基于激光诱导击穿光谱(LIBS)的煤灰熔点快速检测

炉内结渣是影响火电机组和气化工艺可靠运行的关键因素之一,准确预测灰熔点可以提前调整炉膛出口温度以避免结渣。本论文采用激光诱导击穿光谱（LIBS）采集煤灰样中金属元素的光谱,分别建立煤灰中的金属元素的谱线强度与煤灰熔点的随机森林模型、支持向量机回归模型和线性回归模型,直接预测煤灰熔点温度。采用基于马氏距离(MD)的异常数据剔除算法和基于稀疏矩阵的基线估计与降噪算法（BEADS）,对粉煤灰样的全光谱数据进行了预处理。随机森林模型对粉煤灰熔点的预测平均相对误差（MRE）为54.74%,支持向量机回归模型的预测平均相对误差为60.08%,而线性回归模型的预测平均相对误差达到了9.78%。研究结果表明,线性回归模型对煤灰熔点的预测结果更准确。     

A general electron donor–acceptor complex for photoactivation of arenes via thianthrenation

General photoactivation of electron donor–acceptor (EDA) complexes between arylsulfonium salts and 1,4-diazabicyclo[2.2.2]octane with visible light or natural sunlight was discovered. This practical and efficient mode enables the production of aryl radicals under mild conditions, providing an unrealized opportunity for two-step para-selective C–H functionalization of complex arenes. The novel mode for generating aryl radicals via an EDA complex was well supported by UV-vis absorbance measurements, nuclear magnetic resonance titration experiments, and density functional theory (DFT) calculations. The method was applied to the regio- and stereo-selective arylation of various N-heterocycles under mild conditions, yielding an assembly of challengingly linked heteroaryl–(hetero)aryl products. Remarkably, the meaningful couplings of bioactive molecules with structurally complex drugs or agricultural pharmaceuticals were achieved to display favorable in vitro antitumor activities, which will be of great value in academia or industry.

General photoactivation of EDA complexes between arylsulfonium salts and 1,4-diazabicyclo[2.2.2]octane was discovered. This practical mode enables the generation of aryl radicals for C–H functionalization of arenes.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

圆柱类构件超声相控阵聚焦模型

在利用平面相控阵超声换能器对圆柱类构件检测时,受曲界面结构引起的入射波和回波时延的影响,扫描声束的波阵面产生弯曲,在利用传统迭代遍历算法计算延迟时间时效率低,无法发挥相控阵换能器检测优势。针对上述问题,建立了一种基于圆柱类构件特征和耦合介质特性的超声相控阵扫描成像的聚焦模型。该模型基于换能器、耦合介质、圆柱类构件材料特性和几何关系以及声线模型和折射定律,建立了耦合介质及被检构件的声速、曲面曲率半径、阵列与曲面间的距离等关联的延迟时间聚焦控制模型。利用该模型计算出的延时时间,对各阵元发射时间进行控制,从而实现扫描声束的聚焦。该文以液体和有机玻璃制介质楔块为例,对圆柱钢曲面的相控阵声束聚焦进行了仿真实验,结果表明该文方法计算效率显著提升,同时声束可以在预设位置实现聚焦,验证了该模型在计算效率上的优势与有效性。     

晶格畸变检测仪研究碳化硅晶片中位错缺陷分布

利用晶格畸变检测仪研究了SiC晶片位错分布情况,通过对熔融KOH腐蚀后的SiC晶片进行全片或局部扫描,从而得到完整SiC晶片或局部区域的位错分布.与LEXT OLS40003D激光共聚焦显微镜扫描腐蚀图进行比较,晶格畸变检测仪扫描腐蚀图可以将晶片上位错腐蚀坑信息完全呈现出来,且根据腐蚀坑呈现的颜色及尺寸大小,可以分辨出...     

Weak Graph Map Homotopy and Its Applications∗

The authors introduce a notion of a weak graph map homotopy (they call it M-homotopy), discuss its properties and applications. They prove that the weak graph map homotopy equivalence between graphs coincides with the graph homotopy equivalence defined by Yau et al in 2001. The difference between them is that the weak graph map homotopy transformation is defined in terms of maps, while the graph homotopy transformation is defined by means of combinatorial operations. They discuss its advantages over the graph homotopy transformation. As its applications, they investigate the mapping class group of a graph and the 1-order MP-homotopy group of a pointed simple graph. Moreover, they show that the 1-order MP-homotopy group of a pointed simple graph is invariant up to the weak graph map homotopy equivalence.     

Designed Syntheses of Three {Ni6PW9}-Based Polyoxometalates,from Isolated Cluster to Cluster-Organic Helical Chain

Three new hexa-Ni-substituted Keggin-type polyoxometalates (POMs), [Ni₆(OH)₃- (DACH)₃(H₂O)₆(PW₉O₃₄)]·31H₂O (1), [Ni(DACH)₂][Ni₆(OH)₃(DACH)₃(HMIP)₂(H₂O)₂(PW₉O₃₄)]·56 H₂O (2), and [Ni(DACH)₂][Ni₆(OH)₃(DACH)₂(AP)(H₂O)₅(PW₉O₃₄)]·2H₂O (3) (DACH = 1,2-Diami- nocyclohexane, MIP = 5-Methylisophthalate, AP = Adipate) were successfully made in the presence of DACH under hydrothermal conditions. 1 is an isolated hexa-Ni-substituted Keggin unit decorated by DACH. In order to further construct POM cluster-organic frameworks (POMCOFs) on the basis of 1, by analyzing the steric hindrances and orientations of the POM units, the rigid HMIP and flexible AP ligands were successively incorporated, and another anionic monomeric POM 2 and the new 1D POM cluster organic chain (POMCOC) 3 were obtained. HMIP ligand still acts as a decorating group on the Ni₆ core of 2 but results in the different spatial arrangement of the {Ni₆PW₉} units. AP ligands in 3 successfully bridge adjacent isolated POM cluster units to 1D POMCOC with left-hand helices. The AP in 3 is the longest aliphatic carboxylic acid ligand in POMs, and the 1D POM cluster-AP helical chain represents the first 1D POMCOC with a helical feature.     

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.     

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.     

Structural and Bonding Properties of AlnC4-/0 (n=2-4) Clusters:Anion Photoelectron Spectroscopy and Theoretical Calculations

We measured the photoelectron spectra of AlnC4-(n=2-4) clusters by using size-selected anion photoelectron spectroscopy.The structures of AlnC4-/0 (n=2-4) clust...