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- 摘要
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- 实验方案
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Matrix free laser desorption ionization mass spectrometry as an efficient tool for the rapid detection of opiates in crude extracts of <i>Papaver somniferum</i>
摘要： Having a long history of traditional medicinal applications, Papaver somniferum is also known as a source of various pharmacologically highly active opiates. Consequently, their detection from plant extracts is an important analytical task and generally addressed by methods of GC and LC-MS. However, opiates do also show structural similarities to matrix molecules used in matrix assisted laser desorption ionization and may therefore ionize upon simple laser irradiation. Following this analytical approach, the present work thoroughly evaluated the direct detection of opiates by matrix free laser desorption ionization (LDI) from crude extracts of P. somniferum. The method facilitated the identification of ten reported opiates by their molecular formulae without any chromatographic pre-purification. Moreover a principal component analysis based on LDI-MS data permitted the correct grouping of all extracts according to their inherent chemistry. Concluding experiments on serial dilutions of thebaine further evaluated potential quantitative applications of the method. Overall results highlight the promising potential of LDI-MS for the swift detection of opiates from complex mixtures.
关键词： LDI-MS,LC-MS,Papaver somniferum,quantification,PCA,opiates detection
更新于2025-09-12 10:27:22
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Determination of the superficial citral content on microparticles: An application of NIR spectroscopy coupled with chemometric tools
摘要： This work evaluates near-infrared (NIR) spectroscopy coupled with chemometric tools for determining the superficial content of citral (????????) on microparticles. To perform this evaluation, using spray drying, citral was encapsulated in a matrix of dextrin using twelve combinations of citral:dextrin ratios (CDR) and inlet air temperatures (IAT). From each treatment, six samples were extracted, and their ???????? and NIR absorption spectral profiles were measured. Then, the spectral profiles, pretreated and randomly divided into modeling and validation datasets, were used to build the following prediction models: principal component analysis-multilinear regression (PCA-MLR), principal component analysis-artificial neural network (PCA-ANN), partial least squares regression (PLSR) and an artificial neural network (ANN). During the validation stage, the models showed ??2 values from 0.73 to 0.96 and a root mean squared error (RMSE) range of [0.061–0.140]. Moreover, when the models were compared, the full and optimized ANN models showed the best fits. According to this study, NIR coupled with chemometric tools has the potential for application in determining ???????? on microparticles, particularly when using ANN models.
关键词： Food composition,Food science,Spectroscopy,Food chemistry,MLR,PCA,PLSR,Prediction,Chemometrics,Food analysis,ANN
更新于2025-09-12 10:27:22
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Coupling Waveguide-Based Micro-Sensors and Spectral Multivariate Analysis to Improve Spray Deposit Characterization in Agriculture
摘要： The leaf coverage surface is a key measurement of the spraying process to maximize spray efficiency. To determine leaf coverage surface, the development of optical micro-sensors that, coupled with a multivariate spectral analysis, will be able to measure the volume of the droplets deposited on their surface is proposed. Rib optical waveguides based on Ge-Se-Te chalcogenide films were manufactured and their light transmission was studied as a response to the deposition of demineralized water droplets on their surface. The measurements were performed using a dedicated spectrophotometric bench to record the transmission spectra at the output of the waveguides, before (reference) and after drop deposition, in the wavelength range between 1200 and 2000 nm. The presence of a hollow at 1450 nm in the relative transmission spectra has been recorded. This corresponds to the first overtone of the O–H stretching vibration in water. This result tends to show that the optical intensity decrease observed after droplet deposition is partly due to absorption by water of the light energy carried by the guided mode evanescent field. The probe based on Ge-Se-Te rib optical waveguides is thus sensitive throughout the whole range of volumes studied, i.e., from 0.1 to 2.5 μL. Principal Component Analysis and Partial Least Square as multivariate techniques then allowed the analysis of the statistics of the measurements and the predictive character of the transmission spectra. It confirmed the sensitivity of the measurement system to the water absorption, and the predictive model allowed the prediction of droplet volumes on an independent set of measurements, with a correlation of 66.5% and a precision of 0.39 μL.
关键词： principal component analysis (PCA),partial least squares (PLS),precision agriculture,droplet characterization,infrared spectroscopy,optical micro-sensors,crop protection
更新于2025-09-12 10:27:22
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Derivation of Tasseled Cap Transformation Coefficients for Sentinel-2 MSI At-Sensor Reflectance Data
摘要： Tasseled cap transformation (TCT) is a commonly used remote-sensing technique and has been successfully used in various remote sensing-related applications. However, the TCT coefficient set is sensor-specific, and therefore, in this article, we developed the TCT coefficients specifically for Sentinel-2 multispectral instrument at-sensor reflectance data. A total of ten synchronous image pairs of Sentinel-2 and Landsat-8, collected from the different parts of the world, were used for this approach. Instead of using the traditional Gram–Schmidt orthogonalization (GSO) method, we derived the coefficients using a principal component-based Procrustes analysis (PCP) method. This was done by rotating principal component axes of Sentinel-2 data to align to Landsat-8 Operational Land Imager tasseled cap axes via the Procrustes analysis. The results show that the TCT coefficients derived from our PCP method can effectively enhance brightness, greenness, and wetness characteristics of the Sentinel-2 imagery. The results have also been compared with those of a previous study that derived the Sentinel-2 TCT data using the GSO method instead. Landsat-8 and moderate resolution imaging spectroradiometer (MODIS)-derived TCT data have been used as references for comparison. The comparison shows that the PCP method outperforms the GSO method, as the PCP’s results generally have lower root mean square errors and higher correlation coefficients (R) when compared with the corresponding TC components of Landsat-8 and MODIS data, respectively. The greatest difference between the PCP and GSO methods lies in the wetness component. The PCP method can correctly highlight vegetation and soil moisture, as well as water features in the component.
关键词： Principal component analysis (PCA),Sentinel-2,tasseled cap transformation (TCT),Procrustes analysis
更新于2025-09-11 14:15:04
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Low‐resolution fiber‐optic Raman spectroscopy for bladder cancer diagnosis: A comparison study of varying laser power, integration time, and classification methods
摘要： In our previous work, we have demonstrated the great diagnostic potential of a low‐resolution Raman sensing system for bladder cancer through ex vivo experiments. Before forwarding this technique into clinical applications, the system's performance under different experimental conditions must be thoroughly understood. In this paper, a comparison study of this system under different experimental conditions and post‐experiment analysis methods is presented. The different experiment conditions includes two major parts: (a) varying the incident laser power at sample from 30 to 150 mW (30‐mW interval) with fixed integration time of 1 s; (b) varying integration time of 1 s, 2 s, 3 s, and 5 s, with a fixed incident laser power of 150 mW. A total number of 2,916 spectra were collected on 42 bladder tissue specimens under different experimental conditions. Three principal component analysis (PCA)‐based classification methods, including linear discriminant analysis (LDA), support vector machine (SVM), and artificial neural network (ANN), are used in this study for comparison. Results show that increasing the incident laser power has little influence on the overall prediction accuracy; increasing the integration time from 1 to 5 s has a clear improvement on the prediction accuracy; PCA–ANN outperforms PCA–LDA and PCA–SVM consistently under the parameter settings in this study.
关键词： Raman spectroscopy,low resolution,bladder cancer,PCA
更新于2025-09-11 14:15:04
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An advanced approach to control the electro-optical properties of LT-GaAs-based terahertz photoconductive antenna
摘要： This work reports on an advanced approach to the design of THz photoconductive antenna (PCA). The LT-GaAs thin films used for the PCA fabrication were synthesized by MBE method on GaAs (100) substrate by adjusting the As pressure, As/Ga fluxes ratio, growth/annealing temperatures and annealing time. These parameters crucially affect electro-optical properties of the PCA samples as evidenced by the THz radiation power and time-domain spectroscopy measurements. The annealing temperature of 670 °C was found to be optimal for constructing a PCA possessing high amplitude of the THz radiation over the spectral range up to 1 THz at the resonance of 0.1 THz. The comparison of this PCA with the reference ZnTe crystal reveals a 2-fold increase in THz power. Furthermore, this antenna attains a 1.5-, 3-, and 2-fold increase in THz power, photocurrent efficiency, and actuating dc BV, as compared with the commercial ZOMEGA antenna. These results pave the way towards the creation of highly efficient LT-GaAs-based PCAs.
关键词： THz-antenna,Terahertz (THz) radiation,Photoconductive antenna (PCA),Low temperature-grown gallium arsenide (LT-GaAs),THz-spectroscopy
更新于2025-09-11 14:15:04
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PERBANDINGAN TINGKAT PENGENALAN CITRA DIABETIC RETINOPATHY PADA KOMBINASI PRINCIPLE COMPONENT DARI 4 CIRI BERBASIS METODE SVM (SUPPORT VECTOR MACHINE)
摘要： Pattern recoqnition methods for image of diabetic retinopaty are influenced by differences in pigmentation. To help diabetic retinopathy image recognition is required a software. This paper presents the results of research on pattern recognition image of diabetic retinopathy,This study used the image of the yellow canal with Gabor filter.Characteristics that are taken from each image is characteristic of the mean, variance, skewness and entropy, followed by feature extraction with PCA (Principle Component Analysis).At PCA feature extraction, square matrix whose number of columns equal to the number of features is generated.There are four features used. These features are 4 PCs (Principle Component), ie, PC1, PC2, PC3 and PC4.From the combination of these features, we obtained six pairs that consist of two traits. By using a linear model of SVM will been selected the pair with the highest accuracy value. Based on the analysis, we obtained a couple PC1 and PC2 models that have the highest levels of learning (100%) and the fastest recognition time, which is explicitly indicated by the smallest amount of support vector.
关键词： Kanal Kuning,PCA,diabetic retinopathy,SVM
更新于2025-09-11 14:15:04
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Innovative Multi Pcnn Based Network for Green Area Monitoring - Identification and Description of Nearly Indistinguishable Areas - In Hyperspectral Satellite Images
摘要： The paper presents an original neural network approach for region of interest detection and classification in multi-spectral satellite images. The proposed method uses a sequence of Pulse Coupled Neural Networks that identifies plausible regions of interest. These regions are passed to a dimension reduction algorithm, Principle Component Analysis, in order to generate the input data for a Support Vector Machine classifier, that validates the data. The algorithm's parameters are optimized using a Genetic Algorithm. The algorithm is designed to distinguish regions that are extremely similar, such as parks in a city that has entire districts made up of houses with yards. The algorithm has been tested on images provided by the Sentinel-2 satellite, and it proved that it can recall 76.85% of the pixels marked as park in the ground truth data, which was obtained from OpenStreetMap.
关键词： Genetic Algorithm (GA),Pulse Coupled Neural Network (PCNN),Principle Component Analysis (PCA),Support Vector Machine (SVM)
更新于2025-09-10 09:29:36
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Determination of Variance of Secondary Metabolites in Lettuces Grown Under Different Light Sources by Flow Injection Mass Spectrometric (FIMS) Fingerprinting and ANOVA–PCA
摘要： Lettuce (Lactuca sativa L.) is one of the most consumed vegetables in the world and different management practice can result in considerable variability of the secondary metabolites. Flow injection mass spectrometry (FIMS) combined with analysis of variance–principle component analysis (ANOVA–PCA) was used to study differences in the secondary metabolites originating from different lighting conditions (Sunlight, white light, and florescent light) and lettuce varieties (Romaine and Lollo Rossa). Ultra-high-performance liquid chromatography–high-resolution accurate mass spectrometry was used for putative marker compound identification. Quinic acid, caffeic acid, chlorogenic acid, L-chicoric acid, and quercetin malonyl glucoside varied significantly for Romaine lettuce grown under different light conditions. The study showed that the combination of FIMS fingerprinting and ANOVA–PCA can be a useful tool for the characterization of the sources of variance in plant materials regarding to genetic, environmental, and management factors.
关键词： Lactuca sativa L.,Flow injection mass spectrometric fingerprinting,ANOVA–PCA,Lettuce
更新于2025-09-10 09:29:36
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[IEEE 2018 International Conference on Smart City and Emerging Technology (ICSCET) - Mumbai, India (2018.1.5-2018.1.5)] 2018 International Conference on Smart City and Emerging Technology (ICSCET) - IoT Based Facial Recognition Security System
摘要： In recent years, with the demand for better security, computers have played a large role. Due to their precision, large memory banks and high computing power, considerable development has been made in the area of face recognition. Computers now surpass humans in many face recognition tasks. A human being can remember limited number of faces. But a computer doesn’t have any limits, and can hence be used where large databases of facial records are needed. Such a facial recognition system has many potential applications including crowd and airport surveillance, private security and improved human-computer interaction. Such a system is perfectly suited to fix security issues and offer flexibility to smart house control. This project is aimed to be a complete system for face recognition: easy to build, cheap cost and effective. Main purpose is to be set as an alert for home visitors and provide information about the visitors in a dynamic website and phone application. It can also be used in other fields like industries, offices and even air-ports for identifying wanted people. Among the other bio-metric techniques, face recognition method offers one great advantage which is user friendliness.
关键词： principal component analysis (PCA),global system for mobile communication (GSM),raspberry pi (RPI),universal serial bus (USB),Internet of things (IoT),local area network (LAN)
更新于2025-09-10 09:29:36