436 research outputs found

    Efficient Numerical Algorithm for Large-Scale Damped Natural Gradient Descent

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    We propose a new algorithm for efficiently solving the damped Fisher matrix in large-scale scenarios where the number of parameters significantly exceeds the number of available samples. This problem is fundamental for natural gradient descent and stochastic reconfiguration. Our algorithm is based on Cholesky decomposition and is generally applicable. Benchmark results show that the algorithm is significantly faster than existing methods

    From stateflow simulation to verified implementation: A verification approach and a real-time train controller design

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    Simulink is widely used for model driven development (MDD) of industrial software systems. Typically, the Simulink based development is initiated from Stateflow modeling, followed by simulation, validation and code generation mapped to physical execution platforms. However, recent industrial trends have raised the demands of rigorous verification on safety-critical applications, which is unfortunately challenging for Simulink. In this paper, we present an approach to bridge the Stateflow based model driven development and a well- defined rigorous verification. First, we develop a self- contained toolkit to translate Stateflow model into timed automata, where major advanced modeling features in Stateflow are supported. Taking advantage of the strong verification capability of Uppaal, we can not only find bugs in Stateflow models which are missed by Simulink Design Verifier, but also check more important temporal properties. Next, we customize a runtime verifier for the generated nonintrusive VHDL and C code of Stateflow model for monitoring. The major strength of the customization is the flexibility to collect and analyze runtime properties with a pure software monitor, which opens more opportunities for engineers to achieve high reliability of the target system compared with the traditional act that only relies on Simulink Polyspace. We incorporate these two parts into original Stateflow based MDD seamlessly. In this way, safety-critical properties are both verified at the model level, and at the consistent system implementation level with physical execution environment in consideration. We apply our approach on a train controller design, and the verified implementation is tested and deployed on a real hardware platform

    DeePMD-kit v2: A software package for Deep Potential models

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    DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments.Comment: 51 pages, 2 figure

    Modeling and Optimization of Pulling Point Position of Luffing Jib on Portal Crane

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    Portal crane is the most commonly used equipment for cargo handling of large mixed loading ships with its advantages of flexible and convenient operation, wide adaptability, and high loading and unloading efficiency. The reasonable modeling and optimization of the pulling point position of luffing jib of portal crane can reduce the rack force of portal crane and the power consumption output of the rack and pinion during the luffing process. Based on penalty function optimization, the interior point method is used to optimize the pulling point position of luffing jib. Compared with the initial design, the race force of the luffing jib is reduced to a certain extent. In addition, the consistency between the finite element analysis results and the optimization results can be verified, and the effectiveness of the optimization design is also proved through the finite element analysis of portal crane

    Integrative and Comprehensive Pan-Cancer Analysis of Lymphocyte-Specific Protein Tyrosine Kinase in Human Tumors

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    Lymphocyte-specific protein tyrosine kinase (LCK) is common in a variety of hematologic malignancies but comparatively less common in solid tumors. This study aimed to explore the potential diagnostic and prognostic value of LCK across tumors through integrative and comprehensive pan-cancer analysis, as well as experimental validation. Multiple databases were used to explore the expression, alteration, prognostic value, association with immune infiltration, and potential functional pathways of LCK in pan-cancers. The results were further validated by western blotting and qPCR of patient samples as well as tumor cell lines. High LCK expression typically represents a better prognosis. Notably, drug sensitivity prediction of LCK identified P-529 as a candidate for drug development. Gene Annotations (GO) and KEGG analyses showed significant enrichment of PD-L1 and the T-cell receptor pathway. The results from patient samples and tumor cell lines confirmed these conclusions in LIHC. In conclusion, LCK is differentially expressed in multiple tumors and normal tissues. Further analysis highlighted its association with prognostic implications, pan-cancer genetic alterations, and immune signatures. Our data provide evidence for a diagnostic marker of LCK and the possible use of LCK as a target for the treatment of tumors

    Recognition and cleavage mechanism of intron-containing pre-tRNA by human TSEN endonuclease complex

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    Abstract Removal of introns from transfer RNA precursors (pre-tRNAs) occurs in all living organisms. This is a vital phase in the maturation and functionality of tRNA. Here we present a 3.2 Å-resolution cryo-EM structure of an active human tRNA splicing endonuclease complex bound to an intron-containing pre-tRNA. TSEN54, along with the unique regions of TSEN34 and TSEN2, cooperatively recognizes the mature body of pre-tRNA and guides the anticodon-intron stem to the correct position for splicing. We capture the moment when the endonucleases are poised for cleavage, illuminating the molecular mechanism for both 3′ and 5′ cleavage reactions. Two insertion loops from TSEN54 and TSEN2 cover the 3′ and 5′ splice sites, respectively, trapping the scissile phosphate in the center of the catalytic triad of residues. Our findings reveal the molecular mechanism for eukaryotic pre-tRNA recognition and cleavage, as well as the evolutionary relationship between archaeal and eukaryotic TSENs
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