A posteriori error analysis of a quadratic finite volume method for nonlinear elliptic problems

In this article, we construct and analyze a residual-based a posteriori error estimator for a quadratic finite volume method (FVM) for solving nonlinear elliptic partial differential equations with homogeneous Dirichlet boundary conditions. We shall prove that the a posteriori error estimator yields the global upper and local lower bounds for the norm error of the FVM. So that the a posteriori error estimator is equivalent to the true error in a certain sense. Numerical experiments are performed to illustrate the theoretical results.     

Geometry,stability and aromaticity of β-diketiminate-coordinated alkaline-earth compounds

Alkaline-earth (Ae) metals have attracted a wealth of interdependent research from synthetic chemists. In Ae-catalyzed organometallic reactions, β-diketiminate is a typical ligand used to stabilize Ae catalysts by forming six-membered rings comprising Ae metals. Herein, studies focusing on the configuration of β-diketiminate-coordinated Ae compounds observed that the CC and CN bonds are homogeneous and unchanged. Furthermore, energetic studies observed that the formation of the Ae-incorporated six-membered rings results in enhanced stability of >20 kcal/mol. The nucleus-independent chemical shifts, anisotropy of the induced current density, and molecular orbital analyses demonstrated the non-aromaticity of the β-diketiminate-coordinated Ae compounds. The improved stability of these compounds can be explained by the delocalization of the π electrons derived from the β-diketiminate moiety.     

The formation of mesoporous TiO2 spheres via a facile chemical process

The mesoporous TiO(2) solid and hollow spheres have been synthesized via a controllable and simple chemical route. Structural characterization indicates that these TiO(2) mesoporous spheres after calcined at 500 degrees C have an obvious mesoporous structure with the diameters of 200-300 nm for solid spheres and 200-500 nm for hollow spheres. The average pore sizes and BET surface areas of the mesoporous TiO(2) solid and hollow spheres are 6.8, 7.0 nm and 162, 90 m(2)/g, respectively. Optical adsorption investigation shows that TiO(2) solid and hollow spheres possess a direct band gap structure with the optical band gap of 3.68 and 3.75 eV, respectively. A possible formation mechanism for TiO(2) solid and hollow spheres is discussed.     

When does gradient Ricci soliton have one end?

Annals of Global Analysis and Geometry - In this paper, we study a problem of finding compact hypersurfaces of prescribed mean curvature with free boundary in a ball. We transform the problem to an...     

Mass spectrometry-based chemical mapping and profiling toward molecular understanding of diseases in precision medicine

Precision medicine has been strongly promoted in recent years. It is used in clinical management for classifying diseases at the molecular level and for selecting the most appropriate drugs or treatments to maximize efficacy and minimize adverse effects. In precision medicine, an in-depth molecular understanding of diseases is of great importance. Therefore, in the last few years, much attention has been given to translating data generated at the molecular level into clinically relevant information. However, current developments in this field lack orderly implementation. For example, high-quality chemical research is not well integrated into clinical practice, especially in the early phase, leading to a lack of understanding in the clinic of the chemistry underlying diseases. In recent years, mass spectrometry (MS) has enabled significant innovations and advances in chemical research. As reported, this technique has shown promise in chemical mapping and profiling for answering “what”, “where”, “how many” and “whose” chemicals underlie the clinical phenotypes, which are assessed by biochemical profiling, MS imaging, molecular targeting and probing, biomarker grading disease classification, etc. These features can potentially enhance the precision of disease diagnosis, monitoring and treatment and thus further transform medicine. For instance, comprehensive MS-based biochemical profiling of ovarian tumors was performed, and the results revealed a number of molecular insights into the pathways and processes that drive ovarian cancer biology and the ways that these pathways are altered in correspondence with clinical phenotypes. Another study demonstrated that quantitative biomarker mapping can be predictive of responses to immunotherapy and of survival in the supposedly homogeneous group of breast cancer patients, allowing for stratification of patients. In this context, our article attempts to provide an overview of MS-based chemical mapping and profiling, and a perspective on their clinical utility to improve the molecular understanding of diseases for advancing precision medicine.

An overview of MS-based chemical mapping and profiling, indicating its contributions to the molecular understanding of diseases in precision medicine by answering "what", "where", "how many" and "whose” chemicals underlying clinical phenotypes.     

Structural and process controls of AIEgens for NIR-II theranostics

Aggregation-induced emission (AIE) is a cutting-edge fluorescence technology, giving highly-efficient solid-state photoluminescence. Particularly, AIE luminogens (AIEgens) with emission in the range of second near-infrared window (NIR-II, 1000–1700 nm) have displayed salient advantages for biomedical imaging and therapy. However, the molecular design strategy and underlying mechanism for regulating the balance between fluorescence (radiative pathway) and photothermal effect (non-radiative pathway) in these narrow bandgap materials remain obscure. In this review, we outline the latest achievements in the molecular guidelines and photophysical process control for developing highly efficient NIR-II emitters or photothermal agents with aggregation-induced emission (AIE) attributes. We provide insights to optimize fluorescence efficiency by regulating multi-hierarchical structures from single molecules (flexibilization) to molecular aggregates (rigidification). We also discuss the crucial role of intramolecular motions in molecular aggregates for balancing the functions of fluorescence imaging and photothermal therapy. The superiority of the NIR-II region is demonstrated by fluorescence/photoacoustic imaging of blood vessels and the brain as well as photothermal ablation of the tumor. Finally, a summary of the challenges and perspectives of NIR-II AIEgens for in vivo theranostics is given.

Structural and process controls of NIR-II AIEgens realize manipulating of radiative (R) and nonradiative (NR) decay for precise theranostics.     

大气采样器检定规程探讨及修订建议

通过对大气采样器流量示值误差进行计量检定发现,是否有吸收负栽检定结果差别较大,而计量检定规程并没有详细说明,因此对大气采样器检定规程进行了探讨并提出修改建议.     

Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph

An effective fault diagnosis method of bearing is the key to predictive maintenance of modern industrial equipment. With the single use of equipment failure mechanism or operation of data, it is hard to resolve multiple complex variable working conditions, multiple types of fault and equipment malfunctions and failures related to knowledge and data. In order to solve these problems, a fault diagnosis method based on the fusion of deep learning with a knowledge graph is proposed in this paper. Firstly, the knowledge rules of bearing data is used for entity extraction. Next, the multiscale optimized convolutional neural network (MOCNN) proposed in this paper is used for fault classification to achieve relationship extraction. Finally, the fault diagnosis graph of the bearing is constructed for fault-assisted decision-making as well as the detailed display of fault information. According to experiment analysis, the fault diagnosis model based on MOCNN proposed in this paper, which integrates the end-to-end convolutional neural network and the attention mechanism, still achieves an accuracy of 97.86% under the data set of 160 types of faults. Compared with the deep learning models such as Resnet and Inception in the noise environment of multiple working conditions and variable working conditions, the model proposed in this paper not only shows a faster convergence speed and stable performance, but also a higher accuracy in evaluation indicators, which is beneficial to practical use.     

Design,Preparation, and Evaluation of Osthol Poly-Butyl-Cyanoacrylate Nanoparticles with Improved In Vitro Anticancer Activity in Neuroblastoma Treatment

Osthol (osthole), known as a neuroprotective drug, has shown potent anticancer activity. However, the potential clinical application of osthol is limited due to its low water solubility and low bioavailability. Polybutyl cyanoacrylate (PBCA) has been widely used to improve the solubility of drugs with poor water solubility. In this study, an orthogonal experimental design (OED) was applied to design the preparation process of PBCA nanoparticles (NPs). Then, nanoparticles were prepared and evaluated in terms of physicochemical properties, in vitro release, and cellular uptake, etc. Further, the anti-cancer activity of osthol-PBCA NPs was demonstrated in SH-SY5Y cells. The pharmacokinetics and area under the curve (AUC) were investigated. The obtained osthol-NPs presented a spherical shape with a particle size of 110 ± 6.7 nm, a polydispersity index (PDI) of 0.126, and a zeta potential of −13 ± 0.32 mV. Compared with the free osthol, the drugs in osthol-NPs presented better stability and sustained release pattern activity. In vitro analysis using SH-SY5Y neuroblastoma cells showed that osthol-loaded nanoparticles displayed a significantly enhanced intracellular absorption process (three times) and cytotoxicity compared with free osthol (p < 0.05, increased 10–20%). The in vivo pharmacokinetic study revealed that the AUC of osthol-NPs was 3.3-fold higher than that of free osthol. In conclusion, osthol-PBCA NPs can enhance the bioactivity of osthol, being proposed as a novel, promising vehicle for drug delivery.