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.     

埋地热油管道正常运行的数值模拟研究

对高凝原油管道输送的水力热力问题进行分析研究,掌握管线运行规律,保证管线安全经济运行有着重要意义.本文建立了埋地热油管道正常运行的数学模型,采用非结构化网格和有限容积法对该问题进行了研究,计算结果与实验测量值吻合良好.     

Synthesis,Structure and Theoretical Calculation of Metal Coordination Polymers with Pyrazine-2,3-dicarboxylic Acid and 3-(2-Pyridyl)pyrazole as Co-ligands

A new 2D metal coordination polymer(MCP),[Mn(pzdc)_(0.5)(L)]_n(1,pzdc=pyrazine-2,3-dicarboxylic acid,HL=3-(2-pyridyl)pyrazole),was synthesized under hydrothermal conditions and characterized by single-crystal X-ray diffraction,powder XRD,FT-IR,TG,fluorescence and elemental analysis techniques.Pale yellow crystals crystallize in orthorhombic system,space group Fdd2 with a=11.2368(6),b=38.280(2),c=10.5682(6) A,V=4545.9(4) A~3,C_(11)H_7MnN_4O_2,M_r=282.15,D_c=1.649 g/cm~3,μ(MoKα)=1.159 mm~(-1),F(000)=2272,Z=16,the final R=0.0613 and wR=0.1773 for 2856 observed reflections(I 2σ(I)).It shows a two-dimensional network structure and is further assembled into a three-dimensional supramolecular framework via hydrogen bonds and abundant π-π interactions.In addition,we analyzed natural bond orbital(NBO) of 1 in using the PBE0/LANL2DZ method established in Gaussian 03 Program.There is obvious covalent interaction between the coordinated atoms and Mn(Ⅱ) ions.     

氧化镍纳米晶体的制备及其过程分析

为了开发一种新型纳米氧化镍催化剂,能有效地应用于生物质气化过程中去除焦油,本文采用均匀沉淀法成功地制备了纳米氧化镍晶体,并利用TGA、FTIR、XRD、BET、YEM等分析手段对前驱体和产品的性能进行了表征.同时,对前驱体的分解过程进行了全面的分析.分析结果表明前驱体是水合碱式碳酸镍,其分子式为NiCO3·Ni(OH)2·nH2O,它能在360℃下完全分解转化为纳米NiO,同时煅烧条件对合成纳米NiO的晶体粒径影响很大.实验证实所得纳米NiO颗粒呈球形,分散性好,纯度较高,属立方晶系结构,平均粒径约为7.5nm,其BET表面积为187.98m2/g,这显示纳米NiO晶体具有作为高效催化材料的应用可行性.     

低温制备≥99.5%多晶氧化铝陶瓷

本文通过引入稀土氧化物Y2O3、Tm2O3为烧结助剂低温制备了氧化铝含量大于99.5;的多晶氧化铝陶瓷.实验表明:稀土氧化物的加入能够明显降低99.5;多晶氧化铝陶瓷的烧结温度,提高致密度.Y2O3、Tm2O3混合烧结助剂与单一稀土氧化物的烧结助剂相比能够明显抑制晶粒的生长,促进晶粒的均匀发育.当Y2O3+Tm2O3的含量为0.3;质量分数时,99.5;多晶氧化铝陶瓷的相对密度可达99.2;理论密度,抗弯强度为533MPa,显微硬度为17.2GPa.陶瓷断裂主要以穿晶断裂为主.     

Immobilized palladium on surface-modified Fe3O4/SiO2 nanoparticles: as a magnetically separable and stable recyclable high-performance catalyst for Suzuki and Heck cross-coupling reactions

A palladium-based catalyst (Fe₃O₄/SiO₂/HPG–OPPh₂–PNP) supported on chlorodiphenylphosphine-functionalized magnetic nanoparticles was successfully prepared from Fe₃O₄/SiO₂ with sequential attachment of glycerol and chlorodiphenylphosphine, followed by treatment of an ethanolic solution of palladium chloride with hydrazine. The as-prepared catalyst was characterized by ICP-AES, FTIR, XRD, SEM, and TEM. The Fe₃O₄/SiO₂/HPG–OPPh₂–PNP was found as a magnetically separable and highly active catalyst for Suzuki coupling reactions of aryl iodides, bromides, and chlorides as well as Heck reactions of aryl iodides and bromides. Under appropriate conditions, all reactions afforded the desired products in moderate to excellent yields. Moreover, this catalyst can be easily recovered by using a magnetic field and directly reused for at least six cycles without significant loss of its activity.     

Recent advances in theoretical models of respiratory mechanics

As an important branch of biomedical engineering, respiratory mechanics helps to understand the physiology of the respiratory system and provides fundamental data for developing such clinical technologies as ventilators. To solve different clinical problems, researchers have developed numerous models at various scales that describe biological and mechanical properties of the respiratory system. During the past decade, benefiting from the continuous accumulation of clinical data and the dramatic progress of biomedical technologies (e.g. biomedical imaging), the theoretical modeling of respiratory mechanics has made remarkable progress regarding the macroscopic properties of the respiratory process, complexities of the respiratory system, gas exchange within the lungs, and the coupling interaction between lung and heart. The present paper reviews the advances in the above fields and proposes potential future projects.