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.

Prediction of the undrained shear strength of remolded soil with non-linear regression,fuzzy logic,and artificial neural network

This study aims to predict the undrained shear strength of remolded soil samples using non-linear regression analyses,fuzzy logic,and artificial neural network modeling.A total of 1306 undrained shear strength results from 230 different remolded soil test settings reported in 21 publications were collected,utilizing six different measurement devices.Although water content,plastic limit,and liquid limit were used as input parameters for fuzzy logic and artificial neural network modeling,liquidity index or water content ratio was considered as an input parameter for non-linear regression analyses.In non-linear regression analyses,12 different regression equations were derived for the prediction of undrained shear strength of remolded soil.Feed-Forward backpropagation and the TANSIG transfer function were used for artificial neural network modeling,while the Mamdani inference system was preferred with trapezoidal and triangular membership functions for fuzzy logic modeling.The experimental results of 914 tests were used for training of the artificial neural network models,196 for validation and 196 for testing.It was observed that the accuracy of the artificial neural network and fuzzy logic modeling was higher than that of the non-linear regression analyses.Furthermore,a simple and reliable regression equation was proposed for assessments of undrained shear strength values with higher coefficients of determination.

Near resonance vibration isolation on a levered-dual response(LEDAR)Coulomb-damped system by differential preloads/offsets in linear springs

The levered-dual response(LEDAR)Coulomb-damped system attains near resonant vibration isolation by differential preloads/offsets in linear springs.It takes the advantages of both the preloads/offsets in linear springs and the guiderail friction for realizing different levels of vibration isolation.The isolation capacities are investigated on the strategies with both the horizontal and vertical guiderails,with the horizontal rail only,and without guiderails.The compressive preloads generally result in the consumption of most of the initial excitation energy so as to overcome the potential threshold.The isolation onsets at the frequency ratio of 1∓0.095 on the left-hand side(LHS)and the right-hand side(RHS)of the lever are relative to the load plate connector.The observed near resonant isolation thus makes the LEDAR system a candidate for the isolation of the mechanical systems about resonance while opening a path for simultaneous harvesterisolation functions and passive functions at extreme frequencies.

Assessment and Evaluation of Band Ratios, Brovey and HSV Techniques for Lithologic Discrimination and Mapping Using Landsat ETM⁺and SPOT-5 Data

This study aims to assess and to evaluate band ratios, brovey and HSV (Hue-Saturation-Value) techniques for discrimination and mapping the basement rock units exposed at Wadi Bulghah area, Saudi Arabia using multispectral Landsat ETM+ and SPOT-5 panchromatic data.?FieldSpec instrument is utilized to collect the spectral data of diorite, marble, gossan and volcanics, the main rock units exposed at the study area. Spectral profile of diorite exhibits very distinguished absorption features around 2.20 μm and 2.35 μm wavelength regions. These absorption features lead to lowering the band ratio values within the band-7 wavelength region. Diorite intrusions appear to have grey and dark grey image signatures on 7/3 and 7/2 band ratio images respectively. On the false color composite ratio image (7/3:R;7/2:G and 5/2:B), diorite, marble, gossan and volcanics have very dark brown, dark blue, white and yellowish brown image signatures respectively. Image fusion between previously mentioned FCC ratio image and high spatial resolution (5 meters) SPOT-5 panchromatic image is carried out by using brovey and HSV transformation methods. Visual and statistical assessment methods prove that HSV fused image yields best image interpretability results rather than brovey image. It improves the spatial resolution of the original FCC ratios image with acceptable spectral preservation.

Clinical Value of Dual-energy CT in Detection of Pancreatic Adenocarcinoma: Investigation of the Best Pancreatic Tumor Contrast to Noise Ratio

Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNR F ) and CNR of the major psoas muscle (CNR M ) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNR F (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNR F (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNR F in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNR F of mono-energetic image sets vs. CNR F of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.

Band structure characteristics of T-square fractal phononic crystals

The T-square fractal two-dimensional phononic crystal model is presented in this article.A comprehensive study is performed for the Bragg scattering and locally resonant fractal phononic crystal.We find that the band structures of the fractal and non-fractal phononic crystals at the same filling ratio are quite different through using the finite element method.The fractal design has an important impact on the band structures of the two-dimensional phononic crystals.

Application of Different Image Processing Techniques on Aster and ETM+ Images for Exploration of Hydrothermal Alteration Associated with Copper Mineralizations Mapping Kehdolan Area (Eastern Azarbaijan Province-Iran)

The Kehdolan area is located at 20 kilometers to the?south-east of Dozdozan Town (Eastern Azarbaijan Province). According to structural geology, volconic rocks are situated in Alborz-Azarbyjan zone, and faults?are?observed?in?the?same direction to this system with SE-NW trend. The results show that kaolinite alteration trend with Argilic and propylitic veins?is the?same direction with SW-NE faults in this area. Therefore, these faults with these trends can be considered as the mineralization control for determination of the alterations. Different image processing techniques,?such as false color composite?(FCC), band ratios, color ratio composite?(CRC), principal component?analysis?(PCA), Crosta technique, supervised spectral angle mapping?(SAM), are used for?identification of the alteration zones associated with copper mineralization. In this project ASTER?data are process and spectral analysis to fit for recognizing intensity and kind of argillic, propylitic,?philic, and ETM+ data?which?are process and to fit for iron oxide and relation to metal mineralization of the area. For recognizing different alterations of the study area, some chemical and mineralogical analysis data from the samples showed that ASTER data and ETM+ data were?capable of hydrothermal alteration mapping with copper mineralization.?Copper mineralization in the region is in agreement with argillic alteration. SW-NE trending faults controlled the mineralization process.

ON THE PAR REDUCTION OF MB-OFDM ULTRA-WIDEBAND SIGNALS

The Peak to Average power Ratio (PAR) of a Multi-Band Orthogonal Frequency-Division Multiplexing (MB-OFDM) Ultra-Wide Band (UWB) signals can be substantially larger than that of single carrier or carrier-less ultra-wideband signals. In this letter, a novel PAR reduction scheme for the MB-OFDM UWB system based on spreading and interleaving is proposed. By spreading the coded bits over each subcarrier in corresponding band and interleaving the spread symbols across all bands, the PAR statistics of the MB-OFDM signals can be improved and the PAR is reduced obviously. In the PAR reduction scheme, there is no loss in transmission data rate or Bit Error Rate (BER) performance decreasing. Since the spreading and interleaving operation are implemented by unitary Hadamard sequences and used for an approach to provide the robustness of the UWB system to narrowband interference, there is no additional implementation burden. Simulation results show that the investigated scheme gives the PAR reduction of 3dB compared with that of the original MB-OFDM signals.

Speech Resampling Detection Based on Inconsistency of Band Energy

Speech resampling is a typical tempering behavior,which is often integrated into various speech forgeries,such as splicing,electronic disguising,quality faking and so on.By analyzing the principle of resampling,we found that,compared with natural speech,the inconsistency between the bandwidth of the resampled speech and its sampling ratio will be caused because the interpolation process in resampling is imperfect.Based on our observation,a new resampling detection algorithm based on the inconsistency of band energy is proposed.First,according to the sampling ratio of the suspected speech,a band-pass Butterworth filter is designed to filter out the residual signal.Then,the logarithmic ratio of band energy is calculated by the suspected speech and the filtered speech.Finally,with the logarithmic ratio,the resampled and original speech can be discriminated.The experimental results show that the proposed algorithm can effectively detect the resampling behavior under various conditions and is robust to MP3 compression.

The Random Distribution of the Loading and Unloading Response Ratio Under the Assumptions of Poisson Models

This paper discussed the random distribution of the loading and unloading response ratio（LURR） of different definitions（Y1～Y5）using the assumptions that the earthquakes occurfollowing the Poisson process and their magnitudes obey the Gutenberg-Richter law.Theresults show that Y1～Y5 are quite stable or concentrated when the expected number of eventsin the calculation time window is relatively large（】40）;but when this occurrence ratebecomes very small,Y2～Y5 become quite variable or unstable.That is to say,a high value ofthe LURR can be produced not only from seismicity before a large earthquake,but also from arandom sequence of earthquakes that obeys a Poisson process when the expected number ofevents in the window is too small.To check the influence of randomness in the catalogue tothe LURR,the random distribution of the LURR under Poisson models has been calculated bysimulation.90%,95% and 99% confidence ranges of Y1 and Y3 are given in this paper,which is helpful to quantify the random

Preparation and Properties of C-axis Oriented PT/PEK-c Films

The preparation of PT/PEK c films is reported as well as their dielectric and optical properties. The c axis orientation ratio of the films is 68%. Dielectric constant and loss factor at 10 kHz is about 4.023 F/m and 0.003, respectively. The refractive indices of the films, n e and n o, are 1.657 3 and 1.627 8 at 0.63 μm wavelength, respectively. The optical band gap of the film with a thickness of 2.33 μm is found to be 3.06 eV.

基于红光波段日光诱导叶绿素荧光逃逸率的小麦条锈病遥感监测

小麦条锈病是影响小麦产量的主要病害之一,及时探测到病害信息对小麦条锈病的防控具有重要意义。红光波段日光诱导叶绿素荧光(red solar-induced chlorophyll fluorescence,RSIF)能够敏感反映植物光合生理状态,SIF逃逸率与冠层几何结构、叶片光学特性和植被光能利用率密切相关。为实现小麦条锈病及时准确的探测,该研究基于SIF逃逸率函数计算方式,利用野外实测数据计算不同尺度SIF(冠层尺度SIFCanopy、光系统尺度SIFPS)及其逃逸率(εCP),分析了RSIF逃逸率(RεCP)监测小麦条锈病的生理基础,探讨了条锈病胁迫下RεCP的响应特性,并将其与SIF及其衍生参数(荧光产率ФF、表观SIF产量SIFy)、归一化植被指数(normalized difference vegetation index,NDVI)、MERIS陆地叶绿素指数(MERIS terrestrial chlorophyll index,MTCI)、简单比值植被指数(simple ratio vegetation index,SR)进行比较。结果表明:RεCP与氮平衡指数(nitrogen balance index,NBI)、叶绿素(chlorophyll,Chl)、类黄酮(flavonoid,Flav)和花青素(anthocyanin,Anth)4个生理参数的相关性均达到了极显著性水平,且优于光系统尺度RSIF和远红光波段SIF(far-red solar-induced chlorophyll fluorescence,FRSIF),与叶面积指数(leaf area index,LAI)的相关性则优于冠层尺度FRSIF,RεCP能够更好地反映病害胁迫引起的作物生理和冠层结构的变化。在冠层尺度FRSIF(FRSIFCanopy)、光系统尺度FRSIF(FRSIFPS)和RSIF(RSIFPS)、红光波段表观SIF产量(RSIFy)及其荧光产率(RФF)、NDVI、MTCI、SR等特征变量中,RεCP与病情严重度(severity level,DSL)的相关性最高。低叶绿素含量(Chl≤30)和中高叶绿素含量(Chl>30)下,RεCP对小麦条锈病胁迫的响应均最为敏感,其与DSL的相关性均优于达到极显著性水平的SIF及其衍生参数和植被指数。RεCP是小麦条锈病遥感监测的适宜因子,研究结果对提高小麦条锈病的遥感监测精度具有重要意义,同时亦对其他作物胁迫的遥感监测具有一定的参考价值。

广义频分复用系统峰均功率比抑制算法

为了降低广义频分复用系统存在着多载波系统中固有的高峰均功率比问题,本文提出了一种适用于广义频分复用系统的子载波抑制高峰均功率比算法。该算法以限幅法为基础,降低了系统的高峰均功率比,但与限幅法不同的是,该算法几乎不会对带外性能及误码率性能造成影响。由于子载波抑制高峰均功率比算法的峰均功率比抑制性能略差于限幅法,因此本文进一步提出将部分序列传输与子载波抑制高峰均功率比结合来进一步抑制系统高峰均功率比的算法。仿真表明:本文提出的算法的高峰均功率比抑制性能与限幅法相同,且不会对系统的带外与误码率性能造成影响。

Q波段宽带螺旋线行波管输能系统研究

针对Q波段宽带螺旋线行波管所需要的低损耗、低反射输能系统,采用后馈式单脊过渡波导和盒型窗方案,优化设计了过渡波导阻抗变换结构、内导体尺寸和螺旋线大螺距过渡结构,得到33~50 GHz频带内驻波系数小于2的输能系统,并成功应用在Q波段宽带多用途螺旋线行波管中。

大变倍比制冷型红外双波段变焦光学系统设计

第三代红外焦平面探测器的不断发展使得探测器可以同时对两个不同波段的红外辐射进行响应,从而输出双波段对应图像,双波段图像在目标探测和识别领域应用前景广阔。本文针对航空探测应用,采用320×256双色红外制冷型探测器,设计了一种工作波段在中波3.7~4.8μm和长波7.7~9.5μm的大变倍比制冷型红外双波段变焦光学系统,用于对目标的红外探测。该光学系统采用折射式和折反式结构相结合的方式,可实现光学四视场切换式大范围变焦,采用二次成像以达到100%冷光阑效率。该光学系统四视场焦距分别为32 mm、200 mm、800 mm、1600 mm,变倍比为50×。实验结果表明,该光学系统在双波段各变倍状态下,在调制传递函数特征频率为17 lp/mm时均接近衍射极限。该光学系统具有双波段、变倍范围大、大变倍比、快速切换多视场、结构简单紧凑、成像质量高等特征,将在搜索、侦察等安防领域中得到广泛应用。

基于U波段光波产生频率可调谐的微波载波

【目的】具有可调谐能力的高频微波载波(GHz)在第五代移动通信技术(5G)/第六代移动通信技术(6G)无线网络、雷达系统和卫星通信领域中有着广泛的应用。由于比较简单的系统结构、大带宽和低损耗的优点,基于光子技术生成高频可调谐微波载波的技术方案吸引了国内外研究团队的广泛关注。由于目前C波段有着成熟的商用器件,因此目前光生微波实验多在C波段进行。随着波分复用(WDM)—光载射频(ROF)技术借助WDM系统在光频域的合/分波来灵活实现微波频段的合/分波,利用ROF系统采用光生微波技术来简化基站配置,使得C波段的有限带宽资源(35 nm, 1 530~1 565 nm)越来越紧张。因此,光生微波技术的研究有着向更宽光谱范围扩展的驱动力。U波段可以提供宽至50 nm(1 625~1 675 nm)的信道带宽来缓解C波段的信道利用压力。在U波段,标准单模光纤已实现低至0.195 dB/km(@1 625 nm)的光功率损耗,特别是,掺铥光纤放大器在U波段也可实现达到18.7 dB(@1 655 nm)的大带宽增益。因此,基于标准单模光纤的WDM系统可向U波段扩展,从而促使WDM-ROF技术向这一波段延伸,进而带动光生微波技术向U波段拓展。文章研究了U波段的光生微波技术。【方法】从数学模型上看,现有光生微波技术对所应用的光载波波段是透明的,只需选择对应工作波段的光子学器件就可在任意波段使用这些方法来产生微波载波。从原理上看,C波段的光子学器件(如偏振控制器、相位调制器(PM)和光纤移相器(FPS)等)可以工作在U波段,这些器件的工艺技术成熟并易于购置。因此,文章采用C波段的PM、FPS和光耦合器等光子学器件,基于U波段光载波搭建了光生微波载波系统。【结果】最终基于该系统产生了调谐范围覆盖7.5~12.0 GHz、杂散抑制比达29.6~35.2 dB的可调谐微波载波。【结论】文章通过公式原理分析和实验验证,实现了将光生微波载波技术的工作波段扩展至U波段。

基于双波段LiTaO_(3)热释电探测器的目标温度识别研究

针对热释电红外探测器在温度识别领域的难题,本文设计了一种基于长/中波双波段钽酸锂(LiTaO_(3))热释电多元探测器,建立了基于机器学习算法的目标温度识别模型。分析了不同黑体温度下的两波段辐射量与双波段比值的变化趋势,测试了双波段比值与黑体温度的关系以及分析了双波段比值在仿真与实测中的误差,研究了基于热释电数据的决策树、随机森林算法的最优参数选择以及所搭建的模型识别准确率。研究结果表明:基于该探测器构建的温度识别系统的识别准确率最高可大于90%,为基于热释电的目标温度识别提供了一种新的技术路径,拓宽了热释电红外探测器的应用范围。

采用TVFEMD和瞬时能量比的轧辊磨床颤振在线监测方法

在磨削过程中,颤振是轧辊表面产生振纹的一个最重要的原因,严重影响了工件表面质量。为避免颤振带来的不利影响,提出了一种基于时变滤波经验模态分解(TVFEMD)和瞬时能量比的(IER)的颤振在线监测方法。该方法采用可靠的指标提前监测出颤振的发生,解决了轧辊磨床早期颤振特征微弱,在背景噪声下难以快速识别的问题。首先对实时采集的振动信号进行实时分段处理。其次对每个砂轮转动周期内的信号进行时变滤波经验模态分解,提高信噪比。然后运用瞬时频率和瞬时能量比选取颤振敏感频带,将颤振敏感频带的瞬时能量比作为颤振特征。最后基于瞬时能量比上升量确定颤振监测阈值,判断当前加工状态。试验结果表明,在不同的轧辊磨床加工条件下,所提方法均能在颤振过渡阶段将其检测出来,更快地实现颤振早期预警;与EMD等传统时频分析方法相比,在早期颤振监测中具有明显的优势。