APP软件性能效率研究

性能效率是APP软件的重要质量属性，但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征，基于ISO/IEC 25010标准提出了APP软件的性能效率模型，定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型，通过实验对APP软件的性能效率进行了度量及相关分析。     

Combustion synthesis of AlN doped with carbon and oxygen

Carbon-and-oxygen-doped AlN specimens were prepared by combustion synthesis using Al, graphite, and AlN. Graphite addition changed the product color from white to blue. By XRD, the lattice constant increased slightly with increasing carbon content. Blue AlN powder was synthesized with a molar ratio of the diluent AlN of 0.2-0.5 with a fixed graphite content of 0.05. At an AlN molar ratio exceeding 0.6, carbon was not successfully incorporated due to the lower reaction temperature. Calcination at 800°C in air removed residual graphite without changing the crystal structure or product color. Oxygen, nitrogen, and carbon analyses revealed that blue AlN powders contained 0.45-0.54 mass% carbon and 1.4-1.6 mass% oxygen, while the undoped AlN contained 0.021 mass% carbon and 0.94 mass% oxygen. The origin of the white-to-blue color change was investigated via reflection measurements. Blue AlN exhibits an absorption peak at 634 nm (1.96 eV). From first-principles electronic structure calculations, the C-doped AlN and carbon-and-oxygen-doped AlN with a 1:1 ratio could be classified as p-type, whereas the O-doped AlN and 1:3 carbon-and-oxygen-doped AlN were n-type. One reason for the absorption peak at 634 nm may be a transition from the conduction band to an upper unoccupied state. These results suggest the possible control of optical and electronic properties of AlN via carbon-and-oxygen doping.     

Impact of high-intensity ultrasound on physical properties and degree of oxidation of lipase modified menhaden oil with caprylic acid and/or stearic acid

The purpose of this research was to determine the effect of high-intensity ultrasound (HIU) on physical properties, degree of oxidation, and oxidative stability of structured lipids (SLs). Caprylic acid (C) and stearic acid (S) were incorporated into menhaden oil using Lipozyme® 435 lipase to obtain five samples: (1) LC 20 (menhaden oil with 20% of C), (2) LC 30 (menhaden oil with 30% C), (3) LS 20 (menhaden oil with 20% S), (4) LS 30 (menhaden oil with 30% S), and (5) Blend C (menhaden oil with 16.24% C and 13.04% S). Samples were crystallized for 90 min at the following temperatures: (1) LC 20 at 15.5°C, (2) LC 30 at 17.5°C, (3) LS 20 at 24°C, (4) LS 30 at 30°C, and (5) Blend C at 18.0°C, and HIU was applied at the onset of crystallization. Physical properties, degree of oxidation, and oxidative stability were evaluated in sonicated and nonsonicated samples. All SLs had statistically higher G′ after sonication. Sonicated LS 30, LC 30, and Blend C had a higher melting enthalpy than the nonsonicated ones, while enthalpy values in sonicated LS 20 and LC 20 samples were not statistically different than the nonsonicated ones. No significant difference between sonicated and nonsonicated samples was observed in peroxide values (1.2 ± 0.1 meq/kg, p > 0.05) and in the oxidative stability index (6.3 ± 0.2 h, p > 0.05). These results showed that HIU was effective at changing physical properties without affecting the oxidation of the samples.     

Rational Designs for Lithium-Sulfur Batteries with Low Electrolyte/Sulfur Ratio

Lithium-sulfur batteries (LSBs) are considered a promising next-generation energy storage device owing to their high theoretical energy density. However, their overall performance is limited by several critical issues such as lithium polysulfide (PS) shuttles, low sulfur utilization, and unstable Li metal anodes. Despite recent huge progress, the electrolyte/sulfur ratio (E/S) used is usually very high (≥20 µL mg⁻¹), which greatly reduces the practical energy density of devices. To push forward LSBs from the lab to the industry, considerable attention is devoted to reducing E/S while ensuring the electrochemical performance. To date, however, few reviews have comprehensively elucidated the possible strategies to achieve that purpose. In this review, recent advances in low E/S cathodes and anodes based on the issues resulting from low E/S and the corresponding solutions are summarized. These will be beneficial for a systematic understanding of the rational design ideas and research trends of low E/S LSBs. In particular, three strategies are proposed for cathodes: preventing PS formation/aggregation to avoid inadequate dissolution, designing multifunctional macroporous networks to address incomplete infiltration, and utilizing an imprison strategy to relieve the adsorption dependence on specific surface area. Finally, the challenges and future prospects for low E/S LSBs are discussed.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

Preparation of a CeO2–ZrO2 based nano-composite with enhanced thermal stability by a novel chelating precipitation method

In this study, a chelating agent is introduced to prepare CeO₂–ZrO₂ nano-composite through a precipitation process. The physicochemical properties of the oxide precursors, nano composite materials are strongly dependent on the preparation method and whether a chelating agent is used. Adding an appropriate quantity of chelating agent SO₄²⁻ can facilitate thermal stability and phase structure uniformity of CeO₂–ZrO₂ mixed oxides. The calculation results showed that the Gibbs free energy of chelating complex of [ZrSO₄]²⁺ (ΔG = −127.2469 kJ/mol) is higher than the [Ce(III)SO₄]⁺ (ΔG = -29.8279 kJ/mol). The precipitation chemical potential of Zr⁴⁺ moves close to the precipitation chemical potential of Ce³⁺. The novel and low-cost chelating precipitation method can modify the homogeneity of the compounds at the atomic scale, which can offer a powerful opportunity for, and provide direction in, the design of materials with exceptional properties.     

Transport Map sampling with PGD model reduction for fast dynamical Bayesian data assimilation

The motivation of this work is to address real-time sequential inference of parameters with a full Bayesian formulation. First, the proper generalized decomposition (PGD) is used to reduce the computational evaluation of the posterior density in the online phase. Second, Transport Map sampling is used to build a deterministic coupling between a reference measure and the posterior measure. The determination of the transport maps involves the solution of a minimization problem. As the PGD model is quasi-analytical and under a variable separation form, the use of gradient and Hessian information speeds up the minimization algorithm. Eventually, uncertainty quantification on outputs of interest of the model can be easily performed due to the global feature of the PGD solution over all coordinate domains. Numerical examples highlight the performance of the method.     

基于ABAQUS的显式动力学分析方法研究

显式动力学(The Explicit Dynamic)是针对隐式求解器的一个补充,其分析方法对于求解广泛、各类非线性结构力学问题是一个非常有效的工具,显式方法中的单个增量步取决于模型的最高固有频率,与持续时间、载荷类型无关。ABAQUS/Explicit主要用于碰撞、接触以及失效分析。探讨了ABAQUS显式动力学的基本理论、求解的问题,对显示动力学分析方法中的求解算法、稳定时间极限和能量平衡问题进行研究,给出了显示动力学分析的一般性分析方法。通过案例验证了该方法的可行性,应用该方法可有效解决实际工业生产中的碰撞问题、复杂的接触问题以及复杂的后屈曲问题,可为显式动力学分析方法应用于工程实践奠定理论与方法基础。     

A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.