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.     

基于SOANet的圆锥角膜辅助诊断

亚临床期圆锥角膜(subclinical keratoconus, subkc)发病隐匿,现有医疗设备诊断存在局限性,所以提出一种诊断亚临床期圆锥角膜的检测方法是十分必要的。有研究发现圆锥角膜(Keratoconus, kc)力学性能的改变早于形态学,因此从角膜生物力学的角度筛查亚临床期的圆锥角膜更加符合临床实际。本文运用角膜生物力学特征,以点云数据作为网络输入数据,将SO-Net (self-organizing network)和自注意力(self-attention, SA)机制结合构建SOANet,对圆锥角膜、亚临床期圆锥角膜和正常角膜进行分类。首先,利用可视化生物力学分析仪(corneal visualization Scheimpflug technology, Corvis ST)拍摄角膜受力形变视频,对其进行处理得到点云数据集,接着对点云数据进行增强处理,使3种类型的角膜数据量分布均衡。然后按照3∶1的比例划分训练集和测试集,分别对角膜进行二分类和三分类。最终模型在二分类和三分类测试集上的准确率分别达到98.3%和91.26%,即有效识别亚临床期圆锥角膜和圆锥角膜。实验...     

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).     

微流控光脉冲调制器

为了解决常见光调制器偏振依赖或结构复杂的问题,本文基于微流控光学提出一种可控光脉冲调制器。利用基于T形结产生的离散液滴和全反射原理的微流控光开关,将连续光变换成数字脉冲信号,并通过调节液滴的长度和生成速率调制光脉冲的宽度和频率。所提微流控光脉冲调制器具有结构简单、插入损耗低、消光比高、易集成的优点。微流控光脉冲调制器的流场与光场特性被分析,结构被优化。研究结果显示：该光脉冲调制器的消光比为17.74 dB,插入损耗为0.49 dB。     

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.     

一种在抢险抗灾中保障特殊用户通信畅通的无线接入网络应急方案——GSM用户接入等级控制

在某些特殊情况下,移动运营商希望能够实现用户的分级接入网络,以保障一些特殊用户的通信畅通。尤其是在地震、洪灾等自然灾害造成了部分地区通信严重受损的情况下,保障特殊用户的通信顺畅就显得更加重要了。针对这种需求,本文重点介绍了接入等级控制的方案,而且还将此方案与增强多级优先和抢占的方案在实现难度和最终效果等方面进行了简单的对比。     

Single-Stage Extraction and Separation of Co2+ from Ni2+ Using Ionic Liquid of [C4H9NH3][Cyanex 272]

The purpose of this study was to optimize the extraction conditions for separating Co²⁺ from Ni²⁺ using N-butylamine phosphinate ionic liquid of [C₄H₉NH₃][Cyanex 272]. A Box–Behnken design of response surface methodology was used to analyze the effects of the initial pH, extraction time, and extraction temperature on the separation factor of Co²⁺ from sulfuric acid solution containing Ni²⁺. The concentrations of Co²⁺ and Ni²⁺ in an aqueous solution were determined using inductively coupled plasma-optical emission spectrometry. The optimized extraction conditions were as follows: an initial pH of 3.7, an extraction time of 55.8 min, and an extraction temperature of 330.4 K. The separation factor of Co²⁺ from Ni²⁺ under optimized extraction conditions was 66.1, which was very close to the predicted value of 67.2, and the error was 1.7%. The equation for single-stage extraction with high reliability can be used for optimizing the multi-stage extraction process of Co²⁺ from Ni²⁺. The stoichiometry of chemical reaction for ion-exchange extraction was also investigated using the slope method.     

低强度激光辐照对蝗虫活性的影响

为研究低强度激光辐照对蝗虫活动能力的影响,以减少农药的使用量和降低农药的浓度,选择大功率连续型近红外半导体二极管激光器,针对3龄至4龄期东亚飞蝗蝻虫头部位置,在距离激光发光面4cm处,进行2s和4s的辐照试验,分别观察比较辐照前后蝗虫的活性和活性降低程度．试验结果表明,辐照前,蝗虫具有较高的活性,辐照后蝗虫的活性降低,并逐渐趋于一致性;辐照时间越长,蝗虫的活性降低程度越高。说明低强度近红外激光辐照蝗虫头部位置能明显抑制其活动能力。