upper and lower minimax bounds under which testing this problem is possible/impossible respectively. Our results reveal that a key quantity called graph arboricity drives the testability of the problem. On the computational front, under a conjecture of the computational hardness of sparse principal component analysis, we prove that, unless the signal is strong enough, there are no polynomial time linear tests on the sample covariance matrix which are capable of testing this problem. Copyright © 2018, The Authors. All rights reserved.

关键词： Ferromagnetism

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Fundamental bounds on the operation of Fano nonlinear isolators

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Physical Review B 2018年第11期97卷 115431-115431页

作者： Dimitrios L. Sounas Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative Advanced Science Research Center City University of New York New York 10031 USA Physics Program Graduate Center City University of New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Nonlinear isolators have attracted significant attention for their ability to break reciprocity and provide isolation without the need of an external bias. A popular approach for the design of such devices is based on Fano resonators, which, due to their sharp frequency response, can lead to very large isolation for moderate input intensities. Here, we show that, independent of their specific implementation, these devices are subject to fundamental bounds on the transmission coefficient in the forward direction versus their quality factor, input power, and nonreciprocal intensity range. Our analysis quantifies a general tradeoff between forward transmission and these metrics, stemming directly from time-reversal symmetry, and that unitary transmission is only possible for vanishing nonreciprocity. Our results also shed light on the operation of resonant nonlinear isolators, reveal their fundamental limitations, and provide indications on how it is possible to design nonlinear isolators with optimal performance.

关键词： Electromagnetism Metamaterials Nonlinear optics

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Retracted: Implementation Method CUSUM to Determine the Accident Prone Areas in Web Based

Retracted: Implementation Method CUSUM to Determine the Acci...

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2018 Workshop on Multidisciplinary and Its Applications: applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Dinata, Rozzi Kesuma Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Riasti, Berliana Kusuma Iskandar, Akbar Sari, Ifit Novita Nurmawati, N. Nanuru, Ricardo Freedom Putri, Lusi Dwi Manurung, Rosida Tiurma Sriadhi, S. Saleh, A.A. Astari, T. Khaddafi, Muammar Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics Universitas Sebelas Maret Surakarta Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Departement Of: Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Department of Civil Engineering Universitas Lancang Kuning Pekanbaru Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Elementary School Teacher Education STKIP Citra Bangsa Aceh Utara Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

At the Unit Laka Lantas Polres Lhokseumawe determining accident-prone areas on roads in Lhokseumawe still using manual systems. Determination of accident-prone areas are less effective because the police Unit Laka Lantas Polres Lhokseumawe just using the data of the last year and had to repeatedly calculate manually accident-prone areas based on the number of human casualties. In this study the system implementation CUSUM method (Cummulative Summary) to determine the accident-prone areas designed using the web-based programming language PHP. In this system there are three processes to determine areas prone to accidents, the accident rate calculations based on the weighted severity, blacksite calculations using the Z-Score method for determining areas prone to accident blackspots and calculations using the CUSUM method to determine the critical points of an accident. The data used are secondary data obtained from the Police Unit Laka Lantas Polres Lhokseumawe years 2009-2013. © Published under licence by IOP Publishing Ltd.

关键词： Accidents

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