In situ Detection of Amide A Bands of Proteins in Water by Raman Ratio Spectrum

The amide A band of protein is sensitive to the hydrogen bands of amide groups of proteins. However, it is hard to distinguish the amide A band of aqueous protein in situ directly, since it overlaps with O-H stretching vibration of water. In this work, we presented a new analytical method of Raman ratio spectrum, which can extract the amide A band of proteins in water. To obtain the Raman ratio spectrum, the Raman spectrum of aqueous protein was divided by that of pure water. A mathematical simulation was employed to examine whether Raman ratio spectrum is effective. Two kinds of protein, lysozyme and （^-chymotrypsin were employed. The amide A bands of them in water were extracted from Raman ratio spectra. Additionally, the process of thermal denaturation of lysozyme was detected from Raman ratio spectrum. These results demonstrated the Raman ratio spectra could be employed to study the amide A modes of proteins in water.

ASTER Data Processing by Discrete Wavelets Transform and Band Ratio Techniques for the Identification of Lineaments and Hydrothermal Alteration Zones in Poli, North Cameroon

The aim of this study is to carry out hydrothermal alteration mapping and structural mapping using ASTER images in order to identify indices that could guide mining exploration work in the Poli area and its surroundings. To achieve this, the ASTER images were first preprocessed to correct atmospheric effects and remove vegetation influence. Secondly, a lineament mapping was conducted by applying Discrete Wavelet Transform (DWT) algorithms to the First Principal Component Analysis (PCA1) of Visible Near-Infrared (VNIR) and Shortwave Infrared (SWIR) bands. Lastly, band ratio methods were applied to the VNIR, SWIR, and Thermal Infrared (TIR) bands to determine indices of iron oxides/hydroxides (hematite and limonite), hydroxyl-bearing minerals (chlorite, epidote, and muscovite), and the quartz index. The results obtained showed that the lineaments were mainly oriented NE-SW, ENE-WSW, and E-W, with NE-SW being the most predominant direction. Concerning hydrothermal alteration, the identified indices covered almost the entire study area and showed a strong correlation with lithological data. Overlaying the obtained lineaments with the hydrothermal alteration indices revealed a significant correlation between existing mining indices and those observed in the field. Mineralized zones generally coincided with areas of high lineament density exhibiting significant hydrothermal alteration. Based on the correlation between existing mining indices and the results of hydrothermal and structural mapping, the results obtained can then be used as a reference document for any mining exploration in the study area.

Land Use and Land Cover Mapping Based on Band Ratioing with Subpixel Classification by Support Vector Machine Techniques （A Case Study on Ngamoeyeik Dam Area, Yangon Region）

Making map of LULC （Land Use and Land Cover） is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. Band ratioing with subpixel classification is an enhancement process in which the digital number value of one band is divided by that of any other band in the sensor array. The main objective of this study is to increase classification accuracy of LULC mapping based on band ratioing with subpixel classification by Support Vector Machines （SVMs）. This process was applied with a soft approach at allocation as well as at a testing stage and to minimize the shadow and the topographic effects. The result shows the overall accuracy is increased from 61.18% of without band ratioing to 90.35% of band ratioing. The error matrix and confidence limits led to the validation of the result for LULC mapping.

Red Tide Information Extraction Based on Multi-source Remote Sensing Data in Haizhou Bay

[Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment monitoring data of red tide water were acquired.Then,band ratio method,chlorophyll-a concentration method and secondary filtering method were adopted to extract red tide information.[Result] On October 8,2005,the area of red tide was about 20.0 km2 in Haizhou Bay.There was no red tide in Haizhou bay on May 20,2006.On October 6,2006,large areas of red tide occurred in Haizhou bay,with area of 436.5 km2.On April 22,2009,red tide scattered in Haizhou bay,and its area was about 10.8 km2.[Conclusion] The research would provide technical ideas for the environmental monitoring department of Lianyungang to implement red tide forecast and warning effectively.

Effects of Rolling Processes on Yield Ratio and Formability of Hot Rolled Gas Cylinder Steel

Deep drawing properties of hot rolled gas cylinder steel was investigated by using HP295 steel in terms of microstructure, texture, yield ratio, plastic strain ratio （r value） and plastic anisotropy （Ar）. The grains in the hot strip were largely equiaxed, and the texture was weak, containing a- and ？＇fibre. Reheating temperature, finish roll ing temperature and cooling rate after rolling influenced the ferrite-pearlite band formation significantly, and the yield ratio increased steeply with decreasing coiling temperature below 630 ~C. The anisotropy is relatively high due to re- tained severe ferrite-pearlite band. A mechanism of the band formation due to manganese segregation is elaborated and confirmed validly, from which the measures to avoid the band formation are worked out. Rolling parameters have been optimized by the measures, and industrial production of the gas cylinder steel has been made possible with much improved r-and △r-values, while meeting other specifications.

Detection of skin defects on loquat using hyperspectral imaging combining both band radio and improved three-phase level set segmentation method

Background and objectives Skin defects are one of the primary problems that occur in post-harvest grading and processing of loquats.Skin defects lead to the loquat being easily destroyed during transportation and storage,which causes the risk of other loquats being infected,affecting the selling price.Materials and Methods In this paper,a method combining band radio image with an improved three-phase level set segmentation algorithm(ITPLSSM)is proposed to achieve high accuracy,rapid,and non-destructive detection of skin defects of loquats.Principal component analysis(PCA)was used to find the characteristic wavelength and PC images to distinguish four types of skin defects.The best band ratio image based on characteristic wavelength was determined.Results The band ratio image(Q782/944)based on PC2 image is the best segmented image.Based on pseudo-color image enhancement,morphological processing,and local clustering criteria,the band ratio image(Q782/944)has better contrast between defective and normal areas in loquat.Finally,the ITPLSSM was used to segment the processing band ratio image(Q782/944),with an accuracy of 95.28%.Conclusions The proposed ITPLSSM method is effective in distinguishing four types of skin defects.Meanwhile,it also effectively segments images with intensity inhomogeneities.

Lithological Discrimination of the Mafic-Ultramafic Complex, Huitongshan, Beishan, China: Using ASTER Data

The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer（ASTER） data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared（VNIR） and short wave infrared（SWIR） data were transformed using band ratios and minimum noise fraction（MNF）, while the thermal infrared（TIR） data were processed using mafic index（MI） and principal components analysis（PCA）. ASTER band ratios（6/8, 5/4, 2/1） in RGB image and MNF（1, 2, 4） in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China.