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Journal articles on the topic 'Hyperscan'

Author: Grafiati
Published: 28 June 2021
Last updated: 10 February 2022

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1

Shuai, Longwen, and Suo Li. "Performance optimization of Snort based on DPDK and Hyperscan." Procedia Computer Science 183 (2021): 837–43. http://dx.doi.org/10.1016/j.procs.2021.03.007.

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2

Mulyati, Mulyati. "PENINGKATAN KETERAMPILAN MEMBACA PEMAHAMAN MELALUI METODE HYPERSCAN PADA SISWA SMA MUHAMMADIYAH 2 PALEMBANG." Jurnal Ilmiah Bina Edukasi 14, no. 1 (June 30, 2021): 46–58. http://dx.doi.org/10.33557/jedukasi.v14i1.1369.

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The hyper-scan method is one way that instructors employ to help students in class XI improve their reading comprehension. Indeed, many students struggle with reading comprehension. This is a Classroom Action Research (CAR) research comprising two cycles of 4 stages: planning, action, observation, and reflection. was used to analyze the test data. The result shows the average pre-cycle score was 63.83, the first cycle score was 73.77, and the second cycle score was 84.33. According to the percentage of students who qualify, there has traditionally been an increase. The percentage of completion in pre-cycle tests ranged from 10% to 46.6 percent in the first cycle and up to 90% in the second cycle. As a result, it can be concluded that the hyper-scan method can assist in reading comprehension skills development
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3

Anzolin, Alessandra, Arvina Grahl, Kylie Isenburg, Jlenia Toppi, Angela Ciaramidaro, Maya Barton Zuckerman, Meryem Yucel, et al. "Brain-to-brain patient-clinician connectivity is directionally modulated by chronic low back pain therapy: an electroencephalography hyperscan approach." Journal of Pain 22, no. 5 (May 2021): 601. http://dx.doi.org/10.1016/j.jpain.2021.03.093.

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4

Jersky, Brian. "Hyperstat." American Statistician 57, no. 4 (November 2003): 316–17. http://dx.doi.org/10.1198/tas.2003.s229.

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5

Iannella, Renato. "HyperSAM." ACM SIGCHI Bulletin 27, no. 2 (April 1995): 42–45. http://dx.doi.org/10.1145/202511.202522.

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6

White, Keith. "The hypersign." European Legacy 2, no. 3 (May 1997): 478–83. http://dx.doi.org/10.1080/10848779708579761.

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7

Finkelstein, David, Shlomit Ritz Finkelstein, and Christian Holm. "Hyperspin manifolds." International Journal of Theoretical Physics 25, no. 4 (April 1986): 441–63. http://dx.doi.org/10.1007/bf00670769.

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8

Finkelstein, David. "Hyperspin and Hyperspace." Physical Review Letters 56, no. 15 (April 14, 1986): 1532–33. http://dx.doi.org/10.1103/physrevlett.56.1532.

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9

AL-AYYOUB, ABDEL-ELAH, and KHALED DAY. "FAST LU FACTORIZATION ON THE HYPERSTAR INTERCONNECTION NETWORK." Journal of Interconnection Networks 03, no. 03n04 (September 2002): 231–43. http://dx.doi.org/10.1142/s0219265902000641.

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The hyperstar network has been recently proposed as an attractive product network that outperforms many popular topologies in various respects. In this paper we explore additional capabilities for the hyperstar network through an efficient parallel algorithm for solving the LU factorization problem on this network. The proposed parallel algorithm uses O(n) communication time on a hyperstar formed by the cross-product of two n-star graphs. This communication time improves the best known result for the hypercube-based LU factorization by a factor of log(n), and improves the best known result for the mesh-based LU factorization by a factor of (n - 1)!.
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10

Al-Ayyoub, Abdel-Elah, and Khaled Day. "The Hyperstar Interconnection Network." Journal of Parallel and Distributed Computing 48, no. 2 (February 1998): 175–99. http://dx.doi.org/10.1006/jpdc.1997.1414.

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11

Finkelstein, Shlomit Ritz. "Gravity in hyperspin manifolds." International Journal of Theoretical Physics 27, no. 2 (February 1988): 251–72. http://dx.doi.org/10.1007/bf00670753.

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12

Kakwere, Hamilton, Elizabeth S. Ingham, Riley Allen, Lisa M. Mahakian, Sarah M. Tam, Hua Zhang, Matthew T. Silvestrini, Jamal S. Lewis, and Katherine W. Ferrara. "Unimicellar hyperstars as multi-antigen cancer nanovaccines displaying clustered epitopes of immunostimulating peptides." Biomaterials Science 6, no. 11 (2018): 2850–58. http://dx.doi.org/10.1039/c8bm00891d.

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13

Sriraman, Akshitha, and Abhishek Dhanotia. "Understanding Acceleration Opportunities at Hyperscale." IEEE Micro 41, no. 3 (May 1, 2021): 34–41. http://dx.doi.org/10.1109/mm.2021.3066615.

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14

Hartlieb, Matthias, Thomas Floyd, Alexander B. Cook, Carlos Sanchez-Cano, Sylvain Catrouillet, James A. Burns, and Sébastien Perrier. "Well-defined hyperstar copolymers based on a thiol–yne hyperbranched core and a poly(2-oxazoline) shell for biomedical applications." Polymer Chemistry 8, no. 13 (2017): 2041–54. http://dx.doi.org/10.1039/c7py00303j.

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15

Wang, Xiaofeng, Robert W. Graff, Yi Shi, and Haifeng Gao. "One-pot synthesis of hyperstar polymers via sequential ATRP of inimers and functional monomers in aqueous dispersed media." Polymer Chemistry 6, no. 37 (2015): 6739–45. http://dx.doi.org/10.1039/c5py01043h.

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16

McMenamin, Mark A. S., and Dianna L. S. McMenamin. "Hypersea and the land ecosystem." Biosystems 31, no. 2-3 (January 1993): 145–53. http://dx.doi.org/10.1016/0303-2647(93)90043-c.

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17

AL-AYYOUB, ABDEL-ELAH, and KHALED DAY. "EFFICIENT ALGORITHMS ON THE HYPERSTAR NETWORK." Parallel Algorithms and Applications 14, no. 1 (May 1999): 79–88. http://dx.doi.org/10.1080/10637199808947379.

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18

Khalaf, Abdul Jalil M., and Mahdi Gareep Sabbar. "CHROMATIC POLYNOMIAL OF SEMI-UNIFORM HYPERSTAR." Advances and Applications in Discrete Mathematics 20, no. 2 (March 12, 2019): 193–203. http://dx.doi.org/10.17654/dm020020193.

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19

Holm, Christian. "The hyperspin structure of unitary groups." Journal of Mathematical Physics 29, no. 4 (April 1988): 978–86. http://dx.doi.org/10.1063/1.527994.

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20

Borowiec, Andrzej. "Comment on geometry of hyperspin manifolds." International Journal of Theoretical Physics 28, no. 10 (October 1989): 1229–32. http://dx.doi.org/10.1007/bf00669344.

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21

Fleury, N., M. Rausch de Traubenberg, and R. M. Yamaleev. "Generalized Clifford algebras and hyperspin manifolds." International Journal of Theoretical Physics 32, no. 4 (April 1993): 503–16. http://dx.doi.org/10.1007/bf00673754.

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22

Modai, Jonathan, Alexey Kovalyonok, Avigdor Scherz, Dina Preise, Yuval Avda, Igal Shpunt, Keren Sasson, et al. "Single Instillation of Hypertonic Saline Immediately Following Transurethral Resection of Bladder Tumor for Recurrence Prevention –A Phase I Study." Bladder Cancer 7, no. 2 (May 25, 2021): 187–92. http://dx.doi.org/10.3233/blc-200328.

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BACKGROUND: Urologic guidelines recommend perioperative instillation of chemotherapy after transurethral resection of bladder tumor (TURBT) to decrease tumor recurrence, yet implementation of this recommendation is partial due to associated morbidity. Hypertonic saline destroys cells by osmotic dehydration and might present a safer alternative. OBJECTIVE: To evaluate the safety of 3% hypertonic saline (Hypersal) intravesical instillation following TURBT in rats and in humans. METHODS: In 8 rats whose bladders were electrically injured, intravesical blue-dyed Hypersal was administered. We measured serum sodium levels before and after instillation and pathologically evaluated their pelvic cavity for signs of inflammation or blue discoloration. Twenty-four patients were recruited to the human trial (NIH-NCT04147182), 15 comprised the interventional and 10 the control group (one patient crossed over). Hypersal was given postoperatively. Serum sodium was measured before, 1 hour and 12–24 hours after instillation. Adverse effects were documented and compared between the groups. RESULTS: In rats, average sodium levels were 140.0 mEq/L and 140.3 mEq/L before and following instillation, respectively. Necropsy revealed no signs of inflammation or blue discoloration. In humans the average plasma sodium levels were 138.6 mEq∖L, 138.8 mEq∖L and 137.7 mEq∖L before, 1 hour and 12–24 hours after instillation, respectively. During the postoperative follow-up there was one case of fever. A month after the surgery, dysuria was reported by 5 patients while urgency and hematuria were reported by one patient each. The most severe adverse events were grade 2 on the Clavien-Dindo scale. Adverse events were similar in the control group. CONCLUSIONS: Hypersal instillation is safe and tolerable immediately after TURBT.
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23

Misra, S. K., X. Wang, I. Srivastava, M. K. Imgruet, R. W. Graff, A. Ohoka, T. L. Kampert, H. Gao, and D. Pan. "Combinatorial therapy for triple negative breast cancer using hyperstar polymer-based nanoparticles." Chemical Communications 51, no. 93 (2015): 16710–13. http://dx.doi.org/10.1039/c5cc07709e.

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We report the ability of a novel combinatorial therapy obtained from nanoparticles of hyperstar polymers encompassing drugs to selectively target triple negative breast cancer (TNBC) cell proliferation through STAT3 and topoisomerase-II pathways.
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24

Kim, Jong-Seok, Hyeong-Ok Lee, and Sung-Won Kim. "Embedding Algorithms of Hierarchical Folded HyperStar Network." KIPS Transactions:PartA 16A, no. 4 (August 31, 2009): 299–306. http://dx.doi.org/10.3745/kipsta.2009.16-a.4.299.

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25

Brooks, John O. "Hyperstat: A statistical toolbox for the Macintosh." Behavior Research Methods, Instruments, & Computers 26, no. 4 (December 1994): 470–74. http://dx.doi.org/10.3758/bf03204668.

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26

CINICOLA, D., J. WEBSTER, and P. SKERKER. "HyperStak: A PEZ Style Dispenser for Microplates☆." Journal of the Association for Laboratory Automation 10, no. 5 (October 2005): 327–30. http://dx.doi.org/10.1016/j.jala.2005.07.001.

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27

Bell, Michael G. H., Valentina Trozzi, Solmaz Haji Hosseinloo, Guido Gentile, and Achille Fonzone. "Time-dependent Hyperstar algorithm for robust vehicle navigation." Transportation Research Part A: Policy and Practice 46, no. 5 (June 2012): 790–800. http://dx.doi.org/10.1016/j.tra.2012.02.002.

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28

Xu, Qiumin, Huzefa Siyamwala, Mrinmoy Ghosh, Manu Awasthi, Tameesh Suri, Zvika Guz, Anahita Shayesteh, and Vijay Balakrishnan. "Performance Characterization of Hyperscale Applicationson on NVMe SSDs." ACM SIGMETRICS Performance Evaluation Review 43, no. 1 (June 24, 2015): 473–74. http://dx.doi.org/10.1145/2796314.2745901.

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29

Tanaka, Yoichiro. "Characterizing Advanced Recording Technology Assets With Hyperscale Applications." IEEE Transactions on Magnetics 52, no. 2 (February 2016): 1–4. http://dx.doi.org/10.1109/tmag.2015.2480746.

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30

Cromar, Graham L., Anthony Zhao, Alex Yang, and John Parkinson. "Hyperscape: visualization for complex biological networks: Fig. 1." Bioinformatics 31, no. 20 (June 24, 2015): 3390–91. http://dx.doi.org/10.1093/bioinformatics/btv385.

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31

Laurent, Stéphane. "Some Poisson mixtures distributions with a hyperscale parameter." Brazilian Journal of Probability and Statistics 26, no. 3 (August 2012): 265–78. http://dx.doi.org/10.1214/11-bjps139.

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32

Holm, Christian. "Christoffel formula and geodesic motion in hyperspin manifolds." International Journal of Theoretical Physics 25, no. 11 (November 1986): 1209–13. http://dx.doi.org/10.1007/bf00668691.

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33

Urbantke, H. "Hyperspin manifolds and the space problem of Weyl." International Journal of Theoretical Physics 28, no. 10 (October 1989): 1233–35. http://dx.doi.org/10.1007/bf00669345.

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34

Nooruzzaman, Md, and Xavier Fernando. "Hyperscale Data Center Networks with Transparent HyperX Architecture." IEEE Communications Magazine 59, no. 6 (June 2021): 120–25. http://dx.doi.org/10.1109/mcom.001.2001070.

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35

Lu, Jun. "Attractive Nonlinear Schrödinger Equation and Bose-Einstein Condensate in Phase Space." Applied Mechanics and Materials 110-116 (October 2011): 4492–97. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.4492.

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In this paper, we solve the rigorous solutions of attractive nonlinear Schrödinger equation which models the Bose-Einstein condensate, within the framework of the quantum phase space representation established by Torres-Vega and Frederick. By means of the “Fourier-like” projection transformation, we obtain the eigenfunctions in position and momentum spaces from the phase space eigenfunctions. As an example, we discuss the eigenfunction with a hypersecant part.
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36

Newman, Daniel, John Lindsay, and Jaclyn Cockburn. "Measuring Hyperscale Topographic Anisotropy as a Continuous Landscape Property." Geosciences 8, no. 8 (July 28, 2018): 278. http://dx.doi.org/10.3390/geosciences8080278.

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Several landforms are known to exhibit topographic anisotropy, defined as a directional inequality in elevation. The quantitative analysis of topographic anisotropy has largely focused on measurements taken from specific landforms, ignoring the surrounding landscape. Recent research has made progress in measuring topographic anisotropy as a distributed field in natural landscapes. However, current methods are computationally inefficient, as they require specialized hardware and computing environments, or have a limited selection of scales that undermines the feasibility and quality of multiscale analyses by introducing bias. By necessity, current methods operate with a limited set of scales, rather than the full distribution of possible landscapes. Therefore, we present a method for measuring topographic anisotropy in the landscape that has the computational efficiency required for hyperscale analysis by using the integral image filtering approach to compute oriented local topographic position (LTP) measurements, coupled with a root-mean-square deviation (RMSD) model that compares directional samples to an omnidirectional sample. Two tools were developed: One to output a scale signature for a single cell, and the other to output a raster containing the maximum anisotropy value across a range of scales. The performances of both algorithms were tested using two data sets containing repetitive, similarly sized and oriented anisotropic landforms, including a dune field and a drumlin field. The results demonstrated that the method presented has the robustness and sensitivity to identify complex hyperscale anisotropy such as nested features (e.g., a drumlin located within a valley).
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37

Islam, Raihan Ul, Xhesika Ruci, Mohammad Shahadat Hossain, Karl Andersson, and Ah-Lian Kor. "Capacity Management of Hyperscale Data Centers Using Predictive Modelling." Energies 12, no. 18 (September 6, 2019): 3438. http://dx.doi.org/10.3390/en12183438.

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Big Data applications have become increasingly popular with the emergence of cloud computing and the explosion of artificial intelligence. The increasing adoption of data-intensive machines and services is driving the need for more power to keep the data centers of the world running. It has become crucial for large IT companies to monitor the energy efficiency of their data-center facilities and to take actions on the optimization of these heavy electricity consumers. This paper proposes a Belief Rule-Based Expert System (BRBES)-based predictive model to predict the Power Usage Effectiveness (PUE) of a data center. The uniqueness of this model consists of the integration of a novel learning mechanism consisting of parameter and structure optimization by using BRBES-based adaptive Differential Evolution (BRBaDE), significantly improving the accuracy of PUE prediction. This model has been evaluated by using real-world data collected from a Facebook data center located in Luleå, Sweden. In addition, to prove the robustness of the predictive model, it has been compared with other machine learning techniques, such as an Artificial Neural Network (ANN) and an Adaptive Neuro Fuzzy Inference System (ANFIS), where it showed a better result. Further, due to the flexibility of the BRBES-based predictive model, it can be used to capture the nonlinear dependencies of many variables of a data center, allowing the prediction of PUE with much accuracy. Consequently, this plays an important role to make data centers more energy-efficient.
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38

Raizada, Aasheesh, Kishan Pal Singh, and Mohammad Sajid. "Worldwide energy consumption of hyperscale data centers: A Survey." International Research Journal on Advanced Science Hub 2, Special Issue ICAET 11S (November 1, 2020): 8–15. http://dx.doi.org/10.47392/irjash.2020.226.

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39

Newland, Matt, Rene Schmogrow, Mattia Cantono, Vijay Vusirikala, and Tad Hofmeister. "Open optical communication systems at a hyperscale operator [Invited]." Journal of Optical Communications and Networking 12, no. 6 (March 17, 2020): C50. http://dx.doi.org/10.1364/jocn.381897.

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40

Kapnistos, Michael, Alexander N. Semenov, Dimitris Vlassopoulos, and Jacques Roovers. "Viscoelastic response of hyperstar polymers in the linear regime." Journal of Chemical Physics 111, no. 4 (July 22, 1999): 1753–59. http://dx.doi.org/10.1063/1.479436.

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41

Yakhot, Victor, Bruce J. Bayly, and Steven A. Orszag. "Analogy between hyperscale transport and cellular automaton fluid dynamics." Physics of Fluids 29, no. 7 (1986): 2025. http://dx.doi.org/10.1063/1.865584.

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42

Nooruzzaman, Md, and Xavier Fernando. "Interconnected Transparent Island Architectures for Low-Latency Hyperscale Datacenters." IEEE Photonics Technology Letters 33, no. 16 (August 15, 2021): 924–27. http://dx.doi.org/10.1109/lpt.2021.3073080.

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43

Zettler-Mann, Aaron, and Mark Fonstad. "Riverscape mapping and hyperscale analysis of the sediment links concept." Geomorphology 350 (February 2020): 106920. http://dx.doi.org/10.1016/j.geomorph.2019.106920.

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44

Rezaei-Mayahi, Mehdi, Mostafa Rezazad, and Hamid Sarbazi-Azad. "Temperature-aware power consumption modeling in Hyperscale cloud data centers." Future Generation Computer Systems 94 (May 2019): 130–39. http://dx.doi.org/10.1016/j.future.2018.11.029.

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45

Riza, Sativandi, Masahiko Sekine, Ariyo Kanno, Koichi Yamamoto, Tsuyoshi Imai, and Takaya Higuchi. "Modeling soil landscapes and soil textures using hyperscale terrain attributes." Geoderma 402 (November 2021): 115177. http://dx.doi.org/10.1016/j.geoderma.2021.115177.

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46

Reji Kumar, K., and Jasmine Mathew. "Hyperstar Decomposition of r-partite complete, Knodel and Fibonacci Hypergraphs." Journal of Physics: Conference Series 1850, no. 1 (May 1, 2021): 012018. http://dx.doi.org/10.1088/1742-6596/1850/1/012018.

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47

Novoa-Carballal, Ramon, Sergey Nosov, Sandrine Pfaff, Holger Schmalz, and Axel H. E. Müller. "Hyperbranched and Hyperstar Polybutadienes via Anionic Self-Condensing Vinyl Copolymerization." Macromolecules 54, no. 12 (June 7, 2021): 5774–83. http://dx.doi.org/10.1021/acs.macromol.1c00537.

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48

Wang, Yanna, and Bo Zhou. "Extremal properties of the distance spectral radius of hypergraphs." Electronic Journal of Linear Algebra 36, no. 36 (July 8, 2020): 411–29. http://dx.doi.org/10.13001/ela.2020.5121.

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The distance spectral radius of a connected hypergraph is the largest eigenvalue of its distance matrix. The unique hypertrees with minimum distance spectral radii are determined in the class of hypertrees of given diameter, in the class of hypertrees of given matching number, and in the class of non-hyperstar-like hypertrees, respectively. The unique hypergraphs with minimum and second minimum distance spectral radii are determined in the class of unicylic hypergraphs. The unique hypertree with maximum distance spectral radius is determined in the class of $k$-th power hypertrees of given matching number.
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49

Bell, Michael G. H. "Hyperstar: A multi-path Astar algorithm for risk averse vehicle navigation." Transportation Research Part B: Methodological 43, no. 1 (January 2009): 97–107. http://dx.doi.org/10.1016/j.trb.2008.05.010.

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50

Zheng, Yu, and Xiaohan Sun. "Dual MAC Based Hierarchical Optical Access Network for Hyperscale Data Centers." Journal of Lightwave Technology 38, no. 7 (April 1, 2020): 1608–17. http://dx.doi.org/10.1109/jlt.2019.2959882.

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