Group-SMA Algorithm Based Joint Estimation of Train Parameter and State

The braking rate and train arresting operation is important in the train braking performance. It is difficult to obtain the states of the train on time because of the measurement noise and a long calculation time. A type of Group Stochastic M-algorithm (GSMA) based on Rao-Blackwellization Particle Filter (RBPF) algorithm and Stochastic M-algorithm (SMA) is proposed in this paper. Compared with RBPF, GSMA based estimation precisions for the train braking rate and the control accelerations were improved by 78% and 62%, respectively. The calculation time of the GSMA was decreased by 70% compared with SMA

Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning

Cross-modal alignment is essential for vision-language pre-training (VLP) models to learn the correct corresponding information across different modalities. For this purpose, inspired by the success of masked language modeling (MLM) tasks in the NLP pre-training area, numerous masked modeling tasks have been proposed for VLP to further promote cross-modal interactions. The core idea of previous masked modeling tasks is to focus on reconstructing the masked tokens based on visible context for learning local-to-local alignment. However, most of them pay little attention to the global semantic features generated for the masked data, resulting in the limited cross-modal alignment ability of global representations. Therefore, in this paper, we propose a novel Semantic Completion Learning (SCL) task, complementary to existing masked modeling tasks, to facilitate global-to-local alignment. Specifically, the SCL task complements the missing semantics of masked data by capturing the corresponding information from the other modality, promoting learning more representative global features which have a great impact on the performance of downstream tasks. Moreover, we present a flexible vision encoder, which enables our model to perform image-text and video-text multimodal tasks simultaneously. Experimental results show that our proposed method obtains state-of-the-art performance on various vision-language benchmarks, such as visual question answering, image-text retrieval, and video-text retrieval

Near-Infrared Super Resolution Imaging with Metallic Nanoshell Particle Chain Array

We propose a near-infrared super resolution imaging system without a lens or a mirror but with an array of metallic nanoshell particle chain. The imaging array can plasmonically transfer the near-field components of dipole sources in the incoherent and coherent manners and the super resolution images can be reconstructed in the output plane. By tunning the parameters of the metallic nanoshell particle, the plasmon resonance band of the isolate nanoshell particle red-shifts to the near-infrared region. The near-infrared super resolution images are obtained subsequently. We calculate the field intensity distribution at the different planes of imaging process using the finite element method and find that the array has super resolution imaging capability at near-infrared wavelengths. We also show that the image formation highly depends on the coherence of the dipole sources and the image-array distance.Comment: 15 pages, 6 figure

Synergistic Effect of Dual-Doped Carbon on Mo2C Nanocrystals Facilitates Alkaline Hydrogen Evolution

RÉSUMÉ: Molybdenum carbide (Mo2C) materials are promising electrocatalysts with potential applications in hydrogen evolution reaction (HER) due to low cost and Pt-like electronic structures. Nevertheless, their HER activity is usually hindered by the strong hydrogen binding energy. Moreover, the lack of water-cleaving sites makes it difficult for the catalysts to work in alkaline solutions. Here, we designed and synthesized a B and N dual-doped carbon layer that encapsulated on Mo2C nanocrystals (Mo2C@BNC) for accelerating HER under alkaline condition. The electronic interactions between the Mo2C nanocrystals and the multiple-doped carbon layer endow a near-zero H adsorption Gibbs free energy on the defective C atoms over the carbon shell. Meanwhile, the introduced B atoms afford optimal H2O adsorption sites for the water-cleaving step. Accordingly, the dual-doped Mo2C catalyst with synergistic effect of non-metal sites delivers superior HER performances of a low overpotential (99 mV@10 mA cm−2) and a small Tafel slope (58.1 mV dec−1) in 1 M KOH solution. Furthermore, it presents a remarkable activity that outperforming the commercial 10% Pt/C catalyst at large current density, demonstrating its applicability in industrial water splitting. This study provides a reasonable design strategy towards noble-metal-free HER catalysts with high activity

MicroRNA-7 inhibits epithelial-to-mesenchymal transition and metastasis of breast cancer cells via targeting FAK expression

10.1371/journal.pone.0041523PLoS ONE78

Identification of pyroptosis-related subtypes and establishment of prognostic model and immune characteristics in asthma

BackgroundAlthough studies have shown that cell pyroptosis is involved in the progression of asthma, a systematic analysis of the clinical significance of pyroptosis-related genes (PRGs) cooperating with immune cells in asthma patients is still lacking.MethodsTranscriptome sequencing datasets from patients with different disease courses were used to screen pyroptosis-related differentially expressed genes and perform biological function analysis. Clustering based on K-means unsupervised clustering method is performed to identify pyroptosis-related subtypes in asthma and explore biological functional characteristics of poorly controlled subtypes. Diagnostic markers between subtypes were screened and validated using an asthma mouse model. The infiltration of immune cells in airway epithelium was evaluated based on CIBERSORT, and the correlation between diagnostic markers and immune cells was analyzed. Finally, a risk prediction model was established and experimentally verified using differentially expressed genes between pyroptosis subtypes in combination with asthma control. The cMAP database and molecular docking were utilized to predict potential therapeutic drugs.ResultsNineteen differentially expressed PRGs and two subtypes were identified between patients with mild-to-moderate and severe asthma conditions. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes. Poor control subtypes were closely related to glucocorticoid resistance and airway remodeling. BNIP3 was identified as a diagnostic marker and associated with immune cell infiltration such as, M2 macrophages. The risk prediction model containing four genes has accurate classification efficiency and prediction value. Small molecules obtained from the cMAP database that may have therapeutic effects on asthma are mainly DPP4 inhibitors.ConclusionPyroptosis and its mediated immune phenotype are crucial in the occurrence, development, and prognosis of asthma. The predictive models and drugs developed on the basis of PRGs may provide new solutions for the management of asthma

Targeting codon 158 p53-mutant cancers via the induction of p53 acetylation

Abstract: Gain of function (GOF) DNA binding domain (DBD) mutations of TP53 upregulate chromatin regulatory genes that promote genome-wide histone methylation and acetylation. Here, we therapeutically exploit the oncogenic GOF mechanisms of p53 codon 158 (Arg158) mutation, a DBD mutant found to be prevalent in lung carcinomas. Using high throughput compound screening and combination analyses, we uncover that acetylating mutp53R158G could render cancers susceptible to cisplatin-induced DNA stress. Acetylation of mutp53R158G alters DNA binding motifs and upregulates TRAIP, a RING domain-containing E3 ubiquitin ligase which dephosphorylates IĸB and impedes nuclear translocation of RelA (p65), thus repressing oncogenic nuclear factor kappa-B (NF-ĸB) signaling and inducing apoptosis. Given that this mechanism of cytotoxic vulnerability appears inapt in p53 wild-type (WT) or other hotspot GOF mutp53 cells, our work provides a therapeutic opportunity specific to Arg158-mutp53 tumors utilizing a regimen consisting of DNA-damaging agents and mutp53 acetylators, which is currently being pursued clinically

A common MET polymorphism harnesses HER2 signaling to drive aggressive squamous cell carcinoma.

c-MET receptors are activated in cancers through genomic events like tyrosine kinase domain mutations, juxtamembrane splicing mutation and amplified copy numbers, which can be inhibited by c-MET small molecule inhibitors. Here, we discover that the most common polymorphism known to affect MET gene (N375S), involving the semaphorin domain, confers exquisite binding affinity for HER2 and enables METN375S to interact with HER2 in a ligand-independent fashion. The resultant METN375S/HER2 dimer transduces potent proliferative, pro-invasive and pro-metastatic cues through the HER2 signaling axis to drive aggressive squamous cell carcinomas of the head and neck (HNSCC) and lung (LUSC), and is associated with poor prognosis. Accordingly, HER2 blockers, but not c-MET inhibitors, are paradoxically effective at restraining in vivo and in vitro models expressing METN375S. These results establish METN375S as a biologically distinct and clinically actionable molecular subset of SCCs that are uniquely amenable to HER2 blocking therapies

A common MET polymorphism harnesses HER2 signaling to drive aggressive squamous cell carcinoma.

c-MET receptors are activated in cancers through genomic events like tyrosine kinase domain mutations, juxtamembrane splicing mutation and amplified copy numbers, which can be inhibited by c-MET small molecule inhibitors. Here, we discover that the most common polymorphism known to affect MET gene (N375S), involving the semaphorin domain, confers exquisite binding affinity for HER2 and enables METN375S to interact with HER2 in a ligand-independent fashion. The resultant METN375S/HER2 dimer transduces potent proliferative, pro-invasive and pro-metastatic cues through the HER2 signaling axis to drive aggressive squamous cell carcinomas of the head and neck (HNSCC) and lung (LUSC), and is associated with poor prognosis. Accordingly, HER2 blockers, but not c-MET inhibitors, are paradoxically effective at restraining in vivo and in vitro models expressing METN375S. These results establish METN375S as a biologically distinct and clinically actionable molecular subset of SCCs that are uniquely amenable to HER2 blocking therapies