Hydropyridylation of α,ß-Unsaturated Esters through Electroreduction of 4-Cyanopyridine.

A mild and highly efficient method for the hydropyridylation of α,ß-unsaturated esters has been developed. This protocol provides the products smoothly with a wide substrate scope in an undivided cell under ambient conditions. Moreover, studies showed that the scope could be extended to other unsaturated compounds, including enones and aldehydes.

Crystal Structure, Infrared Reflection Spectrum, and Improved Microwave Dielectric Characteristics of Ba4Sm28/3Ti18O54 Ceramics via One-Step Reaction Sintering.

High-k Ba4Sm28/3Ti18O54 ceramics with improved microwave dielectric characteristics were successfully fabricated using the one-step reaction sintering (RS) route. The sintering characteristics, microstructure, crystal structure, infrared reflection spectrum, and microwave dielectric characteristics of Ba4Sm28/3Ti18O54 ceramics prepared by the RS route were systematically investigated. Samples prepared by the RS route exhibited single-phase orthorhombic tungsten-bronze structure and dense microstructure at optimum sintering temperature. Compared with the conventional solid-state (CS) process, the Ba4Sm28/3Ti18O54 ceramics fabricated by the RS route presented a smaller temperature coefficient (TCF), a higher quality factor (Q × f), and a higher permittivity (εr). The improved microwave dielectric characteristics were highly dependent on the theoretical permittivity, atomic packing fraction, suppression of Ti3+, and Ti-site bond valence. Excellent combined microwave dielectric characteristics (TCF = -7.9 ppm/°C, Q × f = 9519 GHz, εr = 80.26) were achieved for Ba4Sm28/3Ti18O54 ceramics prepared by RS route sintered at 1400 °C, suggesting the RS route was a straightforward, economical and effective route to prepare high-performance Ba4Sm28/3Ti18O54 ceramics with promising application potential.

Rank-PointRetrieval: Reranking Point Cloud Retrieval via a Visually Consistent Registration Evaluation.

Point cloud-based place recognition is a fundamental part of the localization task, and it can be achieved through a retrieval process. Reranking is a critical step in improving the retrieval accuracy, yet little effort has been devoted to reranking in point cloud retrieval. In this paper, we investigate the versatility of rigid registration in reranking the point cloud retrieval results. Specifically, after obtaining the initial retrieval list based on the global point cloud feature distance, we perform registration between the query and point clouds in the retrieval list. We propose an efficient strategy based on visual consistency to evaluate each registration with a registration score in an unsupervised manner. The final reranked list is computed by considering both the original global feature distance and the registration score. In addition, we find that the registration score between two point clouds can also be used as a pseudo label to judge whether they represent the same place. Thus, we can create a self-supervised training dataset when there is no ground truth of positional information. Moreover, we develop a new probability-based loss to obtain more discriminative descriptors. The proposed reranking approach and the probability-based loss can be easily applied to current point cloud retrieval baselines to improve the retrieval accuracy. Experiments on various benchmark datasets show that both the reranking registration method and probability-based loss can significantly improve the current state-of-the-art baselines.

Point Cloud Completion Via Skeleton-Detail Transformer.

Point cloud shape completion plays a central role in diverse 3D vision and robotics applications. Early methods used to generate global shapes without local detail refinement. Current methods tend to leverage local features to preserve the observed geometric details. However, they usually adopt the convolutional architecture over the incomplete point cloud to extract local features to restore the diverse information of both latent shape skeleton and geometric details, where long-distance correlation among the skeleton and details is ignored. In this work, we present a coarse-to-fine completion framework, which makes full use of both neighboring and long-distance region cues for point cloud completion. Our network leverages a Skeleton-Detail Transformer, which contains cross-attention and self-attention layers, to fully explore the correlation from local patterns to global shape and utilize it to enhance the overall skeleton. Also, we propose a selective attention mechanism to save memory usage in the attention process without significantly affecting performance. We conduct extensive experiments on the ShapeNet dataset and real-scanned datasets. Qualitative and quantitative evaluations demonstrate that our proposed network outperforms current state-of-the-art methods.

Seamless Texture Optimization for RGB-D Reconstruction.

Restoring high-fidelity textures for 3D reconstructed models are an increasing demand in AR/VR, cultural heritage protection, entertainment, and other relevant fields. Due to geometric errors and camera pose drifting, existing texture mapping algorithms are either plagued by blurring and ghosting or suffer from undesirable visual seams. In this paper, we propose a novel tri-directional similarity texture synthesis method to eliminate the texture inconsistency in RGB-D 3D reconstruction and generate visually realistic texture mapping results. In addition to RGB color information, we incorporate a novel color image texture detail layer serving as an additional context to improve the effectiveness and robustness of the proposed method. First, we select an optimal texture image for each triangle face of the reconstructed model to avoid texture blurring and ghosting. During the selection procedure, the texture details are weighted to avoid generating texture chart partitions across high-frequency areas. Then, we optimize the camera pose of each texture image to align with the reconstructed 3D shape. Next, we propose a tri-directional similarity function to resynthesize the image context within the boundary stripe of texture charts, which can significantly diminish the occurrence of texture seams. Finally, we introduce a global color harmonization method to address the color inconsistency between texture images captured from different viewpoints. The experimental results demonstrate that the proposed method outperforms state-of-the-art texture mapping methods and effectively overcomes texture tearing, blurring, and ghosting artifacts.

A weakly supervised method for named entity recognition of Chinese electronic medical records.

The field of Chinese medical natural language processing faces a significant challenge in training accurate entity recognition models due to the limited availability of high-quality labeled data. In response, we propose a joint training model, MCBERT-GCN-CRF, which achieves high performance in identifying medical-related entities in Chinese electronic medical records. Additionally, we introduce CM-NER, a 5-step framework that effectively mitigates the effects of noise in weakly labeled data and establishes a principled connection between supervised and weakly supervised named entity recognition. We demonstrate significant improvements in recall rate and accuracy. Our approach outperforms traditional fully supervised pre-training models and other state-of-the-art methods by suppressing noise in weakly labeled data. Our proposed framework achieves an F1 score of 86.29% on the CCKS-2019 dataset, significantly higher than pre-trained model baselines ranging from 74.17 to 83.06%, and higher than the top-performing named entity recognition supervised learning models in the CCKS-2019 competition. Our results demonstrate the effectiveness of our proposed framework and highlight the potential of leveraging unlabeled data to train accurate models for named entity recognition in Chinese medical natural language processing. This research has significant implications for advancing natural language processing techniques in the medical domain and improving patient care.

Viscoelastic Numerical Simulation Study on the Co-Extrusion Process of Tri-Composite Tire Tread.

The co-extrusion process is widely used to produce composite tire treads with better performance. This study investigated the rubber co-extrusion flow process and quality influencing factors of tri-composite tire tread through numerical simulation and experimental methods. Here, RPA 2000 rubber processing analyzer was used to carry out rheological tests on the three rubber materials, the PTT viscoelastic constitutive model was fitted, and the fitting curves were in good agreement with the test data. Then, a three-dimensional viscoelastic numerical simulation model of the tri-composite tread co-extrusion process was established using Ansys Polyflow software. The parameter evolution technique is adopted in the model establishment to improve the calculation convergence. In addition, a global remeshing function is used to avoid excessive mesh deformation. A co-extrusion experiment is conducted to verify the model's accuracy using a tri-screw extruder. The extruded tread size error rate between the experiment and simulation is less than 6%. The variation of the velocity field, pressure field and shear rate field during extrusion is analyzed, and the formation mechanism of die swell is explained simultaneously. Finally, the influence of process parameters (inflow rate and traction speed) and die structure (convergence angle and thickness) on the extruded tire tread shape and quality was investigated, which can provide theoretical guidance for improving tread quality and production efficiency. Furthermore, the numerical simulation method can assist the design of the die plate in enhancing the efficiency of the die plate design.

Exploring a Multi-Layer Coupled Network Propagation Model Based on Information Diffusion and Bounded Trust.

Objective: To explore the law of opinion dissemination and individual opinion evolution at the micro level, this paper analyzes the influence of variation and oyster on communication from the perspective of network structure. Methods: In this paper, we introduce the concepts of "variation" and "oyster", build a multi-layer coupled network environment combined with the ISOVR model, and conduct simulation experiments of network information dissemination based on the bounded trust model. Results: The experimental results reveal that the extent and scope of variation's spread in the network are more dependent on the trust of nodes themselves, and decreasing the trust of nodes significantly reduces the rate and peak value of variation. Changing the silence coefficient of variation does not effectively change the direction of rumor propagation, which indicates that rumor has a strong propagation ability after mutation. Conclusion: The insights of this paper on the dissemination of public opinions include: 1) pay attention to people with high trust levels, such as opinion leaders; 2) clarify the misinformation in time to prevent further spread of rumors.

Evasive behavior-based method for threat assessment in different scenarios: A novel framework for intelligent vehicle.

The threat assessment process is a crucial part of intelligent vehicles (IVs) for evaluating the levels of criticality and taking possible measures to avoid the collision, especially for the collision avoidance systems (CAS). In this study, a novel threat assessment framework based on the driver's evasive behavior, namely the CPIC, is proposed, which integrates the crash probability (CP) and inevitable crash (IC) state to be widely used by different CAS in different scenarios. In the first step of the CPIC framework, the detailed evasive driver behavior models (E-DBMs) in the form of probability density functions (PDFs) were introduced to generate more realistic collision-avoidance trajectories. Two techniques for sampling these trajectories, namely the Markov Chain Monte Carlo (MCMC) and adaptive Gaussian mixture framework (GMM) methods, were utilized to ensure the samples were from the area of high probability density in the E-DBMs. The CP value could be derived by considering multiple collision-avoidance trajectories. To confirm the IC state in step 2, the CPIC framework employed the driving limit-based approach for IC checking, which combined the CP value to double-check the unavoidable collision. A total of 82 critical events from the real-world naturalistic driving study, the Strategic Highway Research Program 2 (SHRP2), were extracted to verify the performance of the CPIC framework in different scenarios. Results show that the proposed method clearly revealed the risk levels when two vehicles were approaching, and 80 events were successfully identified as near crashes/crashes. Moreover, the real-time performance of the CPIC framework was also demonstrated. The findings indicate this CPIC framework could be used in practical applications of IVs in different scenarios.

Determining the steering direction in critical situations: A decision tree-based method.

Objective: Factors related to the driver-vehicle-environment system have a significant influence on a driver's decision to perform evasive maneuvers, especially the decision of steering direction (DSD) in critical situations. However, few studies have systematically investigated the relationships between these factors and DSD. The objective of this study is to analyze and model drivers' DSD in critical situations.Methods: Data from the NASS-CDS from 1995 to 2015 were utilized in this study. The decision tree (DT) classifier was utilized to model a driver's DSD for both intersection-related and non-intersection-related subsets, combined with a 10-fold cross-validation technique and grid search approach to evaluate and optimize the model. An analysis of variable importance was also conducted.Results: Two separate DT models of drivers' DSD were obtained based on the optimized hyperparameters, with test accuracies of 84.6% (intersection-related) and 79.2% (non-intersection-related). The variable DIFFANGLE (angle difference between 2 vehicles) ranked as the most important factor influencing drivers' DSD in both models. The variables, in order of importance, were SPEED (travel speed of the subject vehicle) and AGE (driver's age) for the intersection-related model and SPEED, PREMOVE (pre-event movement), TRAFFLOW (trafficway flow), and AGE for the non-intersection-related model. Moreover, an interesting same direction pattern was observed in both DT models.Conclusions: This study employed NASS-CDS data and DT classifiers to analyze and model drivers' DSD behavior. The test accuracies for both classifiers were acceptable. Potential variables influencing drivers' DSD were explored, which improves the research on evasive behavior in lateral movement and promotes further applications for intelligent vehicles using the constructed models.

Preparation and biological imaging of fluorescent hydroxyapatite nanoparticles with poly(2-ethyl-2-oxazoline) through surface-initiated cationic ring-opening polymerization.

Fluorescent hydroxyapatite (HAp) nanoparticles have received significant attention in biomedical fields due to their outstanding advantages, such as low immunogenicity, excellent biocompatibility and biodegradability. However, fluorescent HAp nanoparticles with well controlled size and morphology are coated with hydrophobic molecules and their biomedical applications are largely restricted by their poor dispersibility in physiological solutions. Therefore, surface modification of these hydrophobic fluorescent HAp nanoparticles to render them water dispersibility is of utmost importance for biomedical applications. In this work, we reported for the first time for preparation of water-dispersible hydrophilic fluorescent Eu3+-doped HAp nanoparticles (named as HAp-PEOTx) through the cationic ring-opening polymerization using hydrophilic and biocompatible 2-ethyl-2-oxazoline (EOTx) as the monomer. The characterization techniques, such as nuclear magnetic resonance (NMR) spectroscopy, transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) have been used to characterize these samples. Results confirmed that we could successfully obtain the hydrophilic fluorescent HAp-PEOTx composites through the strategy described above. These fluorescent HAp-PEOTx composites display great water dispersibility, unique fluorescent properties and excellent biocompatibility, making them promising for in vitro bioimaging applications.

[Factors associated with response to lamivudine: retrospective study of 233 patients with chronic hepatitis B].

OBJECTIVE: To identify factors associated with response to lamivudine in chronic hepatitis B patients. METHODS: Clinical data of 233 chronic hepatitis B patients treated with lamivudine 100mg daily (91 patients were switched to Adefovir 10mg daily or Adefovir 10mg in combination with lamivudine 100mg daily) were retrospective. HBV DNA level and serum HBV markers were detected by polymerase chain reaction and enzyme-linked immunosorbent assay. Kaplan-Meier, long-rank, t test were conducted to evaluate the data. RESULTS: (1) The rates of HBV DNA loss, ALT normalization, viral breakthrough(VB), HBeAg loss and seroconversion were 63.4% , 83.8%, 30.9%, 30.9%, and 14.3%, respectively, in HBeAg(+) patients; and these were 84.6%, 81.3%, 14.3%, respectively in HBeAg(-) patients.(2) The rates of HBV DNA loss, HBeAg loss, HBeAg seroconversion, viral breakthrough (VB) were 55% and 66.7% (P more than 0.05), 55.0%, and 66.7% (P less than 0.05), 17.5% and 33.3% (P less than 0.05), 50% and 34.3% (P less than 0.05) in HBeAg(+) patients with baseline ALT less than 2.5 ULN and HBeAg(+) patients with baseline ALT is more than or equal to 2.5 ULN, respectively. (3) For HBeAg(+) patients, viral breakthrough rate was significantly lower in patients with baseline HBV DNA less than 10(6) copies/ml than that in patients with baseline HBV DNA more than 10(6) copies/ml patients (23.4% VS 46.3%, P less than 0.05) among HBeAg(+) patients. (4) The rate of HBV DNA loss, HBeAg loss, HBeAg seroconversion and viral breakthrough for the patients with IVR at week 24 were 76.3%, 72.3%, 40.8% and 28.9% compared to 47.6% (P less than 0.01), 46% (P less than 0.01), 12.7% (P less than 0.01) and 47.6% (P less than 0.05) for those without IVR. (4) For the 44 patients with viral breakthrough, 32 were switched to Adefovir monotherapy or adefovir in combination with lamivudine therapy, and 12 continued to receive lamivudine monotherapy. HBV DNA loss, HBeAg seroconversion were 40.6%, 21.9% for those switch/add group compare to 16.7%, 16.7% for the lamivudine monotherapy group. There were no significant differences in the background factors (sex, diagnosis, antiviral period, pre-tx ALT, pre-tx HBV DNA) between these two groups. CONCLUSION: Both the baseline ALT and HBV DNA are associated with the efficacy of lamivudine in chronic hepatitis B patients. Patients with baseline ALT is more than or equal to 2.5*ULN and (or) HBV DNA level of less than 1*10(6) copies/ml have better efficacy and lower rate of breakthrough rate. IVR at week 24 is an important predictive factor of a favorable response to lamivudine therapy. For the patients with viral breakthrough, those switched to/added on Adefovir have a favorable result.

Surface modification of fluorescent Tb3+-doped layered double hydroxides with hyperbranched polymers through host-guest interaction.

The preparation of fluorescent inorganic-organic polymer composites for biomedical applications has become one of the most interest research focuses recently. In this work, we reported a novel method for the preparation of Tb3+-doped luminescent layered double hydroxides (LDHs) based composites by taken advantage of a one-pot supramolecular chemistry. The adamantane can be immobilized on the surface of Tb3+-doped LDHs to obtain LDH-Ad, which could be further utilized for modified by the ß-cyclodextrin (ß-CD) containing hyperbranched polyglycerols (ß-CD-HPG) through the host-guest interaction. Based on the characterization results, we demonstrated that the hyperbranched polyglycerol could be facilely introduced on these fluorescent Tb3+-doped LDHs through the method described in this work. The obtained Tb3+-doped LDHs based polymer composites (LDHs-ß-CD-HPG) display improved water dispersibility and still maintain their fluorescence. The results based on various biological assays suggest that LDHs-ß-CD-HPG polymer composites are of low cytotoxicity and their cell uptake behavior can be effectively traced using confocal laser imaging. All of the above results demonstrated that the fluorescent Tb3+-doped LDHs based polymer composites could be effectively surface modified with hydrophilic hyperbranched polymers through a one-pot facile host-guest interaction and the resultant fluorescent composites are of excellent physicochemical properties and display great potential for biomedical applications. This novel surface modification method should also be important for fabrication of other multifunctional composites and therefore great advanced the development of biomedical applications of fluorescent LDHs based polymer composites and related materials.

Surface PEGylation and biological imaging of fluorescent Tb3+-doped layered double hydroxides through the photoinduced RAFT polymerization.

Tb3+-doped layered double hydroxides (LDHs) exhibit excellent optical characteristics, uniform size and uniform morphologies when synthesized through a hydrothermal method. However, due to their lack of functional groups and poor dispersibility, applications of these fluorescent Tb3+-doped LDHs have been largely impeded especially in the biomedical fields. In this work, a novel strategy was developed for the surface modification of these fluorescent Tb3+-doped LDHs using photoinduced surface-initiated reversible addition-fragmentation chain transfer (RAFT) polymerization with hydrophilic poly(ethylene glycol) methacrylate (PEGMA) as the monomer. The final products were obtained via the metal free surface-initiated RAFT polymerization with light irradiation. Successful preparation of these fluorescent LDHs polymer composites (LDH-PEG) was confirmed by a number of analytical technologies, such as transmission electron microscopy, Fourier transformed infrared spectroscopy, X-ray photoelectron spectroscopy and thermogravimetric analysis. In addition, laser scanning confocal microscope was employed to examine the cell uptake behavior of the LDH-PEG composites and evaluate their potential for biomedical applications. We demonstrated that the hydrophilic monomer PEGMA could be facilely grafted on the surface of Tb3+-doped LDHs through metal free photoinduced surface-initiated RAFT polymerization. The resultant LDH-PEG composites displayed high water dispersibility, strong fluorescence, low cytotoxicity and a desirable cell uptake performance. These features of the LDH-PEG composites indicated their great potential for biomedical applications. More importantly, photoinduced RAFT polymerization has the advantages of a conventional controlled living radical polymerization, which could overcome drawbacks such as toxicity, the fluorescence quenching effects of metal catalysts and the complex synthesis of chain transfer agents. Therefore, this method could be an alternative tool for the surface modification of materials and fabrication of multifunctional fluorescent nanomaterials based polymer composites.

[A long-term observation and follow-up for patients with HBeAg/Anti-HBe seroconversion after lamivudine treatment].

OBJECTIVE: To observe the resulting change in patients who achieved HBeAg/Anti-HBe seroconversion after lamivudine treatment. METHODS: 68 patients were observed for over 24 months. They were HBeAg/Anti-HBe with a seroconversion time > or = 6 months and the course of lamivudine treatment was > or = 18 months. RESULTS: After lamivudine treatment, the rate of HBeAg/Anti-HBe seroconversion was 25.19%, the rate of YMDD mutations was 20.59%, and the rate of relapse was 27.94% for these patients that achieved HBeAg/Anti-HBe seroconversion in observation and in the follow-up period. Lamivudine was still an effective drug for these patients with relapses. The rate of relapse was in correlation to the patients' age and the ALT level before treatment. The rate of relapse was not correlated to the HBV DNA level before the course of treatment. YMDD mutations were not correlated to the relapses. CONCLUSION: Even with a HBeAg/Anti-HBe seroconversion time > or = 6 months, the rate of relapse was still higher in patients with chronic hepatitis B that received lamivudine. The patients with long-term lamivudine treatment should be observed and have frequent follow-up visits.

[Relation of serological markers of hepatitis B virus and alanine transaminase to hepatic tissue pathology in patients with chronic hepatitis B].

OBJECTIVE: To investigate the association of serological markers of hepatitis B virus (HBV) and alanine transaminase (ALT) with hepatic tissue pathology in patients with chronic hepatitis B. METHODS: The serological marker of HBV, liver function and liver biopsy of 133 patients with chronic hepatitis B were measured and evaluated. The patients were divided into 4 groups according to HBeAg and HBV DNA positivity. Hepatic necrosis/inflammation grade and hepatic fibrosis were compared between the groups. RESULTS: Hepatic histological examination of all these patients showed inflammation, necrosis and different degrees of fibrosis. In patients with normal serum ALT, liver biopsy showed different degrees of inflammation, hepatic fibrosis, and even hepatocirrhosis. In patients with abnormal serum ALT negative for HBeAg, hepatic tissue inflammation and fibrosis were more serious. Hepatic tissue pathology was not paralleled with the level of HBV replication. CONCLUSION: Evaluation of the liver disease can not depend solely on serum ALT and viral loading in these patients. Hepatic tissue pathology in patients with chronic hepatitis B should be served as the most reliable evidence for evaluating hepatitis conditions and making the decision on antiviral therapy.