An Immune Detector-Based Method for the Diagnosis of Compound Faults in a Petrochemical Plant

Aiming at the serious overlap of traditional dimensionless indices in the diagnosis of compound faults in petrochemical plants, we use genetic programming to construct optimal indices for that purpose. In order to solve the problem of losing some useful fault feature information due to classification processing, during the generation of the dimensionless index immune detector, such as reduction and clustering, we propose an integrated diagnosis method using each dimensionless index immune detector. Simulation results show that this method has high diagnostic accuracy

Multi-Label Knowledge Distillation

Existing knowledge distillation methods typically work by imparting the knowledge of output logits or intermediate feature maps from the teacher network to the student network, which is very successful in multi-class single-label learning. However, these methods can hardly be extended to the multi-label learning scenario, where each instance is associated with multiple semantic labels, because the prediction probabilities do not sum to one and feature maps of the whole example may ignore minor classes in such a scenario. In this paper, we propose a novel multi-label knowledge distillation method. On one hand, it exploits the informative semantic knowledge from the logits by dividing the multi-label learning problem into a set of binary classification problems; on the other hand, it enhances the distinctiveness of the learned feature representations by leveraging the structural information of label-wise embeddings. Experimental results on multiple benchmark datasets validate that the proposed method can avoid knowledge counteraction among labels, thus achieving superior performance against diverse comparing methods. Our code is available at: https://github.com/penghui-yang/L2DComment: Accepted by ICCV 2023. The first two authors contributed equally to this wor

Exploration and identification of six novel ferroptosis-related hub genes as potential gene signatures for peripheral nerve injury

Specific biomarkers of ferroptosis after peripheral nerve injury (PNI) are still under debate. In this study, 52 differentially expressed ferroptosis-related genes (DE-FRGs) were retrieved from publicly accessible sequencing data of intact and injured samples of rats with sciatic nerve crush injury. Functional enrichment analyses revealed that adipogenesis, mitochondrial gene sets, and pathways of MAPK, p53, and CD28 family were predominantly engaged in ferroptosis after PNI. Next, Cdkn1a, Cdh1, Hif1a, Hmox1, Nfe2l2, and Tgfb1 were investigated as new ferroptosis-associated hub genes after PNI. Subsequently, clustering correlation heatmap shows six hub genes are linked to mitochondria. The immunofluorescence assay at 0, 1, 4, 7, and 14 days indicated the temporal expression patterns of Tgfb1, Hmox1, and Hif1a after PNI were consistent with ferroptosis validated by PI and ROS staining, while Cdh1, Cdkn1a, and Nfe2l2 were the opposite. In summary, this study identified six hub genes as possible ferroptosis-related biomarkers for PNI, which may offer therapeutic targets for peripheral nerve regeneration and provide a therapeutic window for ferroptosis

Research on extraction method of new type of train control system operation scenario elements in special environments

At present, the construction of high-speed railway in the western region has become one of the key points in China. However, the existing train control systems do not adapt to the environment. So a new type of train control system (TCS-NT) is proposed. However, for TCS-NT, the definition and content of its operating scenarios are not clear, and the construction of operating scenarios is mostly involves subjective analysis. It faces problems such as a lack of a comprehensive operating environment analysis method, a method for selecting scenario elements for varying test requirements, and inexplicable design choices. In this paper, the Operational Design Domain (ODD) and a key element extraction method for simulation scenarios are proposed to analyze the operational environment of the TCS-NT. Using this method, the impact of each scenario element on the sub-functions is sequentially analyzed in the tracking operation scenario of the TCS-NT. According to the influence on each sub-function, a mapping equation is constructed for the three-dimensional plane comprising element, structure, and function, and scenario elements are extracted using the discriminant matrix. In this paper, the method is used to analyze the operation scenario in the train tracking scene, and the feasibility of the method is verified

Modeling and Analyzing Transmission of Infectious Diseases Using Generalized Stochastic Petri Nets

Some infectious diseases such as COVID-19 have the characteristics of long incubation period, high infectivity during the incubation period, and carriers with mild or no symptoms which are more likely to cause negligence. Global researchers are working to find out more about the transmission of infectious diseases. Modeling plays a crucial role in understanding the transmission of the new virus and helps show the evolution of the epidemic in stages. In this paper, we propose a new general transmission model of infectious diseases based on the generalized stochastic Petri net (GSPN). First, we qualitatively analyze the transmission mode of each stage of infectious diseases such as COVID-19 and explain the factors that affect the spread of the epidemic. Second, the GSPN model is built to simulate the evolution of the epidemic. Based on this model’s isomorphic Markov chain, the equilibrium state of the system and its changing laws under different influencing factors are analyzed. Our paper demonstrates that the proposed GSPN model is a compelling tool for representing and analyzing the transmission of infectious diseases from system-level understanding, and thus contributes to providing decision support for effective surveillance and response to epidemic development

Investigation of Particles and Gas Bubbles in Zr–0.8Sn–1Nb–0.3Fe Zr Alloys Irradiated by Krypton Ions

Two types of Zr–0.8Sn–1Nb–0.3Fe Zr alloys were irradiated by krypton ions in the temperature range from 320 to 400 °C. The microstructure of the as-received alloys showed that the sizes of Zr crystals and (Zr, Nb)2Fe particles with face-centered cubic (FCC) structure increased from 3.9 μm to 6.0 μm and from 74.6 nm to 89.6 nm, respectively, after cold rolling and subsequent annealing. Kr+ irradiation-induced bubble formation in the Zr matrix was observed. The size of the gas bubbles increased with increasing ion fluence and irradiation temperature. An equation that related the bubble size, ion fluence, and temperature were established. Irradiation-induced amorphization of particles was observed and found to be related to the fabrication process and irradiation parameters. The particles in alloy #1 showed a higher irradiation tolerance than those in alloy #2. The threshold damage dose for the amorphization of particles in alloy #2 was 3.5 dpa at 320 °C and 4.9 dpa at 360 °C. The mechanisms for bubble growth and particle amorphization are also discussed

Microstructure evolution in Si+ ion irradiated and annealed Ti3SiC2 MAX phase

Ti3SiC2 samples were irradiated by a 6-MeV Si+ ion to a fluence of 2 x$\times$ 10(16) Si+ ions/cm(2) at 300 degrees C followed by annealing at 900 degrees C for 5 h. A transmission electron microscope was used to characterize microstructural evolution. The phase of Ti3SiC2 transformed from the hexagonal close-packed (HCP) to a face-centered cubic structure after irradiation. Hexagonal screw dislocation networks were identified at the deepest position of the irradiated area, which are the products of dislocations reactions. After annealing, the irradiated region has reverted to the original HCP structure. High-density cavities and stacking faults were formed along the basal planes. In addition, ripplocations have been observed in the irradiated region in the Ti3SiC2 sample after annealing. Our insights into the formation processes and corresponding mechanisms of these defect structures might be helpful in the material design of advanced irradiation tolerance materials