无机元素与计量学模型结合的半夏产地溯源研究

目的:建立不同产地半夏无机元素的分析方法和溯源体系,为半夏药材的质量控制和道地性评价提供技术支持。方法:采用电感耦合等离子体质谱法(ICP-MS)和电感耦合等离子体原子发射光谱法(ICP-AES)对我国6个主产区72份半夏样品中K、Ca、Na、Mg、Al等37种无机元素的含量进行测定,并采用方差分析、主成分分析、因子分析等计量学方法进行统计与评价。通过对比BP-神经网络算法、K-最近邻算法、最小二乘支持向量机等多种模式识别方法,探索适合半夏产地溯源的最佳模型。结果:不同产地半夏中无机元素的构成各具特征,各无机元素含量在产地间差异显著(P＜0.05),其中La、Pb、As、Na、Bi、Hg、Sn、Cd、Ag 9种元素在不同产区间的差异最为明显;3D-plots图显示不同产地半夏样品分布相对集中,具备产地分类的可行性;KNN分类模型(曼哈顿距离)是半夏产地溯源的最佳方法,测试集的正确率达到100%。结论:无机元素分析技术结合适当的计量学模型可以实现半夏的产地溯源。     

Joint Optimization of Control Strategy and Energy Consumption for Energy Harvesting WSAN

With the rapid development of wireless sensor technology, recent progress in wireless sensor and actuator networks (WSANs) with energy harvesting provide the possibility for various real-time applications. Meanwhile, extensive research activities are carried out in the fields of efficient energy allocation and control strategy design. However, the joint design considering physical plant control, energy harvesting, and consumption is rarely concerned in existing works. In this paper, in order to enhance system control stability and promote quality of service for the WSAN energy efficiency, a novel three-step joint optimization algorithm is proposed through control strategy and energy management analysis. First, the optimal sampling interval can be obtained based on energy harvesting, consumption, and remaining conditions. Then, the control gain for each sampling interval is derived by using a backward iteration. Finally, the optimal control strategy is determined as a linear function of the current plant states and previous control strategies. The application of UAV formation flight system demonstrates that better system performance and control stability can be achieved by the proposed joint optimization design for all poor, sufficient, and general energy harvesting scenarios.     

Facile Synthesis of Tricyclic 1,2,4-Oxadiazolines-Fused Tetrahydro-Isoquinolines from Oxime Chlorides with 3,4-Dihydroisoquinoline Imines

A mild and efficient strategy for the synthesis of tricyclic 1,2,4-oxadiazolines-fused tetrahydro-isoquinolines derivatives via [3 + 2] cycloaddition reaction is reported. The reactions provided the functionalized tricyclic 1,2,4-oxadiazolines in high yields (up to 96%). This protocol is simple and easy to handle. Moreover, a gram-scale experiment further highlights the synthetic utility. The chemical structure of the product was determined by X-ray single-crystal structure analysis. A possible mechanism for this transformation is proposed to explain the reaction process.     

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm⁻¹) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.     

Investigation Driven by Network Pharmacology on Potential Components and Mechanism of DGS,a Natural Vasoprotective Combination,for the Phytotherapy of Coronary Artery Disease

Phytotherapy offers obvious advantages in the intervention of Coronary Artery Disease (CAD), but it is difficult to clarify the working mechanisms of the medicinal materials it uses. DGS is a natural vasoprotective combination that was screened out in our previous research, yet its potential components and mechanisms are unknown. Therefore, in this study, HPLC-MS and network pharmacology were employed to identify the active components and key signaling pathways of DGS. Transgenic zebrafish and HUVECs cell assays were used to evaluate the effectiveness of DGS. A total of 37 potentially active compounds were identified that interacted with 112 potential targets of CAD. Furthermore, PI3K-Akt, MAPK, relaxin, VEGF, and other signal pathways were determined to be the most promising DGS-mediated pathways. NO kit, ELISA, and Western blot results showed that DGS significantly promoted NO and VEGFA secretion via the upregulation of VEGFR2 expression and the phosphorylation of Akt, Erk1/2, and eNOS to cause angiogenesis and vasodilation. The result of dynamics molecular docking indicated that Salvianolic acid C may be a key active component of DGS in the treatment of CAD. In conclusion, this study has shed light on the network molecular mechanism of DGS for the intervention of CAD using a network pharmacology-driven strategy for the first time to aid in the intervention of CAD.     

A MALDI-MS sensing chip prepared by non-covalent assembly for quantitation of acid phosphatase

A novel sensing chip was designed for MALDI-MS quantitation of acid phosphatase(ACP).The ACP sensing chip was constructed through non-covalent interaction of streptavidin and biotin for the assembly of biotinylated peptide substrate on biotinylated polyethylene-glycol(PEG)modified indium-tin oxide(ITO)slide.In the presence of ACP,the peptide substrate was dephosphorylated under acidic condition to generate a new mass signal.The quantitative assay of ACP was achieved with the mass signal ratio of product to the sum of product and left peptide substrate.Under optimal detection conditions,the ratio was linearly correlated with the concentration of ACP in the range of 0.05–12 g/L with a detection limit(LOD)of 0.04 g/L.The designed ACP sensing chip has been used to analyze ACP in complex clinical samples,which exhibited high selectivity,good repeatability,and admirably anti-interference ability.This work further demonstrates the concept of MS sensing and the application of MALDI-MS in quantitative analysis,and provides a convenient method for the quantitation of proteases in clinical diagnosis.     

Level Statistics Crossover of Chiral Surface States in a Three-Dimensional Quantum Hall System

Recent experiments have demonstrated the realization of the three-dimensional quantum Hall effect in highly anisotropic crystalline materials, such as ZrTe|_5 and BaMnSb_2. Such a system supports chiral surface states in the presence of a strong magnetic field, which exhibit a one-dimensional metal-insulator crossover due to suppression of surface diffusion by disorder potential. We study the nontrivial surface states in a lattice model and find a wide crossover of the level-spacing distribution through a semi-Poisson distribution. We also discover a nonmonotonic evolution of the level statistics due to the disorder-induced mixture of surface and bulk states.     

Steam-assisted crystallization of highly dispersed nanosized hierarchical zeolites from solid raw materials and their catalytic performance in lactide production

A solvent-free route based on solid raw materials affords higher product yield and lower waste production compared to the traditional hydrothermal synthesis. However, the as-made zeolites usually present blocky aggregation states, limiting their mass transfer and exposure of active sites in catalytic applications. Herein, highly dispersed nanosized hierarchical Beta zeolites with varied Si/Al ratios were prepared via steam-assisted crystallization from ball-milled solid raw materials. Thanks to the sufficient mixing of solid raw materials and favorable migration of solid mixture, nanosized Beta zeolites are obtained that are assembled from nanoparticles (∼15 nm) and possess abundant interconnected intraparticle mesopores. The strategy can also be extended to synthesize nanosized hierarchical ZSM-5 zeolites. The as-prepared Beta zeolite (Si/Al = 10) exhibits outstanding catalytic performance in conversion of lactic acid to lactide (as high as 77.5% in yield). This work provides avenues for simple and cost-efficient synthesis of highly dispersed nanosized hierarchical zeolites, promising their important catalytic applications.

A cost-effective synthesis strategy based on steam-assisted crystallization from ball-milled solid raw materials is developed to prepare a highly dispersed nanosized hierarchical Beta zeolite for conversion of lactic acid (LA) to lactide (LT).     

Anisotropic Superconducting Properties of Kagome Metal CsV_3Sb_5

We systematically measure the superconducting(SC) and mixed state properties of high-quality CsV_3 Sb_5 single crystals with T_c～3.5 K.We find that the upper critical field H_(c2)(T) exhibits a large anisotropic ratio of H_(c2)~(ab)/H_(c2)~c～9 at zero temperature and fitting its temperature dependence requires a minimum two-band effective model.Moreover,the ratio of the lower critical field,H_(c1)~(ab)/H_(c1)~c,is also found to be larger than 1,which indicates that the in-plane energy dispersion is strongly renormalized near Fermi energy.Both H_(c1)(T) and SC diamagnetic signal are found to change little initially below T_c～3.5 K and then to increase abruptly upon cooling to a characteristic temperature of ～2.8 K.Furthermore,we identify a two-fold anisotropy of in-plane angular-dependent magnetoresistance in the mixed state.Interestingly,we find that,below the same characteristic T～2.8 K,the orientation of this two-fold anisotropy displays a peculiar twist by an angle of 60° characteristic of the Kagome geometry.Our results suggest an intriguing superconducting state emerging in the complex environment of Kagome lattice,which,at least,is partially driven by electron-electron correlation.     

纳米氧化镱对熔融石英析晶动力学机制的影响

本文研究引入纳米氧化镱对熔融石英析晶机制及动力学过程的影响.通过X射线衍射仪(XRD)测试结果分析了纳米氧化镱的引入对熔融石英陶瓷析晶率的影响,采用动力学方法分析了纳米氧化镱的引入对熔融石英陶瓷析晶机制的影响,同时探讨了其等温析晶动力学过程.研究表明,熔融石英陶瓷的晶粒向二维兼有一维及三维的方式生长,引入纳米氧化镱的熔...