岩巷锚杆支护的力学分析及改进措施

通过对巷道围岩变形、破坏机理分析 ,指出锚杆支护存在的问题 。

《分析化学》教学方法研讨

分析化学是医学检验专业的基础课程之一,但学生普遍认为分化理论性强、内容抽象、计算复杂、不易学习。因此,怎样才能搞好教学、提高教学质量,是一个值得探讨的问题。教学质量的好坏与教学内容的安排和教学方法的应用有着密切的关系。

Improving autoencoder-based unsupervised damage detection in uncontrolled structural health monitoring under noisy conditions

Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.

Kinetics analysis of decomposition of vanadium slag by KOH sub-molten salt method

A novel process was developed for the decomposition of vanadium slag using KOH sub-molten salt under ambient pressure, and the effects of reaction temperature, alkali-to-ore mass ratios, particle size, and stirring speed on vanadium and chromium extraction were studied. The results suggest that the reaction temperature and KOH-to-ore mass ratio are more influential factors for the extraction of vanadium and chromium. Under the optimal reaction conditions （temperature 180 °C, initial KOH-to-ore mass ratio 4：1, stirring speed 700 r/min, gas flow 1 L/min, and reaction time 300 min）, vanadium and chromium extraction rates can reach up to 95% and 90%, respectively. Kinetics analysis results show that the decomposing process of vanadium slag in KOH sub-molten salt can be well interpreted by the shrinking core model under internal diffusion control. The apparent activation energies for vanadium and chromium are 40.54 and 50.27 kJ/mol, respectively.

Preparation and characteristic analysis of rice husk high boiling solvent lignin

Rice husk high boiling solvent lignin （RHL） was prepared by high boiling solvent method, and its characteristics was analyzed by using chemical composition analysis, infrared spectroscopy, and ^1H-NMR and ^13C-NMR spectroscopy. The optimum prepared condition was that the rice husk with 70%-90% aqueous solution of 1, 4-butanediol was mixed with autoclave, under a certain weight ratio of solid raw material and solvent, heated to 200-220℃ for 1.0-3.0 h, then water-insoluble RHL was separated from the liquor reaction mixture by water precipitation. Results suggested that the lower digestion temperature and concentration of 1,4-butanediol were both unfavorable for extracting lignin. Chemical weight-average molecular weight of RHL was 1939 g·mol^-1, and the residual polysaccharide content was 5.12%. The ^1H-NMR spectra of RHL showed the relative intensity ratio, aliphatic over aromatic methoxyl groups, situated at 3.5-3.8 and 3.8-4.0 ppm, respectively. The results from ^13C-NMR spectra showed that β-O-4 bond and β-5 carbon-carbon linkage were the major linkages between RHL units. The C9-formula of RHL was calculated by the experiment data.

High Performance Liquid Chromatography-Electrospray Ionization-Mass Spectrometric Analysis of Bilobalide and Ginkgolides in Ginkgo biloba L. Leaves

The ginkgo terpenoids including bilobalide and ginkgolides are the main pharmaceutical components in the leaves or extracts of Ginkgo biloba L. In this paper, the analysis of bilobalide and ginkgolides in leaves of Ginkgo biloba L. by high performance liquid chromatography (HPLC)-electrospray ionization (ESI)-mass spectrometry (MS) was carried out. The separation was performed on Inertsil ODS3 column with methanol-water (36:64) as mobile phase, with 1 mL·min -1 of flow rate at 35℃. Then the mass spectrum analysis was conducted by ZMD micromass electrospray ionization (ESI)-mass spectrometer (MS). The HPLC total ion chromatogram and selected ion chromatogram (with 325, 407, 423, 439 of m/z) of the sample and ESI-/MS mass spectra of the peaks in the chromatograms were obtained. So bilobalide, ginkgolide A, B, C and J in Ginkgo biloba L. leaves were identified. The method is easy and rapid, with a good accuracy.

Analysis of the major components of root exudates released from several economic forest tree using GC-MS

In 2000 and 2001, 1-year-old seedlings of 7 economic tree species including chestnut, apricot, persimmon, peach, walnut, pear and apple were cultured in garden pots that had a diameter of 40 cm and were filled with clean sand. The major components of exudates released from their roots were isolated and analysed by GC-MS. Totally 200 kinds of organic chemicals were isolated, of which 3 kinds i.e. naphthalene, dimethylbenzene and dibutyl phthalate were principally controlled pollutants according to 'Blacklist of Principal Environment Pollutants in China' and the standard of U.S. Environmental Protection Agency (EPA). The research result provided theoretical evidence for selecting low-pollution economic forest crops in the water source protection area in Miyun Reservoir.

Research on the Correlation between Meteorological Factors and Flue-cured Tobacco Chemical Components in Different Altitudes of Lincang Region

In this study, the relationship between major meteorological factors and tobacco chemical components in different altitudes of Yongde County, Lincang Region of Yunnan Province was studied using correlation analysis and path analysis methods.The results showed that there was a difference on meteorological factors in different altitudes, causing different impacts on chemical components of flue-cured tobacco; contents of nicotine and total nitrogen decreased with the rising of altitude, conversely, total sugar and reducing sugar contents increased with the rising trend of altitude, and the differences on the contents of potassium （K） and chlorine（CI）, and the ratio of K to CI in different altitudes were not significant, at the altitude of 1 250-1 450 m, each chemical component indicator was better. The correlation between main meteorological factors and conventional chemical components of tobacco leaves was as follows： contents of reducing sugar and total sugar increased with the increase of rainfall and relative humidity, and decreased with the increase of sunshine duration; nicotine content increased with the increase of accumulated temperature and sunshine duration; total nitrogen （N） content increased with the increase of daily mean temperature and accumulated temperature; sugar-alkali ratio increased with the increase of rainfall. Path analysis showed that the direct effect of sunshine duration on reducing sugar and total sugar of tobacco leaves was faint, but the indirect effect was obvious; meanwhile, the direct and indirect effects of it on nicotine and total N were the greatest.

Locally linear embedding-based seismic attribute extraction and applications

How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.

Analysis on Chemical Compositions in Chinese Wolfberry from Different Producing Areas

[Objective] This study aimed to conduct correspondence cluster analysis of the trace elements in Chinese wolfberry from Qinghai and Ningxia regions, and to investigate the relationship among the quality of the wolfberry samples, the composition of trace elements and the sample sources. [Method] The determined contents of trace elements and ratios of zinc to copper （Zn/Cu） of wolfberry from 11 different producing areas of Qinghai and Ningxia regions were adopted to construct the raw measurement data matrix, to analyze the distribution characteristics of the trace ele- ments in wolfberry from Qinghai and Ningxia by using the corresponding cluster analysis method. [Result] The quality of wolfberry samples in 7hongning County, Zhongwei City, Pingluo County, Shizuishan City, Heicheng Town of Ningxia Hui Au-tonomous Region and Hehuang Valley, Golmud City of Qinghai Province is mainly related to the contents of Zn and Mn; Zn/Cu greatly affects the quality of Chinese wolfberry in Dulan County of Qinghai Province; Fe has great effect on the quality of Chinese wolfberry in Yinchuan City of Ningxia Hui Autonomous Region; Cu greatly affects the quality of Chinese wolfberry in Nuomuhong Village of Qinghai Province and a wolfberry research institute in Ningxia. [Conclusion] The relationship between the quality of wolfberry from different producing areas and the trace elements was investigated, which provides theoretical and practical basis for the cultivation, har- vesting, processing, and further development and utilization of Chinese wolfberry resources from different producing areas.

Analysis on the Main Botanical Characters of 41 Cucurbita moschata Varieties

In order to scientifically evaluate the values of Cucurbita moschata cultivars, main botanical characters including the initial flowering date, the first fruiting node, fruit length, fruit stem length, stem diameter, internode length, the transverse and longitudinal diameters of the largest leaf, single fruit weight, flesh thickness and soluble solid content of 41 cultivars were measured for conducting diversity, correlation and cluster analysis. The results revealed that the pumpkin cultivars showed large variations in fruit stem length, single fruit weight, fruit length and flesh thickness, but small variations in initial flowering date. Significant, even highly significant correlations were found among the tested traits. Cluster analysis demonstrated that the 41 old Cucurbita moschata cultivars were divided into three groups, of which multiple traits of Group 1 were better than those in the other two groups. High similarities existed in three groups and the cultivars in each group. This research provided basis for selecting excellent traits and parents for the breeding of hybrids.

Morphological Diversity Analysis of Red-seed Watermelon (Citrullus lanatus ssp. vulgaris var. megalaspermus Lin et Chao) Germplasm Resources

[Objective] This study aimed to analyze the morphological diversity of red- seed watermelon （Citrullus lanatus ssp. vulgaris var. megalaspermus Lin et Chao） germplasm resources. [Method] Multiple cluster analysis and principal components analysis on the morphological traits of 51 red-seed watermelon germplasm resources were carried out. [Result] The coefficient of variations （CVs） of 39 morphological traits in 51 red-seed watermelon idioplasm resources ranged from 5.37% to 66.95%, with an average of 22.87%. The average of Shannon diversity information indices was 1.55. Among them, the Shannon diversity information index of seed length was the highest （2.16） and that of seed shell figure pattern was the lowest （0.32）. In ad- dition, the morphological diversity information indices of quantity characters were higher than that of quality characters. The principal components analysis revealed that the variance contribution rates of the first, second and third principal compo- nents were 19.49%, 15.32% and 9.55%, respectively. Cluster analysis divided the 51 materials into three broad branches based on the morphological traits. There was only one material in the fist branch and two in the second branch, and all the three materials were wild. The other 48 materials were divided into the third branch and all of them were cultivars. [Conclusion] This study provided a theoretical basis for the protection and utilization of red-seed watermelon resources.

Conserved quantities from Lie symmetries for nonholonomic systems

This paper presents a new method to seek the conserved quantity from a Lie symmetry without using either Lagrangians or Hamiltonians for nonholonomic systems. The differential equations of motion of the systems are established. The definition of the Lie symmetrical transformations of the systems is given, which only depends upon the infinitesimal transformations of groups for the generalized coordinates. The conserved quantity is directly constructed in terms of the Lie symmetry of the systems. The condition under which the Lie symmetry can lead to the conserved quantity and the form of the conserved quantity are obtained. Finally, an example is given to illustrate the application of the result.

Analysis of Volatile Constituents in Bamboo Leaves Using HS-GC/MS

[Objective] This study aimed to analyze the volatile constituents in bamboo leaves. [Method] The volatile compositions in bamboo leaves were analyzed by headspace-gas chromatography-mass spectrometry （HS-GC/MS）, and identified by searching their mass spectra in NIST database. The relative percentages of them were calculated by the GC peak areas. [Result] Fifty-three chemical constituents in bamboo leaves were separated. Among them, the main components were alcohols, ketones and aldehydes, and these compounds contained unsaturated bonds. [Con- clusion] HS-GC/MS was simple and less sample-demanding and can be used for rapid analysis of volatile constituents in bamboo leaves and provide scientific basis for further research and development of bamboo leaves.

Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Copper corrosion in hot and dry atmosphere environment in Turpan, China

The atmospheric corrosion behavior of pure copper exposed for three years in Turpan, China, which is a typical hot and dry atmosphere environment, was investigated using mass-loss tests, morphology observations, composition analyses, and electrochemical techniques. The results indicated that the annual corrosion rate of pure copper was approximately 2.90 μm/a. An uneven distribution of corrosion products was observed by scanning electron microscopy; this uneven distribution was attributed to the dehydration process during wet–dry and cold–hot cycles, and the compositions mainly consisted of cuprite （Cu2O） and atacamite （Cu2Cl（OH）3）. Electrochemical measurements showed that deposits on copper improved its resistance to corrosion and the protectiveness decreased with increasing temperature. On the other hand, results obtained using the scanning vibrating electrode technique showed that the porous and uneven structure of the deposit layer generated a spatial separation of cathodic and anodic reaction sites, which accelerated the corrosion process in wet and rainy weather.

如何区别香椿和臭椿?

问 每当春天来临的时节，我很喜欢采摘或购买香椿芽时，可有时错把臭椿当香椿，到头来很扫兴。请问，如何区别香椿和臭椿？

FTIR Spectroscopic Study of Broad Bean Diseased Leaves

[Objective] The aim was to indentify diseased leaves of broad bean by vibra- tional spectroscopy. [Method] In this paper, broad bean rust, fusarium rhizome rot, broad bean zonate spot, yellow leaf curl virus and normal leaves were studied using Fourier transform infrared spectroscopy combined with chemometrics. [Result] The spectra of the samples were similar, only with minor differences in absorption inten- sity of several peaks. Second derivative analyses show that the significant difference of all samples was in the range of 1 200-700 cm2. The data in the range of 1 200- 700 cm＇ were selected to evaluate correlation coefficients, hierarchical cluster analy- sis （HCA） and principal component analysis （PCA）. Results showed that the correla- tion coefficients are larger than 0.928 not only between the healthy leaves, but also between the same diseased leaves. The values between healthy and diseased leaves, and among diseased leaves, are all declined. HCA and PCA yielded about 73.3% and 82.2% accuracy, respectively. [Conclusion] This study demonstrated that FTIR techniques might be used to detect crop diseases.

Is it possible to differentiate gastric GISTs from gastric leiomyomas by EUS?

AIM: To evaluate the ultrasonog raphy (EUS) features of gastric gastrointestinal stromal tumors (GISTs) as compared with gastric leiomyomas and then to determine the EUS features that could predict malignant GISTs.METHODS: We evaluated the endoscopic EUS features in 53 patients with gastric mesenchymal tumors conf irmed by histopathologic diagnosis. The GISTs were classif ied into benign and malignant groups according to the histological risk classif ication.RESULTS: Immunohistochemical analyses demon-strated 7 leiomyomas and 46 GISTs. Inhomogenicity, hyperechogenic spots, a marginal halo and higher echogenicity as compared with the surrounding muscle layer appeared more frequently in the GISTs than in the leiomyomas (P < 0.05). The presence of at least two of these four features had a sensitivity of 89.1% and a specifi city of 85.7% for predicting GISTs. Except for tumor size and irregularity of the border, most of the EUS features were not helpful for predicting the malignant potential of GISTs. On multivariate analysis, only the maximal diameter of the GISTs was an independent predictor. The optimal size for predicting malignant GISTs was 35 mm. The sensitivity and specificity using this value were 92.3% and 78.8%, respectively.CONCLUSION: EUS may help to differentiate gastric GISTs from gastric leiomyomas. Once GISTs are suspected, surgery should be considered if the size is greater than 3.5 cm.

Kernel principal component analysis network for image classification

In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the data is mapped into a higher-dimensional space with kernel principal component analysis to make the data linearly separable. Then a two-layer KPCANet is built to obtain the principal components of the image. Finally, the principal components are classified with a linear classifier. Experimental results showthat the proposed KPCANet is effective in face recognition, object recognition and handwritten digit recognition. It also outperforms principal component analysis network（ PCANet） generally. Besides, KPCANet is invariant to illumination and stable to occlusion and slight deformation.