Exploratory Data Analysis Applied in Mapping Multi-element Soil Geochemical Anomalies for Drill Target Definition:A Case Study from the Unpha Layered Non-magmatic Hydrothermal Pb-Zn Deposit,DPR Korea

A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.

Geographical origin identification of winter jujube(Ziziphus jujuba Dongzao')by using multi-element fingerprinting with chemometrics

Winter jujube(Ziziphus jujuba'Dongzao')is greatly appreciated by consumers for its excellent quality,but brand infringement frequently occurs in the market.Here,we first determined a total of 38 elements in 167 winter jujube samples from the main winter jujube producing areas of China by inductively coupled plasma mass spectrometer(ICP-MS).As a result,16 elements(Mg,K,Mn,Cu,Zn,Mo,Ba,Be,As,Se,Cd,Sb,Ce,Er,Tl,and Pb)exhibited significant differences in samples from different producing areas.Supervised linear discriminant analysis(LDA)and orthogonal projection to latent structures discriminant analysis(OPLS-DA)showed better performance in identifying the origin of samples than unsupervised principal component analysis(PCA).LDA and OPLS-DA had a mean identification accuracy of 87.84 and 94.64%in the testing set,respectively.By using the multilayer perceptron(MLP)and C5.0,the prediction accuracy of the models could reach 96.36 and 91.06%,respectively.Based on the above four chemometric methods,Cd,Tl,Mo and Se were selected as the main variables and principal markers for the origin identification of winter jujube.Overall,this study demonstrates that it is practical and precise to identify the origin of winter jujube through multi-element fingerprint analysis with chemometrics,and may also provide reference for establishing the origin traceability system of other fruits.

Near-Infrared Spectroscopy Combined with Partial Least Squares Discriminant Analysis Applied to Identification of Liquor Brands

The identification of liquor brands is very important for food safety. Most of the fake liquors are usually made into the products with the same flavor and alcohol content as regular brand, so the identification for the liquor brands with the same flavor and the same alcohol content is essential. However, it is also difficult because the components of such liquor samples are very similar. Near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was applied to identification of liquor brands with the same flavor and alcohol content. A total of 160 samples of Luzhou Laojiao liquor and 200 samples of non-Luzhou Laojiao liquor with the same flavor and alcohol content were used for identification. Samples of each type were randomly divided into the modeling and validation sets. The modeling samples were further divided into calibration and prediction sets using the Kennard-Stone algorithm to achieve uniformity and representativeness. In the modeling and validation processes based on PLS-DA method, the recognition rates of samples achieved 99.1% and 98.7%, respectively. The results show high prediction performance for the identification of liquor brands, and were obviously better than those obtained from the principal component linear discriminant analysis method. NIR spectroscopy combined with the PLS-DA method provides a quick and effective means of the discriminant analysis of liquor brands, and is also a promising tool for large-scale inspection of liquor food safety.

Discriminant Analysis of Liquor Brands Based on Moving-Window Waveband Screening Using Near-Infrared Spectroscopy

Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.

Influence of increased shares on the performance of liquor listed companies:A factor-based analysis

With the gradual deepening of the reform of the shareholding system,more and more shareholders of listed companies have taken measures to increase their shareholdings to absorb capital,while at the same time achieving the purpose of delivering good news to the market.This article uses the liquor industry as an analysis sample to build six categories of enterprise performance index evaluation systems for debt solvency,development capability,operating capability,per share capability,cash flow capability and profitability.Through factor analysis,it has been shown that the increase in shares of liquor listed companies can improve the performance of enterprises to a certain extent,but the effect of the increase in shares is also affected by other factors such as the size of the enterprise,the operation and management of the company,and the image of the product market.According to the empirical conclusion,it is proposed that on the one hand,the company should increase its shareholdings reasonably according to the company’s own situation.On the other hand,it needs to focus on the current problems of the enterprise and properly solve the current dilemma of the enterprise.Finally,according to the degree of impact of various indicators involved in the empirical test on corporate performance,it is believed that liquor listed companies need to focus on optimizing corporate asset structure and improving product sales,and on the basis of improving profitability and asset return,they should pay attention to corporate cash flow.

Geochemical analysis of marine sediments using fused glass disc by X-ray fluorescence spectrometry

A method was developed for content determination of Na, Mg, A1, Si, P,S, C1, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Nb, Zr, Y, Sr, Rb, Ba, La and Ce etc. covering 26 major, minor, and trace elements in marine sediment samples using fused glass disc by X-ray Fluorescence spectrometry. Calibration was made using marine sediment certified reference materials and the synthetic standard samples prepared by mixing several marine sediments with stream sediment and carbonate standard samples in different proportions. The matrix effect was corrected using theoretical alpha coefficients, experience coefficients and the scattered radiation as the internal standard （for the trace elements）. The accuracy of the method was evaluated by analysis of certified reference materials GBW07314, GBW07334 and GSMS6. The results are in good agreement with the certified values of the standards with RSD less than 2.60%, except for Y, Cr, Ga, Ce, La, Nb, Rb, and V with RSD less than 9.0% （n=12）.

A DDoS Attack Information Fusion Method Based on CNN for Multi-Element Data

Traditional distributed denial of service(DDoS)detection methods need a lot of computing resource,and many of them which are based on single element have high missing rate and false alarm rate.In order to solve the problems,this paper proposes a DDoS attack information fusion method based on CNN for multi-element data.Firstly,according to the distribution,concentration and high traffic abruptness of DDoS attacks,this paper defines six features which are respectively obtained from the elements of source IP address,destination IP address,source port,destination port,packet size and the number of IP packets.Then,we propose feature weight calculation algorithm based on principal component analysis to measure the importance of different features in different network environment.The algorithm of weighted multi-element feature fusion proposed in this paper is used to fuse different features,and obtain multi-element fusion feature(MEFF)value.Finally,the DDoS attack information fusion classification model is established by using convolutional neural network and support vector machine respectively based on the MEFF time series.Experimental results show that the information fusion method proposed can effectively fuse multi-element data,reduce the missing rate and total error rate,memory resource consumption,running time,and improve the detection rate.

Analysis of Factors Affecting the Development of Competitive Level of Mountain Outdoor Sports

Objective: based on the analysis to the elements affecting the results of China's national team in the 2010 mountain outdoor sports adventure challenge race in Abu Dhabi, some theoretical and practical basis on which suggestions are provided on further promoting China's mountain outdoor sports results and the competitive level are given.Subjects: athletic performance of the top six teams and China's national team in 2010 mountain outdoor sports and athletic performance;Methods: using expert interviews, reference and data, mathematical statistics, analyze the athletic performance of the top six teams and China's national team in 2010 mountain outdoor sports and athletic performance on foot and bicycle projects on class projects with the world's top mountain outdoor big gap between sports teams;Result: there are big gaps between China's mountain outdoor sports teams and foreign teams on projects like footing and bicycling;Conclusion: Although in recent years, our mountain outdoor sports performance has been greatly improved, but the large gap do exist on foot and bicycle projects. so these projects need strengthening .

Comparison of Algorithms for an Electronic Nose in Identifying Liquors

When the electronic nose is used to identify different varieties of distilled liquors, the pattern recognition algorithm is chosen on the basis of the experience, which lacks the guiding principle. In this research, the different brands of distilled spirits were identified using the pattern recognition algorithms （principal component analysis and the artificial neural network）. The recognition rates of different algorithms were compared. The recognition rate of the Back Propagation Neural Network （BPNN） is the highest. Owing to the slow convergence speed of the BPNN, it tends easily to get into a local minimum. A chaotic BPNN was tried in order to overcome the disadvantage of the BPNN. The convergence speed of the chaotic BPNN is 75.5 times faster than that of the BPNN.

Multi-element analysis by ArF laser excited atomic fluorescence of laser ablated plumes： Mechanism and applications

A new multi-element analysis technique based on laser-excited atomic fluorescence was reviewed. However, the one-wavelength-one-transition constraint was overcome. Numerous elements were induced to fluoresce at a single excitation wavelength of 193 nm. This was possible provided that the analytes were imbedded in dense plumes, such as those produced by pulsed laser ablation. The underlying mechanism of the technique was explained and corroborated. Analytical applications to metals, plastics, ceramics and their composites were discribed. Detection limits in the ng/g range and mass limits of atto moles were demonstrated. Several real-world problems, including the analysis of paint coating for trace lead, the non-destructive analysis of potteries and ink, the chemical profiling of electrode plastic interfaces, and the analysis of ingestible lead colloids were discussed.

ON THE BLACK LIQUOR AND RECYCLE COOKING OF AS-AQ STRAW PULP

Thick black liquor, thin black liquor and solid state sodium hydroxide are added to the liquor treated by sulfur dioxide, then the blended liquor is used to recycle cooking of straw pulp. The black liquor, separated liquor and pulp of every cycles are analyzed respectively. Result shows that the content of lignin and organism in recycle black liquor and separated liquor increases faster in the first three cycles and then continues to increase slowly till four or five times, after that it trends to a stable state. The main organism separated from waste liquor of AS-AQ treated by sulfur dioxide is alkali-lignin, above 50% of total lignin in black liquor. The yield of pulp made from recycle cooking is steady, the hardness of pulp has a great improvement with recycle cooking. The brightness of pulp reduces correspondingly before bleaching, and after bleaching the brightness of pulp is relatively high and steady at the same sodium hypo chlorite dosage.

红枣蒸馏酒原酒发酵工艺优化及品质分析

以干红枣为原料发酵制备红枣果酒,进而蒸馏获得红枣蒸馏酒,对红枣原酒发酵工艺进行优化及品质分析,探讨酒精度和甲醇含量在发酵阶段和蒸馏阶段随发酵温度、干酵母接种量及初始糖度的变化规律。结果表明,在单因素试验基础上,通过拟合方程得到最佳红枣原酒发酵工艺为发酵温度24℃、酵母接种量0.71 g/L、初始糖度22°Bx。在此优化条件下,甲醇含量为1.71 g/L,酒精度为12.51%vol。在蒸馏过程中,酒精度从66.2%vol逐渐下降直至为0,而甲醇含量从1.69 g/L增加至最大值5.05 g/L,随后迅速降低。采用拟合方程可描述蒸馏酒液收样体积与酒液中酒精度及甲醇对应的函数关系。红枣蒸馏酒酒体澄清透明,具有明显的枣香,独特的风格,感官评分为92分,甲醇含量为1.90 g/L,酒精度54.7%vol,酒精回收率73.0%。

酱香型白酒不同轮次基酒风味特征分析

酱香型白酒由不同轮次基酒分别长期贮存、精心勾调而成,其酒体品质的好坏与基酒质量相关。该研究通过对酱香1~7轮次基酒理化指标、感官特征及风味成分进行分析,以探索不同轮次基酒的风味特征。结果表明,酒精度、总酸、总酯含量随轮次增加而逐渐降低;1、2轮次基酒粮香、酸香及酸涩味突出,3、4、5轮次基酒曲香、酱香、花香、水果香、醇甜感及柔和感突出,6、7轮次基酒焦糊香、苦味及后味突出;共检出风味成分142种,正交偏最小二乘法判别分析结合t检验筛选出重要差异变化成分20种;香气活性值分析筛选出风味贡献成分49种,其中具有统计学意义的特征风味成分13种,以酯类和醇类为主;偏最小二乘回归分析显示粮香、酸香及酸涩味与乙酸乙酯、2-甲基丁酸乙酯、丙醇、乙酸及异丁酸乙酯等呈正相关;酱香、曲香、花香、水果香等与乳酸乙酯、辛酸乙酯、2-十一酮及异戊酸乙酯等呈正相关;焦糊味、苦味及后味与异戊醛、乙醛、乙缩醛、苯乙醛、糠醛等呈正相关。该研究系统解析了酱香轮次基酒的风味特征,对酱香型白酒酒体设计、品质提升及风味创新具有重要意义。

赤藓糖醇玫瑰酒的研制及品质分析

以食用玫瑰、糯米酒为主要原料,赤藓糖醇作为甜味剂,通过单因素试验和正交试验对玫瑰酒的泡制工艺进行优化,并采用色差仪、能量分析仪、气相色谱-离子迁移谱(gas chromatography-ion mobility spectroscopy,GC-IMS)仪、全自动氨基酸分析仪对其色香味进行品质分析。结果表明,赤藓糖醇玫瑰酒最佳泡制工艺条件为酒精度25%vol、玫瑰花与酒泡制比例1∶150(g/mL)、赤藓糖醇添加量8%、泡制时间21 d。此工艺条件下,玫瑰酒感官总分最高,色差特征L值为36.09、a值为11.51、b值为5.05;每100 g玫瑰酒含能量910.70 kJ、蛋白质0.47 g、碳水化合物13.97 g;共有18种游离氨基酸,其中必需氨基酸有6种,占总氨基酸含量的13.45%;GC-IMS检测到62种挥发性成分,其中乙酸乙酯、丁酸乙酯、2-呋喃甲醇、香叶醇、3-甲基-1-丁醇、麦芽酚、β-蒎烯以及己醛占总挥发性物质的46.59%,是构成玫瑰酒的主要特征风味物质。试验得到的低糖型玫瑰酒品质优良、风味独特。

威士忌制备过程中理化指标及挥发性风味物质动态变化规律研究

威士忌是麦芽经糖化、发酵、蒸馏、桶陈等工序制成的蒸馏酒。为明确麦汁发酵及蒸馏过程中理化指标及挥发性风味物质的变化规律,该研究以蒸馏麦芽为原料、以威士忌专用商业酵母为发酵剂制备威士忌。采用高效液相色谱(HPLC)、气相色谱-质谱联用(GC-MS)等技术检测原酒浆发酵及蒸馏过程中理化指标和挥发性风味物质,并基于馏分关键风味物质(气味活度值(OAV)>1)进行主成分分析(PCA)和层次聚类分析(HCA)。结果表明,原酒浆中糖分、酒精度和主要酯类物质在第2天出现拐点;乙酸、丙酸和乳酸含量随着发酵时间增加,在第3天分别达到0.03 g/L、0.13 g/L和0.49 g/L。通过主成分分析(PCA)和层次聚类分析(HCA)可明显区分馏分。该研究结果可为威士忌发酵工艺优化及酒心摘取提供数据支撑。

蒸馏型花酒主要挥发性香气成分及其感官风味研究

以8款贵州花酒(玫瑰花酒和金银花酒)为研究对象,采用气相色谱-质谱联用法(Gas chromatography-mass spectrometry,GC-MS)分析其主要香气成分,感官评价法分析其香气轮廓。丁二酸二乙酯(呈熟苹果和依兰香气)在金银花蒸馏酒中的检出补充了前人在金银花固态发酵酒香气成分方面的研究;在感官评价方面,玫瑰花酒和金银花酒在花香香气上的均表现突出,较高强度的草本/生青气味是金银花组样品的特征风味。运用偏最小二乘-判别分析(Partial least squares discriminant analysis,PLS-DA)可以有效的将两种不同原料的贵州花酒做出区分,并筛选出VIP>1的关键香气标志物7种,分别是丁内酯、乙酸、丁二酸二乙酯、香茅油、2-甲基-1-丁醇、DL-白氨酸乙酯和二甲基苯甲醛。

多元统计分析结合HS-GC-MS对单粮复合香型白酒挥发性特征差异的分析

采用感官定量描述分析法(SQDA)对A(JA1~JA3)、B(JB1~JB3)、C(JC1~JC3)三组复合香型白酒9个样品的风味结构进行分析,结果表明:三组复合香型白酒在香气评分上差异不显著,粮香、焦香、麦芽香突出,在口感评分上差异显著,A组白酒各维度口感评分高于其他两组。采用顶空-气相色谱质谱联用技术(HS-GC-MS)对3种白酒挥发性化合物组成进行检测分析,共检测到148种挥发性物质。相关性分析结果显示,异丁醛、3-甲基呋喃、二甲基二硫醚、巴豆酸、环氧丙烷、丙烯醛和草酸只在A组白酒中被检测出来,丁酸乙酯在B组白酒中含量最高,JA3中含量偏低,表明3组白酒样品间存在明显的风味物质种类和含量差异。同步结合特征差异代谢物分析挖掘出74个VIP>1的潜在差异代谢物,A vs B组、A vs C组、B vs C组分别有14种、7种、4种化合物呈现极显著性差异(p<0.01),这些含量具有显著差异性的化合物可能与复合香型白酒风味特征的差异具有重要联系。综上所述,本研究采用两种技术协同分析,获得了3种白酒更全面的挥发性风味信息,解析了三组复合香型白酒的风味结构特征及差异,为深入研究复合香型白酒风味形成的机理奠定了基础。

3个年份浓香型白酒挥发性成分分析及指纹图谱的建立

以2011年、2014年和2015年3个年份某品牌浓香型白酒为对象,采用顶空固相微萃取-气相色谱/质谱联用技术,结合多元统计学分析方法对挥发性成分进行分析。在3个年份浓香型白酒中共鉴定出75种挥发性物质,其中酯类40种、醇类10种、醛类5种、酮类3种、芳香族5种、萜烯类8种、呋喃类2种。通过相对气味活度值法(ROAV)确定3个年份酒共17种对总体风味起关键作用和重要修饰作用的挥发性化合物,再联合利用正交偏最小二乘判别分析、Spearman相关性、随机森林模型筛选出3个年份浓香型白酒的年份差异性化合物14种。以3个年份浓香型白酒和二曲酒挥发性化合物为数据集,利用此方法筛选出22种真假差异性化合物作为指纹峰,分别建立3个年份浓香型白酒指纹对照图谱,各年份对照图谱与样本图谱相似度均在0.9以上,与掺假验证样本相似度均在0.9以下。结论:建立的指纹图谱可靠,鉴别能力强,为特定品牌浓香型白酒质量控制、假酒鉴别提供了一定的科学依据。

气相色谱法测定白酒中的乙酸、己酸含量

目的准确测量在白酒生产和质量控制中的两个关键成分:乙酸和己酸。方法采用直接进样-气相色谱技术(GC),快速且准确地同时测定了白酒中的乙酸和己酸含量。结果利用本方法,乙酸的检出限达到了0.012 g/L,己酸的检出限为0.0050 g/L。所有相关系数均超过0.999。相对标准偏差(RSD)分别为0.32%(乙酸)和0.33%(己酸),加标回收率分别为96.15%(乙酸)和96.69%(己酸)。结论本研究提出的新检测方法,不仅克服了传统检测方法和气相色谱在诸多方面的限制,而且展示了高效率、高灵敏度和优良选择性。这一方法对于提升白酒的生产工艺、确保产品风味的一致性和安全性具有重要的实际意义。

大曲耐热细菌富集及其在小曲白酒中的应用

大曲中耐热细菌菌群富含多种酶系,对白酒风味物质的产生有重要的影响。该研究采用高温富集方法从大曲中分离目的耐热细菌菌群,制作成麸曲并应用在小曲白酒酿造过程中,初步探究了三种高温条件下大曲耐热细菌菌群在小曲酒中的功能。通过16S rDNA测序技术分析了微生物结构及多样性,并考察了含水量对麸曲中的细菌生物量的影响,结果发现,大曲中以Bacillus为主的耐热细菌菌群被成功复刻至麸曲中,并占主导地位;在一定范围内随着富集温度的升高,耐热细菌占比越大;水分含量在55%时,麸曲中细菌生物量最高可达8.52×10^(10) CFU/g。通过小曲酒酿造试验发现,酿造出的最优小曲酒相较于对照组,出酒率提高3.7%,高级醇含量降低27.27%,酯含量增加23.07%,说明在小曲酒酿造过程中使用大曲耐热细菌菌群,可以提高小曲白酒质量。