A method for rapidly evaluating reliability and predicting remaining useful life using two-dimensional convolutional neural network with signal conversion

Journal of Mechanical Science and Technology - Real-time monitoring and rapid evaluation of bearing operating conditions, especially for the reliability evaluation and remaining useful life (RUL)...     

Analysis of Phytochemical Composition of Camellia oleifera Oil and Evaluation of its Anti-Inflammatory Effect in Lipopolysaccharide-Stimulated RAW 264.7 Macrophages

In China, Camellia oleifera oil (COO) is not only a common edible oil but also a traditional remedy widely applied to ameliorate a variety of illnesses associated with inflammation, such as mouth ulcers, thrush, eczema, etc. However, there has been a lack of relevant biological research on the anti-inflammatory capacity of COO, and the specific bioactive lipid phytochemicals contributing to the anti-inflammatory effect need further research. In this study, the RAW 264.7 macrophages model was used to investigate the anti-inflammatory capacity of COO. Our data showed that 33–200 μg/mL COO markedly inhibited the lipopolysaccharide lipopolysaccharide (LPS)-stimulated nitric oxide (NO.) secretion via the suppression of Nos2 and Cox-2 expression. The enzyme immunoassay confirmed that COO also exhibited a strong suppressive effect on the expression of proinflammatory cytokines such as Tnf-α and Il-6. To further explore the correlation between the anti-inflammatory effects and the lipid phytochemicals in COO, 10 samples were collected and screened for their chemical compositions. It was interestingly demonstrated that the polyphenol extracts of COO play a vital role in its anti-inflammatory properties. In addition, an oil-in-water (O/W) emulsion-based system was also developed to deliver the liposoluble COO into the cells, and the feasibility of this system was confirmed. Our research confirms the anti-inflammatory potential of COO and highlights that the main functional ingredient is polyphenol extracts. This may provide a scientific basis for the comprehensive utilization and development of COO and related functional foods.     

Physical Stability of Octenyl Succinate–Modified Polysaccharides and Whey Proteins for Potential Use as Bioactive Carriers in Food Systems

The high cost and potential toxicity of biodegradable polymers like poly(lactic‐co‐glycolic)acid (PLGA) has increased the interest in natural and modified biopolymers as bioactive carriers. This study characterized the physical stability (water sorption and state transition behavior) of selected starch and proteins: octenyl succinate–modified depolymerized waxy corn starch (DWxCn), waxy rice starch (DWxRc), phytoglycogen, whey protein concentrate (80%, WPC), whey protein isolate (WPI), and α‐lactalbumin (α‐L) to determine their potential as carriers of bioactive compounds under different environmental conditions. After enzyme modification and particle size characterization, glass transition temperature and moisture isotherms were used to characterize the systems. DWxCn and DWxRc had increased water sorption compared to native starch. The level of octenyl succinate anhydrate (OSA) modification (3% and 7%) did not reduce the water sorption of the DWxCn and phytoglycogen samples. The Guggenheim–Andersen–de Boer model indicated that native waxy corn had significantly (P < 0.05) higher water monolayer capacity followed by 3%‐OSA‐modified DWxCn, WPI, 3%‐OSA‐modified DWxRc, α‐L, and native phytoglycogen. WPC had significantly lower water monolayer capacity. All Tg values matched with the solid‐like appearance of the biopolymers. Native polysaccharides and whey proteins had higher glass transition temperature (Tg) values. On the other hand, depolymerized waxy starches at 7%‐OSA modification had a “melted” appearance when exposed to environments with high relative humidity (above 70%) after 10 days at 23 °C. The use of depolymerized and OSA‐modified polysaccharides blended with proteins created more stable blends of biopolymers. Hence, this biopolymer would be suitable for materials exposed to high humidity environments in food applications.     

Experimental and numerical analysis of the influence of cable tray arrangements on the resulting mass loss rate and fire spreading

In the context of industrial buildings and power plants, electrical installations and cable trays represent a main fuel load and a potential initial fire source due to possible short circuits or comparable malfunction. Furthermore, a fire can spread from one tray to additional trays mounted above and/or horizontally on one tray. Because of the high significance of cable fires, several research projects have been carried out, investigating the fire behaviour of cables from small‐scale tests, eg, the cone calorimeter, up to large‐scale tests, analysing complete cable tray constructions. The goal of the work presented in this paper is the extension of the knowledge regarding the influence of geometrical parameters like the packing density and tray distance on the burning behaviour and fire spread of cable tray installations. The results are considered, together with test results from the literature, to quantify the main physical parameters describing the burning behaviour. In a next step, the general applicability of these parameters as input data for the parametrization of the source term of numerical simulations is shown. The test results show that the burning behaviour and the fire spreading highly depend on the cable arrangement of the cables on the cable tray, in combination with other boundary conditions. By applying the results as input for a fire simulation, the mass loss rate is considered appropriately.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Novel thermal-sensitive properties of NBT-BZT composite ceramics for high-temperature NTC thermistors

We found for the first time that (1 − x) Na_0.5Bi_0.5TiO₃-xBiZn_0.5Ti_0.5O₃ (NBT–BZT) composite ceramics showed negative temperature coefficient (NTC) at a high temperature. The NBT–BZT nanopowders were successfully prepared by Pechini method. Their ceramics were sintered at 1100°C. The NBT–BZT ceramic exhibited a good linear relationship between logarithm of electrical resistivity (Inρ) and reciprocal of absolute temperature (1000/T) at 250°C–1050°C. The obtained ρ₆₀₀, ρ₉₀₀, and B_600/900 constants of the NBT–ZBT NTC thermistors are approximately 5.92 × 10⁶ to 3.01 × 10⁴ Ω cm, 7.03 × 10³ to 7.60 × 10² Ω cm and 2.3 × 10⁴-1.3 × 10⁴ K, respectively. The electrical characteristics can be tuned to the desired value by changing the Na_0.5Bi_0.5TiO₃ content in the compound. The electrical conductivity in these compounds is due to the electron jumps between Ti³⁺ and Ti⁴⁺ and oxygen-ion conductivity. Results demonstrate a tremendous potential of the studied system for perovskite materials with NTC performance.     

山东栖霞—大柳行地区金矿找矿靶区地质评价及优选

栖霞—大柳行地区位于胶东中部栖霞—蓬莱金矿成矿带内，是胶东重要的金成矿区，成矿条件优越。为了对圈定靶区进行优选分类，通过对该区地质背景、找矿靶区评价、找矿靶区优选方面展开综合研究，并结合勘查工作程度和矿业权设置情况，划分出3类预测区，选定了5个靶区为今后优先部署勘查工作的方向。