Tentative evidence of spatially extended GeV emission from SS433/W50

We analyze 10 years of Fermi-LAT data towards the SS433/W50 region. With the latest source catalog and diffuse background models, the gamma-ray excess from SS433/W50 is detected with a significance of 6{\sigma} in the photon energy range of 500 MeV - 10 GeV. Our analysis indicates that an extended flat disk morphology is preferred over a point-source description, suggesting that the GeV emission region is much larger than that of the TeV emission detected by HAWC. The size of the GeV emission is instead consistent with the extent of the radio nebula W50, a supernova remnant being distorted by the jets, so we suggest that the GeV emission may originate from this supernova remnant. The spectral result of the GeV emission is also consistent with an supernova remnant origin. We also derive the GeV flux upper limits on the TeV emission region, which put moderate constrains on the leptonic models to explain the multiwavelength data.Comment: 7 pages, 4 figures, accepted for publication in A&

Two-stage flux balance analysis of metabolic networks for drug target identification

<p>Abstract</p> <p>Background</p> <p>Efficient identification of drug targets is one of major challenges for drug discovery and drug development. Traditional approaches to drug target identification include literature search-based target prioritization and <it>in vitro</it> binding assays which are both time-consuming and labor intensive. Computational integration of different knowledge sources is a more effective alternative. Wealth of omics data generated from genomic, proteomic and metabolomic techniques changes the way researchers view drug targets and provides unprecedent opportunities for drug target identification.</p> <p>Results</p> <p>In this paper, we develop a method based on flux balance analysis (FBA) of metabolic networks to identify potential drug targets. This method consists of two linear programming (LP) models, which first finds the steady optimal fluxes of reactions and the mass flows of metabolites in the pathologic state and then determines the fluxes and mass flows in the medication state with the minimal side effect caused by the medication. Drug targets are identified by comparing the fluxes of reactions in both states and examining the change of reaction fluxes. We give an illustrative example to show that the drug target identification problem can be solved effectively by our method, then apply it to a hyperuricemia-related purine metabolic pathway. Known drug targets for hyperuricemia are correctly identified by our two-stage FBA method, and the side effects of these targets are also taken into account. A number of other promising drug targets are found to be both effective and safe.</p> <p>Conclusions</p> <p>Our method is an efficient procedure for drug target identification through flux balance analysis of large-scale metabolic networks. It can generate testable predictions, provide insights into drug action mechanisms and guide experimental design of drug discovery.</p

Cybernetic basis and system practice of remote sensing and spatial information science

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level

Perception of Misalignment States for Sky Survey Telescopes with the Digital Twin and the Deep Neural Networks

Sky survey telescopes play a critical role in modern astronomy, but misalignment of their optical elements can introduce significant variations in point spread functions, leading to reduced data quality. To address this, we need a method to obtain misalignment states, aiding in the reconstruction of accurate point spread functions for data processing methods or facilitating adjustments of optical components for improved image quality. Since sky survey telescopes consist of many optical elements, they result in a vast array of potential misalignment states, some of which are intricately coupled, posing detection challenges. However, by continuously adjusting the misalignment states of optical elements, we can disentangle coupled states. Based on this principle, we propose a deep neural network to extract misalignment states from continuously varying point spread functions in different field of views. To ensure sufficient and diverse training data, we recommend employing a digital twin to obtain data for neural network training. Additionally, we introduce the state graph to store misalignment data and explore complex relationships between misalignment states and corresponding point spread functions, guiding the generation of training data from experiments. Once trained, the neural network estimates misalignment states from observation data, regardless of the impacts caused by atmospheric turbulence, noise, and limited spatial sampling rates in the detector. The method proposed in this paper could be used to provide prior information for the active optics system and the optical system alignment.Comment: The aforementioned submission has been accepted by Optics Express. We kindly request any feedback or comments to be directed to the corresponding author, Peng Jia ([email protected]), or the second corresponding author, Zhengyang Li ([email protected]). Please note that Zhengyang is currently stationed in the South Antarctica and will not be available until after February 1st, 202