Rapid Identification for the Pterocarpus Bracelet by Three-Step Infrared Spectrum Method

In order to explore a rapid identification method for the anti-counterfeit of commercial high value collections, a three-step infrared spectrum method was used for the pterocarpus collection identification to confirm whether a commercial pterocarpus bracelet (PB) was made from the precious species of Pterocarpus santalinus (P. santalinus). In the first step, undertaken by Fourier transform infrared spectroscopy (FTIR) spectrum, the absorption peaks intensity of PB was slightly higher than that of P. santalinus only at 1594 cm⁻¹, 1205 cm⁻¹, 1155 cm⁻¹ and 836 cm⁻¹. In the next step of second derivative IR spectra (SDIR), the FTIR features of the tested samples were further amplified, and the peaks at 1600 cm⁻¹, 1171 cm⁻¹ and 1152 cm⁻¹ become clearly defined in PB. Finally, by means of two-dimensional correlation infrared (2DIR) spectrum, it revealed that the response of holocellulose to thermal perturbation was stronger in P. santalinus than that in PB mainly at 977 cm⁻¹, 1008 cm⁻¹, 1100 cm⁻¹, 1057 cm⁻¹, 1190 cm⁻¹ and 1214 cm⁻¹, while the aromatic functional groups of PB were much more sensitive to the thermal perturbation than those of P. santalinus mainly at 1456 cm⁻¹, 1467 cm⁻¹, 1518 cm⁻¹, 1558 cm⁻¹, 1576 cm⁻¹ and 1605 cm⁻¹. In addition, fluorescence microscopy was used to verify the effectiveness of the above method for wood identification and the results showed good consistency. This study demonstrated that the three-step IR method could provide a rapid and effective way for the anti-counterfeit of pterocarpus collections.     

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

Numerical Study on Entropy Generation of the Multi-Stage Centrifugal Pump

The energy loss of the multi-stage centrifugal pump was investigated by numerical analysis using the entropy generation method with the RNG k-ε turbulence model. Entropy generation due to time-averaged motion and velocity fluctuation was mainly considered. It was found that the entropy generation of guide vanes and impellers account for 71.2% and 23.3% of the total entropy generation under the designed flow condition. The guide vanes are the main hydraulic loss domains and their entropy generation is about 9 W/K, followed by impellers. There are vortices at the tongue of the guide vane inlet as well as flow separations in the impellers, which lead to entropy generation. The fluid impacts the outer surface of the guide vanes, resulting in the increase in entropy generation. There are refluxes near the guide vane tongues which also increase the entropy generation of this part. The entropy generation distribution of the guide vanes and impellers was investigated, which found that the positive guide vane has more entropy generation compared with the reverse guide. The entropy generation of the blade suction surface is higher compared with the pressure surface. This study indicated that the entropy generation method has distinct advantages in the assessment of hydraulic loss.     

Cloning,Expression, Purification,and Characterization of β-Galactosidase from Bifidobacterium longum and Bifidobacterium pseudocatenulatum

Expression and purification of β-galactosidases derived from Bifidobacterium provide a new resource for efficient lactose hydrolysis and lactose intolerance alleviation. Here, we cloned and expressed two β-galactosidases derived from Bifidobacterium. The optimal pH for BLGLB1 was 5.5, and the optimal temperature was 45 °C, at which the enzyme activity of BLGLB1 was higher than that of commercial enzyme E (300 ± 3.6 U/mg) under its optimal conditions, reaching 2200 ± 15 U/mg. The optimal pH and temperature for BPGLB1 were 6.0 and 45 °C, respectively, and the enzyme activity (0.58 ± 0.03 U/mg) under optimum conditions was significantly lower than that of BLGLB1. The structures of the two β-galactosidase were similar, with all known key sites conserved. When o-nitrophenyl-β-D-galactoside (oNPG) was used as an enzyme reaction substrate, the maximum reaction velocity (V_max) for BLGLB1 and BPGLB1 was 3700 ± 100 U/mg and 1.1 ± 0.1 U/mg, respectively. The kinetic constant (K_m) of BLGLB1 and BPGLB1 was 1.9 ± 0.1 and 1.3 ± 0.3 mmol/L, respectively. The respective catalytic constant (k_cat) of BLGLB1 and BPGLB1 was 1700 ± 40 s⁻¹ and 0.5 ± 0.02 s⁻¹, respectively; the respective k_cat/K_m value of BLGLB1 and BPGLB1 was 870 L/(mmol∙s) and 0.36 L/(mmol∙s), respectively. The K_m, k_cat and V_max values of BLGLB1 were superior to those of earlier reported β-galactosidase derived from Bifidobacterium. Overall, BLGLB1 has potential application in the food industry.     

Preparation of Silica Aerogel/Resin Composites and Their Application in Dental Restorative Materials

As the most advanced aerogel material, silica aerogel has had transformative industrial impacts. However, the use of silica aerogel is currently limited to the field of thermal insulation materials, so it is urgent to expand its application into other fields. In this work, silica aerogel/resin composites were successfully prepared by combining silica aerogel with a resin matrix for dental restoration. The applications of this material in the field of dental restoration, as well as its performance, are discussed in depth. It was demonstrated that, when the ratio of the resin matrix Bis-GMA to TEGDMA was 1:1, and the content of silica aerogel with 50 μm particle size was 12.5%, the composite achieved excellent mechanical properties. The flexural strength of the silica aerogel/resin composite reached 62.9546 MPa, which was more than five times that of the pure resin. Due to the presence of the silica aerogel, the composite also demonstrated outstanding antibacterial capabilities, meeting the demand for antimicrobial properties in dental materials. This work successfully investigated the prospect of using commercially available silica aerogels in dental restorative materials; we provide an easy method for using silica aerogels as dental restorative materials, as well as a reference for their application in the field of biomedical materials.     

Computational fluid dynamic-discrete element method coupling analysis of particle transport in branched networks

An understanding of the particle transport characteristics in a branched network helps to predict the particle distribution and prevent undesired plugging in various engineering systems.Quantitative analysis of particle flow characteristics is challenging in that experiments are expensive and particle flow is difficult to detect without disturbing the flow.To overcome this difficulty,man-made fractal tree-like branched networks were built,and a coupled computational fluid dynamic and discrete element method model was applied.A series of numerical simulations was carried out to analyze the influence of fractal structure parameters of networks on the particle flow characteristics.The joint influence of inertial,shunt capacity and superposition from upstream branches on particle flow was investigated.The injection position at the inlet determined the particle velocity and its future flow path.The particle density ratio,particle size and bifurcation angle had a greater influence on the shunting of K2 branches than that in the K1 level and N_k22/N_k21 reached a maximum at 60°.Compared with a network with an even number of branches,there was a preferential branch when the branch number was odd.The preferential branch effect or asymmetry degree of the level(K2)branches had a more significant impact on particle shunting than that from the upstream branches(K1).     

金红石TiO_2中本征缺陷扩散性质的第一性原理计算

基于密度泛函理论的爬坡弹性带方法,对金红石相二氧化钛晶体中钛间隙、钛空位、氧间隙、氧空位4种本征缺陷的扩散特征进行了研究.对比4种本征缺陷在晶格内部沿不同扩散路径的过渡态势垒后发现,缺陷扩散过程呈现出明显的各向异性.其中,钛间隙和氧间隙沿[001]方向具有最小的扩散势垒路径,激活能分别为0.505 eV和0.859 eV;氧空位和钛空位的势垒最小的扩散路径分别沿[110]方向和[111]方向,激活能分别为0.735 eV和2.375 eV.     

在任意温度的热库中量子位的消相干

本文在Markov 近似下推导了在任意温度的热库中,一个量子位(qubit)的主方程,并由此讨论了由于振幅阻尼而引起的量子位消相干(decoherence). 结论表明量子位的跃迁频率与热库的特征频率及截止频率的关系对消相干有明显的影响。     

Necklace solitons in Bessel photonic lattice: Stability and internal oscillation

Stability, internal modes and internal oscillation of 12-pearled necklace solitons in photorefractive crystal with imprinted Bessel photonic lattices are investigated. It is shown that the imaginary parts of internal modes are negligible comparing with real parts. The stable solitons perform long-distance and quasi-periodic oscillation of intensity and shape under the perturbation of internal modes.     

Rapid Detection of Five Estrogens Added Illegally to Dietary Supplements by Combining TLC with Raman Imaging Microscope

Estrogens added illegally to dietary supplements are hazardous to human health. Traditional detection and analysis methods have many limitations, and we have developed an assay that combines thin-layer chromatography with Raman imaging microscopy (TLC-RIM). The five estrogens (estrone, estradiol, estriol, ethinyl estradiol, and diethylstilbestrol) were initially separated by TLC, then detected by area scanning Raman imaging with a 532 nm laser under a microscope. Raman spectra were obtained for each estrogen, which were used for detecting estrogen illegally added to botanical dietary supplements. The LOD of each estrogen was 0.4, 1.0, 0.8, 0.2, and 0.2 mg/mL, respectively. The matrix in the real sample did not interfere with the detection of estrogens. The method was fast, sensitive, stable, specific, and reliable.