specified command【军】 - PMC

Genevieve E. Davis, Mark F. Baumgartner, Peter J. Corkeron, Joel Bell, Catherine Berchok, Julianne M. Bonnell, Jacqueline Bort Thornton, Solange Brault, Gary A. Buchanan, Danielle M. Cholewiak, Christopher W. Clark, Julien Delarue, Leila T. Hatch, Holger Klinck, Scott D. Kraus, Bruce Martin, David K. Mellinger, Hilary Moors‐Murphy, Sharon Nieukirk, Douglas P. Nowacek, Susan E. Parks, Dawn Parry, Nicole Pegg, Andrew J. Read, Aaron N. Rice, Denise Risch, Alyssa Scott, Melissa S. Soldevilla, Kathleen M. Stafford, Joy E. Stanistreet, Erin Summers, Sean Todd, Sofie M. Van Parijs

Glob Chang Biol. 2020 Sep; 26(9): 4812–4840. Published online 2020 Jul 12. doi: 10.1111/gcb.15191

PMCID:: PMC7496396

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Performance Index Based on Predicted Auditory Reaction Time Analysis for the Evaluation of Human-Machine Interface in Flight Control

Weiwei Yu, Dian Jin, Xinliang Yang, Feng Zhao, Haiyang Wang, Ran Peng

Comput Math Methods Med. 2022; 2022: 4661156. Published online 2022 Apr 12. doi: 10.1155/2022/4661156

PMCID:: PMC9019462

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GC/MS and LC/MS serum metabolomic analysis of Chinese LN patients

Wei Wang, Jun Kou, Jie Long, Tao Wang, Mingmei Zhang, Meng Wei, Qingyun Xie

Sci Rep. 2024; 14: 1523. Published online 2024 Jan 17. doi: 10.1038/s41598-024-52137-w

PMCID:: PMC10794181

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Airport Emergency Planning, Part II: Emergency Management Functions

Jeffrey C. Price, Jeffrey S. Forrest

Practical Airport Operations, Safety, and Emergency Management. 2016 : 427–487. Published online 2016 Feb 19. doi: 10.1016/B978-0-12-800515-6.00011-1

PMCID:: PMC7170197

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Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

Norbou Buchler, Sean M. Fitzhugh, Laura R. Marusich, Diane M. Ungvarsky, Christian Lebiere, Cleotilde Gonzalez

Front Psychol. 2016; 7: 937. Published online 2016 Jun 22. doi: 10.3389/fpsyg.2016.00937

PMCID:: PMC4916213

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On-Demand Scheduling of Command and Responses for Low-Power Multihop Wireless Networks

Mingyu Park, Jeongyeup Paek

Sensors (Basel) 2021 Feb; 21(3): 738. Published online 2021 Jan 22. doi: 10.3390/s21030738

PMCID:: PMC7866064

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Coordinating Shared Tasks in Human-Robot Collaboration by Commands

Alexandre Angleraud , Amir Mehman Sefat, Metodi Netzev, Roel Pieters

Front Robot AI. 2021; 8: 734548. Published online 2021 Oct 19. doi: 10.3389/frobt.2021.734548

PMCID:: PMC8560701

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Command or Obey? Homologous Neurons Differ in Hierarchical Position for the Generation of Homologous Behaviors

Akira Sakurai, Paul S. Katz

J Neurosci. 2019 Aug 14; 39(33): 6460–6471. doi: 10.1523/JNEUROSCI.3229-18.2019

PMCID:: PMC6697393

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Boutiques: a flexible framework to integrate command-line applications in computing platforms

Tristan Glatard, Gregory Kiar, Tristan Aumentado-Armstrong, Natacha Beck, Pierre Bellec, Rémi Bernard, Axel Bonnet, Shawn T Brown, Sorina Camarasu-Pop, Frédéric Cervenansky, Samir Das, Rafael Ferreira da Silva, Guillaume Flandin, Pascal Girard, Krzysztof J Gorgolewski, Charles R G Guttmann, Valérie Hayot-Sasson, Pierre-Olivier Quirion, Pierre Rioux, Marc-Étienne Rousseau, Alan C Evans

Gigascience. 2018 May; 7(5): giy016. Published online 2018 Mar 23. doi: 10.1093/gigascience/giy016

PMCID:: PMC6007562

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Dynamics and Embedded Internet of Things Input Shaping Control for Overhead Cranes Transporting Multibody Payloads

Gerardo Peláez, Joshua Vaugan, Pablo Izquierdo, Higinio Rubio, Juan Carlos García-Prada

Sensors (Basel) 2018 Jun; 18(6): 1817. Published online 2018 Jun 4. doi: 10.3390/s18061817

PMCID:: PMC6022085

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The Open EEGLAB Portal Interface: High-Performance Computing with EEGLAB

Ramón Martínez-Cancino, Arnaud Delorme, Dung Truong, Fiorenzo Artoni, Kenneth Kreutz-Delgado, Subhashini Sivagnanam, Kenneth Yoshimoto, Amitava Majumdar, Scott Makeig

Neuroimage. Author manuscript; available in PMC 2022 Jan 1.

Published in final edited form as: Neuroimage. 2021 Jan 1; 224: 116778. Published online 2020 Apr 11. doi: 10.1016/j.neuroimage.2020.116778

PMCID:: PMC8341158

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The Space Physics Environment Data Analysis System (SPEDAS)

V. Angelopoulos, P. Cruce, A. Drozdov, E. W. Grimes, N. Hatzigeorgiu, D. A. King, D. Larson, J. W. Lewis, J. M. McTiernan, D. A. Roberts, C. L. Russell, T. Hori, Y. Kasahara, A. Kumamoto, A. Matsuoka, Y. Miyashita, Y. Miyoshi, I. Shinohara, M. Teramoto, J. B. Faden, A. J. Halford, M. McCarthy, R. M. Millan, J. G. Sample, D. M. Smith, L. A. Woodger, A. Masson, A. A. Narock, K. Asamura, T. F. Chang, C.-Y. Chiang, Y. Kazama, K. Keika, S. Matsuda, T. Segawa, K. Seki, M. Shoji, S. W. Y. Tam, N. Umemura, B.-J. Wang, S.-Y. Wang, R. Redmon, J. V. Rodriguez, H. J. Singer, J. Vandegriff, S. Abe, M. Nose, A. Shinbori, Y.-M. Tanaka, S. UeNo, L. Andersson, P. Dunn, C. Fowler, J. S. Halekas, T. Hara, Y. Harada, C. O. Lee, R. Lillis, D. L. Mitchell, M. R. Argall, K. Bromund, J. L. Burch, I. J. Cohen, M. Galloy, B. Giles, A. N. Jaynes, O. Le Contel, M. Oka, T. D. Phan, B. M. Walsh, J. Westlake, F. D. Wilder, S. D. Bale, R. Livi, M. Pulupa, P. Whittlesey, A. DeWolfe, B. Harter, E. Lucas, U. Auster, J. W. Bonnell, C. M. Cully, E. Donovan, R. E. Ergun, H. U. Frey, B. Jackel, A. Keiling, H. Korth, J. P. McFadden, Y. Nishimura, F. Plaschke, P. Robert, D. L. Turner, J. M. Weygand, R. M. Candey, R. C. Johnson, T. Kovalick, M. H. Liu, R. E. McGuire, A. Breneman, K. Kersten, P. Schroeder

Space Sci Rev. 2019; 215(1): 9. Published online 2019 Jan 22. doi: 10.1007/s11214-018-0576-4

PMCID:: PMC6380193

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CIAlign: A highly customisable command line tool to clean, interpret and visualise multiple sequence alignments

Charlotte Tumescheit, Andrew E. Firth, Katherine Brown

PeerJ. 2022; 10: e12983. Published online 2022 Mar 15. doi: 10.7717/peerj.12983

PMCID:: PMC8932311

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An Application of Inverse Reinforcement Learning to Estimate Interference in Drone Swarms

Keum Joo Kim, Eugene Santos, Jr., Hien Nguyen, Shawn Pieper

Entropy (Basel) 2022 Oct; 24(10): 1364. Published online 2022 Sep 27. doi: 10.3390/e24101364

PMCID:: PMC9601803

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Modeling the Sequential Pattern Variability of the Electromotor Command System of Pulse Electric Fish

Angel Lareo, Pablo Varona, Francisco B. Rodriguez

Front Neuroinform. 2022; 16: 912654. Published online 2022 Jun 28. doi: 10.3389/fninf.2022.912654

PMCID:: PMC9275807

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Bringing Things Closer: Enhancing Low-Vision Interaction Experience with Office Productivity Applications

HAE-NA LEE, VIKAS ASHOK, IV RAMAKRISHNAN

Proc ACM Hum Comput Interact. Author manuscript; available in PMC 2022 Feb 24.

Published in final edited form as: Proc ACM Hum Comput Interact. 2021 Jun; 5(EICS): 197. Published online 2021 May 29. doi: 10.1145/3457144

PMCID:: PMC8871469

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Characterization of EEG signals revealing covert cognition in the injured brain

William H Curley, Peter B Forgacs, Henning U Voss, Mary M Conte, Nicholas D Schiff

Brain. 2018 May; 141(5): 1404–1421. Published online 2018 Mar 19. doi: 10.1093/brain/awy070

PMCID:: PMC5917770

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PMC Images search for specified command【军】

Figure 4Protocol VIs: 4A Time Protocol.

Protocol command parameters are variable name, update value, execution time and optional parameter, load path. The VI parses the selected CSV file and stores its contents in the command history indicator. When running, the Protocol VI parses commands for time parameters that have been surpassed by the present time. These commands are removed from the command list and executed by assigning the specified variable with the update value. If there is a load path parameter present, the protocol located at that path is loaded and appended to the commands in the command list. After a command has been executed it is stored in the command history indicator, which displays the last 1000 commands executed. 4B Python Protocol The python protocol VI uses an open source library called LabPython to execute script protocols through an interface with the Python scripting language. Protocols can be loaded by selecting the open button and developed in the protocol script control using variable inserted from the variable menu.

Open Source Software to Control Bioflo Bioreactors

PLoS One. 2014;9(3):e92108.
Figure 1.Illustration of tool descriptions for printing simple greetings.

In the examples associated with this article, we provide tool descriptions that illustrate how to print custom greetings at the command line. These diagrams illustrate the 02_hello.cwl (A) and 03_hello.cwl (B) examples. In (A), the tool description indicates which inputs that must be specified, along with a template for executing the command; it also indicates that a message will be printed to standard output and that this message should be stored in a file called 02_output.txt. The hello_objects_age.yml input-object file stores values for a particular invocation of the tool. In (A), the cwltool workflow engine uses the host computer’s operating system to execute the tool; thus, the echo command must be supported on that operating system. In (B), the tool description defines a software container environment; thus, cwltool executes the command within a container, which provides the echo command (packaged with the Debian Linux operating system).

Simplifying the development of portable, scalable, and reproducible workflows

eLife. 2021;10:e71069.
Figure 2

Network visualization of email communications between the Mission Command staff across a 2-week training exercise event encompassing two echelons of Command—a Division and two-subordinate Brigades. Email communications are aggregated at the cell level to reveal functional cell-to-cell correspondences (A) and disaggregated at individual node level (B). Node color indicates functional cell assignments for all members of the Mission Command staff, which are specified in the legend. The color and thickness of the lines denote the functional cell of the sender and message volume.

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

Front Psychol. 2016;7:937.
Figure 4

Image thresholding using inclusive threshold and show region statistics command in MetaMorph software
(A) Show region statistics command to measure average and standard deviation of the intensity for the entire confocal PSD95 image. The set of objects meeting specified criteria are marked in green color.
(B) Inclusive threshold function for thresholding confocal PSD95 image.
(C) A thresholded confocal PSD95 image.

Quantifying molecular aggregation by super resolution microscopy within an excitatory synapse from mouse hippocampal neurons

STAR Protoc. 2021 Jun 18;2(2):100470.