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Cover Image, Volume 5, Number 3, March 2023

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Carbon Energy 2023年第3期5卷

作者： Jun Yang Xing Li Ke Qu Yixian Wang Kangqi Shen Changhuan Jiang Bo Yu Pan Luo Zhuangzhi Li Mingyang Chen Bingshu Guo Mingshan Wang Junchen Chen Zhiyuan Ma Yun Huang Zhenzhong Yang Pengcheng Liu Rong Huang Xiaodi Ren David Mitlin School of New Energy and Materials Southwest Petroleum University Chengdu China Energy Storage Research Institute Southwest Petroleum University Chengdu China Ke Qu Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. China Key Laboratory of Polar Materials and Devices (MOE) and Department of Electronics East China Normal University Shanghai 200062 China. Mingyang Chen Beijing Computational Science Research Center Beijing 100193 China. Center for Green Innovation School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 China. Rong Huang China Key Laboratory of Polar Materials and Devices (MOE) and Department of Electronics East China Normal University Shanghai 200062 China. Xiaodi Ren Hefei National Research Center for Physical Sciences at the Microscale Department of Materials Science and Engineering University of Science and Technology of China Hefei Anhui 230026 China. David Mitlin Materials Science Program and Texas Materials Institute The University of Texas at Austin Austin Texas 78712-1591 USA. Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China China Key Laboratory of Polar Materials and Devices (MOE) Department of Electronics East China Normal University Shanghai China Xing Li School of New Energy and Materials Southwest Petroleum University Chengdu China. Materials Science Program and Texas Materials Institute The University of Texas at Austin Austin Texas USA Beijing Computational Science Research Center Beijing China School of Materials Science and Engineering Center for Green Innovation University of Science and Technology Beijing Beijing China Department of Materials Science and Engineering Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Hefei Anhui China

Interference mitigation of adjacent radio frequency signals on a flexible software-defined radio testbed platform 55

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Interference mitigation of adjacent radio frequency signals ...

55th Annual International Telemetering Conference: Cultivating the Next Generation of Range Engineers, ITC 2019

作者： Elahi, Mirza M. Sandoval, Jose C. Gonzalez, Virgilio Corral, Pabel Yasuda, Susumu Gonzalez, Virgilio Computational Science Program University of Texas at El Paso El PasoTX79968 United States Department of Electrical and Computer Engineering University of Texas at El Paso El PasoTX79968 United States U.S. Army Test and Evaluation Command White Sands Missile Range White SandsNM United States

ISBN: (纸本)9781713801887

The radio frequency (RF) spectrum is crowded with users and adjacent frequency users are facing an increase in interference from each other. The spectrum governing body Federal Communications Commission (FCC) has the difficult task of allocating spectral bands for new users for mobile devices using 4G LTE technology. Telemetry (TM) is affected by the adjacent band 4G LTE users in terms of signal degradation. To minimize the interference between adjacent frequency users, several methods can be used. A common but inefficient method separates adjacent band frequencies using guard bands which leaves a big portion of the spectrum unused. Alternatively, adjacent RF signals can be separated using digital filtering techniques with the signal of interest being unharmed and reducing the signal power of the interfering signal. A digital filtering technique includes bandpass filter (BPF) rejection, which has the ability to filter out adjacent interfering signals. This is accomplished by designing bandpass digital filters where the passband and stopband frequencies are adjusted to achieve maximum signal power and reject the interfering signal by reducing its power. A flexible software-defined radio testbed is set up to experiment and analyze this scenario with ease and effective measures. © 2019 International Foundation for Telemetering. All rights reserved.

关键词： Bandpass filters

Core collapse supernova gravitational wave emission for progenitors of 9.6, 15, and 25M⊙

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Physical Review D 2023年第4期107卷 043008-043008页

作者： Anthony Mezzacappa Pedro Marronetti Ryan E. Landfield Eric J. Lentz R. Daniel Murphy W. Raphael Hix J. Austin Harris Stephen W. Bruenn John M. Blondin O. E. Bronson Messer Jordi Casanova Luke L. Kronzer Department of Physics and Astronomy University of Tennessee 1408 Circle Drive Knoxville Tennessee 37996-1200 USA Physics Division National Science Foundation Alexandria Virginia 22314 USA National Center for Computational Sciences Oak Ridge National Laboratory P.O. Box 2008 Oak Ridge Tennessee 37831-6164 USA Physics Division Oak Ridge National Laboratory P.O. Box 2008 Oak Ridge Tennessee 37831-6354 USA Joint Institute for Nuclear Physics and its Applications Oak Ridge National Laboratory P.O. Box 2008 Oak Ridge Tennessee 37831-6374 USA Department of Physics Florida Atlantic University 777 Glades Road Boca Raton Florida 33431-0991 USA Department of Physics North Carolina State University Raleigh North Carolina 27695-8202 USA Physics Program Community College of Denver P.O. Box 173363 Denver Colorado 80217-3363 USA Department of Aerospace Engineering and Mechanics University of Alabama Box 870280 Tuscaloosa Alabama 35487-0280 USA

We present gravitational wave emission predictions based on three core collapse supernova simulations corresponding to three different progenitor masses. The masses span a large range, between 9.6 and 25M⊙, are all initially nonrotating, and are of two metallicities: zero and solar. We compute both the temporal evolution of the gravitational wave strains for both the plus and the cross polarizations, as well as their spectral decomposition and characteristic strains. The temporal evolution of our zero metallicity 9.6M⊙ progenitor model is distinct from the temporal evolution of our solar metallicity 15M⊙ progenitor model and our zero metallicity 25M⊙ progenitor model. In the former case, the high-frequency gravitational wave emission is largely confined to a brief time period ∼75 ms after bounce, whereas in the latter two cases high-frequency emission does not commence until ∼125 ms after bounce or later. The excitation mechanisms of the high-frequency emission in all three cases correspond to proto-neutron star convection and accretion onto the proto-neutron star from the convective gain layer above it, with the former playing the dominant role for most of the evolution. The low-frequency emission in all three models exhibits very similar behavior. At frequencies below ∼250 Hz, gravitational waves are emitted by neutrino-driven convection and the standing accretion shock instability (SASI). This emission extends throughout the simulations when a gain region is present. In all three models, explosion is observed at ∼125, ∼500, and ∼250 ms after bounce in the 9.6, 15, and 25M⊙ progenitor models, respectively. At these times, the low-frequency gravitational wave emission is joined by very low-frequency emission, below ∼10 Hz. These very low-frequency episodes are the result of explosion and begin at the above designated explosion times in each of our models. Our characteristic strains tell us that, in principle, all three gravitational wave signals would be detec

关键词： Gravitation Gravitational waves Novae & supernovae Transient & explosive astronomical phenomena

An Open-Source Knowledge Graph Ecosystem for the Life sciences

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arXiv 2023年

作者： Callahan, Tiffany J. Tripodi, Ignacio J. Stefanski, Adrianne L. Cappelletti, Luca Taneja, Sanya B. Wyrwa, Jordan M. Casiraghi, Elena Matentzoglu, Nicolas A. Reese, Justin Silverstein, Jonathan C. Hoyt, Charles Tapley Boyce, Richard D. Malec, Scott A. Unni, Deepak R. Joachimiak, Marcin P. Robinson, Peter N. Mungall, Christopher J. Cavalleri, Emanuele Fontana, Tommaso Valentini, Giorgio Mesiti, Marco Gillenwater, Lucas A. Santangelo, Brook Vasilevsky, Nicole A. Hoehndorf, Robert Bennett, Tellen D. Ryan, Patrick B. Hripcsak, George Kahn, Michael G. Bada, Michael Baumgartner, William A. Hunter, Lawrence E. Computational Bioscience Program University of Colorado Anschutz Medical Campus AuroraCO80045 United States Department of Biomedical Informatics Columbia University Irving Medical Center New YorkNY10032 United States Computer Science Department Interdisciplinary Quantitative Biology University of Colorado Boulder BoulderCO80301 United States AnacletoLab Computer Science Department University of Milan 20122 Italy Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Department of Physical Medicine and Rehabilitation School of Medicine University of Colorado Anschutz Medical Campus AuroraCO80045 United States Division of Environmental Genomics and Systems Biology Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Semanticly Ltd Athens Greece Department of Biomedical Informatics University of Pittsburgh School of Medicine PittsburghPA15206 United States Laboratory of Systems Pharmacology Harvard Medical School BostonMA02115 United States Division of Translational Informatics University of New Mexico School of Medicine AlbuquerqueNM87131 United States SIB Swiss Institute of Bioinformatics Basel Switzerland Berlin Institute of Health at Charité-Universitatsmedizin Berlin10117 Germany ELLIS European Laboratory for Learning and Intelligent Systems Germany Department of Biomedical Informatics University of Colorado School of Medicine AuroraCO80045 United States Data Collaboration Center Critical Path Institute 1840 E River Rd. Suite 100 TucsonAZ85718 United States Computer Electrical and Mathematical Sciences & Engineering Division Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Pediatrics University of Colorado School of Medicine AuroraCO80045 United States Janssen Research and Development RaritanNJ08869 United States Division of General Internal Medicine University of Colorado School of Medicine A

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoints and abstraction algorithms), and benchmarks (e.g., prebuilt KGs and embeddings). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability. © 2023, CC BY.

关键词： Ecosystems

What affects the performance of POD for the simulation of heat transfer through building component?

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Journal of Physics: Conference Series 2021年第1期2069卷

作者： Tianfeng Hou Staf Roels Hans Janssen KU Leuven Department of Civil Engineering Building Physics Section 3001 Leuven Belgium Data Assimilation Research Team RIKEN Center for Computational Science Kobe Japan RIKEN Prediction Science Laboratory Kobe Japan RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program Kobe Japan

The capability of the proper orthogonal decomposition for the simulation of heat transfer in building components is investigated via three applications: linear heat transfer (not coupled to mass transfer), mildly non-linear heat transfer (coupled to air and moisture transfer (hygroscopic)) and highly non-linear heat transfer (coupled to moisture transfer (capillary)). It is shown that increasing non-linearity leads to an increasing number of required construction modes. To further investigate the reason for this degrading performance of POD, the singular values' decay progress from the different training snapshots is addressed in this paper. The results confirm that a fast decay of the singular values implies a high interrelation of the snapshots and a better performance of the POD method.

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Critical mass effect in evolutionary games triggered by zealots

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Physical Review Research 2020年第2期2卷 023305-023305页

作者： Alessio Cardillo Naoki Masuda Department of Engineering Mathematics University of Bristol Bristol BS8 1UB United Kingdom Department of Computer Science and Mathematics University Rovira i Virgili E-43007 Tarragona Spain GOTHAM Lab – Institute for Biocomputation and Physics of Complex Systems (BIFI) University of Zaragoza E-50018 Zaragoza Spain Department of Mathematics State University of New York at Buffalo Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260-5030 USA

Tiny perturbations may trigger large responses in systems near criticality, shifting them across equilibria. Committed minorities are suggested to be responsible for the emergence of collective behaviors in many physical, social, and biological systems. Using evolutionary game theory, we address the question whether a finite fraction of zealots can drive the system to large-scale coordination. We find that a tipping point exists in coordination games, whereas the same phenomenon depends on the selection pressure, update rule, and network structure in other types of games. Our study paves the way to understand social systems driven by the individuals' benefit in the presence of zealots, such as human vaccination behavior or cooperative transports in animal groups.

关键词： Patterns in complex systems Social systems

Detecting anomalous citation groups in journal networks

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arXiv 2020年

作者： Kojaku, Sadamori Livan, Giacomo Masuda, Naoki Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Computer Science University College London LondonWC1E 6EA United Kingdom Systemic Risk Centre London School of Economics and Political Science LondonWC2A 2AE United Kingdom Department of Mathematics University at Buffalo State University of New York BuffaloNY United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-2900 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact factors leads some journals to artificially boost impact factors through the coordinated effort of a "citation cartel" of journals. "Citation cartel" behavior has become increasingly common in recent years, with several instances being reported. Here, we propose an algorithm—-named CIDRE—to detect anomalous groups of journals that exchange citations at excessively high rates when compared against a null model that accounts for scientific communities and journal size. CIDRE detects more than half of the journals suspended from Journal Citation Reports due to anomalous citation behavior in the year of suspension or in advance. Furthermore, CIDRE detects many new anomalous groups, where the impact factors of the member journals are lifted substantially higher by the citations from other member journals. We describe a number of such examples in detail and discuss the implications of our findings with regard to the current academic climate. Copyright © 2020, The Authors. All rights reserved.

关键词： Publishing

Opinion dynamics on tie-decay networks

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arXiv 2020年

作者： Sugishita, Kashin Porter, Mason A. Beguerisse-Díaz, Mariano Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Department of Mathematics University of California Los AngelesCA90095 United States Mathematical Institute University of Oxford OxfordOX2 6GG United Kingdom Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

In social networks, interaction patterns typically change over time. We study opinion dynamics on tie-decay networks in which tie strength increases instantaneously when there is an interaction and decays exponentially between interactions. Specifically, we formulate continuous-time Laplacian dynamics and a discrete-time DeGroot model of opinion dynamics on these tie-decay networks, and we carry out numerical computations for the continuous-time Laplacian dynamics. We examine the speed of convergence by studying the spectral gaps of combinatorial Laplacian matrices of tie-decay networks. First, we compare the spectral gaps of the Laplacian matrices of tie-decay networks that we construct from empirical data with the spectral gaps for corresponding randomized and aggregate networks. We find that the spectral gaps for the empirical networks tend to be smaller than those for the randomized and aggregate networks. Second, we study the spectral gap as a function of the tie-decay rate and time. Intuitively, we expect small tie-decay rates to lead to fast convergence because the influence of each interaction between two nodes lasts longer for smaller decay rates. Moreover, as time progresses and more interactions occur, we expect eventual convergence. However, we demonstrate that the spectral gap need not decrease monotonically with respect to the decay rate or increase monotonically with respect to time. Our results highlight the importance of the interplay between the times that edges strengthen and decay in temporal networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Laplace transforms

A meta-analysis of Boolean network models reveals design principles of gene regulatory networks

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arXiv 2020年

作者： Kadelka, Claus Butrie, Taras-Michael Hilton, Evan Kinseth, Jack Schmidt, Addison Serdarevic, Haris Department of Mathematics Iowa State University AmesIA50011 United States Department of Aerospace Engineering Iowa State University AmesIA50011 United States Department of Computer Science Iowa State University AmesIA50011 United States Bioinformatics and Computational Biology Program Iowa State University AmesIA50011 United States

Gene regulatory networks (GRNs) play a central role in cellular decision-making. Understanding their structure and how it impacts their dynamics constitutes thus a fundamental biological question. GRNs are frequently modeled as Boolean networks, which are intuitive, simple to describe, and can yield qualitative results even when data is sparse. We assembled the largest repository of expert-curated Boolean GRN models. A meta-analysis of this diverse set of models reveals several design principles. GRNs exhibit more canalization, redundancy and stable dynamics than expected. Moreover, they are enriched for certain recurring network motifs. This raises the important question why evolution favors these design mechanisms. Copyright © 2020, The Authors. All rights reserved.

关键词： Decision making