基于LSTM的浮选钼精矿品位软测量模型

战略性稀有金属钼矿品位低,组分复杂、嵌布粒度细等特点,其有价金属分离回收难。浮选作为微细粒钼矿分离回收的主要选矿方法之一,其浮选钼精矿品位一直是选厂的关键性产品指标。国内大多数选厂采取轮班制采样,人工化验得到精矿品位结果,但此方式严重滞后于浮选工艺,难以满足对生产过程进行实时监测和操作指导。LSTM是一种特殊的循环神经网络,引入门机制有效的传递或选择性遗忘长时间序列中的信息,解决RNN中的长期依赖、梯度消失和爆炸问题。本文分析整理东坡选厂中各平台源数据,结合选厂浮选工艺及机理,筛选出多个影响浮选钼精矿品位的变量作为模型输入;将输入变量进行异常值判定,缺失值填充和数据降噪等数据预处理,建立高质量浮选钼精矿品位数据库;软测量模型采用PyCharm软件编码,使用BatchNorm批量规范化处理样本数据,加入Dropout正则化防止过拟合,建立基于LSTM的浮选钼精矿品位软测量模型,通过前向传播算法更新神经网络结构参数,并于Linear模型和CNN模型的预测性能指标结果比较。结果表明：基于LSTM的浮选钼精矿品位软测量模型预测准确度高,样本数据误差波动平稳,浮动范围小,模型泛化能力强,模型平均绝对百分比误差MAPE为1.13%,均方根误差RMSE为0.7049%,决定系数R2为0.8763,实现了浮选钼精矿品位的在线预测。     

最大泡压法测表面张力等温线的数据处理方法比较*

对乙酸、丙酸、正丁酸、2-甲基丁酸、3-甲基丁酸、正戊酸、正己酸、乙醇、丙醇、异丙醇、正丁醇、异丁醇、1,2-丙二醇等13种常用试剂在25 ℃下的表面张力数据拟合方法进行了比较,分析了图解法处理数据及多项式、一阶指数函数、幂函数、Shishkovsky经验公式拟合数据的优缺点。指出Shishkovsky经验公式拟合结果准确,受数据样本量影响小,是理想的表面张力数据拟合方法。     

Development and Molecular Understanding of a Pd-Catalyzed Cyanation of Aryl Boronic Acids Enabled by High-Throughput Experimentation and Data Analysis

A synthetic method for the palladium-catalyzed cyanation of aryl boronic acids using bench stable and non-toxic N-cyanosuccinimide has been developed. High-throughput experimentation facilitated the screen of 90 different ligands and the resultant statistical data analysis identified that ligand σ-donation, π-acidity and sterics are key drivers that govern yield. Categorization into three ligand groups – monophosphines, bisphosphines and miscellaneous – was performed before the analysis. For the monophosphines, the yield of the reaction increases for strong σ-donating, weak π-accepting ligands, with flexible pendant substituents. For the bisphosphines, the yield predominantly correlates with ligand lability. The applicability of the designed reaction to a wider substrate scope was investigated, showing good functional group tolerance in particular with boronic acids bearing electron-withdrawing substituents. This work outlines the development of a novel reaction, coupled with a fast and efficient workflow to gain understanding of the optimal ligand properties for the design of improved palladium cross-coupling catalysts.     

金团簇二十面体结构融合过程中其催化活性的演变

近年来,由有机配体保护的原子精确金属团簇在合成方面已取得了重要进展,其独特的原子结构对一些化学反应产生独特的催化效果.原子精确的团簇催化剂明显不同于纳米颗粒催化剂和单原子催化剂,是一种关联均相和多相的、原子数目确定、尺寸均一、结构精确的新型催化剂.从原子尺度上精确构筑团簇催化剂,探究亚纳米尺度的微观结构对催化性能的影响,为常规催化剂所未能解决的关键科学问题提供解决的机会,为在分子尺度上揭示催化作用机制以及准确关联催化剂结构与催化性能提供新的研究体系,具有重要的科学研究意义.本文设计和使用了三种结构精确的金团簇催化剂,即Au25(PPh3)10(SC2H4Ph)5Cl2,Au38(SC2H4Ph)24和Au25(SC2H4Ph)18,分别由二十面体结构的Au13单元通过中心顶点融合、面融合、体相融合形成的(简写为Auvf、Auff和Aubf),详细研究了这三个金团簇催化剂在二十面体Au13单元的结构融合过程中,其催化活性的演变规律.在催化吡咯烷与O2反应制备γ-丁内酰胺反应中,金团簇催化剂的催化活性顺序为Aubf>Auff>Auvf,表明这三个金团簇中Au13单元的结构随着点、面、体的融合,其催化活性随之增加.同时研究发现,对于同一个Au团簇催化剂,其表面硫醇配体的烷基链越短,其催化活性越高,这主要是由于短链硫醇分子的空间位阻较小,吡咯烷分子更容易进入催化剂的金表面,接触到活性位点,进行催化反应.实验表明,三个团簇金原子均带正电荷,正价金物种可能是催化吡咯烷与O2反应的催化活化物种.研究发现,Aubf团簇表面的活性位数目高于Auff和Auvf团簇的,因此Aubf的催化活性最高;同时,团簇表面配体的烷基链越短,其表面活性位数目也越多,这也进一步解释了表面硫醇配体的烷基链越短,其相应的金团簇催化剂的催化活性越高的原因.吡咯烷与O2在金团簇上反应的可能路径为O2在Au活性位上裂解的O原子和吡咯烷β-H转移至Au活性位的β-H反应脱水后形成亚胺,亚胺经过水解进一步氧化得到产物.这项研究将为在原子层次上调变金属团簇催化剂的结构进而改变其催化性能提供新的思路,对精准设计和构筑高效催化剂具有一定的科学指导意义.     

In Silico Analysis of P450s and Their Role in Secondary Metabolism in the Bacterial Class Gammaproteobacteria

The impact of lifestyle on shaping the genome content of an organism is a well-known phenomenon and cytochrome P450 enzymes (CYPs/P450s), heme-thiolate proteins that are ubiquitously present in organisms, are no exception. Recent studies focusing on a few bacterial species such as Streptomyces, Mycobacterium, Cyanobacteria and Firmicutes revealed that the impact of lifestyle affected the P450 repertoire in these species. However, this phenomenon needs to be understood in other bacterial species. We therefore performed genome data mining, annotation, phylogenetic analysis of P450s and their role in secondary metabolism in the bacterial class Gammaproteobacteria. Genome-wide data mining for P450s in 1261 Gammaproteobacterial species belonging to 161 genera revealed that only 169 species belonging to 41 genera have P450s. A total of 277 P450s found in 169 species grouped into 84 P450 families and 105 P450 subfamilies, where 38 new P450 families were found. Only 18% of P450s were found to be involved in secondary metabolism in Gammaproteobacterial species, as observed in Firmicutes as well. The pathogenic or commensal lifestyle of Gammaproteobacterial species influences them to such an extent that they have the lowest number of P450s compared to other bacterial species, indicating the impact of lifestyle on shaping the P450 repertoire. This study is the first report on comprehensive analysis of P450s in Gammaproteobacteria.     

Optimization of Vacuum-Microwave-Assisted Extraction of Natural Polyphenols and Flavonoids from Raw Solid Waste of the Orange Juice Producing Industry at Industrial Scale

Orange pomace (OP) is a solid waste produced in bulk as a byproduct of the orange juice industry and accounts for approximately 50% of the quantity of the fruits processed into juice. In numerous literature references there is information about diverse uses of orange pomace for the production of high-added-value products including production of natural antioxidant and antimicrobial extracts rich in polyphenols and flavonoids which can substitute the hazardous chemical antioxidants/antimicrobials used in agro-food and cosmetics sectors. In this work and for the first time, according to our knowledge, the eco-friendly aqueous vacuum microwave assisted extraction of orange pomace was investigated and optimized at real industrial scale in order to produce aqueous antioxidant/antimicrobial extracts. A Response Surface Optimization methodology with a multipoint historical data experimental design was employed to obtain the optimal values of the process parameters in order to achieve the maximum rates of extraction of OP total polyphenols and/or total flavonoids for economically optimum production at industrial scale. The three factors used for the optimization were: (a) microwave power (b) water to raw pomace ratio and (c) extraction time. Moreover, the effectiveness and statistical soundness of the derived cubic polynomial predictive models were verified by ANOVA.     

Crowned Macrocycles Containing Two Pyrrolo[1,2-a] Indoles Created By Intramolecular Fusion

Heterocyclic fused-ring systems are of utmost importance because of their presence in many natural products with biological activity. Pyrroloindoles are tricyclic heterocycles that are present in various bioactive and medicinally valuable compounds. Herein, we report the synthesis of phenylene-bridged bis-pyrrolo[1,2-a]indole crowned macrocycles 1 – 3 in which the pyrrolo[1,2-a]indole moieties were formed via intramolecular fusion. The macrocycles were thoroughly characterized by 1D and 2D NMR, HRMS and X-ray crystallographic studies. The X-ray structure revealed that the two pyrrolo[1,2-a]indole moieties were parallel to each other, and one pyrrolo[1,2-a]indole unit was deviated by an angle of 9.54° while the other pyrrolo[1,2-a]indole unit was deviated by an angle of 12.0° from the mean plane defined by 28 core atoms. The macrocycles 1 – 3 absorb in the visible region and readily undergo oxidations because of their electron rich nature. The macrocycles 1 – 3 upon treatment with trifluoroacetic acid (TFA) generates the corresponding cation radicals 1 – 3 ^.+ which were stable in the open air for a week. The cation radicals 1 – 3 ^.+ absorb strongly in the NIR region and the experimental observations on crowned macrocycles 1 – 3 were corroborated by DFT and TD-DFT studies.     

Data fusion methodologies for food and beverage authentication and quality assessment – A review

The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment.     

Thermodynamic properties of xanthone: Heat capacities,phase-transition properties,and thermodynamic-consistency analyses using computational results

Heat capacities and phase-transition properties for xanthone (IUPAC name 9H-xanthen-9-one and Chemical Abstracts registry number [90-47-1]) are reported for the temperature range 5 < T/K < 524. Statistical calculations were performed and thermodynamic properties for the ideal gas were derived based on molecular geometry optimization and vibrational frequencies calculated at the B3LYP/6-31+G(d,p) level of theory. These results are combined with sublimation pressures from the literature to allow critical evaluation of inconsistent enthalpies of sublimation for xanthone, also reported in the literature. Literature values for the enthalpy of combustion of xanthone are re-assessed, a revision is recommended for one result, and a new value for the enthalpy of formation of the ideal gas is derived. Comparisons with thermophysical properties reported in the literature are made for all other reported and derived properties, where possible.     

Multivariate analysis of extremely large ToFSIMS imaging datasets by a rapid PCA method

Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth profiles in X‐ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and secondary ion mass spectrometry (SIMS). These methods have proved equally useful in fundamental studies as in applied work where speed of interpretation is very valuable. Until now these methods have been difficult to apply to very large datasets such as spectra associated with 2D images or 3D depth‐profiles. Existing algorithms for computing PCA matrices have been either too slow or demanded more memory than is available on desktop PCs. This often forces analysts to ‘bin’ spectra on much more coarse a grid than they would like, perhaps even to unity mass bins even though much higher resolution is available, or select only part of an image for PCA analysis, even though PCA of the full data would be preferred. We apply the new ‘random vectors’ method of singular value decomposition proposed by Halko and co‐authors to time‐of‐flight (ToF)SIMS data for the first time. This increases the speed of calculation by a factor of several hundred, making PCA of these datasets practical on desktop PCs for the first time. For large images or 3D depth profiles we have implemented a version of this algorithm which minimises memory needs, so that even datasets too large to store in memory can be processed into PCA results on an ordinary PC with a few gigabytes of memory in a few hours. We present results from ToFSIMS imaging of a citrate crystal and a basalt rock sample, the largest of which is 134GB in file size corresponding to 67 111 mass values at each of 512 × 512 pixels. This was processed into 100 PCA components in six hours on a conventional Windows desktop PC. © 2015 The Authors. Surface and Interface Analysis published by John Wiley & Sons Ltd.