Principle of expert library reinforcement learning designed.

Principle of expert library reinforcement learning designed.

<p>Principle of expert library reinforcement learning designed.</p>

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Bibliografiset tiedot
Päätekijä:	Ziyang Xing (22683634) (author)
Julkaistu:	2025
Aiheet:	Biotechnology Cancer Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified require high coverage experimental verification shows achieve retrieval enhancement wireless network status wireless network environments network transmission technology wireless data transmission data transmission system wireless network data transmission unstable transmission mechanical system xlink "> strong generalizability reward functions mountainous areas continuous advancement
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The simulation parameters.
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Convergence normalization comparison.
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Throughput normalization comparison of several algorithms under different transmission conditions.
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Data transmission scenario diagram in integrated network.
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Extended Data Figure 4 – Source Data (sEPSC properties after sub-chronic ketamine)
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Filamin A KO and S2152A KI reduce KSHV de novo infection of cell-free virions.
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ORF45 promotes cell migration during early primary infection.
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ORF45 reduces cell adhesion through RSK activation.
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Filamin A phosphorylation is induced by ORF45-mediated RSK activation.
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The expression levels of Filamin A in KSHV-positive cells.
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Filamin A KO and S2152A KI in donor cells do not affect KSHV cell-to-cell viral transmission.
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Filamin A KO or S2152A KI does not affect KSHV lytic reactivation.
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Validation of Filamin A KO and S2152A KI stable HEK293-mcherry cells.
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The treatment of RSK inhibitors attenuates ORF45-increased ability of cell migration.
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RSK inhibitors suppress ORF45-induced Filamin A phosphorylation.
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Initial five rows from the metadata CSV file for executed trajectories of 2019-06-28. Distances and entropies are rounded to 10<sup>−3</sup>.
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Structure of the metadata CSV files.
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Initial five rows from the interaction CSV file for executed trajectories of 2019-06-28. Distances are rounded to 10<sup>−3</sup>.
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Structure of the CSV files with information about interactions.
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Information about number of flights deleted during the pre-processing of the trajectory data, for June 28<sup><i>th</i></sup>, 2019.
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Computational cost of the analyses.
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Evolution of daily network metrics as a function of the total distance flown.
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Topological properties of individual networks.
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Time series of complex networks measurements extracted from interactions for planned trajectories over the whole European airspace.
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Spatial and temporal distribution of interactions.
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Graphical representation of the main components of the network of interactions in a single FIR for June 28<sup><i>th</i></sup>, 2019.
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Temporal snapshots of a simulated interaction network reconstruction.
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Flowchart of the trajectory pre-processing and interaction extraction.
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Microscopic agglutination test results.
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Occupational and other individual exposure factors.
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