A Method for SINS Alignment with Large Initial Misalignment Angles Based on Kalman Filter with Parameters Resetting

In the initial alignment process of strapdown inertial navigation system (SINS), large initial misalignment angles always bring nonlinear problem, which causes alignment failure when the classical linear error model and standard Kalman filter are used. In this paper, the problem of large misalignment angles in SINS initial alignment is investigated, and the key reason for alignment failure is given as the state covariance from Kalman filter cannot represent the true one during the steady filtering process. According to the analysis, an alignment method for SINS based on multiresetting the state covariance matrix of Kalman filter is designed to deal with large initial misalignment angles, in which classical linear error model and standard Kalman filter are used, but the state covariance matrix should be multireset before the steady process until large misalignment angles are decreased to small ones. The performance of the proposed method is evaluated by simulation and car test, and the results indicate that the proposed method can fulfill initial alignment with large misalignment angles effectively and the alignment accuracy of the proposed method is as precise as that of alignment with small misalignment angles

Joint Learning of Local and Global Features for Aspect-based Sentiment Classification

Aspect-based sentiment classification (ASC) aims to judge the sentiment polarity conveyed by the given aspect term in a sentence. The sentiment polarity is not only determined by the local context but also related to the words far away from the given aspect term. Most recent efforts related to the attention-based models can not sufficiently distinguish which words they should pay more attention to in some cases. Meanwhile, graph-based models are coming into ASC to encode syntactic dependency tree information. But these models do not fully leverage syntactic dependency trees as they neglect to incorporate dependency relation tag information into representation learning effectively. In this paper, we address these problems by effectively modeling the local and global features. Firstly, we design a local encoder containing: a Gaussian mask layer and a covariance self-attention layer. The Gaussian mask layer tends to adjust the receptive field around aspect terms adaptively to deemphasize the effects of unrelated words and pay more attention to local information. The covariance self-attention layer can distinguish the attention weights of different words more obviously. Furthermore, we propose a dual-level graph attention network as a global encoder by fully employing dependency tag information to capture long-distance information effectively. Our model achieves state-of-the-art performance on both SemEval 2014 and Twitter datasets.Comment: under revie

H∞ filter for flexure deformation and lever arm effect compensation in M/S INS integration

ABSTRACTOn ship, especially on large ship, the flexure deformation between Master (M)/Slave (S) Inertial Navigation System (INS) is a key factor which determines the accuracy of the integrated system of M/S INS. In engineering this flexure deformation will be increased with the added ship size. In the M/S INS integrated system, the attitude error between MINS and SINS cannot really reflect the misalignment angle change of SINS due to the flexure deformation. At the same time, the flexure deformation will bring the change of the lever arm size, which further induces the uncertainty of lever arm velocity, resulting in the velocity matching error. To solve this problem, a H∞ algorithm is proposed, in which the attitude and velocity matching error caused by deformation is considered as measurement noise with limited energy, and measurement noise will be restrained by the robustness of H∞ filter. Based on the classical “attitude plus velocity” matching method, the progress of M/S INS information fusion is simulated and compared by using three kinds of schemes, which are known and unknown flexure deformation with standard Kalman filter, and unknown flexure deformation with H∞ filter, respectively. Simulation results indicate that H∞ filter can effectively improve the accuracy of information fusion when flexure deformation is unknown but non-ignorable

An Explicit Method for Fast Monocular Depth Recovery in Corridor Environments

Monocular cameras are extensively employed in indoor robotics, but their performance is limited in visual odometry, depth estimation, and related applications due to the absence of scale information.Depth estimation refers to the process of estimating a dense depth map from the corresponding input image, existing researchers mostly address this issue through deep learning-based approaches, yet their inference speed is slow, leading to poor real-time capabilities. To tackle this challenge, we propose an explicit method for rapid monocular depth recovery specifically designed for corridor environments, leveraging the principles of nonlinear optimization. We adopt the virtual camera assumption to make full use of the prior geometric features of the scene. The depth estimation problem is transformed into an optimization problem by minimizing the geometric residual. Furthermore, a novel depth plane construction technique is introduced to categorize spatial points based on their possible depths, facilitating swift depth estimation in enclosed structural scenarios, such as corridors. We also propose a new corridor dataset, named Corr\_EH\_z, which contains images as captured by the UGV camera of a variety of corridors. An exhaustive set of experiments in different corridors reveal the efficacy of the proposed algorithm.Comment: 10 pages, 8 figures. arXiv admin note: text overlap with arXiv:2111.08600 by other author

Total Bilirubin Level is Associated with the Risk of Left Atrial Appendage Thrombosis in Patients with Non-Valvular Atrial Fibrillation

Objectives: There are some evidence suggesting that total bilirubin (TBIL) appears to be associated with stroke in patients with nonvalvular atrial fibrillation (NVAF). The left atrial appendage (LAA) is the most common orgin of thrombus in patients with NVAF. The purpose of this study was to assess a possible relationship between plasma TBIL levels and LAA thrombus in NVAF patients. Methods: We retrospectively screened 459 consecutive hospitalized patients with NVAF at three AF centers, who underwent transesophageal echocardiography or cardiac CT. According to the examination results, the patients were divided into either the LAA thrombosis group (41 cases) or the no LAA thrombosis group (418 cases). Independent sample t test, Mann-Whitney U-test and chi-square test were used to compare and analyze the general clinical data of the two groups. Multivariate Logistic regression was used to analyze whether TBIL was a risk factor for LAA thrombosis in patients with NVAF. Pearson correlation analysis was used to explore the correlation between TBIL and other influencing factors. The predictive value of TBIL for LAA thrombosis in patients with NVAF was evaluated by ROC curve. Results: A total of 459 patients were enrolled in this study. Compared with the group without LAA thrombosis, the level of TBIL in LAA thrombosis group was significantly increased (21.34 ± 9.34 umol/L vs. 13.98 ± 4.25 umol/L, 'P' < 0.001). Multivariate logistic regression showed that TBIL level was a risk factor for LAA thrombosis ('OR', 1.229; 95% 'CI', 1.122~1.345; 'P' < 0.001). The AUC of the ROC curve is 0.801 (95% 'CI', 0.725~0.877; 'P' < 0.001). At 17.4 umol/L of TBIL, the patient may have LAA thrombosis (sensitivity 73.2%; specificity 82.1%). Conclusions: In patients with NVAF, TBIL level is positively associated with LAA thrombosis, and TBIL level may be an index reflecting LAA thrombosis

Possible Mechanisms of SARS-CoV2-Mediated Myocardial Injury

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has rapidly become a global health emergency. In addition to causing respiratory effects, SARS-CoV-2 can result in cardiac involvement leading to myocardial damage, which is increasingly being explored in the literature. Myocardial injury is an important pathogenic feature of COVID-19. The angiotensin-converting enzyme-2 receptor plays a key role in the pathogenesis of the virus, serving as a “bridge” allowing SARS-CoV-2 to invade the body. However, the exact mechanism underlying how SARS-CoV-2 causes myocardial injury remains unclear. This review summarizes the main possible mechanisms of myocardial injury in patients with COVID-19, including direct myocardial cell injury, microvascular dysfunction, cytokine responses and systemic inflammation, hypoxemia, stress responses, and drug-induced myocardial injury. Understanding of the underlying mechanisms would aid in proper identification and treatment of myocardial injury in patients with COVID-19

Cuproptosis-related risk score predicts prognosis and characterizes the tumor microenvironment in colon adenocarcinoma

IntroductionCuproptosis is a novel copper-dependent regulatory cell death (RCD), which is closely related to the occurrence and development of multiple cancers. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of colon adenocarcinoma (COAD) remains unclear.MethodsTranscriptome, somatic mutation, somatic copy number alteration and the corresponding clinicopathological data of COAD were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). Difference, survival and correlation analyses were conducted to evaluate the characteristics of CRGs in COAD patients. Consensus unsupervised clustering analysis of CRGs expression profile was used to classify patients into different cuproptosis molecular and gene subtypes. TME characteristics of different molecular subtypes were investigated by using Gene set variation analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA). Next, CRG Risk scoring system was constructed by applying logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis and multivariate cox analysis. Real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) were used to exam the expression of key Risk scoring genes.ResultsOur study indicated that CRGs had relatively common genetic and transcriptional variations in COAD tissues. We identified three cuproptosis molecular subtypes and three gene subtypes based on CRGs expression profile and prognostic differentially expressed genes (DEGs) expression profile, and found that changes in multilayer CRGs were closely related to the clinical characteristics, overall survival (OS), different signaling pathways, and immune cell infiltration of TME. CRG Risk scoring system was constructed according to the expression of 7 key cuproptosis-related risk genes (GLS, NOX1, HOXC6, TNNT1, GLS, HOXC6 and PLA2G12B). RT-qPCR and IHC indicated that the expression of GLS, NOX1, HOXC6, TNNT1 and PLA2G12B were up-regulated in tumor tissues, compared with those in normal tissues, and all of GLS, HOXC6, NOX1 and PLA2G12B were closely related with patient survival. In addition, high CRG risk scores were significantly associated with high microsatellite instability (MSI-H), tumor mutation burden (TMB), cancer stem cell (CSC) indices, stromal and immune scores in TME, drug susceptibility, as well as patient survival. Finally, a highly accurate nomogram was constructed to promote the clinical application of the CRG Risk scoring system.DiscussionOur comprehensive analysis showed that CRGs were greatly associated with TME, clinicopathological characteristics, and prognosis of patient with COAD. These findings may promote our understanding of CRGs in COAD, providing new insights for physicians to predict prognosis and develop more precise and individualized therapy strategies

Efficacy and safety comparison of esketamine-propofol with nalbuphine-propofol for upper gastrointestinal endoscopy in children: a multi-center randomized controlled trial

Background and AimsAnesthetics such as propofol, esketamine and nalbuphine are used during the upper gastrointestinal endoscopy to achieve and maintain the desired sedation level. The aim of the study was to evaluate the effectiveness and safety of propofol-nalbuphine and propofol-esketamine in children.MethodsA multi-centered study was performed at three tertiary class-A hospitals. Children between 3 and 12 years old undergoing diagnostic painless upper gastrointestinal endoscopy were included and randomly divided into esketamine or nalbuphine group to estimate the primary outcome of successful endoscope insertion. The patients were given esketamine 0.5 mg/kg and propofol 2 mg/kg intravenously in esketamine group, with nalbuphine 0.2 mg/kg and propofol 2 mg/kg in the nalbuphine group. The primary outcome was success rate for the first attempt of endoscope insertion in each group. Secondary outcomes included the safety of both anesthesia regimens and gastroenterologist's satisfaction. We used the Face, Leg, Activity, Cry and Consolability (FLACC) scale to evaluate the level of pain before and during the procedure and the Pediatric Anesthesia Emergence Delirium (PAED) scale to assess the level of agitation and delirium after awakening from anesthesia.ResultsAmong 246 patients, 200 were randomly included in the final intention-to-treat analysis, with 100 patients in each group. The success rate for the first attempt of endoscope insertion in the esketamine group was higher than the nalbuphine group (97% vs. 66%; P &lt; 0.01). The heart rate and mean arterial pressure after intraoperative administration in the esketamine group were higher than those in the nalbuphine group, while the delirium incidence during awakening was higher in esketamine group (all P &lt; 0.05).ConclusionThe success rate for the first attempt of endoscope insertion of children undergoing upper gastrointestinal endoscopy in the esketamine group was higher than the nalbuphine group, propofol-related hemodynamic changes were reduced accordingly, while the incidence of esketamine-related adverse effects could be high.Clinical Trial RegistrationChinese Clinical Trial Registry: ChiCTR2000040500